diff --git a/404.html b/404.html index 14b861ce..82be08b0 100644 --- a/404.html +++ b/404.html @@ -4,8 +4,8 @@ OpenRAG - - + + diff --git a/agents/index.html b/agents/index.html index 8c2c69d3..9949e269 100644 --- a/agents/index.html +++ b/agents/index.html @@ -3,55 +3,70 @@ -Langflow in OpenRAG | OpenRAG - - +Use Langflow in OpenRAG | OpenRAG + + -
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Langflow in OpenRAG

OpenRAG leverages Langflow's Agent component to power the OpenRAG OpenSearch Agent flow.

-

Flows in Langflow are functional representations of application workflows, with multiple component nodes connected as single steps in a workflow.

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In the OpenRAG OpenSearch Agent flow, components like the Langflow Agent component and OpenSearch component are connected to intelligently chat with your knowledge by embedding your query, comparing it the vector database embeddings, and generating a response with the LLM.

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OpenRAG Open Search Agent Flow

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The Agent component shines here in its ability to make decisions on not only what query should be sent, but when a query is necessary to solve the problem at hand.

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How do agents work?

Agents extend Large Language Models (LLMs) by integrating tools, which are functions that provide additional context and enable autonomous task execution. These integrations make agents more specialized and powerful than standalone LLMs.

Whereas an LLM might generate acceptable, inert responses to general queries and tasks, an agent can leverage the integrated context and tools to provide more relevant responses and even take action. For example, you might create an agent that can access your company's documentation, repositories, and other resources to help your team with tasks that require knowledge of your specific products, customers, and code.

Agents use LLMs as a reasoning engine to process input, determine which actions to take to address the query, and then generate a response. The response could be a typical text-based LLM response, or it could involve an action, like editing a file, running a script, or calling an external API.

In an agentic context, tools are functions that the agent can run to perform tasks or access external resources. A function is wrapped as a Tool object with a common interface that the agent understands. Agents become aware of tools through tool registration, which is when the agent is provided a list of available tools typically at agent initialization. The Tool object's description tells the agent what the tool can do so that it can decide whether the tool is appropriate for a given request.

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Use the OpenRAG OpenSearch Agent flow​

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If you've chatted with your knowledge in OpenRAG, you've already experienced the OpenRAG OpenSearch Agent chat flow. -To switch OpenRAG over to the Langflow visual editor and view the OpenRAG OpenSearch Agentflow, click Settings, and then click Edit in Langflow. -This flow contains eight components connected together to chat with your data:

+

Use Langflow in OpenRAG

OpenRAG includes a built-in Langflow instance for creating and managing functional application workflows called flows. +In a flow, the individual workflow steps are represented by components that are connected together to form a complete process.

+

OpenRAG includes several built-in flows:

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  • The Agent component orchestrates the entire flow by deciding when to search the knowledge base, how to formulate search queries, and how to combine retrieved information with the user's question to generate a comprehensive response. -The Agent behaves according to the prompt in the Agent Instructions field.
    • -
  • The Chat Input component is connected to the Agent component's Input port. This allows to flow to be triggered by an incoming prompt from a user or application.
    • -
  • The OpenSearch component is connected to the Agent component's Tools port. The agent might not use this database for every request; the agent only uses this connection if it decides the knowledge can help respond to the prompt.
    • -
  • The Language Model component is connected to the Agent component's Language Model port. The agent uses the connected LLM to reason through the request sent through Chat Input.
    • -
  • The Embedding Model component is connected to the OpenSearch component's Embedding port. This component converts text queries into vector representations that are compared with document embeddings stored in OpenSearch for semantic similarity matching. This gives your Agent's queries context.
    • -
  • The Text Input component is populated with the global variable OPENRAG-QUERY-FILTER. -This filter is the Knowledge filter, and filters which knowledge sources to search through.
    • -
  • The Agent component's Output port is connected to the Chat Output component, which returns the final response to the user or application.
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  • An MCP Tools component is connected to the Agent's Tools port. This component calls the OpenSearch URL Ingestion flow, which Langflow uses as an MCP server to fetch content from URLs and store in OpenSearch.
    • +
  • The OpenRAG OpenSearch Agent flow powers the Chat feature in OpenRAG.
    • +
  • The OpenSearch Ingestion and OpenSearch URL Ingestion flows process documents and web content for storage in your OpenSearch knowledge base.
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  • The OpenRAG OpenSearch Nudges flow provides optional contextual suggestions in the OpenRAG Chat.
-

All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic. -To modify a flow, click Settings, and click Edit in Langflow. -OpenRAG's visual editor is based on the Langflow visual editor, so you can edit your flows to match your specific use case.

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For an example of changing out the agent's language model in OpenRAG, see the Quickstart.

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To restore the flow to its initial state, in OpenRAG, click Settings, and then click Restore Flow. -OpenRAG warns you that this discards all custom settings. Click Restore to restore the flow.

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Additional Langflow functionality​

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Langflow includes features beyond Agents to help you integrate OpenRAG into your application, and all Langflow features are included in OpenRAG.

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You can customize these flows and create your own flows using OpenRAG's embedded Langflow visual editor.

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Inspect and modify flows​

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All OpenRAG flows are designed to be modular, performant, and provider-agnostic.

+

To modify a flow in OpenRAG, click Settings. +From here, you can quickly edit commonly used parameters, such as the Language model and Agent Instructions. +To further explore and edit the flow, click Edit in Langflow to launch the embedded Langflow visual editor where you can fully customize the flow to suit your use case.

+

For example, to view and edit the built-in Chat flow (the OpenRAG OpenSearch Agent flow), do the following:

+
    +
  1. +

    In OpenRAG, click Chat.

    +
    2. +
  2. +

    Click Settings, and then click Edit in Langflow to launch the Langflow visual editor in a new browser window.

    +

    If prompted to acknowledge that you are entering Langflow, click Proceed.

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    If Langflow requests login information, enter the LANGFLOW_SUPERUSER and LANGFLOW_SUPERUSER_PASSWORD from the .env file in your OpenRAG installation directory.

    +

    OpenRAG OpenSearch Agent flow

    +
    3. +
  3. +

    Modify the flow as desired, and then press Command+S (Ctrl+S) to save your changes.

    +

    You can close the Langflow browser window, or leave it open if you want to continue experimenting with the flow editor.

    +
    tip

    If you modify the built-in Chat flow, make sure you click in the Conversations tab to start a new conversation. This ensures that the chat doesn't persist any context from the previous conversation with the original flow settings.

    +
    4. +
+

Revert a built-in flow to its original configuration​

+

After you edit a built-in flow, you can click Restore flow on the Settings page to revert the flow to its original state when you first installed OpenRAG. +This is a destructive action that discards all customizations to the flow.

+

Build custom flows and use other Langflow functionality​

+

In addition to OpenRAG's built-in flows, all Langflow features are available through OpenRAG, including the ability to create your own flows and popular extensibility features such as the following:

+ +

Explore the Langflow documentation to learn more about the Langflow platform, features, and visual editor.

+

Set the Langflow version​

+

By default, OpenRAG is pinned to the latest Langflow Docker image for stability.

+

If necessary, you can set a specific Langflow version with the LANGFLOW_VERSION. However, there are risks to changing this setting:

  • -

    Langflow can serve your flows as an MCP server, or consume other MCP servers as an MCP client. Get started with the MCP tutorial.

    +

    The Langflow documentation describes the functionality present in the latest release of the Langflow OSS Python package. If your LANGFLOW_VERSION is different, the Langflow documentation might not align with the features and default settings in your OpenRAG installation.

  • -

    If you don't see the component you need, extend Langflow's functionality by creating custom Python components.

    +

    Components might break, including components in OpenRAG's built-in flows.

  • -

    Langflow offers component bundles to integrate with many popular vector stores, AI/ML providers, and search APIs.

    +

    Default settings and behaviors might change causing unexpected results when OpenRAG expects a newer default.

    • -
diff --git a/assets/js/0ba6a408.5aaf70c7.js b/assets/js/0ba6a408.5aaf70c7.js deleted file mode 100644 index 844f630f..00000000 --- a/assets/js/0ba6a408.5aaf70c7.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[571],{3227:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>p,contentTitle:()=>h,default:()=>x,frontMatter:()=>a,metadata:()=>i,toc:()=>u});const i=JSON.parse('{"id":"core-components/knowledge","title":"OpenSearch in OpenRAG","description":"OpenRAG uses OpenSearch for its vector-backed knowledge store.","source":"@site/docs/core-components/knowledge.mdx","sourceDirName":"core-components","slug":"/knowledge","permalink":"/knowledge","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/core-components/knowledge.mdx","tags":[],"version":"current","frontMatter":{"title":"OpenSearch in OpenRAG","slug":"/knowledge"},"sidebar":"tutorialSidebar","previous":{"title":"Langflow in OpenRAG","permalink":"/agents"},"next":{"title":"Docling in OpenRAG","permalink":"/ingestion"}}');var t=s(4848),o=s(8453),r=s(1610),l=s(1470),d=s(9365),c=s(3782);const a={title:"OpenSearch in OpenRAG",slug:"/knowledge"},h=void 0,p={},u=[{value:"Authentication and document access",id:"auth",level:2},{value:"Ingest knowledge",id:"ingest-knowledge",level:2},{value:"Direct file ingestion",id:"direct-file-ingestion",level:3},{value:"Ingest files through OAuth connectors",id:"oauth-ingestion",level:3},{value:"Monitor ingestion tasks",id:"monitor-ingestion-tasks",level:2},{value:"Explore knowledge",id:"explore-knowledge",level:2},...c.RM,{value:"Create knowledge filters",id:"create-knowledge-filters",level:2},{value:"OpenRAG default configuration",id:"openrag-default-configuration",level:2}];function g(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(n.p,{children:["OpenRAG uses ",(0,t.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"})," for its vector-backed knowledge store.\nThis is a specialized database for storing and retrieving embeddings, which helps your Agent efficiently find relevant information.\nOpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support."]}),"\n",(0,t.jsx)(n.h2,{id:"auth",children:"Authentication and document access"}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG supports two authentication modes based on how you ",(0,t.jsx)(n.a,{href:"/install",children:"install OpenRAG"}),", and which mode you choose affects document access."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"No-auth mode (Basic Setup)"}),": This mode uses a single anonymous JWT token for OpenSearch authentication, so documents uploaded to the ",(0,t.jsx)(n.code,{children:"documents"})," index by one user are visible to all other users on the OpenRAG server."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"OAuth mode (Advanced Setup)"}),": Each OpenRAG user is granted a JWT token, and each document is tagged with user ownership. Documents are filtered by user ownership, ensuring users only see documents they uploaded or have access to."]}),"\n",(0,t.jsx)(n.h2,{id:"ingest-knowledge",children:"Ingest knowledge"}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG supports knowledge ingestion through direct file uploads and OAuth connectors.\nTo configure the knowledge ingestion pipeline parameters, see ",(0,t.jsx)(n.a,{href:"/ingestion",children:"Docling Ingestion"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"direct-file-ingestion",children:"Direct file ingestion"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow uses Langflow's ",(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/components-data#file",children:[(0,t.jsx)(n.strong,{children:"File"})," component"]})," to split and embed files loaded from your local machine into the OpenSearch database."]}),"\n",(0,t.jsxs)(n.p,{children:["The default path to your local folder is mounted from the ",(0,t.jsx)(n.code,{children:"./openrag-documents"})," folder in your OpenRAG project directory to the ",(0,t.jsx)(n.code,{children:"/app/openrag-documents/"})," directory inside the Docker container. Files added to the host or the container will be visible in both locations. To configure this location, modify the ",(0,t.jsx)(n.strong,{children:"Documents Paths"})," variable in either the TUI's ",(0,t.jsx)(n.a,{href:"/install#setup",children:"Advanced Setup"})," menu or in the ",(0,t.jsx)(n.code,{children:".env"})," used by Docker Compose."]}),"\n",(0,t.jsxs)(n.p,{children:["To load and process a single file from the mapped location, click ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,t.jsx)(r.A,{name:"File","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"File"}),".\nThe file is loaded into your OpenSearch database, and appears in the Knowledge page."]}),"\n",(0,t.jsxs)(n.p,{children:["To load and process a directory from the mapped location, click ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,t.jsx)(r.A,{name:"Folder","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Folder"}),".\nThe files are loaded into your OpenSearch database, and appear in the Knowledge page."]}),"\n",(0,t.jsxs)(n.p,{children:["To add files directly to a chat session, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," in the chat input and select the files you want to include. Files added this way are processed and made available to the agent for the current conversation, and are not permanently added to the knowledge base."]}),"\n",(0,t.jsx)(n.h3,{id:"oauth-ingestion",children:"Ingest files through OAuth connectors"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG supports Google Drive, OneDrive, and Sharepoint as OAuth connectors for seamless document synchronization."}),"\n",(0,t.jsx)(n.p,{children:"OAuth integration allows individual users to connect their personal cloud storage accounts to OpenRAG. Each user must separately authorize OpenRAG to access their own cloud storage files. When a user connects a cloud service, they are redirected to authenticate with that service provider and grant OpenRAG permission to sync documents from their personal cloud storage."}),"\n",(0,t.jsx)(n.p,{children:"Before users can connect their cloud storage accounts, you must configure OAuth credentials in OpenRAG. This requires registering OpenRAG as an OAuth application with a cloud provider and obtaining client ID and secret keys for each service you want to support."}),"\n",(0,t.jsx)(n.p,{children:"To add an OAuth connector to OpenRAG, do the following.\nThis example uses Google OAuth.\nIf you wish to use another provider, add the secrets to another provider."}),"\n",(0,t.jsxs)(l.A,{groupId:"Installation type",children:[(0,t.jsx)(d.A,{value:"TUI",label:"TUI",default:!0,children:(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["If OpenRAG is running, stop it with ",(0,t.jsx)(n.strong,{children:"Status"})," > ",(0,t.jsx)(n.strong,{children:"Stop Services"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,t.jsx)(n.a,{href:"/install#setup",children:"Advanced Setup"})," menu."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Save Configuration"}),".\nThe TUI generates a new ",(0,t.jsx)(n.code,{children:".env"})," file with your OAuth values."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Start Container Services"}),"."]}),"\n"]})}),(0,t.jsx)(d.A,{value:".env",label:".env",children:(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsx)(n.li,{children:"Stop the Docker deployment."}),"\n",(0,t.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,t.jsx)(n.code,{children:".env"})," file for Docker Compose.","\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"GOOGLE_OAUTH_CLIENT_ID='YOUR_OAUTH_CLIENT_ID'\nGOOGLE_OAUTH_CLIENT_SECRET='YOUR_OAUTH_CLIENT_SECRET'\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["Save your ",(0,t.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,t.jsx)(n.li,{children:"Start the Docker deployment."}),"\n"]})})]}),"\n",(0,t.jsxs)(n.p,{children:["The OpenRAG frontend at ",(0,t.jsx)(n.code,{children:"http://localhost:3000"})," now redirects to an OAuth callback login page for your OAuth provider.\nA successful authentication opens OpenRAG with the required scopes for your connected storage."]}),"\n",(0,t.jsx)(n.p,{children:"To add knowledge from an OAuth-connected storage provider, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then select the storage provider, for example, ",(0,t.jsx)(n.strong,{children:"Google Drive"}),".\nThe ",(0,t.jsx)(n.strong,{children:"Add Cloud Knowledge"})," page opens."]}),"\n",(0,t.jsxs)(n.li,{children:["To add files or folders from the connected storage, click ",(0,t.jsx)(n.strong,{children:"Add Files"}),".\nSelect the files or folders you want and click ",(0,t.jsx)(n.strong,{children:"Select"}),".\nYou can select multiple files."]}),"\n",(0,t.jsxs)(n.li,{children:["When your files are selected, click ",(0,t.jsx)(n.strong,{children:"Ingest Files"}),".\nThe ingestion process can take some time depending on the size of your documents."]}),"\n",(0,t.jsx)(n.li,{children:"When ingestion is complete, your documents are available in the Knowledge screen."}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["If ingestion fails, click ",(0,t.jsx)(n.strong,{children:"Status"})," to view the logged error."]}),"\n",(0,t.jsx)(n.h2,{id:"monitor-ingestion-tasks",children:"Monitor ingestion tasks"}),"\n",(0,t.jsxs)(n.p,{children:["When you upload files, process folders, or sync documents, OpenRAG processes them as background tasks.\nA badge appears on the ",(0,t.jsx)(r.A,{name:"Bell","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Tasks"})," icon when there are active tasks running.\nTo open the Tasks menu, click ",(0,t.jsx)(r.A,{name:"Bell","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Tasks"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Active Tasks"})," shows tasks that are currently processing.\nA ",(0,t.jsx)(n.strong,{children:"Pending"})," task is queued and waiting to start, a ",(0,t.jsx)(n.strong,{children:"Running"})," task is actively processing files, and a ",(0,t.jsx)(n.strong,{children:"Processing"})," task is performing ingestion operations. For each active task, you can find the task ID, start time, duration, the number of files processed so far, and the total files."]}),"\n",(0,t.jsxs)(n.p,{children:["You can cancel active tasks by clicking ",(0,t.jsx)(r.A,{name:"X","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Cancel"}),". Canceling a task stops processing immediately and marks the task as failed."]}),"\n",(0,t.jsx)(n.h2,{id:"explore-knowledge",children:"Explore knowledge"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"Knowledge"})," page lists the documents OpenRAG has ingested into the OpenSearch vector database's ",(0,t.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,t.jsxs)(n.p,{children:["To explore your current knowledge, click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"}),".\nClick on a document to display the chunks derived from splitting the default documents into the vector database."]}),"\n",(0,t.jsxs)(n.p,{children:["Documents are processed with the default ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow, so if you want to split your documents differently, edit the ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow."]}),"\n",(0,t.jsx)(c.Ay,{}),"\n",(0,t.jsx)(n.h2,{id:"create-knowledge-filters",children:"Create knowledge filters"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG includes a knowledge filter system for organizing and managing document collections.\nKnowledge filters are saved search configurations that allow you to create custom views of your document collection. They store search queries, filter criteria, and display settings that can be reused across different parts of OpenRAG."}),"\n",(0,t.jsx)(n.p,{children:"Knowledge filters help agents work more efficiently with large document collections by focusing their context within relevant documents sets."}),"\n",(0,t.jsx)(n.p,{children:"To create a knowledge filter, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Knowledge"}),", and then click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge Filters"}),".\nThe ",(0,t.jsx)(n.strong,{children:"Knowledge Filter"})," pane appears."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Enter a ",(0,t.jsx)(n.strong,{children:"Name"})," and ",(0,t.jsx)(n.strong,{children:"Description"}),", and then click ",(0,t.jsx)(n.strong,{children:"Create Filter"}),".\nA new filter is created with default settings that match all documents."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To modify the filter, click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"}),", and then click your new filter to edit it in the ",(0,t.jsx)(n.strong,{children:"Knowledge Filter"})," pane."]}),"\n",(0,t.jsx)(n.p,{children:"The following filter options are configurable."}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Search Query"}),': Enter text for semantic search, such as "financial reports from Q4".']}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Sources"}),": Select specific data sources or folders to include."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Document Types"}),": Filter by file type."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Owners"}),": Filter by who uploaded the documents."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Connectors"}),": Filter by connector types, such as local upload or Google Drive."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Response Limit"}),": Set maximum number of results. The default is ",(0,t.jsx)(n.code,{children:"10"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Score Threshold"}),": Set minimum relevance score. The default score is ",(0,t.jsx)(n.code,{children:"0"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["When you're done editing the filter, click ",(0,t.jsx)(n.strong,{children:"Update Filter"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To apply the filter to OpenRAG globally, click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"}),", and then select the filter to apply. One filter can be enabled at a time."]}),"\n",(0,t.jsxs)(n.p,{children:["To apply the filter to a single chat session, in the ",(0,t.jsx)(r.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Chat"})," window, click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"}),", and then select the filter to apply."]}),"\n",(0,t.jsxs)(n.p,{children:["To delete the filter, in the ",(0,t.jsx)(n.strong,{children:"Knowledge Filter"})," pane, click ",(0,t.jsx)(n.strong,{children:"Delete Filter"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"openrag-default-configuration",children:"OpenRAG default configuration"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG automatically detects and configures the correct vector dimensions for embedding models, ensuring optimal search performance and compatibility."}),"\n",(0,t.jsxs)(n.p,{children:["The complete list of supported models is available at ",(0,t.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/services/models_service.py",children:[(0,t.jsx)(n.code,{children:"models_service.py"})," in the OpenRAG repository"]}),"."]}),"\n",(0,t.jsx)(n.p,{children:"You can use custom embedding models by specifying them in your configuration."}),"\n",(0,t.jsxs)(n.p,{children:["If you use an unknown embedding model, OpenRAG automatically falls back to ",(0,t.jsx)(n.code,{children:"1536"})," dimensions and logs a warning. The system continues to work, but search quality can be affected if the actual model dimensions differ from ",(0,t.jsx)(n.code,{children:"1536"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["The default embedding dimension is ",(0,t.jsx)(n.code,{children:"1536"})," and the default model is ",(0,t.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["For models with known vector dimensions, see ",(0,t.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/config/settings.py",children:[(0,t.jsx)(n.code,{children:"settings.py"})," in the OpenRAG repository"]}),"."]})]})}function x(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(g,{...e})}):g(e)}},3782:(e,n,s)=>{s.d(n,{Ay:()=>d,RM:()=>r});var i=s(4848),t=s(8453),o=s(1610);const r=[];function l(e){const n={a:"a",p:"p",strong:"strong",...(0,t.R)(),...e.components};return(0,i.jsxs)(n.p,{children:["All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic.\nTo modify a flow, click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nOpenRAG's visual editor is based on the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),", so you can edit your flows to match your specific use case."]})}function d(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(l,{...e})}):l(e)}}}]); \ No newline at end of file diff --git a/assets/js/0ba6a408.dd2959ac.js b/assets/js/0ba6a408.dd2959ac.js new file mode 100644 index 00000000..198a1846 --- /dev/null +++ b/assets/js/0ba6a408.dd2959ac.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[571],{3227:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>h,contentTitle:()=>c,default:()=>g,frontMatter:()=>l,metadata:()=>t,toc:()=>u});const t=JSON.parse('{"id":"core-components/knowledge","title":"Configure knowledge","description":"OpenRAG includes a built-in OpenSearch instance that serves as the underlying datastore for your knowledge (documents).","source":"@site/docs/core-components/knowledge.mdx","sourceDirName":"core-components","slug":"/knowledge","permalink":"/knowledge","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/core-components/knowledge.mdx","tags":[],"version":"current","frontMatter":{"title":"Configure knowledge","slug":"/knowledge"},"sidebar":"tutorialSidebar","previous":{"title":"Flows","permalink":"/agents"},"next":{"title":"Ingest knowledge","permalink":"/ingestion"}}');var i=s(4848),o=s(8453),r=s(1610),a=s(1470),d=s(9365);const l={title:"Configure knowledge",slug:"/knowledge"},c=void 0,h={},u=[{value:"Browse knowledge",id:"browse-knowledge",level:2},{value:"OpenSearch authentication and document access",id:"auth",level:2},{value:"OpenSearch indexes",id:"opensearch-indexes",level:2},{value:"Knowledge ingestion settings",id:"knowledge-ingestion-settings",level:2},{value:"Set the embedding model and dimensions",id:"set-the-embedding-model-and-dimensions",level:3},{value:"Set Docling parameters",id:"set-docling-parameters",level:3},{value:"Set the local documents path",id:"set-the-local-documents-path",level:3},{value:"Delete knowledge",id:"delete-knowledge",level:2},{value:"See also",id:"see-also",level:2}];function p(e){const n={a:"a",admonition:"admonition",code:"code",em:"em",h2:"h2",h3:"h3",li:"li",p:"p",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsxs)(n.p,{children:["OpenRAG includes a built-in ",(0,i.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"})," instance that serves as the underlying datastore for your ",(0,i.jsx)(n.em,{children:"knowledge"})," (documents).\nThis specialized database is used to store and retrieve your documents and the associated vector data (embeddings)."]}),"\n",(0,i.jsxs)(n.p,{children:["The documents in your OpenSearch knowledge base provide specialized context in addition to the general knowledge available to the language model that you select when you ",(0,i.jsx)(n.a,{href:"/install",children:"install OpenRAG"})," or ",(0,i.jsx)(n.a,{href:"/agents",children:"edit a flow"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["You can ",(0,i.jsx)(n.a,{href:"/ingestion",children:"upload documents"})," from a variety of sources to populate your knowledge base with unique content, such as your own company documents, research papers, or websites.\nDocuments are processed through OpenRAG's knowledge ingestion flows with Docling."]}),"\n",(0,i.jsxs)(n.p,{children:["Then, the ",(0,i.jsxs)(n.a,{href:"/chat",children:["OpenRAG ",(0,i.jsx)(n.strong,{children:"Chat"})]})," can run ",(0,i.jsx)(n.a,{href:"https://www.ibm.com/think/topics/vector-search",children:"similarity searches"})," against your OpenSearch database to retrieve relevant information and generate context-aware responses."]}),"\n",(0,i.jsxs)(n.p,{children:["You can configure how documents are ingested and how the ",(0,i.jsx)(n.strong,{children:"Chat"})," interacts with your knowledge base."]}),"\n",(0,i.jsx)(n.h2,{id:"browse-knowledge",children:"Browse knowledge"}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Knowledge"})," page lists the documents OpenRAG has ingested into your OpenSearch database, specifically in an ",(0,i.jsx)(n.a,{href:"https://docs.opensearch.org/latest/getting-started/intro/#index",children:"OpenSearch index"})," named ",(0,i.jsx)(n.code,{children:"documents"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To explore the raw contents of your knowledge base, click ",(0,i.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Knowledge"})," to get a list of all ingested documents.\nClick a document to view the chunks produced from splitting the document during ingestion."]}),"\n",(0,i.jsxs)(n.p,{children:["OpenRAG includes some initial documents about OpenRAG. You can use these documents to ask OpenRAG about itself, and to test the ",(0,i.jsx)(n.a,{href:"/chat",children:(0,i.jsx)(n.strong,{children:"Chat"})})," feature before uploading your own documents.\nIf you ",(0,i.jsx)(n.a,{href:"#delete-knowledge",children:"delete these documents"}),", you won't be able to ask OpenRAG about itself and it's own functionality.\nIt is recommended that you keep these documents, and use ",(0,i.jsx)(n.a,{href:"/knowledge-filters",children:"filters"})," to separate them from your other knowledge."]}),"\n",(0,i.jsx)(n.h2,{id:"auth",children:"OpenSearch authentication and document access"}),"\n",(0,i.jsxs)(n.p,{children:["When you ",(0,i.jsx)(n.a,{href:"/install",children:"install OpenRAG"}),", you can choose between two setup modes: ",(0,i.jsx)(n.strong,{children:"Basic Setup"})," and ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),".\nThe mode you choose determines how OpenRAG authenticates with OpenSearch and controls access to documents:"]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Basic Setup (no-auth mode)"}),": If you choose ",(0,i.jsx)(n.strong,{children:"Basic Setup"}),", then OpenRAG is installed in no-auth mode.\nThis mode uses one, anonymous JWT token for OpenSearch authentication.\nThere is no differentiation between users.\nAll users that access your OpenRAG instance can access all documents uploaded to your OpenSearch knowledge base."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Advanced Setup (OAuth mode)"}),": If you choose ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),", then OpenRAG is installed in OAuth mode.\nThis mode uses a unique JWT token for each OpenRAG user, and each document is tagged with user ownership. Documents are filtered by user owner.\nThis means users see only the documents that they uploaded or have access to."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["You can enable OAuth mode after installation.\nFor more information, see ",(0,i.jsx)(n.a,{href:"/ingestion#oauth-ingestion",children:"Ingest files with OAuth connectors"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"opensearch-indexes",children:"OpenSearch indexes"}),"\n",(0,i.jsxs)(n.p,{children:["An ",(0,i.jsx)(n.a,{href:"https://docs.opensearch.org/latest/getting-started/intro/#index",children:"OpenSearch index"})," is a collection of documents in an OpenSearch database."]}),"\n",(0,i.jsxs)(n.p,{children:["By default, all documents you upload to your OpenRAG knowledge base are stored in an index named ",(0,i.jsx)(n.code,{children:"documents"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["It is possible to change the index name by ",(0,i.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"editing the ingestion flow"}),".\nHowever, this can impact dependent processes, such as the ",(0,i.jsx)(n.a,{href:"/knowledge-filters",children:"filters"})," and ",(0,i.jsx)(n.a,{href:"/chat",children:(0,i.jsx)(n.strong,{children:"Chat"})})," flow, that reference the ",(0,i.jsx)(n.code,{children:"documents"})," index by default.\nMake sure you edit other flows as needed to ensure all processes use the same index name."]}),"\n",(0,i.jsxs)(n.p,{children:["If you encounter errors or unexpected behavior after changing the index name, you can ",(0,i.jsx)(n.a,{href:"/agents#revert-a-built-in-flow-to-its-original-configuration",children:"revert the flows to their original configuration"}),", or ",(0,i.jsx)(n.a,{href:"/knowledge#delete-knowledge",children:"delete knowledge"})," to clear the existing documents from your knowledge base."]}),"\n",(0,i.jsx)(n.h2,{id:"knowledge-ingestion-settings",children:"Knowledge ingestion settings"}),"\n",(0,i.jsx)(n.admonition,{type:"warning",children:(0,i.jsx)(n.p,{children:"Knowledge ingestion settings apply to documents you upload after making the changes.\nDocuments uploaded before changing these settings aren't reprocessed."})}),"\n",(0,i.jsx)(n.p,{children:"After changing knowledge ingestion settings, you must determine if you need to reupload any documents to be consistent with the new settings."}),"\n",(0,i.jsx)(n.p,{children:"It isn't always necessary to reupload documents after changing knowledge ingestion settings.\nFor example, it is typical to upload some documents with OCR enabled and others without OCR enabled."}),"\n",(0,i.jsxs)(n.p,{children:["If needed, you can use ",(0,i.jsx)(n.a,{href:"/knowledge-filters",children:"filters"})," to separate documents that you uploaded with different settings, such as different embedding models."]}),"\n",(0,i.jsx)(n.h3,{id:"set-the-embedding-model-and-dimensions",children:"Set the embedding model and dimensions"}),"\n",(0,i.jsxs)(n.p,{children:["When you ",(0,i.jsx)(n.a,{href:"/install",children:"install OpenRAG"}),", you select at least one embedding model during ",(0,i.jsx)(n.a,{href:"/install#application-onboarding",children:"application onboarding"}),".\nOpenRAG automatically detects and configures the appropriate vector dimensions for your selected embedding model, ensuring optimal search performance and compatibility."]}),"\n",(0,i.jsxs)(n.p,{children:["In the OpenRAG repository, you can find the complete list of supported models in ",(0,i.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/services/models_service.py",children:(0,i.jsx)(n.code,{children:"models_service.py"})})," and the corresponding vector dimensions in ",(0,i.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/config/settings.py",children:(0,i.jsx)(n.code,{children:"settings.py"})}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["During application onboarding, you can select from the supported models.\nThe default embedding dimension is ",(0,i.jsx)(n.code,{children:"1536"}),", and the default model is the OpenAI ",(0,i.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["If you want to use an unsupported model, you must manually set the model in your ",(0,i.jsx)(n.a,{href:"/reference/configuration",children:"OpenRAG configuration"}),".\nIf you use an unsupported embedding model that doesn't have defined dimensions in ",(0,i.jsx)(n.code,{children:"settings.py"}),", then OpenRAG falls back to the default dimensions (1536) and logs a warning. OpenRAG's OpenSearch instance and flows continue to work, but ",(0,i.jsx)(n.a,{href:"https://www.ibm.com/think/topics/vector-search",children:"similarity search"})," quality can be affected if the actual model dimensions aren't 1536."]}),"\n",(0,i.jsxs)(n.p,{children:["To change the embedding model after onboarding, it is recommended that you modify the embedding model setting in the OpenRAG ",(0,i.jsx)(n.strong,{children:"Settings"})," page or in your ",(0,i.jsx)(n.a,{href:"/reference/configuration",children:"OpenRAG configuration"}),".\nThis will automatically update all relevant ",(0,i.jsx)(n.a,{href:"/agents",children:"OpenRAG flows"})," to use the new embedding model configuration."]}),"\n",(0,i.jsx)(n.h3,{id:"set-docling-parameters",children:"Set Docling parameters"}),"\n",(0,i.jsxs)(n.p,{children:["OpenRAG uses ",(0,i.jsx)(n.a,{href:"https://docling-project.github.io/docling/",children:"Docling"})," for document ingestion because it supports many file formats, processes tables and images well, and performs efficiently."]}),"\n",(0,i.jsxs)(n.p,{children:["When you ",(0,i.jsx)(n.a,{href:"/ingestion",children:"upload documents"}),", Docling processes the files, splits them into chunks, and stores them as separate, structured documents in your OpenSearch knowledge base."]}),"\n",(0,i.jsx)(n.p,{children:"You can use either Docling Serve or OpenRAG's built-in Docling ingestion pipeline to process documents."}),"\n",(0,i.jsxs)(a.A,{children:[(0,i.jsx)(d.A,{value:"serve",label:"Docling Serve ingestion",default:!0,children:(0,i.jsxs)(n.p,{children:["By default, OpenRAG uses ",(0,i.jsx)(n.a,{href:"https://github.com/docling-project/docling-serve",children:"Docling Serve"}),".\nThis means that OpenRAG starts a ",(0,i.jsx)(n.code,{children:"docling serve"})," process on your local machine and runs Docling ingestion through an API service."]})}),(0,i.jsxs)(d.A,{value:"docling",label:"Built-in Docling ingestion",children:[(0,i.jsxs)(n.p,{children:["If you want to use OpenRAG's built-in Docling ingestion pipeline instead of the separate Docling Serve service, set ",(0,i.jsx)(n.code,{children:"DISABLE_INGEST_WITH_LANGFLOW=true"})," in your ",(0,i.jsx)(n.a,{href:"/reference/configuration#document-processing",children:"OpenRAG environment variables"}),"."]}),(0,i.jsx)(n.p,{children:"The built-in pipeline uses the Docling processor directly instead of through the Docling Serve API."}),(0,i.jsxs)(n.p,{children:["For the underlying functionality, see ",(0,i.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/models/processors.py#L58",children:(0,i.jsx)(n.code,{children:"processors.py"})})," in the OpenRAG repository."]})]})]}),"\n",(0,i.jsxs)(n.p,{children:["To modify the Docling ingestion and embedding parameters, click ",(0,i.jsx)(r.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"})," in the OpenRAG user interface."]}),"\n",(0,i.jsx)(n.admonition,{type:"tip",children:(0,i.jsxs)(n.p,{children:["OpenRAG warns you if ",(0,i.jsx)(n.code,{children:"docling serve"})," isn't running.\nYou can ",(0,i.jsx)(n.a,{href:"/install#tui-container-management",children:"start and stop OpenRAG services"})," from the TUI main menu with ",(0,i.jsx)(n.strong,{children:"Start Native Services"})," or ",(0,i.jsx)(n.strong,{children:"Stop Native Services"}),"."]})}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Embedding model"}),": Select the model to use to generate vector embeddings for your documents."]}),"\n",(0,i.jsxs)(n.p,{children:["This is initially set during installation.\nThe recommended way to change this setting is in the OpenRAG ",(0,i.jsx)(n.strong,{children:"Settings"})," or your ",(0,i.jsx)(n.a,{href:"/reference/configuration",children:"OpenRAG configuration"}),".\nThis will automatically update all relevant ",(0,i.jsx)(n.a,{href:"/agents",children:"OpenRAG flows"})," to use the new embedding model configuration."]}),"\n",(0,i.jsxs)(n.p,{children:["If you uploaded documents prior to changing the embedding model, you can ",(0,i.jsx)(n.a,{href:"/knowledge-filters",children:"create filters"})," to separate documents embedded with different models, or you can reupload all documents to regenerate embeddings with the new model.\nIf you want to use multiple embeddings models, similarity search (in the ",(0,i.jsx)(n.strong,{children:"Chat"}),") can take longer as it searching each model's embeddings separately."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Chunk size"}),": Set the number of characters for each text chunk when breaking down a file.\nLarger chunks yield more context per chunk, but can include irrelevant information. Smaller chunks yield more precise semantic search, but can lack context.\nThe default value is 1000 characters, which is usually a good balance between context and precision."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Chunk overlap"}),": Set the number of characters to overlap over chunk boundaries.\nUse larger overlap values for documents where context is most important. Use smaller overlap values for simpler documents or when optimization is most important.\nThe default value is 200 characters, which represents an overlap of 20 percent if the ",(0,i.jsx)(n.strong,{children:"Chunk size"})," is 1000. This is suitable for general use. For faster processing, decrease the overlap to approximately 10 percent. For more complex documents where you need to preserve context across chunks, increase it to approximately 40 percent."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Table Structure"}),": Enables Docling's ",(0,i.jsx)(n.a,{href:"https://docling-project.github.io/docling/reference/document_converter/",children:(0,i.jsx)(n.code,{children:"DocumentConverter"})})," tool for parsing tables. Instead of treating tables as plain text, tables are output as structured table data with preserved relationships and metadata. This option is enabled by default."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"OCR"}),": Enables Optical Character Recognition (OCR) processing when extracting text from images and ingesting scanned documents. This setting is best suited for processing text-based documents faster with Docling's ",(0,i.jsx)(n.a,{href:"https://docling-project.github.io/docling/reference/document_converter/",children:(0,i.jsx)(n.code,{children:"DocumentConverter"})}),". Images are ignored and not processed."]}),"\n",(0,i.jsx)(n.p,{children:"This option is disabled by default. Enabling OCR can slow ingestion performance."}),"\n",(0,i.jsxs)(n.p,{children:["If OpenRAG detects that the local machine is running on macOS, OpenRAG uses the ",(0,i.jsx)(n.a,{href:"https://www.piwheels.org/project/ocrmac/",children:"ocrmac"})," OCR engine. Other platforms use ",(0,i.jsx)(n.a,{href:"https://www.jaided.ai/easyocr/",children:"easyocr"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Picture descriptions"}),": Only applicable if ",(0,i.jsx)(n.strong,{children:"OCR"})," is enabled. Adds image descriptions generated by the ",(0,i.jsx)(n.a,{href:"https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct",children:(0,i.jsx)(n.code,{children:"SmolVLM-256M-Instruct"})})," model. Enabling picture descriptions can slow ingestion performance."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h3,{id:"set-the-local-documents-path",children:"Set the local documents path"}),"\n",(0,i.jsxs)(n.p,{children:["The default path for local uploads is the ",(0,i.jsx)(n.code,{children:"./openrag-documents"})," subdirectory in your OpenRAG installation directory. This is mounted to the ",(0,i.jsx)(n.code,{children:"/app/openrag-documents/"})," directory inside the OpenRAG container. 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188:this.$={stmt:"dir",value:"LR"}}},"anonymous"),table:[{3:1,4:2,9:e,10:s,12:i},{1:[3]},t(n,r,{5:6}),{4:7,9:e,10:s,12:i},{4:8,9:e,10:s,12:i},{13:[1,9],14:[1,10]},{1:[2,1],6:11,7:12,8:a,9:u,10:o,11:c,20:17,22:18,23:19,24:20,25:21,26:22,27:l,33:24,34:d,36:p,38:g,42:28,43:38,44:A,45:39,47:40,60:b,84:k,85:y,86:f,87:m,88:E,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v,121:w,122:L,123:$,124:I},t(n,[2,9]),t(n,[2,10]),t(n,[2,11]),{8:[1,54],9:[1,55],10:R,15:53,18:56},t(N,[2,3]),t(N,[2,4]),t(N,[2,5]),t(N,[2,6]),t(N,[2,7]),t(N,[2,8]),{8:P,9:G,11:K,21:58,41:59,72:63,75:[1,64],77:[1,66],78:[1,65]},{8:P,9:G,11:K,21:67},{8:P,9:G,11:K,21:68},{8:P,9:G,11:K,21:69},{8:P,9:G,11:K,21:70},{8:P,9:G,11:K,21:71},{8:P,9:G,10:[1,72],11:K,21:73},t(N,[2,36]),{35:[1,74]},{37:[1,75]},t(N,[2,39]),t(O,[2,50],{18:76,39:77,10:R,40:M}),{10:[1,79]},{10:[1,80]},{10:[1,81]},{10:[1,82]},{14:U,44:V,60:W,80:[1,86],89:Y,95:[1,83],97:[1,84],101:85,105:j,106:z,109:X,111:H,114:q,115:Q,116:Z,120:87},t(N,[2,185]),t(N,[2,186]),t(N,[2,187]),t(N,[2,188]),t(J,[2,51]),t(J,[2,54],{46:[1,99]}),t(tt,[2,72],{113:112,29:[1,100],44:A,48:[1,101],50:[1,102],52:[1,103],54:[1,104],56:[1,105],58:[1,106],60:b,63:[1,107],65:[1,108],67:[1,109],68:[1,110],70:[1,111],89:C,102:D,105:x,106:T,109:S,111:F,114:_,115:B,116:v}),t(et,[2,181]),t(et,[2,142]),t(et,[2,143]),t(et,[2,144]),t(et,[2,145]),t(et,[2,146]),t(et,[2,147]),t(et,[2,148]),t(et,[2,149]),t(et,[2,150]),t(et,[2,151]),t(et,[2,152]),t(n,[2,12]),t(n,[2,18]),t(n,[2,19]),{9:[1,113]},t(st,[2,26],{18:114,10:R}),t(N,[2,27]),{42:115,43:38,44:A,45:39,47:40,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},t(N,[2,40]),t(N,[2,41]),t(N,[2,42]),t(it,[2,76],{73:116,62:[1,118],74:[1,117]}),{76:119,79:120,80:nt,81:rt,116:at,119:ut},{75:[1,125],77:[1,126]},t(ot,[2,83]),t(N,[2,28]),t(N,[2,29]),t(N,[2,30]),t(N,[2,31]),t(N,[2,32]),{10:ct,12:lt,14:ht,27:dt,28:127,32:pt,44:gt,60:At,75:bt,80:[1,129],81:[1,130],83:140,84:kt,85:yt,86:ft,87:mt,88:Et,89:Ct,90:Dt,91:128,105:xt,109:Tt,111:St,114:Ft,115:_t,116:Bt},t(vt,r,{5:153}),t(N,[2,37]),t(N,[2,38]),t(O,[2,48],{44:wt}),t(O,[2,49],{18:155,10:R,40:Lt}),t(J,[2,44]),{44:A,47:157,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},{102:[1,158],103:159,105:[1,160]},{44:A,47:161,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},{44:A,47:162,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},t($t,[2,107],{10:[1,163],96:[1,164]}),{80:[1,165]},t($t,[2,115],{120:167,10:[1,166],14:U,44:V,60:W,89:Y,105:j,106:z,109:X,111:H,114:q,115:Q,116:Z}),t($t,[2,117],{10:[1,168]}),t(It,[2,183]),t(It,[2,170]),t(It,[2,171]),t(It,[2,172]),t(It,[2,173]),t(It,[2,174]),t(It,[2,175]),t(It,[2,176]),t(It,[2,177]),t(It,[2,178]),t(It,[2,179]),t(It,[2,180]),{44:A,47:169,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},{30:170,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:178,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:180,50:[1,179],67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:181,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:182,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:183,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{109:[1,184]},{30:185,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:186,65:[1,187],67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:188,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:189,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:190,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},t(et,[2,182]),t(n,[2,20]),t(st,[2,25]),t(O,[2,46],{39:191,18:192,10:R,40:M}),t(it,[2,73],{10:[1,193]}),{10:[1,194]},{30:195,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{77:[1,196],79:197,116:at,119:ut},t(Mt,[2,79]),t(Mt,[2,81]),t(Mt,[2,82]),t(Mt,[2,168]),t(Mt,[2,169]),{76:198,79:120,80:nt,81:rt,116:at,119:ut},t(ot,[2,84]),{8:P,9:G,10:ct,11:K,12:lt,14:ht,21:200,27:dt,29:[1,199],32:pt,44:gt,60:At,75:bt,83:140,84:kt,85:yt,86:ft,87:mt,88:Et,89:Ct,90:Dt,91:201,105:xt,109:Tt,111:St,114:Ft,115:_t,116:Bt},t(Ut,[2,101]),t(Ut,[2,103]),t(Ut,[2,104]),t(Ut,[2,157]),t(Ut,[2,158]),t(Ut,[2,159]),t(Ut,[2,160]),t(Ut,[2,161]),t(Ut,[2,162]),t(Ut,[2,163]),t(Ut,[2,164]),t(Ut,[2,165]),t(Ut,[2,166]),t(Ut,[2,167]),t(Ut,[2,90]),t(Ut,[2,91]),t(Ut,[2,92]),t(Ut,[2,93]),t(Ut,[2,94]),t(Ut,[2,95]),t(Ut,[2,96]),t(Ut,[2,97]),t(Ut,[2,98]),t(Ut,[2,99]),t(Ut,[2,100]),{6:11,7:12,8:a,9:u,10:o,11:c,20:17,22:18,23:19,24:20,25:21,26:22,27:l,32:[1,202],33:24,34:d,36:p,38:g,42:28,43:38,44:A,45:39,47:40,60:b,84:k,85:y,86:f,87:m,88:E,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v,121:w,122:L,123:$,124:I},{10:R,18:203},{44:[1,204]},t(J,[2,43]),{10:[1,205],44:A,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:112,114:_,115:B,116:v},{10:[1,206]},{10:[1,207],106:[1,208]},t(Vt,[2,128]),{10:[1,209],44:A,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:112,114:_,115:B,116:v},{10:[1,210],44:A,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:112,114:_,115:B,116:v},{80:[1,211]},t($t,[2,109],{10:[1,212]}),t($t,[2,111],{10:[1,213]}),{80:[1,214]},t(It,[2,18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F=[],a[E])this.terminals_[x]&&x>2&&F.push("'"+this.terminals_[x]+"'");B=p.showPosition?"Parse error on line "+(o+1)+":\n"+p.showPosition()+"\nExpecting "+F.join(", ")+", got '"+(this.terminals_[f]||f)+"'":"Parse error on line "+(o+1)+": Unexpected "+(1==f?"end of input":"'"+(this.terminals_[f]||f)+"'"),this.parseError(B,{text:p.match,token:this.terminals_[f]||f,line:p.yylineno,loc:b,expected:F})}if(C[0]instanceof Array&&C.length>1)throw new Error("Parse Error: multiple actions possible at state: "+E+", token: "+f);switch(C[0]){case 1:s.push(f),n.push(p.yytext),r.push(p.yylloc),s.push(C[1]),f=null,m?(f=m,m=null):(c=p.yyleng,u=p.yytext,o=p.yylineno,b=p.yylloc,l>0&&l--);break;case 2:if(T=this.productions_[C[1]][1],_.$=n[n.length-T],_._$={first_line:r[r.length-(T||1)].first_line,last_line:r[r.length-1].last_line,first_column:r[r.length-(T||1)].first_column,last_column:r[r.length-1].last_column},k&&(_._$.range=[r[r.length-(T||1)].range[0],r[r.length-1].range[1]]),void 0!==(D=this.performAction.apply(_,[u,c,o,g.yy,C[1],n,r].concat(d))))return D;T&&(s=s.slice(0,-1*T*2),n=n.slice(0,-1*T),r=r.slice(0,-1*T)),s.push(this.productions_[C[1]][0]),n.push(_.$),r.push(_._$),S=a[s[s.length-2]][s[s.length-1]],s.push(S);break;case 3:return!0}}return!0},"parse")},ie=function(){return{EOF:1,parseError:(0,h.K2)(function(t,e){if(!this.yy.parser)throw new Error(t);this.yy.parser.parseError(t,e)},"parseError"),setInput:(0,h.K2)(function(t,e){return this.yy=e||this.yy||{},this._input=t,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:(0,h.K2)(function(){var t=this._input[0];return this.yytext+=t,this.yyleng++,this.offset++,this.match+=t,this.matched+=t,t.match(/(?:\r\n?|\n).*/g)?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),t},"input"),unput:(0,h.K2)(function(t){var e=t.length,s=t.split(/(?:\r\n?|\n)/g);this._input=t+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-e),this.offset-=e;var i=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),s.length-1&&(this.yylineno-=s.length-1);var n=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:s?(s.length===i.length?this.yylloc.first_column:0)+i[i.length-s.length].length-s[0].length:this.yylloc.first_column-e},this.options.ranges&&(this.yylloc.range=[n[0],n[0]+this.yyleng-e]),this.yyleng=this.yytext.length,this},"unput"),more:(0,h.K2)(function(){return this._more=!0,this},"more"),reject:(0,h.K2)(function(){return this.options.backtrack_lexer?(this._backtrack=!0,this):this.parseError("Lexical error on line "+(this.yylineno+1)+". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"reject"),less:(0,h.K2)(function(t){this.unput(this.match.slice(t))},"less"),pastInput:(0,h.K2)(function(){var t=this.matched.substr(0,this.matched.length-this.match.length);return(t.length>20?"...":"")+t.substr(-20).replace(/\n/g,"")},"pastInput"),upcomingInput:(0,h.K2)(function(){var t=this.match;return t.length<20&&(t+=this._input.substr(0,20-t.length)),(t.substr(0,20)+(t.length>20?"...":"")).replace(/\n/g,"")},"upcomingInput"),showPosition:(0,h.K2)(function(){var t=this.pastInput(),e=new Array(t.length+1).join("-");return t+this.upcomingInput()+"\n"+e+"^"},"showPosition"),test_match:(0,h.K2)(function(t,e){var s,i,n;if(this.options.backtrack_lexer&&(n={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(n.yylloc.range=this.yylloc.range.slice(0))),(i=t[0].match(/(?:\r\n?|\n).*/g))&&(this.yylineno+=i.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:i?i[i.length-1].length-i[i.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+t[0].length},this.yytext+=t[0],this.match+=t[0],this.matches=t,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(t[0].length),this.matched+=t[0],s=this.performAction.call(this,this.yy,this,e,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),s)return s;if(this._backtrack){for(var r in n)this[r]=n[r];return!1}return!1},"test_match"),next:(0,h.K2)(function(){if(this.done)return this.EOF;var t,e,s,i;this._input||(this.done=!0),this._more||(this.yytext="",this.match="");for(var n=this._currentRules(),r=0;re[0].length)){if(e=s,i=r,this.options.backtrack_lexer){if(!1!==(t=this.test_match(s,n[r])))return t;if(this._backtrack){e=!1;continue}return!1}if(!this.options.flex)break}return e?!1!==(t=this.test_match(e,n[i]))&&t:""===this._input?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+". Unrecognized text.\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"next"),lex:(0,h.K2)(function(){var t=this.next();return t||this.lex()},"lex"),begin:(0,h.K2)(function(t){this.conditionStack.push(t)},"begin"),popState:(0,h.K2)(function(){return this.conditionStack.length-1>0?this.conditionStack.pop():this.conditionStack[0]},"popState"),_currentRules:(0,h.K2)(function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},"_currentRules"),topState:(0,h.K2)(function(t){return(t=this.conditionStack.length-1-Math.abs(t||0))>=0?this.conditionStack[t]:"INITIAL"},"topState"),pushState:(0,h.K2)(function(t){this.begin(t)},"pushState"),stateStackSize:(0,h.K2)(function(){return this.conditionStack.length},"stateStackSize"),options:{},performAction:(0,h.K2)(function(t,e,s,i){switch(s){case 0:return this.begin("acc_title"),34;case 1:return this.popState(),"acc_title_value";case 2:return this.begin("acc_descr"),36;case 3:return this.popState(),"acc_descr_value";case 4:this.begin("acc_descr_multiline");break;case 5:case 12:case 14:case 17:case 20:case 23:case 33:this.popState();break;case 6:return"acc_descr_multiline_value";case 7:return this.pushState("shapeData"),e.yytext="",40;case 8:return this.pushState("shapeDataStr"),40;case 9:return this.popState(),40;case 10:const s=/\n\s*/g;return e.yytext=e.yytext.replace(s,"
"),40;case 11:return 40;case 13:this.begin("callbackname");break;case 15:this.popState(),this.begin("callbackargs");break;case 16:return 95;case 18:return 96;case 19:return"MD_STR";case 21:this.begin("md_string");break;case 22:return"STR";case 24:this.pushState("string");break;case 25:return 84;case 26:return 102;case 27:return 85;case 28:return 104;case 29:return 86;case 30:return 87;case 31:return 97;case 32:this.begin("click");break;case 34:return 88;case 35:case 36:case 37:return t.lex.firstGraph()&&this.begin("dir"),12;case 38:return 27;case 39:return 32;case 40:case 41:case 42:case 43:return 98;case 44:return this.popState(),13;case 45:case 46:case 47:case 48:case 49:case 50:case 51:case 52:case 53:case 54:return this.popState(),14;case 55:return 121;case 56:return 122;case 57:return 123;case 58:return 124;case 59:return 78;case 60:return 105;case 61:case 102:return 111;case 62:return 46;case 63:return 60;case 64:case 103:return 44;case 65:return 8;case 66:return 106;case 67:case 101:return 115;case 68:case 71:case 74:return this.popState(),77;case 69:return this.pushState("edgeText"),75;case 70:case 73:case 76:return 119;case 72:return this.pushState("thickEdgeText"),75;case 75:return this.pushState("dottedEdgeText"),75;case 77:return 77;case 78:return this.popState(),53;case 79:case 115:return"TEXT";case 80:return this.pushState("ellipseText"),52;case 81:return this.popState(),55;case 82:return this.pushState("text"),54;case 83:return this.popState(),57;case 84:return this.pushState("text"),56;case 85:return 58;case 86:return this.pushState("text"),67;case 87:return this.popState(),64;case 88:return this.pushState("text"),63;case 89:return this.popState(),49;case 90:return this.pushState("text"),48;case 91:return this.popState(),69;case 92:return this.popState(),71;case 93:return 117;case 94:return this.pushState("trapText"),68;case 95:return this.pushState("trapText"),70;case 96:return 118;case 97:return 67;case 98:return 90;case 99:return"SEP";case 100:return 89;case 104:return 109;case 105:return 114;case 106:return 116;case 107:return this.popState(),62;case 108:return this.pushState("text"),62;case 109:return this.popState(),51;case 110:return this.pushState("text"),50;case 111:return this.popState(),31;case 112:return this.pushState("text"),29;case 113:return this.popState(),66;case 114:return this.pushState("text"),65;case 116:return"QUOTE";case 117:return 9;case 118:return 10;case 119:return 11}},"anonymous"),rules:[/^(?:accTitle\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*\{\s*)/,/^(?:[\}])/,/^(?:[^\}]*)/,/^(?:@\{)/,/^(?:["])/,/^(?:["])/,/^(?:[^\"]+)/,/^(?:[^}^"]+)/,/^(?:\})/,/^(?:call[\s]+)/,/^(?:\([\s]*\))/,/^(?:\()/,/^(?:[^(]*)/,/^(?:\))/,/^(?:[^)]*)/,/^(?:[^`"]+)/,/^(?:[`]["])/,/^(?:["][`])/,/^(?:[^"]+)/,/^(?:["])/,/^(?:["])/,/^(?:style\b)/,/^(?:default\b)/,/^(?:linkStyle\b)/,/^(?:interpolate\b)/,/^(?:classDef\b)/,/^(?:class\b)/,/^(?:href[\s])/,/^(?:click[\s]+)/,/^(?:[\s\n])/,/^(?:[^\s\n]*)/,/^(?:flowchart-elk\b)/,/^(?:graph\b)/,/^(?:flowchart\b)/,/^(?:subgraph\b)/,/^(?:end\b\s*)/,/^(?:_self\b)/,/^(?:_blank\b)/,/^(?:_parent\b)/,/^(?:_top\b)/,/^(?:(\r?\n)*\s*\n)/,/^(?:\s*LR\b)/,/^(?:\s*RL\b)/,/^(?:\s*TB\b)/,/^(?:\s*BT\b)/,/^(?:\s*TD\b)/,/^(?:\s*BR\b)/,/^(?:\s*<)/,/^(?:\s*>)/,/^(?:\s*\^)/,/^(?:\s*v\b)/,/^(?:.*direction\s+TB[^\n]*)/,/^(?:.*direction\s+BT[^\n]*)/,/^(?:.*direction\s+RL[^\n]*)/,/^(?:.*direction\s+LR[^\n]*)/,/^(?:[^\s\"]+@(?=[^\{\"]))/,/^(?:[0-9]+)/,/^(?:#)/,/^(?::::)/,/^(?::)/,/^(?:&)/,/^(?:;)/,/^(?:,)/,/^(?:\*)/,/^(?:\s*[xo<]?--+[-xo>]\s*)/,/^(?:\s*[xo<]?--\s*)/,/^(?:[^-]|-(?!-)+)/,/^(?:\s*[xo<]?==+[=xo>]\s*)/,/^(?:\s*[xo<]?==\s*)/,/^(?:[^=]|=(?!))/,/^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,/^(?:\s*[xo<]?-\.\s*)/,/^(?:[^\.]|\.(?!))/,/^(?:\s*~~[\~]+\s*)/,/^(?:[-/\)][\)])/,/^(?:[^\(\)\[\]\{\}]|!\)+)/,/^(?:\(-)/,/^(?:\]\))/,/^(?:\(\[)/,/^(?:\]\])/,/^(?:\[\[)/,/^(?:\[\|)/,/^(?:>)/,/^(?:\)\])/,/^(?:\[\()/,/^(?:\)\)\))/,/^(?:\(\(\()/,/^(?:[\\(?=\])][\]])/,/^(?:\/(?=\])\])/,/^(?:\/(?!\])|\\(?!\])|[^\\\[\]\(\)\{\}\/]+)/,/^(?:\[\/)/,/^(?:\[\\)/,/^(?:<)/,/^(?:>)/,/^(?:\^)/,/^(?:\\\|)/,/^(?:v\b)/,/^(?:\*)/,/^(?:#)/,/^(?:&)/,/^(?:([A-Za-z0-9!"\#$%&'*+\.`?\\_\/]|-(?=[^\>\-\.])|(?!))+)/,/^(?:-)/,/^(?:[\u00AA\u00B5\u00BA\u00C0-\u00D6\u00D8-\u00F6]|[\u00F8-\u02C1\u02C6-\u02D1\u02E0-\u02E4\u02EC\u02EE\u0370-\u0374\u0376\u0377]|[\u037A-\u037D\u0386\u0388-\u038A\u038C\u038E-\u03A1\u03A3-\u03F5]|[\u03F7-\u0481\u048A-\u0527\u0531-\u0556\u0559\u0561-\u0587\u05D0-\u05EA]|[\u05F0-\u05F2\u0620-\u064A\u066E\u066F\u0671-\u06D3\u06D5\u06E5\u06E6\u06EE]|[\u06EF\u06FA-\u06FC\u06FF\u0710\u0712-\u072F\u074D-\u07A5\u07B1\u07CA-\u07EA]|[\u07F4\u07F5\u07FA\u0800-\u0815\u081A\u0824\u0828\u0840-\u0858\u08A0]|[\u08A2-\u08AC\u0904-\u0939\u093D\u0950\u0958-\u0961\u0971-\u0977]|[\u0979-\u097F\u0985-\u098C\u098F\u0990\u0993-\u09A8\u09AA-\u09B0\u09B2]|[\u09B6-\u09B9\u09BD\u09CE\u09DC\u09DD\u09DF-\u09E1\u09F0\u09F1\u0A05-\u0A0A]|[\u0A0F\u0A10\u0A13-\u0A28\u0A2A-\u0A30\u0A32\u0A33\u0A35\u0A36\u0A38\u0A39]|[\u0A59-\u0A5C\u0A5E\u0A72-\u0A74\u0A85-\u0A8D\u0A8F-\u0A91\u0A93-\u0AA8]|[\u0AAA-\u0AB0\u0AB2\u0AB3\u0AB5-\u0AB9\u0ABD\u0AD0\u0AE0\u0AE1\u0B05-\u0B0C]|[\u0B0F\u0B10\u0B13-\u0B28\u0B2A-\u0B30\u0B32\u0B33\u0B35-\u0B39\u0B3D\u0B5C]|[\u0B5D\u0B5F-\u0B61\u0B71\u0B83\u0B85-\u0B8A\u0B8E-\u0B90\u0B92-\u0B95\u0B99]|[\u0B9A\u0B9C\u0B9E\u0B9F\u0BA3\u0BA4\u0BA8-\u0BAA\u0BAE-\u0BB9\u0BD0]|[\u0C05-\u0C0C\u0C0E-\u0C10\u0C12-\u0C28\u0C2A-\u0C33\u0C35-\u0C39\u0C3D]|[\u0C58\u0C59\u0C60\u0C61\u0C85-\u0C8C\u0C8E-\u0C90\u0C92-\u0CA8\u0CAA-\u0CB3]|[\u0CB5-\u0CB9\u0CBD\u0CDE\u0CE0\u0CE1\u0CF1\u0CF2\u0D05-\u0D0C\u0D0E-\u0D10]|[\u0D12-\u0D3A\u0D3D\u0D4E\u0D60\u0D61\u0D7A-\u0D7F\u0D85-\u0D96\u0D9A-\u0DB1]|[\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6\u0E01-\u0E30\u0E32\u0E33\u0E40-\u0E46\u0E81]|[\u0E82\u0E84\u0E87\u0E88\u0E8A\u0E8D\u0E94-\u0E97\u0E99-\u0E9F\u0EA1-\u0EA3]|[\u0EA5\u0EA7\u0EAA\u0EAB\u0EAD-\u0EB0\u0EB2\u0EB3\u0EBD\u0EC0-\u0EC4\u0EC6]|[\u0EDC-\u0EDF\u0F00\u0F40-\u0F47\u0F49-\u0F6C\u0F88-\u0F8C\u1000-\u102A]|[\u103F\u1050-\u1055\u105A-\u105D\u1061\u1065\u1066\u106E-\u1070\u1075-\u1081]|[\u108E\u10A0-\u10C5\u10C7\u10CD\u10D0-\u10FA\u10FC-\u1248\u124A-\u124D]|[\u1250-\u1256\u1258\u125A-\u125D\u1260-\u1288\u128A-\u128D\u1290-\u12B0]|[\u12B2-\u12B5\u12B8-\u12BE\u12C0\u12C2-\u12C5\u12C8-\u12D6\u12D8-\u1310]|[\u1312-\u1315\u1318-\u135A\u1380-\u138F\u13A0-\u13F4\u1401-\u166C]|[\u166F-\u167F\u1681-\u169A\u16A0-\u16EA\u1700-\u170C\u170E-\u1711]|[\u1720-\u1731\u1740-\u1751\u1760-\u176C\u176E-\u1770\u1780-\u17B3\u17D7]|[\u17DC\u1820-\u1877\u1880-\u18A8\u18AA\u18B0-\u18F5\u1900-\u191C]|[\u1950-\u196D\u1970-\u1974\u1980-\u19AB\u19C1-\u19C7\u1A00-\u1A16]|[\u1A20-\u1A54\u1AA7\u1B05-\u1B33\u1B45-\u1B4B\u1B83-\u1BA0\u1BAE\u1BAF]|[\u1BBA-\u1BE5\u1C00-\u1C23\u1C4D-\u1C4F\u1C5A-\u1C7D\u1CE9-\u1CEC]|[\u1CEE-\u1CF1\u1CF5\u1CF6\u1D00-\u1DBF\u1E00-\u1F15\u1F18-\u1F1D]|[\u1F20-\u1F45\u1F48-\u1F4D\u1F50-\u1F57\u1F59\u1F5B\u1F5D\u1F5F-\u1F7D]|[\u1F80-\u1FB4\u1FB6-\u1FBC\u1FBE\u1FC2-\u1FC4\u1FC6-\u1FCC\u1FD0-\u1FD3]|[\u1FD6-\u1FDB\u1FE0-\u1FEC\u1FF2-\u1FF4\u1FF6-\u1FFC\u2071\u207F]|[\u2090-\u209C\u2102\u2107\u210A-\u2113\u2115\u2119-\u211D\u2124\u2126\u2128]|[\u212A-\u212D\u212F-\u2139\u213C-\u213F\u2145-\u2149\u214E\u2183\u2184]|[\u2C00-\u2C2E\u2C30-\u2C5E\u2C60-\u2CE4\u2CEB-\u2CEE\u2CF2\u2CF3]|[\u2D00-\u2D25\u2D27\u2D2D\u2D30-\u2D67\u2D6F\u2D80-\u2D96\u2DA0-\u2DA6]|[\u2DA8-\u2DAE\u2DB0-\u2DB6\u2DB8-\u2DBE\u2DC0-\u2DC6\u2DC8-\u2DCE]|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ne(){this.yy={}}return se.lexer=ie,(0,h.K2)(ne,"Parser"),ne.prototype=se,se.Parser=ne,new ne}();k.parser=k;var y=k,f=Object.assign({},y);f.parse=t=>{const e=t.replace(/}\s*\n/g,"}\n");return y.parse(e)};var m=f,E=(0,h.K2)((t,e)=>{const s=g.A,i=s(t,"r"),n=s(t,"g"),r=s(t,"b");return p.A(i,n,r,e)},"fade"),C=(0,h.K2)(t=>`.label {\n font-family: ${t.fontFamily};\n color: ${t.nodeTextColor||t.textColor};\n }\n .cluster-label text {\n fill: ${t.titleColor};\n }\n .cluster-label span {\n color: ${t.titleColor};\n }\n .cluster-label span p {\n background-color: transparent;\n }\n\n .label text,span {\n fill: ${t.nodeTextColor||t.textColor};\n color: ${t.nodeTextColor||t.textColor};\n }\n\n .node rect,\n .node circle,\n .node ellipse,\n .node polygon,\n .node path {\n fill: ${t.mainBkg};\n stroke: ${t.nodeBorder};\n stroke-width: 1px;\n }\n .rough-node .label text , .node .label text, .image-shape .label, .icon-shape .label {\n text-anchor: middle;\n }\n // .flowchart-label .text-outer-tspan {\n // text-anchor: middle;\n // }\n // .flowchart-label .text-inner-tspan {\n // text-anchor: start;\n // }\n\n .node .katex path {\n fill: #000;\n stroke: #000;\n stroke-width: 1px;\n }\n\n .rough-node .label,.node .label, .image-shape .label, .icon-shape .label {\n text-align: center;\n }\n .node.clickable {\n cursor: pointer;\n }\n\n\n .root .anchor path {\n fill: ${t.lineColor} !important;\n stroke-width: 0;\n stroke: ${t.lineColor};\n }\n\n .arrowheadPath {\n fill: ${t.arrowheadColor};\n }\n\n .edgePath .path {\n stroke: ${t.lineColor};\n stroke-width: 2.0px;\n }\n\n .flowchart-link {\n stroke: ${t.lineColor};\n fill: none;\n }\n\n .edgeLabel {\n background-color: ${t.edgeLabelBackground};\n p {\n background-color: ${t.edgeLabelBackground};\n }\n rect {\n opacity: 0.5;\n background-color: ${t.edgeLabelBackground};\n fill: ${t.edgeLabelBackground};\n }\n text-align: center;\n }\n\n /* For html labels only */\n .labelBkg {\n background-color: ${E(t.edgeLabelBackground,.5)};\n // 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l.Y2.sanitizeText(t,this.config)}lookUpDomId(t){for(const e of this.vertices.values())if(e.id===t)return e.domId;return t}addVertex(t,e,s,i,r,a,u={},c){if(!t||0===t.trim().length)return;let h;if(void 0!==c){let t;t=c.includes("\n")?c+"\n":"{\n"+c+"\n}",h=(0,n.H)(t,{schema:n.r})}const d=this.edges.find(e=>e.id===t);if(d){const t=h;return void 0!==t?.animate&&(d.animate=t.animate),void 0!==t?.animation&&(d.animation=t.animation),void(void 0!==t?.curve&&(d.interpolate=t.curve))}let p,g=this.vertices.get(t);if(void 0===g&&(g={id:t,labelType:"text",domId:"flowchart-"+t+"-"+this.vertexCounter,styles:[],classes:[]},this.vertices.set(t,g)),this.vertexCounter++,void 0!==e?(this.config=(0,l.D7)(),p=this.sanitizeText(e.text.trim()),g.labelType=e.type,p.startsWith('"')&&p.endsWith('"')&&(p=p.substring(1,p.length-1)),g.text=p):void 0===g.text&&(g.text=t),void 0!==s&&(g.type=s),null!=i&&i.forEach(t=>{g.styles.push(t)}),null!=r&&r.forEach(t=>{g.classes.push(t)}),void 0!==a&&(g.dir=a),void 0===g.props?g.props=u:void 0!==u&&Object.assign(g.props,u),void 0!==h){if(h.shape){if(h.shape!==h.shape.toLowerCase()||h.shape.includes("_"))throw new Error(`No such shape: ${h.shape}. Shape names should be lowercase.`);if(!(0,o.aP)(h.shape))throw new Error(`No such shape: ${h.shape}.`);g.type=h?.shape}h?.label&&(g.text=h?.label),h?.icon&&(g.icon=h?.icon,h.label?.trim()||g.text!==t||(g.text="")),h?.form&&(g.form=h?.form),h?.pos&&(g.pos=h?.pos),h?.img&&(g.img=h?.img,h.label?.trim()||g.text!==t||(g.text="")),h?.constraint&&(g.constraint=h.constraint),h.w&&(g.assetWidth=Number(h.w)),h.h&&(g.assetHeight=Number(h.h))}}addSingleLink(t,e,s,i){const n={start:t,end:e,type:void 0,text:"",labelType:"text",classes:[],isUserDefinedId:!1,interpolate:this.edges.defaultInterpolate};h.Rm.info("abc78 Got edge...",n);const r=s.text;if(void 0!==r&&(n.text=this.sanitizeText(r.text.trim()),n.text.startsWith('"')&&n.text.endsWith('"')&&(n.text=n.text.substring(1,n.text.length-1)),n.labelType=r.type),void 0!==s&&(n.type=s.type,n.stroke=s.stroke,n.length=s.length>10?10:s.length),i&&!this.edges.some(t=>t.id===i))n.id=i,n.isUserDefinedId=!0;else{const t=this.edges.filter(t=>t.start===n.start&&t.end===n.end);0===t.length?n.id=(0,c.rY)(n.start,n.end,{counter:0,prefix:"L"}):n.id=(0,c.rY)(n.start,n.end,{counter:t.length+1,prefix:"L"})}if(!(this.edges.length<(this.config.maxEdges??500)))throw new Error(`Edge limit exceeded. ${this.edges.length} edges found, but the limit is ${this.config.maxEdges}.\n\nInitialize mermaid with maxEdges set to a higher number to allow more edges.\nYou cannot set this config via configuration inside the diagram as it is a secure config.\nYou have to call mermaid.initialize.`);h.Rm.info("Pushing edge..."),this.edges.push(n)}isLinkData(t){return null!==t&&"object"==typeof t&&"id"in t&&"string"==typeof t.id}addLink(t,e,s){const i=this.isLinkData(s)?s.id.replace("@",""):void 0;h.Rm.info("addLink",t,e,i);for(const n of t)for(const r of e){const a=n===t[t.length-1],u=r===e[0];a&&u?this.addSingleLink(n,r,s,i):this.addSingleLink(n,r,s,void 0)}}updateLinkInterpolate(t,e){t.forEach(t=>{"default"===t?this.edges.defaultInterpolate=e:this.edges[t].interpolate=e})}updateLink(t,e){t.forEach(t=>{if("number"==typeof t&&t>=this.edges.length)throw new Error(`The index ${t} for linkStyle is out of bounds. Valid indices for linkStyle are between 0 and ${this.edges.length-1}. (Help: Ensure that the index is within the range of existing edges.)`);"default"===t?this.edges.defaultStyle=e:(this.edges[t].style=e,(this.edges[t]?.style?.length??0)>0&&!this.edges[t]?.style?.some(t=>t?.startsWith("fill"))&&this.edges[t]?.style?.push("fill:none"))})}addClass(t,e){const s=e.join().replace(/\\,/g,"\xa7\xa7\xa7").replace(/,/g,";").replace(/\xa7\xa7\xa7/g,",").split(";");t.split(",").forEach(t=>{let e=this.classes.get(t);void 0===e&&(e={id:t,styles:[],textStyles:[]},this.classes.set(t,e)),null!=s&&s.forEach(t=>{if(/color/.exec(t)){const s=t.replace("fill","bgFill");e.textStyles.push(s)}e.styles.push(t)})})}setDirection(t){this.direction=t.trim(),/.*/.exec(this.direction)&&(this.direction="LR"),/.*v/.exec(this.direction)&&(this.direction="TB"),"TD"===this.direction&&(this.direction="TB")}setClass(t,e){for(const s of t.split(",")){const t=this.vertices.get(s);t&&t.classes.push(e);const i=this.edges.find(t=>t.id===s);i&&i.classes.push(e);const n=this.subGraphLookup.get(s);n&&n.classes.push(e)}}setTooltip(t,e){if(void 0!==e){e=this.sanitizeText(e);for(const s of t.split(","))this.tooltips.set("gen-1"===this.version?this.lookUpDomId(s):s,e)}}setClickFun(t,e,s){const i=this.lookUpDomId(t);if("loose"!==(0,l.D7)().securityLevel)return;if(void 0===e)return;let n=[];if("string"==typeof s){n=s.split(/,(?=(?:(?:[^"]*"){2})*[^"]*$)/);for(let t=0;t{const t=document.querySelector(`[id="${i}"]`);null!==t&&t.addEventListener("click",()=>{c._K.runFunc(e,...n)},!1)}))}setLink(t,e,s){t.split(",").forEach(t=>{const i=this.vertices.get(t);void 0!==i&&(i.link=c._K.formatUrl(e,this.config),i.linkTarget=s)}),this.setClass(t,"clickable")}getTooltip(t){return this.tooltips.get(t)}setClickEvent(t,e,s){t.split(",").forEach(t=>{this.setClickFun(t,e,s)}),this.setClass(t,"clickable")}bindFunctions(t){this.funs.forEach(e=>{e(t)})}getDirection(){return this.direction?.trim()}getVertices(){return this.vertices}getEdges(){return this.edges}getClasses(){return this.classes}setupToolTips(t){let e=(0,d.Ltv)(".mermaidTooltip");null===(e._groups||e)[0][0]&&(e=(0,d.Ltv)("body").append("div").attr("class","mermaidTooltip").style("opacity",0));(0,d.Ltv)(t).select("svg").selectAll("g.node").on("mouseover",t=>{const s=(0,d.Ltv)(t.currentTarget);if(null===s.attr("title"))return;const i=t.currentTarget?.getBoundingClientRect();e.transition().duration(200).style("opacity",".9"),e.text(s.attr("title")).style("left",window.scrollX+i.left+(i.right-i.left)/2+"px").style("top",window.scrollY+i.bottom+"px"),e.html(e.html().replace(/<br\/>/g,"
")),s.classed("hover",!0)}).on("mouseout",t=>{e.transition().duration(500).style("opacity",0);(0,d.Ltv)(t.currentTarget).classed("hover",!1)})}clear(t="gen-2"){this.vertices=new Map,this.classes=new Map,this.edges=[],this.funs=[this.setupToolTips.bind(this)],this.subGraphs=[],this.subGraphLookup=new Map,this.subCount=0,this.tooltips=new Map,this.firstGraphFlag=!0,this.version=t,this.config=(0,l.D7)(),(0,l.IU)()}setGen(t){this.version=t||"gen-2"}defaultStyle(){return"fill:#ffa;stroke: #f66; stroke-width: 3px; stroke-dasharray: 5, 5;fill:#ffa;stroke: #666;"}addSubGraph(t,e,s){let i=t.text.trim(),n=s.text;t===s&&/\s/.exec(s.text)&&(i=void 0);const r=(0,h.K2)(t=>{const e={boolean:{},number:{},string:{}},s=[];let i;return{nodeList:t.filter(function(t){const n=typeof t;return t.stmt&&"dir"===t.stmt?(i=t.value,!1):""!==t.trim()&&(n in e?!e[n].hasOwnProperty(t)&&(e[n][t]=!0):!s.includes(t)&&s.push(t))}),dir:i}},"uniq")(e.flat()),a=r.nodeList;let u=r.dir;const o=(0,l.D7)().flowchart??{};if(u=u??(o.inheritDir?this.getDirection()??(0,l.D7)().direction??void 0:void 0),"gen-1"===this.version)for(let l=0;l2e3)return{result:!1,count:0};if(this.posCrossRef[this.secCount]=e,this.subGraphs[e].id===t)return{result:!0,count:0};let i=0,n=1;for(;i=0){const s=this.indexNodes2(t,e);if(s.result)return{result:!0,count:n+s.count};n+=s.count}i+=1}return{result:!1,count:n}}getDepthFirstPos(t){return this.posCrossRef[t]}indexNodes(){this.secCount=-1,this.subGraphs.length>0&&this.indexNodes2("none",this.subGraphs.length-1)}getSubGraphs(){return this.subGraphs}firstGraph(){return!!this.firstGraphFlag&&(this.firstGraphFlag=!1,!0)}destructStartLink(t){let e=t.trim(),s="arrow_open";switch(e[0]){case"<":s="arrow_point",e=e.slice(1);break;case"x":s="arrow_cross",e=e.slice(1);break;case"o":s="arrow_circle",e=e.slice(1)}let i="normal";return e.includes("=")&&(i="thick"),e.includes(".")&&(i="dotted"),{type:s,stroke:i}}countChar(t,e){const s=e.length;let i=0;for(let n=0;n":i="arrow_point",e.startsWith("<")&&(i="double_"+i,s=s.slice(1));break;case"o":i="arrow_circle",e.startsWith("o")&&(i="double_"+i,s=s.slice(1))}let n="normal",r=s.length-1;s.startsWith("=")&&(n="thick"),s.startsWith("~")&&(n="invisible");const a=this.countChar(".",s);return a&&(n="dotted",r=a),{type:i,stroke:n,length:r}}destructLink(t,e){const s=this.destructEndLink(t);let i;if(e){if(i=this.destructStartLink(e),i.stroke!==s.stroke)return{type:"INVALID",stroke:"INVALID"};if("arrow_open"===i.type)i.type=s.type;else{if(i.type!==s.type)return{type:"INVALID",stroke:"INVALID"};i.type="double_"+i.type}return"double_arrow"===i.type&&(i.type="double_arrow_point"),i.length=s.length,i}return s}exists(t,e){for(const s of t)if(s.nodes.includes(e))return!0;return!1}makeUniq(t,e){const s=[];return t.nodes.forEach((i,n)=>{this.exists(e,i)||s.push(t.nodes[n])}),{nodes:s}}getTypeFromVertex(t){if(t.img)return"imageSquare";if(t.icon)return"circle"===t.form?"iconCircle":"square"===t.form?"iconSquare":"rounded"===t.form?"iconRounded":"icon";switch(t.type){case"square":case void 0:return"squareRect";case"round":return"roundedRect";case"ellipse":return"ellipse";default:return t.type}}findNode(t,e){return t.find(t=>t.id===e)}destructEdgeType(t){let e="none",s="arrow_point";switch(t){case"arrow_point":case"arrow_circle":case"arrow_cross":s=t;break;case"double_arrow_point":case"double_arrow_circle":case"double_arrow_cross":e=t.replace("double_",""),s=e}return{arrowTypeStart:e,arrowTypeEnd:s}}addNodeFromVertex(t,e,s,i,n,r){const a=s.get(t.id),u=i.get(t.id)??!1,o=this.findNode(e,t.id);if(o)o.cssStyles=t.styles,o.cssCompiledStyles=this.getCompiledStyles(t.classes),o.cssClasses=t.classes.join(" ");else{const s={id:t.id,label:t.text,labelStyle:"",parentId:a,padding:n.flowchart?.padding||8,cssStyles:t.styles,cssCompiledStyles:this.getCompiledStyles(["default","node",...t.classes]),cssClasses:"default "+t.classes.join(" "),dir:t.dir,domId:t.domId,look:r,link:t.link,linkTarget:t.linkTarget,tooltip:this.getTooltip(t.id),icon:t.icon,pos:t.pos,img:t.img,assetWidth:t.assetWidth,assetHeight:t.assetHeight,constraint:t.constraint};u?e.push({...s,isGroup:!0,shape:"rect"}):e.push({...s,isGroup:!1,shape:this.getTypeFromVertex(t)})}}getCompiledStyles(t){let e=[];for(const s of t){const t=this.classes.get(s);t?.styles&&(e=[...e,...t.styles??[]].map(t=>t.trim())),t?.textStyles&&(e=[...e,...t.textStyles??[]].map(t=>t.trim()))}return e}getData(){const t=(0,l.D7)(),e=[],s=[],i=this.getSubGraphs(),n=new Map,r=new Map;for(let u=i.length-1;u>=0;u--){const t=i[u];t.nodes.length>0&&r.set(t.id,!0);for(const e of t.nodes)n.set(e,t.id)}for(let u=i.length-1;u>=0;u--){const s=i[u];e.push({id:s.id,label:s.title,labelStyle:"",parentId:n.get(s.id),padding:8,cssCompiledStyles:this.getCompiledStyles(s.classes),cssClasses:s.classes.join(" "),shape:"rect",dir:s.dir,isGroup:!0,look:t.look})}this.getVertices().forEach(s=>{this.addNodeFromVertex(s,e,n,r,t,t.look||"classic")});const a=this.getEdges();return a.forEach((e,i)=>{const{arrowTypeStart:n,arrowTypeEnd:r}=this.destructEdgeType(e.type),u=[...a.defaultStyle??[]];e.style&&u.push(...e.style);const o={id:(0,c.rY)(e.start,e.end,{counter:i,prefix:"L"},e.id),isUserDefinedId:e.isUserDefinedId,start:e.start,end:e.end,type:e.type??"normal",label:e.text,labelpos:"c",thickness:e.stroke,minlen:e.length,classes:"invisible"===e?.stroke?"":"edge-thickness-normal edge-pattern-solid flowchart-link",arrowTypeStart:"invisible"===e?.stroke||"arrow_open"===e?.type?"none":n,arrowTypeEnd:"invisible"===e?.stroke||"arrow_open"===e?.type?"none":r,arrowheadStyle:"fill: #333",cssCompiledStyles:this.getCompiledStyles(e.classes),labelStyle:u,style:u,pattern:e.stroke,look:t.look,animate:e.animate,animation:e.animation,curve:e.interpolate||this.edges.defaultInterpolate||t.flowchart?.curve};s.push(o)}),{nodes:e,edges:s,other:{},config:t}}defaultConfig(){return l.ME.flowchart}},b={getClasses:(0,h.K2)(function(t,e){return e.db.getClasses()},"getClasses"),draw:(0,h.K2)(async function(t,e,s,i){h.Rm.info("REF0:"),h.Rm.info("Drawing state diagram (v2)",e);const{securityLevel:n,flowchart:o,layout:p}=(0,l.D7)();let g;"sandbox"===n&&(g=(0,d.Ltv)("#i"+e));const A="sandbox"===n?g.nodes()[0].contentDocument:document;h.Rm.debug("Before getData: ");const b=i.db.getData();h.Rm.debug("Data: ",b);const k=(0,r.A)(e,n),y=i.db.getDirection();b.type=i.type,b.layoutAlgorithm=(0,u.q7)(p),"dagre"===b.layoutAlgorithm&&"elk"===p&&h.Rm.warn("flowchart-elk was moved to an external package in Mermaid v11. Please refer [release notes](https://github.com/mermaid-js/mermaid/releases/tag/v11.0.0) for more details. 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188:this.$={stmt:"dir",value:"LR"}}},"anonymous"),table:[{3:1,4:2,9:e,10:s,12:i},{1:[3]},t(n,r,{5:6}),{4:7,9:e,10:s,12:i},{4:8,9:e,10:s,12:i},{13:[1,9],14:[1,10]},{1:[2,1],6:11,7:12,8:a,9:u,10:o,11:c,20:17,22:18,23:19,24:20,25:21,26:22,27:l,33:24,34:d,36:p,38:g,42:28,43:38,44:A,45:39,47:40,60:b,84:k,85:y,86:f,87:m,88:E,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v,121:w,122:L,123:$,124:I},t(n,[2,9]),t(n,[2,10]),t(n,[2,11]),{8:[1,54],9:[1,55],10:R,15:53,18:56},t(N,[2,3]),t(N,[2,4]),t(N,[2,5]),t(N,[2,6]),t(N,[2,7]),t(N,[2,8]),{8:P,9:G,11:K,21:58,41:59,72:63,75:[1,64],77:[1,66],78:[1,65]},{8:P,9:G,11:K,21:67},{8:P,9:G,11:K,21:68},{8:P,9:G,11:K,21:69},{8:P,9:G,11:K,21:70},{8:P,9:G,11:K,21:71},{8:P,9:G,10:[1,72],11:K,21:73},t(N,[2,36]),{35:[1,74]},{37:[1,75]},t(N,[2,39]),t(O,[2,50],{18:76,39:77,10:R,40:M}),{10:[1,79]},{10:[1,80]},{10:[1,81]},{10:[1,82]},{14:U,44:V,60:W,80:[1,86],89:Y,95:[1,83],97:[1,84],101:85,105:j,106:z,109:X,111:H,114:q,115:Q,116:Z,120:87},t(N,[2,185]),t(N,[2,186]),t(N,[2,187]),t(N,[2,188]),t(J,[2,51]),t(J,[2,54],{46:[1,99]}),t(tt,[2,72],{113:112,29:[1,100],44:A,48:[1,101],50:[1,102],52:[1,103],54:[1,104],56:[1,105],58:[1,106],60:b,63:[1,107],65:[1,108],67:[1,109],68:[1,110],70:[1,111],89:C,102:D,105:x,106:T,109:S,111:F,114:_,115:B,116:v}),t(et,[2,181]),t(et,[2,142]),t(et,[2,143]),t(et,[2,144]),t(et,[2,145]),t(et,[2,146]),t(et,[2,147]),t(et,[2,148]),t(et,[2,149]),t(et,[2,150]),t(et,[2,151]),t(et,[2,152]),t(n,[2,12]),t(n,[2,18]),t(n,[2,19]),{9:[1,113]},t(st,[2,26],{18:114,10:R}),t(N,[2,27]),{42:115,43:38,44:A,45:39,47:40,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},t(N,[2,40]),t(N,[2,41]),t(N,[2,42]),t(it,[2,76],{73:116,62:[1,118],74:[1,117]}),{76:119,79:120,80:nt,81:rt,116:at,119:ut},{75:[1,125],77:[1,126]},t(ot,[2,83]),t(N,[2,28]),t(N,[2,29]),t(N,[2,30]),t(N,[2,31]),t(N,[2,32]),{10:ct,12:lt,14:ht,27:dt,28:127,32:pt,44:gt,60:At,75:bt,80:[1,129],81:[1,130],83:140,84:kt,85:yt,86:ft,87:mt,88:Et,89:Ct,90:Dt,91:128,105:xt,109:Tt,111:St,114:Ft,115:_t,116:Bt},t(vt,r,{5:153}),t(N,[2,37]),t(N,[2,38]),t(O,[2,48],{44:wt}),t(O,[2,49],{18:155,10:R,40:Lt}),t(J,[2,44]),{44:A,47:157,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},{102:[1,158],103:159,105:[1,160]},{44:A,47:161,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},{44:A,47:162,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},t($t,[2,107],{10:[1,163],96:[1,164]}),{80:[1,165]},t($t,[2,115],{120:167,10:[1,166],14:U,44:V,60:W,89:Y,105:j,106:z,109:X,111:H,114:q,115:Q,116:Z}),t($t,[2,117],{10:[1,168]}),t(It,[2,183]),t(It,[2,170]),t(It,[2,171]),t(It,[2,172]),t(It,[2,173]),t(It,[2,174]),t(It,[2,175]),t(It,[2,176]),t(It,[2,177]),t(It,[2,178]),t(It,[2,179]),t(It,[2,180]),{44:A,47:169,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v},{30:170,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:178,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:180,50:[1,179],67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:181,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:182,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:183,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{109:[1,184]},{30:185,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:186,65:[1,187],67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:188,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:189,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{30:190,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},t(et,[2,182]),t(n,[2,20]),t(st,[2,25]),t(O,[2,46],{39:191,18:192,10:R,40:M}),t(it,[2,73],{10:[1,193]}),{10:[1,194]},{30:195,67:Rt,80:Nt,81:Pt,82:171,116:Gt,117:Kt,118:Ot},{77:[1,196],79:197,116:at,119:ut},t(Mt,[2,79]),t(Mt,[2,81]),t(Mt,[2,82]),t(Mt,[2,168]),t(Mt,[2,169]),{76:198,79:120,80:nt,81:rt,116:at,119:ut},t(ot,[2,84]),{8:P,9:G,10:ct,11:K,12:lt,14:ht,21:200,27:dt,29:[1,199],32:pt,44:gt,60:At,75:bt,83:140,84:kt,85:yt,86:ft,87:mt,88:Et,89:Ct,90:Dt,91:201,105:xt,109:Tt,111:St,114:Ft,115:_t,116:Bt},t(Ut,[2,101]),t(Ut,[2,103]),t(Ut,[2,104]),t(Ut,[2,157]),t(Ut,[2,158]),t(Ut,[2,159]),t(Ut,[2,160]),t(Ut,[2,161]),t(Ut,[2,162]),t(Ut,[2,163]),t(Ut,[2,164]),t(Ut,[2,165]),t(Ut,[2,166]),t(Ut,[2,167]),t(Ut,[2,90]),t(Ut,[2,91]),t(Ut,[2,92]),t(Ut,[2,93]),t(Ut,[2,94]),t(Ut,[2,95]),t(Ut,[2,96]),t(Ut,[2,97]),t(Ut,[2,98]),t(Ut,[2,99]),t(Ut,[2,100]),{6:11,7:12,8:a,9:u,10:o,11:c,20:17,22:18,23:19,24:20,25:21,26:22,27:l,32:[1,202],33:24,34:d,36:p,38:g,42:28,43:38,44:A,45:39,47:40,60:b,84:k,85:y,86:f,87:m,88:E,89:C,102:D,105:x,106:T,109:S,111:F,113:41,114:_,115:B,116:v,121:w,122:L,123:$,124:I},{10:R,18:203},{44:[1,204]},t(J,[2,43]),{10:[1,205],44:A,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:112,114:_,115:B,116:v},{10:[1,206]},{10:[1,207],106:[1,208]},t(Vt,[2,128]),{10:[1,209],44:A,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:112,114:_,115:B,116:v},{10:[1,210],44:A,60:b,89:C,102:D,105:x,106:T,109:S,111:F,113:112,114:_,115:B,116:v},{80:[1,211]},t($t,[2,109],{10:[1,212]}),t($t,[2,111],{10:[1,213]}),{80:[1,214]},t(It,[2,18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F=[],a[E])this.terminals_[x]&&x>2&&F.push("'"+this.terminals_[x]+"'");B=p.showPosition?"Parse error on line "+(o+1)+":\n"+p.showPosition()+"\nExpecting "+F.join(", ")+", got '"+(this.terminals_[f]||f)+"'":"Parse error on line "+(o+1)+": Unexpected "+(1==f?"end of input":"'"+(this.terminals_[f]||f)+"'"),this.parseError(B,{text:p.match,token:this.terminals_[f]||f,line:p.yylineno,loc:b,expected:F})}if(C[0]instanceof Array&&C.length>1)throw new Error("Parse Error: multiple actions possible at state: "+E+", token: "+f);switch(C[0]){case 1:s.push(f),n.push(p.yytext),r.push(p.yylloc),s.push(C[1]),f=null,m?(f=m,m=null):(c=p.yyleng,u=p.yytext,o=p.yylineno,b=p.yylloc,l>0&&l--);break;case 2:if(T=this.productions_[C[1]][1],_.$=n[n.length-T],_._$={first_line:r[r.length-(T||1)].first_line,last_line:r[r.length-1].last_line,first_column:r[r.length-(T||1)].first_column,last_column:r[r.length-1].last_column},k&&(_._$.range=[r[r.length-(T||1)].range[0],r[r.length-1].range[1]]),void 0!==(D=this.performAction.apply(_,[u,c,o,g.yy,C[1],n,r].concat(d))))return D;T&&(s=s.slice(0,-1*T*2),n=n.slice(0,-1*T),r=r.slice(0,-1*T)),s.push(this.productions_[C[1]][0]),n.push(_.$),r.push(_._$),S=a[s[s.length-2]][s[s.length-1]],s.push(S);break;case 3:return!0}}return!0},"parse")},ie=function(){return{EOF:1,parseError:(0,h.K2)(function(t,e){if(!this.yy.parser)throw new Error(t);this.yy.parser.parseError(t,e)},"parseError"),setInput:(0,h.K2)(function(t,e){return this.yy=e||this.yy||{},this._input=t,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:(0,h.K2)(function(){var t=this._input[0];return this.yytext+=t,this.yyleng++,this.offset++,this.match+=t,this.matched+=t,t.match(/(?:\r\n?|\n).*/g)?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),t},"input"),unput:(0,h.K2)(function(t){var e=t.length,s=t.split(/(?:\r\n?|\n)/g);this._input=t+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-e),this.offset-=e;var i=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),s.length-1&&(this.yylineno-=s.length-1);var n=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:s?(s.length===i.length?this.yylloc.first_column:0)+i[i.length-s.length].length-s[0].length:this.yylloc.first_column-e},this.options.ranges&&(this.yylloc.range=[n[0],n[0]+this.yyleng-e]),this.yyleng=this.yytext.length,this},"unput"),more:(0,h.K2)(function(){return this._more=!0,this},"more"),reject:(0,h.K2)(function(){return this.options.backtrack_lexer?(this._backtrack=!0,this):this.parseError("Lexical error on line "+(this.yylineno+1)+". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"reject"),less:(0,h.K2)(function(t){this.unput(this.match.slice(t))},"less"),pastInput:(0,h.K2)(function(){var t=this.matched.substr(0,this.matched.length-this.match.length);return(t.length>20?"...":"")+t.substr(-20).replace(/\n/g,"")},"pastInput"),upcomingInput:(0,h.K2)(function(){var t=this.match;return t.length<20&&(t+=this._input.substr(0,20-t.length)),(t.substr(0,20)+(t.length>20?"...":"")).replace(/\n/g,"")},"upcomingInput"),showPosition:(0,h.K2)(function(){var t=this.pastInput(),e=new Array(t.length+1).join("-");return t+this.upcomingInput()+"\n"+e+"^"},"showPosition"),test_match:(0,h.K2)(function(t,e){var s,i,n;if(this.options.backtrack_lexer&&(n={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(n.yylloc.range=this.yylloc.range.slice(0))),(i=t[0].match(/(?:\r\n?|\n).*/g))&&(this.yylineno+=i.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:i?i[i.length-1].length-i[i.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+t[0].length},this.yytext+=t[0],this.match+=t[0],this.matches=t,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(t[0].length),this.matched+=t[0],s=this.performAction.call(this,this.yy,this,e,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),s)return s;if(this._backtrack){for(var r in n)this[r]=n[r];return!1}return!1},"test_match"),next:(0,h.K2)(function(){if(this.done)return this.EOF;var t,e,s,i;this._input||(this.done=!0),this._more||(this.yytext="",this.match="");for(var n=this._currentRules(),r=0;re[0].length)){if(e=s,i=r,this.options.backtrack_lexer){if(!1!==(t=this.test_match(s,n[r])))return t;if(this._backtrack){e=!1;continue}return!1}if(!this.options.flex)break}return e?!1!==(t=this.test_match(e,n[i]))&&t:""===this._input?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+". Unrecognized text.\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"next"),lex:(0,h.K2)(function(){var t=this.next();return t||this.lex()},"lex"),begin:(0,h.K2)(function(t){this.conditionStack.push(t)},"begin"),popState:(0,h.K2)(function(){return this.conditionStack.length-1>0?this.conditionStack.pop():this.conditionStack[0]},"popState"),_currentRules:(0,h.K2)(function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},"_currentRules"),topState:(0,h.K2)(function(t){return(t=this.conditionStack.length-1-Math.abs(t||0))>=0?this.conditionStack[t]:"INITIAL"},"topState"),pushState:(0,h.K2)(function(t){this.begin(t)},"pushState"),stateStackSize:(0,h.K2)(function(){return this.conditionStack.length},"stateStackSize"),options:{},performAction:(0,h.K2)(function(t,e,s,i){switch(s){case 0:return this.begin("acc_title"),34;case 1:return this.popState(),"acc_title_value";case 2:return this.begin("acc_descr"),36;case 3:return this.popState(),"acc_descr_value";case 4:this.begin("acc_descr_multiline");break;case 5:case 12:case 14:case 17:case 20:case 23:case 33:this.popState();break;case 6:return"acc_descr_multiline_value";case 7:return this.pushState("shapeData"),e.yytext="",40;case 8:return this.pushState("shapeDataStr"),40;case 9:return this.popState(),40;case 10:const s=/\n\s*/g;return e.yytext=e.yytext.replace(s,"
"),40;case 11:return 40;case 13:this.begin("callbackname");break;case 15:this.popState(),this.begin("callbackargs");break;case 16:return 95;case 18:return 96;case 19:return"MD_STR";case 21:this.begin("md_string");break;case 22:return"STR";case 24:this.pushState("string");break;case 25:return 84;case 26:return 102;case 27:return 85;case 28:return 104;case 29:return 86;case 30:return 87;case 31:return 97;case 32:this.begin("click");break;case 34:return 88;case 35:case 36:case 37:return t.lex.firstGraph()&&this.begin("dir"),12;case 38:return 27;case 39:return 32;case 40:case 41:case 42:case 43:return 98;case 44:return this.popState(),13;case 45:case 46:case 47:case 48:case 49:case 50:case 51:case 52:case 53:case 54:return this.popState(),14;case 55:return 121;case 56:return 122;case 57:return 123;case 58:return 124;case 59:return 78;case 60:return 105;case 61:case 102:return 111;case 62:return 46;case 63:return 60;case 64:case 103:return 44;case 65:return 8;case 66:return 106;case 67:case 101:return 115;case 68:case 71:case 74:return this.popState(),77;case 69:return this.pushState("edgeText"),75;case 70:case 73:case 76:return 119;case 72:return this.pushState("thickEdgeText"),75;case 75:return this.pushState("dottedEdgeText"),75;case 77:return 77;case 78:return this.popState(),53;case 79:case 115:return"TEXT";case 80:return this.pushState("ellipseText"),52;case 81:return this.popState(),55;case 82:return this.pushState("text"),54;case 83:return this.popState(),57;case 84:return this.pushState("text"),56;case 85:return 58;case 86:return this.pushState("text"),67;case 87:return this.popState(),64;case 88:return this.pushState("text"),63;case 89:return this.popState(),49;case 90:return this.pushState("text"),48;case 91:return this.popState(),69;case 92:return this.popState(),71;case 93:return 117;case 94:return this.pushState("trapText"),68;case 95:return this.pushState("trapText"),70;case 96:return 118;case 97:return 67;case 98:return 90;case 99:return"SEP";case 100:return 89;case 104:return 109;case 105:return 114;case 106:return 116;case 107:return this.popState(),62;case 108:return this.pushState("text"),62;case 109:return this.popState(),51;case 110:return this.pushState("text"),50;case 111:return this.popState(),31;case 112:return this.pushState("text"),29;case 113:return this.popState(),66;case 114:return this.pushState("text"),65;case 116:return"QUOTE";case 117:return 9;case 118:return 10;case 119:return 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\ No newline at end of file diff --git a/assets/js/27b4a875.26de3408.js b/assets/js/27b4a875.26de3408.js new file mode 100644 index 00000000..e06bab39 --- /dev/null +++ b/assets/js/27b4a875.26de3408.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[3207],{2361:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>d,contentTitle:()=>h,default:()=>u,frontMatter:()=>c,metadata:()=>s,toc:()=>p});const s=JSON.parse('{"id":"core-components/chat","title":"Chat in OpenRAG","description":"After you upload documents to your knowledge base, you can use the OpenRAG Chat feature to interact with your knowledge through natural language queries.","source":"@site/docs/core-components/chat.mdx","sourceDirName":"core-components","slug":"/chat","permalink":"/chat","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/core-components/chat.mdx","tags":[],"version":"current","frontMatter":{"title":"Chat in OpenRAG","slug":"/chat"},"sidebar":"tutorialSidebar","previous":{"title":"Filter knowledge","permalink":"/knowledge-filters"},"next":{"title":"Environment variables","permalink":"/reference/configuration"}}');var o=t(4848),r=t(8453),i=t(1610),a=(t(1470),t(9365),t(7224)),l=t(8401);const c={title:"Chat in OpenRAG",slug:"/chat"},h=void 0,d={},p=[{value:"OpenRAG OpenSearch Agent flow",id:"flow",level:2},{value:"Nudges",id:"nudges",level:2},{value:"Upload documents to the chat",id:"upload-documents-to-the-chat",level:2},...l.RM,{value:"Inspect tool calls and knowledge",id:"inspect-tool-calls-and-knowledge",level:2},{value:"Integrate OpenRAG chat into an application",id:"integrate-openrag-chat-into-an-application",level:2},...a.RM];function g(e){const n={a:"a",admonition:"admonition",code:"code",h2:"h2",img:"img",li:"li",p:"p",strong:"strong",ul:"ul",...(0,r.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.p,{children:["After you ",(0,o.jsx)(n.a,{href:"/ingestion",children:"upload documents to your knowledge base"}),", you can use the OpenRAG ",(0,o.jsx)(i.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Chat"})," feature to interact with your knowledge through natural language queries."]}),"\n",(0,o.jsx)(n.admonition,{type:"tip",children:(0,o.jsxs)(n.p,{children:["Try chatting, uploading documents, and modifying chat settings in the ",(0,o.jsx)(n.a,{href:"/quickstart",children:"quickstart"}),"."]})}),"\n",(0,o.jsx)(n.h2,{id:"flow",children:"OpenRAG OpenSearch Agent flow"}),"\n",(0,o.jsxs)(n.p,{children:["When you use the OpenRAG ",(0,o.jsx)(n.strong,{children:"Chat"}),", the ",(0,o.jsx)(n.strong,{children:"OpenRAG OpenSearch Agent"})," ",(0,o.jsx)(n.a,{href:"/agents",children:"flow"})," runs in the background to retrieve relevant information from your knowledge base and generate a response."]}),"\n",(0,o.jsxs)(n.p,{children:["If you ",(0,o.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"inspect the flow in Langflow"}),", you'll see that it is comprised of eight components that work together to ingest chat messages, retrieve relevant information from your knowledge base, and then generate responses."]}),"\n",(0,o.jsx)(n.p,{children:(0,o.jsx)(n.img,{alt:"OpenRAG Open Search Agent Flow",src:t(3982).A+"",width:"4084",height:"2176"})}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsxs)(n.a,{href:"https://docs.langflow.org/components-io",children:[(0,o.jsx)(n.strong,{children:"Chat Input"})," component"]}),": This component starts the flow when it receives a chat message. 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The agent might not use this database for every request; the agent uses this connection only if it decides that documents in your knowledge base are relevant to your query."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsxs)(n.a,{href:"https://docs.langflow.org/components-embedding-models",children:[(0,o.jsx)(n.strong,{children:"Embedding Model"})," component"]}),": Connected to the ",(0,o.jsx)(n.strong,{children:"OpenSearch"})," component's ",(0,o.jsx)(n.strong,{children:"Embedding"})," port, this component generates embeddings from chat input that are used in ",(0,o.jsx)(n.a,{href:"https://www.ibm.com/think/topics/vector-search",children:"similarity search"})," to find content in your knowledge base that is relevant to the chat input. 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For more detail, you can inspect individual tool calls. This is helpful for troubleshooting because it shows you how the agent used particular tools. For example, click ",(0,o.jsx)(i.A,{name:"Gear","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Function Call: search_documents (tool_call)"})," to view the log of tool calls made by the agent to the ",(0,o.jsx)(n.strong,{children:"OpenSearch"})," component."]}),"\n",(0,o.jsxs)(n.p,{children:["If documents in your knowledge base seem to be missing or interpreted incorrectly, see ",(0,o.jsx)(n.a,{href:"/ingestion#troubleshoot-ingestion",children:"Troubleshoot ingestion"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["If tool calls and knowledge appear normal, but the agent's responses seem off-topic or incorrect, consider changing the agent's language model or prompt, as explained in ",(0,o.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"Inspect and modify flows"}),"."]}),"\n",(0,o.jsx)(n.h2,{id:"integrate-openrag-chat-into-an-application",children:"Integrate OpenRAG chat into an application"}),"\n",(0,o.jsxs)(n.p,{children:["You can integrate OpenRAG flows into your applications using the ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Langflow API"}),".\nTo simplify this integration, you can get pre-configured code snippets directly from the embedded Langflow visual editor."]}),"\n",(0,o.jsxs)(n.p,{children:["The following example demonstrates how to generate and use code snippets for the ",(0,o.jsx)(n.strong,{children:"OpenRAG OpenSearch Agent"})," flow:"]}),"\n",(0,o.jsx)(a.Ay,{})]})}function u(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(g,{...e})}):g(e)}},3982:(e,n,t)=>{t.d(n,{A:()=>s});const s=t.p+"assets/images/opensearch-agent-flow-f3b279e02425cd043002eb7749067108.png"},7224:(e,n,t)=>{t.d(n,{Ay:()=>h,RM:()=>l});var s=t(4848),o=t(8453),r=t(1610),i=t(1470),a=t(9365);const l=[];function c(e){const n={a:"a",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsxs)(n.ol,{children:["\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:["Open the ",(0,s.jsx)(n.strong,{children:"OpenRAG OpenSearch Agent"})," flow in the Langflow visual editor: From the ",(0,s.jsx)(n.strong,{children:"Chat"})," window, click ",(0,s.jsx)(r.A,{name:"Settings2","aria-hidden":"true"})," ",(0,s.jsx)(n.strong,{children:"Settings"}),", click ",(0,s.jsx)(n.strong,{children:"Edit in Langflow"}),", and then click ",(0,s.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:["Create a ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"}),", which is a user-specific token required to send requests to the Langflow server.\nThis key doesn't grant access to OpenRAG."]}),"\n",(0,s.jsxs)(n.ol,{children:["\n",(0,s.jsxs)(n.li,{children:["In the Langflow visual editor, click your user icon in the header, and then select ",(0,s.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,s.jsxs)(n.li,{children:["Click ",(0,s.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,s.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,s.jsx)(n.strong,{children:"Add New"}),"."]}),"\n",(0,s.jsxs)(n.li,{children:["Name your key, and then click ",(0,s.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n",(0,s.jsx)(n.li,{children:"Copy the API key and store it securely."}),"\n",(0,s.jsxs)(n.li,{children:["Exit the Langflow ",(0,s.jsx)(n.strong,{children:"Settings"})," page to return to the visual editor."]}),"\n"]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:["Click ",(0,s.jsx)(n.strong,{children:"Share"}),", and then select ",(0,s.jsx)(n.strong,{children:"API access"})," to get pregenerated code snippets that call the Langflow API and run the flow."]}),"\n",(0,s.jsxs)(n.p,{children:["These code snippets construct API requests with your Langflow server URL (",(0,s.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"}),"), the flow to run (",(0,s.jsx)(n.code,{children:"FLOW_ID"}),"), required headers (",(0,s.jsx)(n.code,{children:"LANGFLOW_API_KEY"}),", ",(0,s.jsx)(n.code,{children:"Content-Type"}),"), and a payload containing the required inputs to run the flow, including a default chat input message."]}),"\n",(0,s.jsx)(n.p,{children:"In production, you would modify the inputs to suit your application logic. For example, you could replace the default chat input message with dynamic user input."}),"\n",(0,s.jsxs)(i.A,{children:[(0,s.jsx)(a.A,{value:"python",label:"Python",children:(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-python",children:'import requests\nimport os\nimport uuid\n\napi_key = \'LANGFLOW_API_KEY\'\nurl = "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" # The complete API endpoint URL for this flow\n\n# Request payload configuration\npayload = {\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n}\npayload["session_id"] = str(uuid.uuid4())\n\nheaders = {"x-api-key": api_key}\n\ntry:\n # Send API request\n response = requests.request("POST", url, json=payload, headers=headers)\n response.raise_for_status() # Raise exception for bad status codes\n\n # Print response\n print(response.text)\n\nexcept requests.exceptions.RequestException as e:\n print(f"Error making API request: {e}")\nexcept ValueError as e:\n print(f"Error parsing response: {e}")\n'})})}),(0,s.jsx)(a.A,{value:"typescript",label:"TypeScript",children:(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-typescript",children:'const crypto = require(\'crypto\');\nconst apiKey = \'LANGFLOW_API_KEY\';\nconst payload = {\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n};\npayload.session_id = crypto.randomUUID();\n\nconst options = {\n method: \'POST\',\n headers: {\n \'Content-Type\': \'application/json\',\n "x-api-key": apiKey\n },\n body: JSON.stringify(payload)\n};\n\nfetch(\'http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID\', options)\n .then(response => response.json())\n .then(response => console.warn(response))\n .catch(err => console.error(err));\n'})})}),(0,s.jsx)(a.A,{value:"curl",label:"curl",children:(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-bash",children:'curl --request POST \\\n --url \'http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID?stream=false\' \\\n --header \'Content-Type: application/json\' \\\n --header "x-api-key: LANGFLOW_API_KEY" \\\n --data \'{\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n }\'\n'})})})]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsx)(n.p,{children:"Copy your preferred snippet, and then run it:"}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsxs)(n.li,{children:[(0,s.jsx)(n.strong,{children:"Python"}),": Paste the snippet into a ",(0,s.jsx)(n.code,{children:".py"})," file, save it, and then run it with ",(0,s.jsx)(n.code,{children:"python filename.py"}),"."]}),"\n",(0,s.jsxs)(n.li,{children:[(0,s.jsx)(n.strong,{children:"TypeScript"}),": Paste the snippet into a ",(0,s.jsx)(n.code,{children:".ts"})," file, save it, and then run it with ",(0,s.jsx)(n.code,{children:"ts-node filename.ts"}),"."]}),"\n",(0,s.jsxs)(n.li,{children:[(0,s.jsx)(n.strong,{children:"curl"}),": Paste and run snippet directly in your terminal."]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,s.jsx)(n.p,{children:"If the request is successful, the response includes many details about the flow run, including the session ID, inputs, outputs, components, durations, and more."}),"\n",(0,s.jsxs)(n.p,{children:["In production, you won't pass the raw response to the user in its entirety.\nInstead, you extract and reformat relevant fields for different use cases, as demonstrated in the ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/quickstart#extract-data-from-the-response",children:"Langflow quickstart"}),".\nFor example, you could pass the chat output text to a front-end user-facing application, and store specific fields in logs and backend data stores for monitoring, chat history, or analytics.\nYou could also pass the output from one flow as input to another flow."]})]})}function h(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(c,{...e})}):c(e)}},8401:(e,n,t)=>{t.d(n,{Ay:()=>l,RM:()=>i});var s=t(4848),o=t(8453),r=t(1610);const i=[];function a(e){const n={p:"p",strong:"strong",...(0,o.R)(),...e.components};return(0,s.jsxs)(n.p,{children:["When using the OpenRAG ",(0,s.jsx)(n.strong,{children:"Chat"}),", click ",(0,s.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," in the chat input field to upload a file to the current chat session.\nFiles added this way are processed and made available to the agent for the current conversation only.\nThese files aren't stored in the knowledge base permanently."]})}function l(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(a,{...e})}):a(e)}}}]); \ No newline at end of file diff --git a/assets/js/33362219.2c5776a2.js b/assets/js/33362219.2c5776a2.js deleted file mode 100644 index e6b7a953..00000000 --- a/assets/js/33362219.2c5776a2.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[9532],{3782:(e,n,t)=>{t.d(n,{Ay:()=>c,RM:()=>i});var o=t(4848),s=t(8453),r=t(1610);const i=[];function a(e){const n={a:"a",p:"p",strong:"strong",...(0,s.R)(),...e.components};return(0,o.jsxs)(n.p,{children:["All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic.\nTo modify a flow, click ",(0,o.jsx)(r.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"}),", and click ",(0,o.jsx)(n.strong,{children:"Edit in Langflow"}),".\nOpenRAG's visual editor is based on the ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),", so you can edit your flows to match your specific use case."]})}function c(e={}){const{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(a,{...e})}):a(e)}},3982:(e,n,t)=>{t.d(n,{A:()=>o});const o=t.p+"assets/images/opensearch-agent-flow-f3b279e02425cd043002eb7749067108.png"},8748:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>h,contentTitle:()=>l,default:()=>g,frontMatter:()=>c,metadata:()=>o,toc:()=>d});const o=JSON.parse('{"id":"core-components/agents","title":"Langflow in OpenRAG","description":"OpenRAG leverages Langflow\'s Agent component to power the OpenRAG OpenSearch Agent flow.","source":"@site/docs/core-components/agents.mdx","sourceDirName":"core-components","slug":"/agents","permalink":"/agents","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/core-components/agents.mdx","tags":[],"version":"current","frontMatter":{"title":"Langflow in OpenRAG","slug":"/agents"},"sidebar":"tutorialSidebar","previous":{"title":"Install OpenRAG containers","permalink":"/docker"},"next":{"title":"OpenSearch in OpenRAG","permalink":"/knowledge"}}');var s=t(4848),r=t(8453),i=t(1610),a=(t(1470),t(9365),t(3782));const c={title:"Langflow in OpenRAG",slug:"/agents"},l=void 0,h={},d=[{value:"Use the OpenRAG OpenSearch Agent flow",id:"flow",level:2},...a.RM,{value:"Additional Langflow functionality",id:"additional-langflow-functionality",level:2}];function p(e){const n={a:"a",code:"code",h2:"h2",img:"img",li:"li",p:"p",strong:"strong",ul:"ul",...(0,r.R)(),...e.components},{Details:o}=n;return o||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.p,{children:"OpenRAG leverages Langflow's Agent component to power the OpenRAG OpenSearch Agent flow."}),"\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Flows"})," in Langflow are functional representations of application workflows, with multiple ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/concepts-components",children:"component"})," nodes connected as single steps in a workflow."]}),"\n",(0,s.jsxs)(n.p,{children:["In the OpenRAG OpenSearch Agent flow, components like the Langflow ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/agents",children:[(0,s.jsx)(n.strong,{children:"Agent"})," component"]})," and ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/bundles-elastic#opensearch",children:[(0,s.jsx)(n.strong,{children:"OpenSearch"})," component"]})," are connected to intelligently chat with your knowledge by embedding your query, comparing it the vector database embeddings, and generating a response with the LLM."]}),"\n",(0,s.jsx)(n.p,{children:(0,s.jsx)(n.img,{alt:"OpenRAG Open Search Agent Flow",src:t(3982).A+"",width:"4084",height:"2176"})}),"\n",(0,s.jsx)(n.p,{children:"The Agent component shines here in its ability to make decisions on not only what query should be sent, but when a query is necessary to solve the problem at hand."}),"\n",(0,s.jsxs)(o,{closed:!0,children:[(0,s.jsx)("summary",{children:"How do agents work?"}),(0,s.jsx)(n.p,{children:"Agents extend Large Language Models (LLMs) by integrating tools, which are functions that provide additional context and enable autonomous task execution. These integrations make agents more specialized and powerful than standalone LLMs."}),(0,s.jsx)(n.p,{children:"Whereas an LLM might generate acceptable, inert responses to general queries and tasks, an agent can leverage the integrated context and tools to provide more relevant responses and even take action. For example, you might create an agent that can access your company's documentation, repositories, and other resources to help your team with tasks that require knowledge of your specific products, customers, and code."}),(0,s.jsx)(n.p,{children:"Agents use LLMs as a reasoning engine to process input, determine which actions to take to address the query, and then generate a response. The response could be a typical text-based LLM response, or it could involve an action, like editing a file, running a script, or calling an external API."}),(0,s.jsx)(n.p,{children:"In an agentic context, tools are functions that the agent can run to perform tasks or access external resources. A function is wrapped as a Tool object with a common interface that the agent understands. Agents become aware of tools through tool registration, which is when the agent is provided a list of available tools typically at agent initialization. The Tool object's description tells the agent what the tool can do so that it can decide whether the tool is appropriate for a given request."})]}),"\n",(0,s.jsx)(n.h2,{id:"flow",children:"Use the OpenRAG OpenSearch Agent flow"}),"\n",(0,s.jsxs)(n.p,{children:["If you've chatted with your knowledge in OpenRAG, you've already experienced the OpenRAG OpenSearch Agent chat flow.\nTo switch OpenRAG over to the ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"})," and view the OpenRAG OpenSearch Agentflow, click ",(0,s.jsx)(i.A,{name:"Settings2","aria-hidden":"true"})," ",(0,s.jsx)(n.strong,{children:"Settings"}),", and then click ",(0,s.jsx)(n.strong,{children:"Edit in Langflow"}),".\nThis flow contains eight components connected together to chat with your data:"]}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/agents",children:[(0,s.jsx)(n.strong,{children:"Agent"})," component"]})," orchestrates the entire flow by deciding when to search the knowledge base, how to formulate search queries, and how to combine retrieved information with the user's question to generate a comprehensive response.\nThe ",(0,s.jsx)(n.strong,{children:"Agent"})," behaves according to the prompt in the ",(0,s.jsx)(n.strong,{children:"Agent Instructions"})," field."]}),"\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/components-io",children:[(0,s.jsx)(n.strong,{children:"Chat Input"})," component"]})," is connected to the Agent component's Input port. This allows to flow to be triggered by an incoming prompt from a user or application."]}),"\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/bundles-elastic#opensearch",children:[(0,s.jsx)(n.strong,{children:"OpenSearch"})," component"]})," is connected to the Agent component's Tools port. The agent might not use this database for every request; the agent only uses this connection if it decides the knowledge can help respond to the prompt."]}),"\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/components-models",children:[(0,s.jsx)(n.strong,{children:"Language Model"})," component"]})," is connected to the Agent component's Language Model port. The agent uses the connected LLM to reason through the request sent through Chat Input."]}),"\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/components-embedding-models",children:[(0,s.jsx)(n.strong,{children:"Embedding Model"})," component"]})," is connected to the OpenSearch component's Embedding port. This component converts text queries into vector representations that are compared with document embeddings stored in OpenSearch for semantic similarity matching. This gives your Agent's queries context."]}),"\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/components-io",children:[(0,s.jsx)(n.strong,{children:"Text Input"})," component"]})," is populated with the global variable ",(0,s.jsx)(n.code,{children:"OPENRAG-QUERY-FILTER"}),".\nThis filter is the ",(0,s.jsx)(n.a,{href:"/knowledge#create-knowledge-filters",children:"Knowledge filter"}),", and filters which knowledge sources to search through."]}),"\n",(0,s.jsxs)(n.li,{children:["The ",(0,s.jsx)(n.strong,{children:"Agent"})," component's Output port is connected to the ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/components-io",children:[(0,s.jsx)(n.strong,{children:"Chat Output"})," component"]}),", which returns the final response to the user or application."]}),"\n",(0,s.jsxs)(n.li,{children:["An ",(0,s.jsxs)(n.a,{href:"https://docs.langflow.org/mcp-client",children:[(0,s.jsx)(n.strong,{children:"MCP Tools"})," component"]})," is connected to the Agent's ",(0,s.jsx)(n.strong,{children:"Tools"})," port. This component calls the ",(0,s.jsx)(n.a,{href:"/ingestion#url-flow",children:"OpenSearch URL Ingestion flow"}),", which Langflow uses as an MCP server to fetch content from URLs and store in OpenSearch."]}),"\n"]}),"\n",(0,s.jsx)(a.Ay,{}),"\n",(0,s.jsxs)(n.p,{children:["For an example of changing out the agent's language model in OpenRAG, see the ",(0,s.jsx)(n.a,{href:"/quickstart#change-components",children:"Quickstart"}),"."]}),"\n",(0,s.jsxs)(n.p,{children:["To restore the flow to its initial state, in OpenRAG, click ",(0,s.jsx)(i.A,{name:"Settings2","aria-hidden":"true"})," ",(0,s.jsx)(n.strong,{children:"Settings"}),", and then click ",(0,s.jsx)(n.strong,{children:"Restore Flow"}),".\nOpenRAG warns you that this discards all custom settings. Click ",(0,s.jsx)(n.strong,{children:"Restore"})," to restore the flow."]}),"\n",(0,s.jsx)(n.h2,{id:"additional-langflow-functionality",children:"Additional Langflow functionality"}),"\n",(0,s.jsx)(n.p,{children:"Langflow includes features beyond Agents to help you integrate OpenRAG into your application, and all Langflow features are included in OpenRAG."}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:["Langflow can serve your flows as an ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/mcp-server",children:"MCP server"}),", or consume other MCP servers as an ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/mcp-client",children:"MCP client"}),". Get started with the ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/mcp-tutorial",children:"MCP tutorial"}),"."]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:["If you don't see the component you need, extend Langflow's functionality by creating ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/components-custom-components",children:"custom Python components"}),"."]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:["Langflow offers component ",(0,s.jsx)(n.a,{href:"https://docs.langflow.org/components-bundle-components",children:"bundles"})," to integrate with many popular vector stores, AI/ML providers, and search APIs."]}),"\n"]}),"\n"]})]})}function g(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(p,{...e})}):p(e)}}}]); \ No newline at end of file diff --git a/assets/js/33362219.356477a0.js b/assets/js/33362219.356477a0.js new file mode 100644 index 00000000..438df4ef --- /dev/null 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0!==(k=this.performAction.apply(C,[o,d,l,p.yy,L[1],s,i].concat(g))))return k;v&&(r=r.slice(0,-1*v*2),s=s.slice(0,-1*v),i=i.slice(0,-1*v)),r.push(this.productions_[L[1]][0]),s.push(C.$),i.push(C._$),E=n[r[r.length-2]][r[r.length-1]],r.push(E);break;case 3:return!0}}return!0},"parse")},f=function(){return{EOF:1,parseError:(0,c.K2)(function(t,e){if(!this.yy.parser)throw new Error(t);this.yy.parser.parseError(t,e)},"parseError"),setInput:(0,c.K2)(function(t,e){return this.yy=e||this.yy||{},this._input=t,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:(0,c.K2)(function(){var t=this._input[0];return this.yytext+=t,this.yyleng++,this.offset++,this.match+=t,this.matched+=t,t.match(/(?:\r\n?|\n).*/g)?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),t},"input"),unput:(0,c.K2)(function(t){var e=t.length,r=t.split(/(?:\r\n?|\n)/g);this._input=t+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-e),this.offset-=e;var a=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),r.length-1&&(this.yylineno-=r.length-1);var s=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:r?(r.length===a.length?this.yylloc.first_column:0)+a[a.length-r.length].length-r[0].length:this.yylloc.first_column-e},this.options.ranges&&(this.yylloc.range=[s[0],s[0]+this.yyleng-e]),this.yyleng=this.yytext.length,this},"unput"),more:(0,c.K2)(function(){return this._more=!0,this},"more"),reject:(0,c.K2)(function(){return this.options.backtrack_lexer?(this._backtrack=!0,this):this.parseError("Lexical error on line "+(this.yylineno+1)+". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"reject"),less:(0,c.K2)(function(t){this.unput(this.match.slice(t))},"less"),pastInput:(0,c.K2)(function(){var t=this.matched.substr(0,this.matched.length-this.match.length);return(t.length>20?"...":"")+t.substr(-20).replace(/\n/g,"")},"pastInput"),upcomingInput:(0,c.K2)(function(){var t=this.match;return t.length<20&&(t+=this._input.substr(0,20-t.length)),(t.substr(0,20)+(t.length>20?"...":"")).replace(/\n/g,"")},"upcomingInput"),showPosition:(0,c.K2)(function(){var t=this.pastInput(),e=new Array(t.length+1).join("-");return t+this.upcomingInput()+"\n"+e+"^"},"showPosition"),test_match:(0,c.K2)(function(t,e){var r,a,s;if(this.options.backtrack_lexer&&(s={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(s.yylloc.range=this.yylloc.range.slice(0))),(a=t[0].match(/(?:\r\n?|\n).*/g))&&(this.yylineno+=a.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:a?a[a.length-1].length-a[a.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+t[0].length},this.yytext+=t[0],this.match+=t[0],this.matches=t,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(t[0].length),this.matched+=t[0],r=this.performAction.call(this,this.yy,this,e,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),r)return r;if(this._backtrack){for(var i in s)this[i]=s[i];return!1}return!1},"test_match"),next:(0,c.K2)(function(){if(this.done)return this.EOF;var t,e,r,a;this._input||(this.done=!0),this._more||(this.yytext="",this.match="");for(var s=this._currentRules(),i=0;ie[0].length)){if(e=r,a=i,this.options.backtrack_lexer){if(!1!==(t=this.test_match(r,s[i])))return t;if(this._backtrack){e=!1;continue}return!1}if(!this.options.flex)break}return e?!1!==(t=this.test_match(e,s[a]))&&t:""===this._input?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+". Unrecognized text.\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"next"),lex:(0,c.K2)(function(){var t=this.next();return t||this.lex()},"lex"),begin:(0,c.K2)(function(t){this.conditionStack.push(t)},"begin"),popState:(0,c.K2)(function(){return this.conditionStack.length-1>0?this.conditionStack.pop():this.conditionStack[0]},"popState"),_currentRules:(0,c.K2)(function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},"_currentRules"),topState:(0,c.K2)(function(t){return(t=this.conditionStack.length-1-Math.abs(t||0))>=0?this.conditionStack[t]:"INITIAL"},"topState"),pushState:(0,c.K2)(function(t){this.begin(t)},"pushState"),stateStackSize:(0,c.K2)(function(){return this.conditionStack.length},"stateStackSize"),options:{},performAction:(0,c.K2)(function(t,e,r,a){switch(r){case 0:return t.getLogger().debug("Found block-beta"),10;case 1:return t.getLogger().debug("Found id-block"),29;case 2:return t.getLogger().debug("Found block"),10;case 3:t.getLogger().debug(".",e.yytext);break;case 4:t.getLogger().debug("_",e.yytext);break;case 5:return 5;case 6:return e.yytext=-1,28;case 7:return e.yytext=e.yytext.replace(/columns\s+/,""),t.getLogger().debug("COLUMNS (LEX)",e.yytext),28;case 8:case 76:case 77:case 99:this.pushState("md_string");break;case 9:return"MD_STR";case 10:case 34:case 79:this.popState();break;case 11:this.pushState("string");break;case 12:t.getLogger().debug("LEX: POPPING STR:",e.yytext),this.popState();break;case 13:return t.getLogger().debug("LEX: STR end:",e.yytext),"STR";case 14:return e.yytext=e.yytext.replace(/space\:/,""),t.getLogger().debug("SPACE NUM (LEX)",e.yytext),21;case 15:return e.yytext="1",t.getLogger().debug("COLUMNS (LEX)",e.yytext),21;case 16:return 42;case 17:return"LINKSTYLE";case 18:return"INTERPOLATE";case 19:return this.pushState("CLASSDEF"),39;case 20:return this.popState(),this.pushState("CLASSDEFID"),"DEFAULT_CLASSDEF_ID";case 21:return this.popState(),this.pushState("CLASSDEFID"),40;case 22:return this.popState(),41;case 23:return this.pushState("CLASS"),43;case 24:return this.popState(),this.pushState("CLASS_STYLE"),44;case 25:return this.popState(),45;case 26:return this.pushState("STYLE_STMNT"),46;case 27:return this.popState(),this.pushState("STYLE_DEFINITION"),47;case 28:return this.popState(),48;case 29:return this.pushState("acc_title"),"acc_title";case 30:return this.popState(),"acc_title_value";case 31:return this.pushState("acc_descr"),"acc_descr";case 32:return this.popState(),"acc_descr_value";case 33:this.pushState("acc_descr_multiline");break;case 35:return"acc_descr_multiline_value";case 36:return 30;case 37:case 38:case 40:case 41:case 44:return this.popState(),t.getLogger().debug("Lex: (("),"NODE_DEND";case 39:return this.popState(),t.getLogger().debug("Lex: ))"),"NODE_DEND";case 42:return this.popState(),t.getLogger().debug("Lex: (-"),"NODE_DEND";case 43:return this.popState(),t.getLogger().debug("Lex: -)"),"NODE_DEND";case 45:return this.popState(),t.getLogger().debug("Lex: ]]"),"NODE_DEND";case 46:return this.popState(),t.getLogger().debug("Lex: ("),"NODE_DEND";case 47:return this.popState(),t.getLogger().debug("Lex: ])"),"NODE_DEND";case 48:case 49:return this.popState(),t.getLogger().debug("Lex: /]"),"NODE_DEND";case 50:return this.popState(),t.getLogger().debug("Lex: )]"),"NODE_DEND";case 51:return this.popState(),t.getLogger().debug("Lex: )"),"NODE_DEND";case 52:return this.popState(),t.getLogger().debug("Lex: ]>"),"NODE_DEND";case 53:return this.popState(),t.getLogger().debug("Lex: ]"),"NODE_DEND";case 54:return t.getLogger().debug("Lexa: -)"),this.pushState("NODE"),35;case 55:return t.getLogger().debug("Lexa: (-"),this.pushState("NODE"),35;case 56:return t.getLogger().debug("Lexa: ))"),this.pushState("NODE"),35;case 57:case 59:case 60:case 61:case 64:return t.getLogger().debug("Lexa: )"),this.pushState("NODE"),35;case 58:return t.getLogger().debug("Lex: ((("),this.pushState("NODE"),35;case 62:return t.getLogger().debug("Lexc: >"),this.pushState("NODE"),35;case 63:return t.getLogger().debug("Lexa: (["),this.pushState("NODE"),35;case 65:case 66:case 67:case 68:case 69:case 70:case 71:return this.pushState("NODE"),35;case 72:return t.getLogger().debug("Lexa: ["),this.pushState("NODE"),35;case 73:return this.pushState("BLOCK_ARROW"),t.getLogger().debug("LEX ARR START"),37;case 74:return t.getLogger().debug("Lex: NODE_ID",e.yytext),31;case 75:return t.getLogger().debug("Lex: EOF",e.yytext),8;case 78:return"NODE_DESCR";case 80:t.getLogger().debug("Lex: Starting string"),this.pushState("string");break;case 81:t.getLogger().debug("LEX ARR: Starting string"),this.pushState("string");break;case 82:return t.getLogger().debug("LEX: NODE_DESCR:",e.yytext),"NODE_DESCR";case 83:t.getLogger().debug("LEX POPPING"),this.popState();break;case 84:t.getLogger().debug("Lex: =>BAE"),this.pushState("ARROW_DIR");break;case 85:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (right): dir:",e.yytext),"DIR";case 86:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (left):",e.yytext),"DIR";case 87:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (x):",e.yytext),"DIR";case 88:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (y):",e.yytext),"DIR";case 89:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (up):",e.yytext),"DIR";case 90:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (down):",e.yytext),"DIR";case 91:return e.yytext="]>",t.getLogger().debug("Lex (ARROW_DIR end):",e.yytext),this.popState(),this.popState(),"BLOCK_ARROW_END";case 92:return t.getLogger().debug("Lex: LINK","#"+e.yytext+"#"),15;case 93:case 94:case 95:return t.getLogger().debug("Lex: LINK",e.yytext),15;case 96:case 97:case 98:return t.getLogger().debug("Lex: START_LINK",e.yytext),this.pushState("LLABEL"),16;case 100:return t.getLogger().debug("Lex: Starting string"),this.pushState("string"),"LINK_LABEL";case 101:return this.popState(),t.getLogger().debug("Lex: LINK","#"+e.yytext+"#"),15;case 102:case 103:return this.popState(),t.getLogger().debug("Lex: LINK",e.yytext),15;case 104:return t.getLogger().debug("Lex: COLON",e.yytext),e.yytext=e.yytext.slice(1),27}},"anonymous"),rules:[/^(?:block-beta\b)/,/^(?:block:)/,/^(?:block\b)/,/^(?:[\s]+)/,/^(?:[\n]+)/,/^(?:((\u000D\u000A)|(\u000A)))/,/^(?:columns\s+auto\b)/,/^(?:columns\s+[\d]+)/,/^(?:["][`])/,/^(?:[^`"]+)/,/^(?:[`]["])/,/^(?:["])/,/^(?:["])/,/^(?:[^"]*)/,/^(?:space[:]\d+)/,/^(?:space\b)/,/^(?:default\b)/,/^(?:linkStyle\b)/,/^(?:interpolate\b)/,/^(?:classDef\s+)/,/^(?:DEFAULT\s+)/,/^(?:\w+\s+)/,/^(?:[^\n]*)/,/^(?:class\s+)/,/^(?:(\w+)+((,\s*\w+)*))/,/^(?:[^\n]*)/,/^(?:style\s+)/,/^(?:(\w+)+((,\s*\w+)*))/,/^(?:[^\n]*)/,/^(?:accTitle\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*\{\s*)/,/^(?:[\}])/,/^(?:[^\}]*)/,/^(?:end\b\s*)/,/^(?:\(\(\()/,/^(?:\)\)\))/,/^(?:[\)]\))/,/^(?:\}\})/,/^(?:\})/,/^(?:\(-)/,/^(?:-\))/,/^(?:\(\()/,/^(?:\]\])/,/^(?:\()/,/^(?:\]\))/,/^(?:\\\])/,/^(?:\/\])/,/^(?:\)\])/,/^(?:[\)])/,/^(?:\]>)/,/^(?:[\]])/,/^(?:-\))/,/^(?:\(-)/,/^(?:\)\))/,/^(?:\))/,/^(?:\(\(\()/,/^(?:\(\()/,/^(?:\{\{)/,/^(?:\{)/,/^(?:>)/,/^(?:\(\[)/,/^(?:\()/,/^(?:\[\[)/,/^(?:\[\|)/,/^(?:\[\()/,/^(?:\)\)\))/,/^(?:\[\\)/,/^(?:\[\/)/,/^(?:\[\\)/,/^(?:\[)/,/^(?:<\[)/,/^(?:[^\(\[\n\-\)\{\}\s\<\>:]+)/,/^(?:$)/,/^(?:["][`])/,/^(?:["][`])/,/^(?:[^`"]+)/,/^(?:[`]["])/,/^(?:["])/,/^(?:["])/,/^(?:[^"]+)/,/^(?:["])/,/^(?:\]>\s*\()/,/^(?:,?\s*right\s*)/,/^(?:,?\s*left\s*)/,/^(?:,?\s*x\s*)/,/^(?:,?\s*y\s*)/,/^(?:,?\s*up\s*)/,/^(?:,?\s*down\s*)/,/^(?:\)\s*)/,/^(?:\s*[xo<]?--+[-xo>]\s*)/,/^(?:\s*[xo<]?==+[=xo>]\s*)/,/^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,/^(?:\s*~~[\~]+\s*)/,/^(?:\s*[xo<]?--\s*)/,/^(?:\s*[xo<]?==\s*)/,/^(?:\s*[xo<]?-\.\s*)/,/^(?:["][`])/,/^(?:["])/,/^(?:\s*[xo<]?--+[-xo>]\s*)/,/^(?:\s*[xo<]?==+[=xo>]\s*)/,/^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,/^(?::\d+)/],conditions:{STYLE_DEFINITION:{rules:[28],inclusive:!1},STYLE_STMNT:{rules:[27],inclusive:!1},CLASSDEFID:{rules:[22],inclusive:!1},CLASSDEF:{rules:[20,21],inclusive:!1},CLASS_STYLE:{rules:[25],inclusive:!1},CLASS:{rules:[24],inclusive:!1},LLABEL:{rules:[99,100,101,102,103],inclusive:!1},ARROW_DIR:{rules:[85,86,87,88,89,90,91],inclusive:!1},BLOCK_ARROW:{rules:[76,81,84],inclusive:!1},NODE:{rules:[37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,77,80],inclusive:!1},md_string:{rules:[9,10,78,79],inclusive:!1},space:{rules:[],inclusive:!1},string:{rules:[12,13,82,83],inclusive:!1},acc_descr_multiline:{rules:[34,35],inclusive:!1},acc_descr:{rules:[32],inclusive:!1},acc_title:{rules:[30],inclusive:!1},INITIAL:{rules:[0,1,2,3,4,5,6,7,8,11,14,15,16,17,18,19,23,26,29,31,33,36,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,92,93,94,95,96,97,98,104],inclusive:!0}}}}();function m(){this.yy={}}return x.lexer=f,(0,c.K2)(m,"Parser"),m.prototype=x,x.Parser=m,new m}();y.parser=y;var b=y,x=new Map,f=[],m=new Map,w="color",_="fill",L=(0,l.D7)(),k=new Map,S=(0,c.K2)(t=>l.Y2.sanitizeText(t,L),"sanitizeText"),v=(0,c.K2)(function(t,e=""){let r=k.get(t);r||(r={id:t,styles:[],textStyles:[]},k.set(t,r)),null!=e&&e.split(",").forEach(t=>{const e=t.replace(/([^;]*);/,"$1").trim();if(RegExp(w).exec(t)){const t=e.replace(_,"bgFill").replace(w,_);r.textStyles.push(t)}r.styles.push(e)})},"addStyleClass"),E=(0,c.K2)(function(t,e=""){const r=x.get(t);null!=e&&(r.styles=e.split(","))},"addStyle2Node"),D=(0,c.K2)(function(t,e){t.split(",").forEach(function(t){let r=x.get(t);if(void 0===r){const e=t.trim();r={id:e,type:"na",children:[]},x.set(e,r)}r.classes||(r.classes=[]),r.classes.push(e)})},"setCssClass"),C=(0,c.K2)((t,e)=>{const r=t.flat(),a=[],s=r.find(t=>"column-setting"===t?.type),i=s?.columns??-1;for(const n of r)if("number"==typeof 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You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"reject"),less:(0,c.K2)(function(t){this.unput(this.match.slice(t))},"less"),pastInput:(0,c.K2)(function(){var t=this.matched.substr(0,this.matched.length-this.match.length);return(t.length>20?"...":"")+t.substr(-20).replace(/\n/g,"")},"pastInput"),upcomingInput:(0,c.K2)(function(){var t=this.match;return t.length<20&&(t+=this._input.substr(0,20-t.length)),(t.substr(0,20)+(t.length>20?"...":"")).replace(/\n/g,"")},"upcomingInput"),showPosition:(0,c.K2)(function(){var t=this.pastInput(),e=new Array(t.length+1).join("-");return t+this.upcomingInput()+"\n"+e+"^"},"showPosition"),test_match:(0,c.K2)(function(t,e){var r,a,s;if(this.options.backtrack_lexer&&(s={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(s.yylloc.range=this.yylloc.range.slice(0))),(a=t[0].match(/(?:\r\n?|\n).*/g))&&(this.yylineno+=a.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:a?a[a.length-1].length-a[a.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+t[0].length},this.yytext+=t[0],this.match+=t[0],this.matches=t,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(t[0].length),this.matched+=t[0],r=this.performAction.call(this,this.yy,this,e,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),r)return r;if(this._backtrack){for(var i in s)this[i]=s[i];return!1}return!1},"test_match"),next:(0,c.K2)(function(){if(this.done)return this.EOF;var t,e,r,a;this._input||(this.done=!0),this._more||(this.yytext="",this.match="");for(var s=this._currentRules(),i=0;ie[0].length)){if(e=r,a=i,this.options.backtrack_lexer){if(!1!==(t=this.test_match(r,s[i])))return t;if(this._backtrack){e=!1;continue}return!1}if(!this.options.flex)break}return e?!1!==(t=this.test_match(e,s[a]))&&t:""===this._input?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+". Unrecognized text.\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"next"),lex:(0,c.K2)(function(){var t=this.next();return t||this.lex()},"lex"),begin:(0,c.K2)(function(t){this.conditionStack.push(t)},"begin"),popState:(0,c.K2)(function(){return this.conditionStack.length-1>0?this.conditionStack.pop():this.conditionStack[0]},"popState"),_currentRules:(0,c.K2)(function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},"_currentRules"),topState:(0,c.K2)(function(t){return(t=this.conditionStack.length-1-Math.abs(t||0))>=0?this.conditionStack[t]:"INITIAL"},"topState"),pushState:(0,c.K2)(function(t){this.begin(t)},"pushState"),stateStackSize:(0,c.K2)(function(){return this.conditionStack.length},"stateStackSize"),options:{},performAction:(0,c.K2)(function(t,e,r,a){switch(r){case 0:return t.getLogger().debug("Found block-beta"),10;case 1:return t.getLogger().debug("Found id-block"),29;case 2:return t.getLogger().debug("Found block"),10;case 3:t.getLogger().debug(".",e.yytext);break;case 4:t.getLogger().debug("_",e.yytext);break;case 5:return 5;case 6:return e.yytext=-1,28;case 7:return e.yytext=e.yytext.replace(/columns\s+/,""),t.getLogger().debug("COLUMNS (LEX)",e.yytext),28;case 8:case 76:case 77:case 99:this.pushState("md_string");break;case 9:return"MD_STR";case 10:case 34:case 79:this.popState();break;case 11:this.pushState("string");break;case 12:t.getLogger().debug("LEX: POPPING STR:",e.yytext),this.popState();break;case 13:return t.getLogger().debug("LEX: STR end:",e.yytext),"STR";case 14:return e.yytext=e.yytext.replace(/space\:/,""),t.getLogger().debug("SPACE NUM (LEX)",e.yytext),21;case 15:return e.yytext="1",t.getLogger().debug("COLUMNS (LEX)",e.yytext),21;case 16:return 42;case 17:return"LINKSTYLE";case 18:return"INTERPOLATE";case 19:return this.pushState("CLASSDEF"),39;case 20:return this.popState(),this.pushState("CLASSDEFID"),"DEFAULT_CLASSDEF_ID";case 21:return this.popState(),this.pushState("CLASSDEFID"),40;case 22:return this.popState(),41;case 23:return this.pushState("CLASS"),43;case 24:return this.popState(),this.pushState("CLASS_STYLE"),44;case 25:return this.popState(),45;case 26:return this.pushState("STYLE_STMNT"),46;case 27:return this.popState(),this.pushState("STYLE_DEFINITION"),47;case 28:return this.popState(),48;case 29:return this.pushState("acc_title"),"acc_title";case 30:return this.popState(),"acc_title_value";case 31:return this.pushState("acc_descr"),"acc_descr";case 32:return this.popState(),"acc_descr_value";case 33:this.pushState("acc_descr_multiline");break;case 35:return"acc_descr_multiline_value";case 36:return 30;case 37:case 38:case 40:case 41:case 44:return this.popState(),t.getLogger().debug("Lex: (("),"NODE_DEND";case 39:return this.popState(),t.getLogger().debug("Lex: ))"),"NODE_DEND";case 42:return this.popState(),t.getLogger().debug("Lex: (-"),"NODE_DEND";case 43:return this.popState(),t.getLogger().debug("Lex: -)"),"NODE_DEND";case 45:return this.popState(),t.getLogger().debug("Lex: ]]"),"NODE_DEND";case 46:return this.popState(),t.getLogger().debug("Lex: ("),"NODE_DEND";case 47:return this.popState(),t.getLogger().debug("Lex: ])"),"NODE_DEND";case 48:case 49:return this.popState(),t.getLogger().debug("Lex: /]"),"NODE_DEND";case 50:return this.popState(),t.getLogger().debug("Lex: )]"),"NODE_DEND";case 51:return this.popState(),t.getLogger().debug("Lex: )"),"NODE_DEND";case 52:return this.popState(),t.getLogger().debug("Lex: ]>"),"NODE_DEND";case 53:return this.popState(),t.getLogger().debug("Lex: ]"),"NODE_DEND";case 54:return t.getLogger().debug("Lexa: -)"),this.pushState("NODE"),35;case 55:return t.getLogger().debug("Lexa: (-"),this.pushState("NODE"),35;case 56:return t.getLogger().debug("Lexa: ))"),this.pushState("NODE"),35;case 57:case 59:case 60:case 61:case 64:return t.getLogger().debug("Lexa: )"),this.pushState("NODE"),35;case 58:return t.getLogger().debug("Lex: ((("),this.pushState("NODE"),35;case 62:return t.getLogger().debug("Lexc: >"),this.pushState("NODE"),35;case 63:return t.getLogger().debug("Lexa: (["),this.pushState("NODE"),35;case 65:case 66:case 67:case 68:case 69:case 70:case 71:return this.pushState("NODE"),35;case 72:return t.getLogger().debug("Lexa: ["),this.pushState("NODE"),35;case 73:return this.pushState("BLOCK_ARROW"),t.getLogger().debug("LEX ARR START"),37;case 74:return t.getLogger().debug("Lex: NODE_ID",e.yytext),31;case 75:return t.getLogger().debug("Lex: EOF",e.yytext),8;case 78:return"NODE_DESCR";case 80:t.getLogger().debug("Lex: Starting string"),this.pushState("string");break;case 81:t.getLogger().debug("LEX ARR: Starting string"),this.pushState("string");break;case 82:return t.getLogger().debug("LEX: NODE_DESCR:",e.yytext),"NODE_DESCR";case 83:t.getLogger().debug("LEX POPPING"),this.popState();break;case 84:t.getLogger().debug("Lex: =>BAE"),this.pushState("ARROW_DIR");break;case 85:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (right): dir:",e.yytext),"DIR";case 86:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (left):",e.yytext),"DIR";case 87:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (x):",e.yytext),"DIR";case 88:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (y):",e.yytext),"DIR";case 89:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (up):",e.yytext),"DIR";case 90:return e.yytext=e.yytext.replace(/^,\s*/,""),t.getLogger().debug("Lex (down):",e.yytext),"DIR";case 91:return e.yytext="]>",t.getLogger().debug("Lex (ARROW_DIR end):",e.yytext),this.popState(),this.popState(),"BLOCK_ARROW_END";case 92:return t.getLogger().debug("Lex: LINK","#"+e.yytext+"#"),15;case 93:case 94:case 95:return t.getLogger().debug("Lex: LINK",e.yytext),15;case 96:case 97:case 98:return t.getLogger().debug("Lex: START_LINK",e.yytext),this.pushState("LLABEL"),16;case 100:return t.getLogger().debug("Lex: Starting string"),this.pushState("string"),"LINK_LABEL";case 101:return this.popState(),t.getLogger().debug("Lex: LINK","#"+e.yytext+"#"),15;case 102:case 103:return this.popState(),t.getLogger().debug("Lex: LINK",e.yytext),15;case 104:return t.getLogger().debug("Lex: COLON",e.yytext),e.yytext=e.yytext.slice(1),27}},"anonymous"),rules:[/^(?:block-beta\b)/,/^(?:block:)/,/^(?:block\b)/,/^(?:[\s]+)/,/^(?:[\n]+)/,/^(?:((\u000D\u000A)|(\u000A)))/,/^(?:columns\s+auto\b)/,/^(?:columns\s+[\d]+)/,/^(?:["][`])/,/^(?:[^`"]+)/,/^(?:[`]["])/,/^(?:["])/,/^(?:["])/,/^(?:[^"]*)/,/^(?:space[:]\d+)/,/^(?:space\b)/,/^(?:default\b)/,/^(?:linkStyle\b)/,/^(?:interpolate\b)/,/^(?:classDef\s+)/,/^(?:DEFAULT\s+)/,/^(?:\w+\s+)/,/^(?:[^\n]*)/,/^(?:class\s+)/,/^(?:(\w+)+((,\s*\w+)*))/,/^(?:[^\n]*)/,/^(?:style\s+)/,/^(?:(\w+)+((,\s*\w+)*))/,/^(?:[^\n]*)/,/^(?:accTitle\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*:\s*)/,/^(?:(?!\n||)*[^\n]*)/,/^(?:accDescr\s*\{\s*)/,/^(?:[\}])/,/^(?:[^\}]*)/,/^(?:end\b\s*)/,/^(?:\(\(\()/,/^(?:\)\)\))/,/^(?:[\)]\))/,/^(?:\}\})/,/^(?:\})/,/^(?:\(-)/,/^(?:-\))/,/^(?:\(\()/,/^(?:\]\])/,/^(?:\()/,/^(?:\]\))/,/^(?:\\\])/,/^(?:\/\])/,/^(?:\)\])/,/^(?:[\)])/,/^(?:\]>)/,/^(?:[\]])/,/^(?:-\))/,/^(?:\(-)/,/^(?:\)\))/,/^(?:\))/,/^(?:\(\(\()/,/^(?:\(\()/,/^(?:\{\{)/,/^(?:\{)/,/^(?:>)/,/^(?:\(\[)/,/^(?:\()/,/^(?:\[\[)/,/^(?:\[\|)/,/^(?:\[\()/,/^(?:\)\)\))/,/^(?:\[\\)/,/^(?:\[\/)/,/^(?:\[\\)/,/^(?:\[)/,/^(?:<\[)/,/^(?:[^\(\[\n\-\)\{\}\s\<\>:]+)/,/^(?:$)/,/^(?:["][`])/,/^(?:["][`])/,/^(?:[^`"]+)/,/^(?:[`]["])/,/^(?:["])/,/^(?:["])/,/^(?:[^"]+)/,/^(?:["])/,/^(?:\]>\s*\()/,/^(?:,?\s*right\s*)/,/^(?:,?\s*left\s*)/,/^(?:,?\s*x\s*)/,/^(?:,?\s*y\s*)/,/^(?:,?\s*up\s*)/,/^(?:,?\s*down\s*)/,/^(?:\)\s*)/,/^(?:\s*[xo<]?--+[-xo>]\s*)/,/^(?:\s*[xo<]?==+[=xo>]\s*)/,/^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,/^(?:\s*~~[\~]+\s*)/,/^(?:\s*[xo<]?--\s*)/,/^(?:\s*[xo<]?==\s*)/,/^(?:\s*[xo<]?-\.\s*)/,/^(?:["][`])/,/^(?:["])/,/^(?:\s*[xo<]?--+[-xo>]\s*)/,/^(?:\s*[xo<]?==+[=xo>]\s*)/,/^(?:\s*[xo<]?-?\.+-[xo>]?\s*)/,/^(?::\d+)/],conditions:{STYLE_DEFINITION:{rules:[28],inclusive:!1},STYLE_STMNT:{rules:[27],inclusive:!1},CLASSDEFID:{rules:[22],inclusive:!1},CLASSDEF:{rules:[20,21],inclusive:!1},CLASS_STYLE:{rules:[25],inclusive:!1},CLASS:{rules:[24],inclusive:!1},LLABEL:{rules:[99,100,101,102,103],inclusive:!1},ARROW_DIR:{rules:[85,86,87,88,89,90,91],inclusive:!1},BLOCK_ARROW:{rules:[76,81,84],inclusive:!1},NODE:{rules:[37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,77,80],inclusive:!1},md_string:{rules:[9,10,78,79],inclusive:!1},space:{rules:[],inclusive:!1},string:{rules:[12,13,82,83],inclusive:!1},acc_descr_multiline:{rules:[34,35],inclusive:!1},acc_descr:{rules:[32],inclusive:!1},acc_title:{rules:[30],inclusive:!1},INITIAL:{rules:[0,1,2,3,4,5,6,7,8,11,14,15,16,17,18,19,23,26,29,31,33,36,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,92,93,94,95,96,97,98,104],inclusive:!0}}}}();function m(){this.yy={}}return x.lexer=f,(0,c.K2)(m,"Parser"),m.prototype=x,x.Parser=m,new m}();y.parser=y;var b=y,x=new Map,f=[],m=new Map,w="color",_="fill",L=(0,l.D7)(),k=new Map,S=(0,c.K2)(t=>l.Y2.sanitizeText(t,L),"sanitizeText"),v=(0,c.K2)(function(t,e=""){let r=k.get(t);r||(r={id:t,styles:[],textStyles:[]},k.set(t,r)),null!=e&&e.split(",").forEach(t=>{const e=t.replace(/([^;]*);/,"$1").trim();if(RegExp(w).exec(t)){const t=e.replace(_,"bgFill").replace(w,_);r.textStyles.push(t)}r.styles.push(e)})},"addStyleClass"),E=(0,c.K2)(function(t,e=""){const r=x.get(t);null!=e&&(r.styles=e.split(","))},"addStyle2Node"),D=(0,c.K2)(function(t,e){t.split(",").forEach(function(t){let r=x.get(t);if(void 0===r){const e=t.trim();r={id:e,type:"na",children:[]},x.set(e,r)}r.classes||(r.classes=[]),r.classes.push(e)})},"setCssClass"),C=(0,c.K2)((t,e)=>{const r=t.flat(),a=[],s=r.find(t=>"column-setting"===t?.type),i=s?.columns??-1;for(const n of r)if("number"==typeof 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To install Ollama, see the ",(0,o.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"}),"."]})}),(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["To connect to an Ollama server running on your local machine, enter your Ollama server's base URL address.\nThe default Ollama server address is ",(0,o.jsx)(n.code,{children:"http://localhost:11434"}),".\nOpenRAG connects to the Ollama server and populates the model lists with the server's available models."]}),"\n",(0,o.jsxs)(n.li,{children:["Select the ",(0,o.jsx)(n.strong,{children:"Embedding Model"})," and ",(0,o.jsx)(n.strong,{children:"Language Model"})," your Ollama server is running.","\n",(0,o.jsxs)(s,{closed:!0,children:[(0,o.jsx)("summary",{children:"Ollama model selection and external server configuration"}),(0,o.jsx)(d,{})]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,o.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add a Document"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Continue with the ",(0,o.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})]})]})]})}function p(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(h,{...e})}):h(e)}},3862:(e,n,s)=>{s.d(n,{Ay:()=>t,RM:()=>i});var o=s(4848),r=s(8453);const i=[];function l(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,r.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install",children:"Install WSL"})," with the Ubuntu distribution using WSL 2:"]}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-powershell",children:"wsl --install -d Ubuntu\n"})}),"\n",(0,o.jsxs)(n.p,{children:["For new installations, the ",(0,o.jsx)(n.code,{children:"wsl --install"})," command uses WSL 2 and Ubuntu by default."]}),"\n",(0,o.jsxs)(n.p,{children:["For existing WSL installations, you can ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#change-the-default-linux-distribution-installed",children:"change the distribution"})," and ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2",children:"check the WSL version"}),"."]}),"\n",(0,o.jsx)(n.admonition,{title:"Known limitation",type:"warning",children:(0,o.jsx)(n.p,{children:"OpenRAG isn't compatible with nested virtualization, which can cause networking issues.\nDon't install OpenRAG on a WSL distribution that is installed inside a Windows VM.\nInstead, install OpenRAG on your base OS or a non-nested Linux VM."})}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#ways-to-run-multiple-linux-distributions-with-wsl",children:"Start your WSL Ubuntu distribution"})," if it doesn't start automatically."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/setup/environment#set-up-your-linux-username-and-password",children:"Set up a username and password for your WSL distribution"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers",children:"Install Docker Desktop for Windows with WSL 2"}),". When you reach the Docker Desktop ",(0,o.jsx)(n.strong,{children:"WSL integration"})," settings, make sure your Ubuntu distribution is enabled, and then click ",(0,o.jsx)(n.strong,{children:"Apply & Restart"})," to enable Docker support in WSL."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Install and run OpenRAG from within your WSL Ubuntu distribution."}),"\n"]}),"\n"]}),"\n",(0,o.jsx)("br",{}),"\n",(0,o.jsxs)(n.p,{children:["If you encounter issues with port forwarding or the Windows Firewall, you might need to adjust the ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/security/operating-system-security/network-security/windows-firewall/hyper-v-firewall",children:"Hyper-V firewall settings"})," to allow communication between your WSL distribution and the Windows host. For more troubleshooting advice for networking issues, see ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/troubleshooting#common-issues",children:"Troubleshooting WSL common issues"}),"."]})]})}function t(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(l,{...e})}):l(e)}},5788:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>p,contentTitle:()=>h,default:()=>x,frontMatter:()=>c,metadata:()=>o,toc:()=>u});const o=JSON.parse('{"id":"get-started/docker","title":"Install OpenRAG containers","description":"OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments:","source":"@site/docs/get-started/docker.mdx","sourceDirName":"get-started","slug":"/docker","permalink":"/docker","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/docker.mdx","tags":[],"version":"current","frontMatter":{"title":"Install OpenRAG containers","slug":"/docker"},"sidebar":"tutorialSidebar","previous":{"title":"Install OpenRAG with TUI","permalink":"/install"},"next":{"title":"Langflow in OpenRAG","permalink":"/agents"}}');var r=s(4848),i=s(8453),l=s(1470),t=s(9365),a=s(3656),d=s(3862);const c={title:"Install OpenRAG containers",slug:"/docker"},h=void 0,p={},u=[{value:"Prerequisites",id:"prerequisites",level:2},...d.RM,{value:"Install OpenRAG with Docker Compose",id:"install-openrag-with-docker-compose",level:2},...a.RM,{value:"Container management commands",id:"container-management-commands",level:2},{value:"Upgrade containers",id:"upgrade-containers",level:3},{value:"Rebuild containers (destructive)",id:"rebuild-containers-destructive",level:3},{value:"Remove all containers and data (destructive)",id:"remove-all-containers-and-data-destructive",level:3}];function m(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",table:"table",tbody:"tbody",td:"td",th:"th",thead:"thead",tr:"tr",ul:"ul",...(0,i.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.p,{children:"OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml",children:(0,r.jsx)(n.code,{children:"docker-compose.yml"})})," is an OpenRAG deployment with GPU support for accelerated AI processing. This Docker Compose file requires an NVIDIA GPU with ",(0,r.jsx)(n.a,{href:"https://docs.nvidia.com/cuda/",children:"CUDA"})," support."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml",children:(0,r.jsx)(n.code,{children:"docker-compose-cpu.yml"})})," is a CPU-only version of OpenRAG for systems without NVIDIA GPU support. Use this Docker Compose file for environments where GPU drivers aren't available."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Install the following:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://www.python.org/downloads/release/python-3100/",children:"Python"})," version 3.13 or later."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://docs.astral.sh/uv/getting-started/installation/",children:"uv"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://podman.io/docs/installation",children:"Podman"})," (recommended) or ",(0,r.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"Docker"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://docs.podman.io/en/latest/markdown/podman-compose.1.html",children:(0,r.jsx)(n.code,{children:"podman-compose"})})," or ",(0,r.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"Docker Compose"}),". To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Microsoft Windows only: To run OpenRAG on Windows, you must use the Windows Subsystem for Linux (WSL)."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Install WSL for OpenRAG"}),(0,r.jsx)(d.Ay,{})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Prepare model providers and credentials."}),"\n",(0,r.jsxs)(n.p,{children:["During ",(0,r.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),", you must select language model and embedding model providers.\nIf your chosen provider offers both types, you can use the same provider for both selections.\nIf your provider offers only one type, such as Anthropic, you must select two providers."]}),"\n",(0,r.jsx)(n.p,{children:"Gather the credentials and connection details for your chosen model providers before starting onboarding:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["OpenAI: Create an ",(0,r.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI API key"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Anthropic language models: Create an ",(0,r.jsx)(n.a,{href:"https://www.anthropic.com/docs/api/reference",children:"Anthropic API key"}),"."]}),"\n",(0,r.jsx)(n.li,{children:"IBM watsonx.ai: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment."}),"\n",(0,r.jsxs)(n.li,{children:["Ollama: Use the ",(0,r.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"})," to set up your Ollama instance locally, in the cloud, or on a remote server, and then get your Ollama server's base URL."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Optional: Install GPU support with an NVIDIA GPU, ",(0,r.jsx)(n.a,{href:"https://docs.nvidia.com/cuda/",children:"CUDA"})," support, and compatible NVIDIA drivers on the OpenRAG host machine. This is required to use the GPU-accelerated Docker Compose file. If you choose not to use GPU support, you must use the CPU-only Docker Compose file instead."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"install-openrag-with-docker-compose",children:"Install OpenRAG with Docker Compose"}),"\n",(0,r.jsx)(n.p,{children:"To install OpenRAG with Docker Compose, do the following:"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Clone the OpenRAG repository."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"git clone https://github.com/langflow-ai/openrag.git\ncd openrag\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Install dependencies."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"uv sync\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Copy the example ",(0,r.jsx)(n.code,{children:".env"})," file included in the repository root.\nThe example file includes all environment variables with comments to guide you in finding and setting their values."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"cp .env.example .env\n"})}),"\n",(0,r.jsxs)(n.p,{children:["Alternatively, create a new ",(0,r.jsx)(n.code,{children:".env"})," file in the repository root."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{children:"touch .env\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["The Docker Compose files are populated with the values from your ",(0,r.jsx)(n.code,{children:".env"})," file.\nThe ",(0,r.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})," value must be set.\n",(0,r.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})," can be automatically generated when using the TUI, but for a Docker Compose installation, you can set it manually instead. To generate an OpenSearch admin password, see the ",(0,r.jsx)(n.a,{href:"https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password",children:"OpenSearch documentation"}),"."]}),"\n",(0,r.jsx)(n.p,{children:"The following values are optional:"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"OPENAI_API_KEY=your_openai_api_key\nLANGFLOW_SECRET_KEY=your_secret_key\n"})}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"OPENAI_API_KEY"})," is optional. You can provide it during ",(0,r.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"})," or choose a different model provider. If you want to set it in your ",(0,r.jsx)(n.code,{children:".env"})," file, you can find your OpenAI API key in your ",(0,r.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI account"}),"."]}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"LANGFLOW_SECRET_KEY"})," is optional. Langflow will auto-generate it if not set. For more information, see the ",(0,r.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key",children:"Langflow documentation"}),"."]}),"\n",(0,r.jsx)(n.p,{children:"The following Langflow configuration values are optional but important to consider:"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"LANGFLOW_SUPERUSER=admin\nLANGFLOW_SUPERUSER_PASSWORD=your_langflow_password\n"})}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"LANGFLOW_SUPERUSER"})," defaults to ",(0,r.jsx)(n.code,{children:"admin"}),". You can omit it or set it to a different username. ",(0,r.jsx)(n.code,{children:"LANGFLOW_SUPERUSER_PASSWORD"})," is optional. If omitted, Langflow runs in ",(0,r.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required. If set, Langflow requires password authentication."]}),"\n",(0,r.jsxs)(n.p,{children:["For more information on configuring OpenRAG with environment variables, see ",(0,r.jsx)(n.a,{href:"/reference/configuration",children:"Environment variables"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Start ",(0,r.jsx)(n.code,{children:"docling serve"})," on the host machine.\nOpenRAG Docker installations require that ",(0,r.jsx)(n.code,{children:"docling serve"})," is running on port 5001 on the host machine.\nThis enables ",(0,r.jsx)(n.a,{href:"https://opensource.apple.com/projects/mlx/",children:"Mac MLX"})," support for document processing."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"uv run python scripts/docling_ctl.py start --port 5001\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Confirm ",(0,r.jsx)(n.code,{children:"docling serve"})," is running."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{children:"uv run python scripts/docling_ctl.py status\n"})}),"\n",(0,r.jsxs)(n.p,{children:["Make sure the response shows that ",(0,r.jsx)(n.code,{children:"docling serve"})," is running, for example:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"Status: running\nEndpoint: http://127.0.0.1:5001\nDocs: http://127.0.0.1:5001/docs\nPID: 27746\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Deploy OpenRAG locally with Docker Compose based on your deployment type."}),"\n",(0,r.jsxs)(l.A,{groupId:"Compose file",children:[(0,r.jsx)(t.A,{value:"docker-compose.yml",label:"docker-compose.yml",default:!0,children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose build\ndocker compose up -d\n"})})}),(0,r.jsx)(t.A,{value:"docker-compose-cpu.yml",label:"docker-compose-cpu.yml",children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose -f docker-compose-cpu.yml up -d\n"})})})]}),"\n",(0,r.jsx)(n.p,{children:"The OpenRAG Docker Compose file starts five containers:"}),"\n",(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Container Name"}),(0,r.jsx)(n.th,{children:"Default Address"}),(0,r.jsx)(n.th,{children:"Purpose"})]})}),(0,r.jsxs)(n.tbody,{children:[(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"OpenRAG Backend"}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.a,{href:"http://localhost:8000",children:"http://localhost:8000"})}),(0,r.jsx)(n.td,{children:"FastAPI server and core functionality."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"OpenRAG Frontend"}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.a,{href:"http://localhost:3000",children:"http://localhost:3000"})}),(0,r.jsx)(n.td,{children:"React web interface for users."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"Langflow"}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"})}),(0,r.jsx)(n.td,{children:"AI workflow engine and flow management."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"OpenSearch"}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.a,{href:"http://localhost:9200",children:"http://localhost:9200"})}),(0,r.jsx)(n.td,{children:"Vector database for document storage."})]}),(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:"OpenSearch Dashboards"}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.a,{href:"http://localhost:5601",children:"http://localhost:5601"})}),(0,r.jsx)(n.td,{children:"Database administration interface."})]})]})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Verify installation by confirming all services are running."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose ps\n"})}),"\n",(0,r.jsx)(n.p,{children:"You can now access OpenRAG at the following endpoints:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.strong,{children:"Frontend"}),": ",(0,r.jsx)(n.a,{href:"http://localhost:3000",children:"http://localhost:3000"})]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.strong,{children:"Backend API"}),": ",(0,r.jsx)(n.a,{href:"http://localhost:8000",children:"http://localhost:8000"})]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.strong,{children:"Langflow"}),": ",(0,r.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"})]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Continue with ",(0,r.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:["To stop ",(0,r.jsx)(n.code,{children:"docling serve"})," when you're done with your OpenRAG deployment, run:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"uv run python scripts/docling_ctl.py stop\n"})}),"\n",(0,r.jsx)(a.Ay,{}),"\n",(0,r.jsx)(n.h2,{id:"container-management-commands",children:"Container management commands"}),"\n",(0,r.jsxs)(n.p,{children:["Manage your OpenRAG containers with the following commands.\nThese commands are also available in the TUI's ",(0,r.jsx)(n.a,{href:"/install#status",children:"Status menu"}),"."]}),"\n",(0,r.jsx)(n.h3,{id:"upgrade-containers",children:"Upgrade containers"}),"\n",(0,r.jsx)(n.p,{children:"Upgrade your containers to the latest version while preserving your data."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose pull\ndocker compose up -d --force-recreate\n"})}),"\n",(0,r.jsx)(n.h3,{id:"rebuild-containers-destructive",children:"Rebuild containers (destructive)"}),"\n",(0,r.jsxs)(n.p,{children:["Reset state by rebuilding all of your containers.\nYour OpenSearch and Langflow databases will be lost.\nDocuments stored in the ",(0,r.jsx)(n.code,{children:"./openrag-documents"})," directory will persist, since the directory is mounted as a volume in the OpenRAG backend container."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose up --build --force-recreate --remove-orphans\n"})}),"\n",(0,r.jsx)(n.h3,{id:"remove-all-containers-and-data-destructive",children:"Remove all containers and data (destructive)"}),"\n",(0,r.jsx)(n.p,{children:"Completely remove your OpenRAG installation and delete all data.\nThis deletes all of your data, including OpenSearch data, uploaded documents, and authentication."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose down --volumes --remove-orphans --rmi local\ndocker system prune -f\n"})})]})}function x(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(m,{...e})}):m(e)}}}]); \ No newline at end of file diff --git a/assets/js/749371cc.6ea54965.js b/assets/js/749371cc.6ea54965.js new file mode 100644 index 00000000..d6a05ac3 --- /dev/null +++ b/assets/js/749371cc.6ea54965.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[2272],{3656:(e,n,s)=>{s.d(n,{Ay:()=>p,RM:()=>c});var o=s(4848),r=s(8453),i=s(1610),l=s(1470),t=s(9365);function a(e){const n={a:"a",code:"code",li:"li",ol:"ol",p:"p",strong:"strong",...(0,r.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.p,{children:"Using Ollama for your OpenRAG language model provider offers greater flexibility and configuration, but can also be overwhelming to start.\nThese recommendations are a reasonable starting point for users with at least one GPU and experience running LLMs locally."}),"\n",(0,o.jsxs)(n.p,{children:["For best performance, OpenRAG recommends OpenAI's ",(0,o.jsx)(n.code,{children:"gpt-oss:20b"})," language model. However, this model uses 16GB of RAM, so consider using Ollama Cloud or running Ollama on a remote machine."]}),"\n",(0,o.jsxs)(n.p,{children:["For generating embeddings, OpenRAG recommends the ",(0,o.jsx)(n.a,{href:"https://ollama.com/library/nomic-embed-text",children:(0,o.jsx)(n.code,{children:"nomic-embed-text"})})," embedding model, which provides high-quality embeddings optimized for retrieval tasks."]}),"\n",(0,o.jsxs)(n.p,{children:["To run models in ",(0,o.jsx)(n.a,{href:"https://docs.ollama.com/cloud",children:(0,o.jsx)(n.strong,{children:"Ollama Cloud"})}),", follow these steps:"]}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Sign in to Ollama Cloud.\nIn a terminal, enter ",(0,o.jsx)(n.code,{children:"ollama signin"})," to connect your local environment with Ollama Cloud."]}),"\n",(0,o.jsxs)(n.li,{children:["To run the model, in Ollama, select the ",(0,o.jsx)(n.code,{children:"gpt-oss:20b-cloud"})," model, or run ",(0,o.jsx)(n.code,{children:"ollama run gpt-oss:20b-cloud"})," in a terminal.\nOllama Cloud models are run at the same URL as your local Ollama server at ",(0,o.jsx)(n.code,{children:"http://localhost:11434"}),", and automatically offloaded to Ollama's cloud service."]}),"\n",(0,o.jsxs)(n.li,{children:["Connect OpenRAG to the same local Ollama server as you would for local models in onboarding, using the default address of ",(0,o.jsx)(n.code,{children:"http://localhost:11434"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["In the ",(0,o.jsx)(n.strong,{children:"Language model"})," field, select the ",(0,o.jsx)(n.code,{children:"gpt-oss:20b-cloud"})," model."]}),"\n"]}),"\n",(0,o.jsx)("br",{}),"\n",(0,o.jsxs)(n.p,{children:["To run models on a ",(0,o.jsx)(n.strong,{children:"remote Ollama server"}),", follow these steps:"]}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsx)(n.li,{children:"Ensure your remote Ollama server is accessible from your OpenRAG instance."}),"\n",(0,o.jsxs)(n.li,{children:["In the ",(0,o.jsx)(n.strong,{children:"Ollama Base URL"})," field, enter your remote Ollama server's base URL, such as ",(0,o.jsx)(n.code,{children:"http://your-remote-server:11434"}),".\nOpenRAG connects to the remote Ollama server and populates the lists with the server's available models."]}),"\n",(0,o.jsxs)(n.li,{children:["Select your ",(0,o.jsx)(n.strong,{children:"Embedding model"})," and ",(0,o.jsx)(n.strong,{children:"Language model"})," from the available options."]}),"\n"]})]})}function d(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(a,{...e})}):a(e)}const c=[{value:"Application onboarding",id:"application-onboarding",level:2}];function h(e){const n={a:"a",admonition:"admonition",code:"code",h2:"h2",li:"li",ol:"ol",p:"p",strong:"strong",...(0,r.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.h2,{id:"application-onboarding",children:"Application onboarding"}),"\n",(0,o.jsx)(n.p,{children:"The first time you start OpenRAG, regardless of how you installed it, you must complete application onboarding."}),"\n",(0,o.jsxs)(n.p,{children:["Some of these variables, such as the embedding models, can be changed seamlessly after onboarding.\nOthers are immutable and require you to destroy and recreate the OpenRAG containers.\nFor more information, see ",(0,o.jsx)(n.a,{href:"/reference/configuration",children:"Environment variables"}),"."]}),"\n",(0,o.jsx)(n.p,{children:"You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embeddings model.\nAdditionally, you can set multiple embedding models."}),"\n",(0,o.jsx)(n.p,{children:"You only need to complete onboarding for your preferred providers."}),"\n",(0,o.jsxs)(l.A,{groupId:"Provider",children:[(0,o.jsxs)(t.A,{value:"Anthropic",label:"Anthropic",default:!0,children:[(0,o.jsx)(n.admonition,{type:"info",children:(0,o.jsx)(n.p,{children:"Anthropic doesn't provide embedding models. If you select Anthropic for your language model, you must select a different provider for embeddings."})}),(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Enable ",(0,o.jsx)(n.strong,{children:"Use environment Anthropic API key"})," to automatically use your key from the ",(0,o.jsx)(n.code,{children:".env"})," file.\nAlternatively, paste an Anthropic API key into the field."]}),"\n",(0,o.jsxs)(n.li,{children:["Under ",(0,o.jsx)(n.strong,{children:"Advanced settings"}),", select your ",(0,o.jsx)(n.strong,{children:"Language Model"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["In the second onboarding panel, select a provider for embeddings and select your ",(0,o.jsx)(n.strong,{children:"Embedding Model"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,o.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add a Document"}),".\nAlternatively, click ",(0,o.jsx)(i.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Skip overview"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Continue with the ",(0,o.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})]}),(0,o.jsx)(t.A,{value:"OpenAI",label:"OpenAI",children:(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Enable ",(0,o.jsx)(n.strong,{children:"Get API key from environment variable"})," to automatically enter your key from the TUI-generated ",(0,o.jsx)(n.code,{children:".env"})," file.\nAlternatively, paste an OpenAI API key into the field."]}),"\n",(0,o.jsxs)(n.li,{children:["Under ",(0,o.jsx)(n.strong,{children:"Advanced settings"}),", select your ",(0,o.jsx)(n.strong,{children:"Language Model"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["In the second onboarding panel, select a provider for embeddings and select your ",(0,o.jsx)(n.strong,{children:"Embedding Model"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,o.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add a Document"}),".\nAlternatively, click ",(0,o.jsx)(i.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Skip overview"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Continue with the ",(0,o.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})}),(0,o.jsx)(t.A,{value:"IBM watsonx.ai",label:"IBM watsonx.ai",children:(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Complete the fields for ",(0,o.jsx)(n.strong,{children:"watsonx.ai API Endpoint"}),", ",(0,o.jsx)(n.strong,{children:"IBM Project ID"}),", and ",(0,o.jsx)(n.strong,{children:"IBM API key"}),".\nThese values are found in your IBM watsonx deployment."]}),"\n",(0,o.jsxs)(n.li,{children:["Under ",(0,o.jsx)(n.strong,{children:"Advanced settings"}),", select your ",(0,o.jsx)(n.strong,{children:"Language Model"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["In the second onboarding panel, select a provider for embeddings and select your ",(0,o.jsx)(n.strong,{children:"Embedding Model"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,o.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add a Document"}),".\nAlternatively, click ",(0,o.jsx)(i.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Skip overview"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Continue with the ",(0,o.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})}),(0,o.jsxs)(t.A,{value:"Ollama",label:"Ollama",children:[(0,o.jsx)(n.admonition,{type:"info",children:(0,o.jsxs)(n.p,{children:["Ollama isn't installed with OpenRAG. To install Ollama, see the ",(0,o.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"}),"."]})}),(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["To connect to an Ollama server running on your local machine, enter your Ollama server's base URL address.\nThe default Ollama server address is ",(0,o.jsx)(n.code,{children:"http://localhost:11434"}),".\nOpenRAG connects to the Ollama server and populates the model lists with the server's available models."]}),"\n",(0,o.jsxs)(n.li,{children:["Select the ",(0,o.jsx)(n.strong,{children:"Embedding Model"})," and ",(0,o.jsx)(n.strong,{children:"Language Model"})," your Ollama server is running.","\n",(0,o.jsxs)(s,{closed:!0,children:[(0,o.jsx)("summary",{children:"Ollama model selection and external server configuration"}),(0,o.jsx)(d,{})]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,o.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add a Document"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Continue with the ",(0,o.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})]})]})]})}function p(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(h,{...e})}):h(e)}},3862:(e,n,s)=>{s.d(n,{Ay:()=>t,RM:()=>i});var o=s(4848),r=s(8453);const i=[];function l(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,r.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install",children:"Install WSL"})," with the Ubuntu distribution using WSL 2:"]}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-powershell",children:"wsl --install -d Ubuntu\n"})}),"\n",(0,o.jsxs)(n.p,{children:["For new installations, the ",(0,o.jsx)(n.code,{children:"wsl --install"})," command uses WSL 2 and Ubuntu by default."]}),"\n",(0,o.jsxs)(n.p,{children:["For existing WSL installations, you can ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#change-the-default-linux-distribution-installed",children:"change the distribution"})," and ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2",children:"check the WSL version"}),"."]}),"\n",(0,o.jsx)(n.admonition,{title:"Known limitation",type:"warning",children:(0,o.jsx)(n.p,{children:"OpenRAG isn't compatible with nested virtualization, which can cause networking issues.\nDon't install OpenRAG on a WSL distribution that is installed inside a Windows VM.\nInstead, install OpenRAG on your base OS or a non-nested Linux VM."})}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#ways-to-run-multiple-linux-distributions-with-wsl",children:"Start your WSL Ubuntu distribution"})," if it doesn't start automatically."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/setup/environment#set-up-your-linux-username-and-password",children:"Set up a username and password for your WSL distribution"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers",children:"Install Docker Desktop for Windows with WSL 2"}),". When you reach the Docker Desktop ",(0,o.jsx)(n.strong,{children:"WSL integration"})," settings, make sure your Ubuntu distribution is enabled, and then click ",(0,o.jsx)(n.strong,{children:"Apply & Restart"})," to enable Docker support in WSL."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Install and run OpenRAG from within your WSL Ubuntu distribution."}),"\n"]}),"\n"]}),"\n",(0,o.jsx)("br",{}),"\n",(0,o.jsxs)(n.p,{children:["If you encounter issues with port forwarding or the Windows Firewall, you might need to adjust the ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/security/operating-system-security/network-security/windows-firewall/hyper-v-firewall",children:"Hyper-V firewall settings"})," to allow communication between your WSL distribution and the Windows host. For more troubleshooting advice for networking issues, see ",(0,o.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/troubleshooting#common-issues",children:"Troubleshooting WSL common issues"}),"."]})]})}function t(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(l,{...e})}):l(e)}},5788:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>p,contentTitle:()=>h,default:()=>x,frontMatter:()=>c,metadata:()=>o,toc:()=>u});const o=JSON.parse('{"id":"get-started/docker","title":"Install OpenRAG containers","description":"OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments:","source":"@site/docs/get-started/docker.mdx","sourceDirName":"get-started","slug":"/docker","permalink":"/docker","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/docker.mdx","tags":[],"version":"current","frontMatter":{"title":"Install OpenRAG containers","slug":"/docker"},"sidebar":"tutorialSidebar","previous":{"title":"Install OpenRAG with TUI","permalink":"/install"},"next":{"title":"Flows","permalink":"/agents"}}');var r=s(4848),i=s(8453),l=s(1470),t=s(9365),a=s(3656),d=s(3862);const c={title:"Install OpenRAG containers",slug:"/docker"},h=void 0,p={},u=[{value:"Prerequisites",id:"prerequisites",level:2},...d.RM,{value:"Install OpenRAG with Docker Compose",id:"install-openrag-with-docker-compose",level:2},...a.RM,{value:"Container management commands",id:"container-management-commands",level:2},{value:"Upgrade containers",id:"upgrade-containers",level:3},{value:"Rebuild containers (destructive)",id:"rebuild-containers-destructive",level:3},{value:"Remove all containers and data (destructive)",id:"remove-all-containers-and-data-destructive",level:3}];function m(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",table:"table",tbody:"tbody",td:"td",th:"th",thead:"thead",tr:"tr",ul:"ul",...(0,i.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.p,{children:"OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/docker-compose.yml",children:(0,r.jsx)(n.code,{children:"docker-compose.yml"})})," is an OpenRAG deployment with GPU support for accelerated AI processing. This Docker Compose file requires an NVIDIA GPU with ",(0,r.jsx)(n.a,{href:"https://docs.nvidia.com/cuda/",children:"CUDA"})," support."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/docker-compose-cpu.yml",children:(0,r.jsx)(n.code,{children:"docker-compose-cpu.yml"})})," is a CPU-only version of OpenRAG for systems without NVIDIA GPU support. Use this Docker Compose file for environments where GPU drivers aren't available."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Install the following:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://www.python.org/downloads/release/python-3100/",children:"Python"})," version 3.13 or later."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://docs.astral.sh/uv/getting-started/installation/",children:"uv"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://podman.io/docs/installation",children:"Podman"})," (recommended) or ",(0,r.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"Docker"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"https://docs.podman.io/en/latest/markdown/podman-compose.1.html",children:(0,r.jsx)(n.code,{children:"podman-compose"})})," or ",(0,r.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"Docker Compose"}),". To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Microsoft Windows only: To run OpenRAG on Windows, you must use the Windows Subsystem for Linux (WSL)."}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Install WSL for OpenRAG"}),(0,r.jsx)(d.Ay,{})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Prepare model providers and credentials."}),"\n",(0,r.jsxs)(n.p,{children:["During ",(0,r.jsx)(n.a,{href:"#application-onboarding",children:"application onboarding"}),", you must select language model and embedding model providers.\nIf your chosen provider offers both types, you can use the same provider for both selections.\nIf your provider offers only one type, such as Anthropic, you must select two providers."]}),"\n",(0,r.jsx)(n.p,{children:"Gather the credentials and connection details for your chosen model providers before starting onboarding:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["OpenAI: Create an ",(0,r.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI API key"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Anthropic language models: Create an ",(0,r.jsx)(n.a,{href:"https://www.anthropic.com/docs/api/reference",children:"Anthropic API key"}),"."]}),"\n",(0,r.jsx)(n.li,{children:"IBM watsonx.ai: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment."}),"\n",(0,r.jsxs)(n.li,{children:["Ollama: Use the ",(0,r.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"})," to set up your Ollama instance locally, in the cloud, or on a remote server, and then get your Ollama server's base URL."]}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Optional: Install GPU support with an NVIDIA GPU, ",(0,r.jsx)(n.a,{href:"https://docs.nvidia.com/cuda/",children:"CUDA"})," support, and compatible NVIDIA drivers on the OpenRAG host machine. This is required to use the GPU-accelerated Docker Compose file. If you choose not to use GPU support, you must use the CPU-only Docker Compose file instead."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"install-openrag-with-docker-compose",children:"Install OpenRAG with Docker Compose"}),"\n",(0,r.jsx)(n.p,{children:"To install OpenRAG with Docker Compose, do the following:"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Clone the OpenRAG repository."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"git clone https://github.com/langflow-ai/openrag.git\ncd openrag\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Install dependencies."}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"uv sync\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Copy the example ",(0,r.jsx)(n.code,{children:".env"})," file included in the repository root.\nThe example file includes all environment variables with comments to guide you in finding and setting their values."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"cp .env.example .env\n"})}),"\n",(0,r.jsxs)(n.p,{children:["Alternatively, create a new ",(0,r.jsx)(n.code,{children:".env"})," file in the repository root."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{children:"touch .env\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["The Docker Compose files are populated with the values from your ",(0,r.jsx)(n.code,{children:".env"})," file.\nThe ",(0,r.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})," value must be set.\n",(0,r.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})," can be automatically generated when using the TUI, but for a Docker Compose installation, you can set it manually instead. To generate an OpenSearch admin password, see the ",(0,r.jsx)(n.a,{href:"https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password",children:"OpenSearch documentation"}),"."]}),"\n",(0,r.jsx)(n.p,{children:"The following values are optional:"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"OPENAI_API_KEY=your_openai_api_key\nLANGFLOW_SECRET_KEY=your_secret_key\n"})}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"OPENAI_API_KEY"})," is optional. You can provide it during ",(0,r.jsx)(n.a,{href:"#application-onboarding",children:"application onboarding"})," or choose a different model provider. If you want to set it in your ",(0,r.jsx)(n.code,{children:".env"})," file, you can find your OpenAI API key in your ",(0,r.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI account"}),"."]}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"LANGFLOW_SECRET_KEY"})," is optional. Langflow will auto-generate it if not set. For more information, see the ",(0,r.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-secret-key",children:"Langflow documentation"}),"."]}),"\n",(0,r.jsx)(n.p,{children:"The following Langflow configuration values are optional but important to consider:"}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"LANGFLOW_SUPERUSER=admin\nLANGFLOW_SUPERUSER_PASSWORD=your_langflow_password\n"})}),"\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.code,{children:"LANGFLOW_SUPERUSER"})," defaults to ",(0,r.jsx)(n.code,{children:"admin"}),". You can omit it or set it to a different username. 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running."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{children:"uv run python scripts/docling_ctl.py status\n"})}),"\n",(0,r.jsxs)(n.p,{children:["Make sure the response shows that ",(0,r.jsx)(n.code,{children:"docling serve"})," is running, for example:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"Status: running\nEndpoint: http://127.0.0.1:5001\nDocs: http://127.0.0.1:5001/docs\nPID: 27746\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Deploy OpenRAG locally with Docker Compose based on your deployment type."}),"\n",(0,r.jsxs)(l.A,{groupId:"Compose file",children:[(0,r.jsx)(t.A,{value:"docker-compose.yml",label:"docker-compose.yml",default:!0,children:(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose build\ndocker compose up 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75:this.$=i.Identification.IDENTIFYING}},"anonymous"),table:[{3:1,4:[1,2]},{1:[3]},t(e,[2,2],{5:3}),{6:[1,4],7:5,8:[1,6],9:7,10:[1,8],11:9,22:s,24:i,26:n,28:r,29:14,30:15,31:16,32:17,33:a,34:c,35:l,36:h,37:u,40:y,43:d,44:p,50:_},t(e,[2,7],{1:[2,1]}),t(e,[2,3]),{9:27,11:9,22:s,24:i,26:n,28:r,29:14,30:15,31:16,32:17,33:a,34:c,35:l,36:h,37:u,40:y,43:d,44:p,50:_},t(e,[2,5]),t(e,[2,6]),t(e,[2,16],{12:28,61:32,15:[1,29],17:[1,30],20:[1,31],63:g,64:b,65:m,66:f,67:E}),{23:[1,38]},{25:[1,39]},{27:[1,40]},t(e,[2,27]),t(e,[2,28]),t(e,[2,29]),t(e,[2,30]),t(e,[2,31]),t(k,[2,54]),t(k,[2,55]),t(e,[2,32]),t(e,[2,33]),t(e,[2,34]),t(e,[2,35]),{16:41,40:O,41:S},{16:44,40:O,41:S},{16:45,40:O,41:S},t(e,[2,4]),{11:46,40:y,50:_},{16:47,40:O,41:S},{18:48,19:[1,49],51:50,52:51,56:T},{11:53,40:y,50:_},{62:54,68:[1,55],69:[1,56]},t(R,[2,69]),t(R,[2,70]),t(R,[2,71]),t(R,[2,72]),t(R,[2,73]),t(e,[2,24]),t(e,[2,25]),t(e,[2,26]),{13:A,38:57,41:N,42:I,45:59,46:60,48:C,49:x},t(D,[2,37]),t(D,[2,38]),{16:65,40:O,41:S,42:I},{13:A,38:66,41:N,42:I,45:59,46:60,48:C,49:x},{13:[1,67],15:[1,68]},t(e,[2,17],{61:32,12:69,17:[1,70],42:I,63:g,64:b,65:m,66:f,67:E}),{19:[1,71]},t(e,[2,14]),{18:72,19:[2,56],51:50,52:51,56:T},{53:73,56:[1,74]},{56:[2,62]},{21:[1,75]},{61:76,63:g,64:b,65:m,66:f,67:E},t(v,[2,74]),t(v,[2,75]),{6:$,10:K,39:77,42:w,47:L},{40:[1,82],41:[1,83]},t(M,[2,43],{46:84,13:A,41:N,48:C,49:x}),t(F,[2,45]),t(F,[2,50]),t(F,[2,51]),t(F,[2,52]),t(F,[2,53]),t(e,[2,41],{42:I}),{6:$,10:K,39:85,42:w,47:L},{14:86,40:B,50:Y,70:P},{16:90,40:O,41:S},{11:91,40:y,50:_},{18:92,19:[1,93],51:50,52:51,56:T},t(e,[2,12]),{19:[2,57]},t(z,[2,58],{54:94,55:95,57:96,59:G,60:U}),t([19,56,59,60],[2,63]),t(e,[2,22],{15:[1,100],17:[1,99]}),t([40,50],[2,68]),t(e,[2,36]),{13:A,41:N,45:101,46:60,48:C,49:x},t(e,[2,47]),t(e,[2,48]),t(e,[2,49]),t(D,[2,39]),t(D,[2,40]),t(F,[2,46]),t(e,[2,42]),t(e,[2,8]),t(e,[2,76]),t(e,[2,77]),t(e,[2,78]),{13:[1,102],42:I},{13:[1,104],15:[1,103]},{19:[1,105]},t(e,[2,15]),t(z,[2,59],{55:106,58:[1,107],60:U}),t(z,[2,60]),t(Z,[2,64]),t(z,[2,67]),t(Z,[2,66]),{18:108,19:[1,109],51:50,52:51,56:T},{16:110,40:O,41:S},t(M,[2,44],{46:84,13:A,41:N,48:C,49:x}),{14:111,40:B,50:Y,70:P},{16:112,40:O,41:S},{14:113,40:B,50:Y,70:P},t(e,[2,13]),t(z,[2,61]),{57:114,59:G},{19:[1,115]},t(e,[2,20]),t(e,[2,23],{17:[1,116],42:I}),t(e,[2,11]),{13:[1,117],42:I},t(e,[2,10]),t(Z,[2,65]),t(e,[2,18]),{18:118,19:[1,119],51:50,52:51,56:T},{14:120,40:B,50:Y,70:P},{19:[1,121]},t(e,[2,21]),t(e,[2,9]),t(e,[2,19])],defaultActions:{52:[2,62],72:[2,57]},parseError:(0,o.K2)(function(t,e){if(!e.recoverable){var s=new Error(t);throw s.hash=e,s}this.trace(t)},"parseError"),parse:(0,o.K2)(function(t){var e=this,s=[0],i=[],n=[null],r=[],a=this.table,c="",l=0,h=0,u=0,y=r.slice.call(arguments,1),d=Object.create(this.lexer),p={yy:{}};for(var _ in this.yy)Object.prototype.hasOwnProperty.call(this.yy,_)&&(p.yy[_]=this.yy[_]);d.setInput(t,p.yy),p.yy.lexer=d,p.yy.parser=this,void 0===d.yylloc&&(d.yylloc={});var g=d.yylloc;r.push(g);var b=d.options&&d.options.ranges;function m(){var t;return"number"!=typeof(t=i.pop()||d.lex()||1)&&(t instanceof Array&&(t=(i=t).pop()),t=e.symbols_[t]||t),t}"function"==typeof p.yy.parseError?this.parseError=p.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError,(0,o.K2)(function(t){s.length=s.length-2*t,n.length=n.length-t,r.length=r.length-t},"popStack"),(0,o.K2)(m,"lex");for(var f,E,k,O,S,T,R,A,N,I={};;){if(k=s[s.length-1],this.defaultActions[k]?O=this.defaultActions[k]:(null==f&&(f=m()),O=a[k]&&a[k][f]),void 0===O||!O.length||!O[0]){var C="";for(T in N=[],a[k])this.terminals_[T]&&T>2&&N.push("'"+this.terminals_[T]+"'");C=d.showPosition?"Parse error on line "+(l+1)+":\n"+d.showPosition()+"\nExpecting "+N.join(", ")+", got '"+(this.terminals_[f]||f)+"'":"Parse error on line "+(l+1)+": Unexpected "+(1==f?"end of input":"'"+(this.terminals_[f]||f)+"'"),this.parseError(C,{text:d.match,token:this.terminals_[f]||f,line:d.yylineno,loc:g,expected:N})}if(O[0]instanceof Array&&O.length>1)throw new Error("Parse Error: multiple actions possible at state: "+k+", token: "+f);switch(O[0]){case 1:s.push(f),n.push(d.yytext),r.push(d.yylloc),s.push(O[1]),f=null,E?(f=E,E=null):(h=d.yyleng,c=d.yytext,l=d.yylineno,g=d.yylloc,u>0&&u--);break;case 2:if(R=this.productions_[O[1]][1],I.$=n[n.length-R],I._$={first_line:r[r.length-(R||1)].first_line,last_line:r[r.length-1].last_line,first_column:r[r.length-(R||1)].first_column,last_column:r[r.length-1].last_column},b&&(I._$.range=[r[r.length-(R||1)].range[0],r[r.length-1].range[1]]),void 0!==(S=this.performAction.apply(I,[c,h,l,p.yy,O[1],n,r].concat(y))))return S;R&&(s=s.slice(0,-1*R*2),n=n.slice(0,-1*R),r=r.slice(0,-1*R)),s.push(this.productions_[O[1]][0]),n.push(I.$),r.push(I._$),A=a[s[s.length-2]][s[s.length-1]],s.push(A);break;case 3:return!0}}return!0},"parse")},W=function(){return{EOF:1,parseError:(0,o.K2)(function(t,e){if(!this.yy.parser)throw new Error(t);this.yy.parser.parseError(t,e)},"parseError"),setInput:(0,o.K2)(function(t,e){return this.yy=e||this.yy||{},this._input=t,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:(0,o.K2)(function(){var t=this._input[0];return this.yytext+=t,this.yyleng++,this.offset++,this.match+=t,this.matched+=t,t.match(/(?:\r\n?|\n).*/g)?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),t},"input"),unput:(0,o.K2)(function(t){var e=t.length,s=t.split(/(?:\r\n?|\n)/g);this._input=t+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-e),this.offset-=e;var i=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),s.length-1&&(this.yylineno-=s.length-1);var n=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:s?(s.length===i.length?this.yylloc.first_column:0)+i[i.length-s.length].length-s[0].length:this.yylloc.first_column-e},this.options.ranges&&(this.yylloc.range=[n[0],n[0]+this.yyleng-e]),this.yyleng=this.yytext.length,this},"unput"),more:(0,o.K2)(function(){return this._more=!0,this},"more"),reject:(0,o.K2)(function(){return this.options.backtrack_lexer?(this._backtrack=!0,this):this.parseError("Lexical error on line "+(this.yylineno+1)+". You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"reject"),less:(0,o.K2)(function(t){this.unput(this.match.slice(t))},"less"),pastInput:(0,o.K2)(function(){var t=this.matched.substr(0,this.matched.length-this.match.length);return(t.length>20?"...":"")+t.substr(-20).replace(/\n/g,"")},"pastInput"),upcomingInput:(0,o.K2)(function(){var t=this.match;return t.length<20&&(t+=this._input.substr(0,20-t.length)),(t.substr(0,20)+(t.length>20?"...":"")).replace(/\n/g,"")},"upcomingInput"),showPosition:(0,o.K2)(function(){var t=this.pastInput(),e=new Array(t.length+1).join("-");return t+this.upcomingInput()+"\n"+e+"^"},"showPosition"),test_match:(0,o.K2)(function(t,e){var s,i,n;if(this.options.backtrack_lexer&&(n={yylineno:this.yylineno,yylloc:{first_line:this.yylloc.first_line,last_line:this.last_line,first_column:this.yylloc.first_column,last_column:this.yylloc.last_column},yytext:this.yytext,match:this.match,matches:this.matches,matched:this.matched,yyleng:this.yyleng,offset:this.offset,_more:this._more,_input:this._input,yy:this.yy,conditionStack:this.conditionStack.slice(0),done:this.done},this.options.ranges&&(n.yylloc.range=this.yylloc.range.slice(0))),(i=t[0].match(/(?:\r\n?|\n).*/g))&&(this.yylineno+=i.length),this.yylloc={first_line:this.yylloc.last_line,last_line:this.yylineno+1,first_column:this.yylloc.last_column,last_column:i?i[i.length-1].length-i[i.length-1].match(/\r?\n?/)[0].length:this.yylloc.last_column+t[0].length},this.yytext+=t[0],this.match+=t[0],this.matches=t,this.yyleng=this.yytext.length,this.options.ranges&&(this.yylloc.range=[this.offset,this.offset+=this.yyleng]),this._more=!1,this._backtrack=!1,this._input=this._input.slice(t[0].length),this.matched+=t[0],s=this.performAction.call(this,this.yy,this,e,this.conditionStack[this.conditionStack.length-1]),this.done&&this._input&&(this.done=!1),s)return s;if(this._backtrack){for(var r in n)this[r]=n[r];return!1}return!1},"test_match"),next:(0,o.K2)(function(){if(this.done)return this.EOF;var t,e,s,i;this._input||(this.done=!0),this._more||(this.yytext="",this.match="");for(var n=this._currentRules(),r=0;re[0].length)){if(e=s,i=r,this.options.backtrack_lexer){if(!1!==(t=this.test_match(s,n[r])))return t;if(this._backtrack){e=!1;continue}return!1}if(!this.options.flex)break}return e?!1!==(t=this.test_match(e,n[i]))&&t:""===this._input?this.EOF:this.parseError("Lexical error on line "+(this.yylineno+1)+". Unrecognized text.\n"+this.showPosition(),{text:"",token:null,line:this.yylineno})},"next"),lex:(0,o.K2)(function(){var t=this.next();return t||this.lex()},"lex"),begin:(0,o.K2)(function(t){this.conditionStack.push(t)},"begin"),popState:(0,o.K2)(function(){return this.conditionStack.length-1>0?this.conditionStack.pop():this.conditionStack[0]},"popState"),_currentRules:(0,o.K2)(function(){return this.conditionStack.length&&this.conditionStack[this.conditionStack.length-1]?this.conditions[this.conditionStack[this.conditionStack.length-1]].rules:this.conditions.INITIAL.rules},"_currentRules"),topState:(0,o.K2)(function(t){return(t=this.conditionStack.length-1-Math.abs(t||0))>=0?this.conditionStack[t]:"INITIAL"},"topState"),pushState:(0,o.K2)(function(t){this.begin(t)},"pushState"),stateStackSize:(0,o.K2)(function(){return this.conditionStack.length},"stateStackSize"),options:{"case-insensitive":!0},performAction:(0,o.K2)(function(t,e,s,i){switch(s){case 0:return this.begin("acc_title"),24;case 1:return this.popState(),"acc_title_value";case 2:return this.begin("acc_descr"),26;case 3:return this.popState(),"acc_descr_value";case 4:this.begin("acc_descr_multiline");break;case 5:this.popState();break;case 6:return"acc_descr_multiline_value";case 7:return 33;case 8:return 34;case 9:return 35;case 10:return 36;case 11:return 10;case 12:case 23:case 28:case 35:break;case 13:return 8;case 14:return 50;case 15:return 70;case 16:return 4;case 17:return this.begin("block"),17;case 18:case 19:case 38:return 49;case 20:case 37:return 42;case 21:return 15;case 22:case 36:return 13;case 24:return 59;case 25:case 26:return 56;case 27:return 60;case 29:return this.popState(),19;case 30:case 73:return e.yytext[0];case 31:return 20;case 32:return 21;case 33:return this.begin("style"),44;case 34:return this.popState(),10;case 39:return this.begin("style"),37;case 40:return 43;case 41:case 45:case 46:case 59:return 63;case 42:case 43:case 44:case 52:case 54:case 61:return 65;case 47:case 48:case 49:case 50:case 51:case 53:case 60:return 64;case 55:case 56:case 57:case 58:return 66;case 62:return 67;case 63:case 66:case 67:case 68:return 68;case 64:case 65:return 69;case 69:return 41;case 70:return 47;case 71:return 40;case 72:return 48;case 74:return 6}},"anonymous"),rules:[/^(?:accTitle\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*:\s*)/i,/^(?:(?!\n||)*[^\n]*)/i,/^(?:accDescr\s*\{\s*)/i,/^(?:[\}])/i,/^(?:[^\}]*)/i,/^(?:.*direction\s+TB[^\n]*)/i,/^(?:.*direction\s+BT[^\n]*)/i,/^(?:.*direction\s+RL[^\n]*)/i,/^(?:.*direction\s+LR[^\n]*)/i,/^(?:[\n]+)/i,/^(?:\s+)/i,/^(?:[\s]+)/i,/^(?:"[^"%\r\n\v\b\\]+")/i,/^(?:"[^"]*")/i,/^(?:erDiagram\b)/i,/^(?:\{)/i,/^(?:#)/i,/^(?:#)/i,/^(?:,)/i,/^(?::::)/i,/^(?::)/i,/^(?:\s+)/i,/^(?:\b((?:PK)|(?:FK)|(?:UK))\b)/i,/^(?:([^\s]*)[~].*[~]([^\s]*))/i,/^(?:([\*A-Za-z_\u00C0-\uFFFF][A-Za-z0-9\-\_\[\]\(\)\u00C0-\uFFFF\*]*))/i,/^(?:"[^"]*")/i,/^(?:[\n]+)/i,/^(?:\})/i,/^(?:.)/i,/^(?:\[)/i,/^(?:\])/i,/^(?:style\b)/i,/^(?:[\n]+)/i,/^(?:\s+)/i,/^(?::)/i,/^(?:,)/i,/^(?:#)/i,/^(?:classDef\b)/i,/^(?:class\b)/i,/^(?:one or zero\b)/i,/^(?:one or more\b)/i,/^(?:one or many\b)/i,/^(?:1\+)/i,/^(?:\|o\b)/i,/^(?:zero or one\b)/i,/^(?:zero or more\b)/i,/^(?:zero or many\b)/i,/^(?:0\+)/i,/^(?:\}o\b)/i,/^(?:many\(0\))/i,/^(?:many\(1\))/i,/^(?:many\b)/i,/^(?:\}\|)/i,/^(?:one\b)/i,/^(?:only one\b)/i,/^(?:1\b)/i,/^(?:\|\|)/i,/^(?:o\|)/i,/^(?:o\{)/i,/^(?:\|\{)/i,/^(?:\s*u\b)/i,/^(?:\.\.)/i,/^(?:--)/i,/^(?:to\b)/i,/^(?:optionally to\b)/i,/^(?:\.-)/i,/^(?:-\.)/i,/^(?:([^\x00-\x7F]|\w|-|\*)+)/i,/^(?:;)/i,/^(?:([^\x00-\x7F]|\w|-|\*)+)/i,/^(?:[0-9])/i,/^(?:.)/i,/^(?:$)/i],conditions:{style:{rules:[34,35,36,37,38,69,70],inclusive:!1},acc_descr_multiline:{rules:[5,6],inclusive:!1},acc_descr:{rules:[3],inclusive:!1},acc_title:{rules:[1],inclusive:!1},block:{rules:[23,24,25,26,27,28,29,30],inclusive:!1},INITIAL:{rules:[0,2,4,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,31,32,33,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,71,72,73,74],inclusive:!0}}}}();function X(){this.yy={}}return j.lexer=W,(0,o.K2)(X,"Parser"),X.prototype=j,j.Parser=X,new X}();y.parser=y;var d=y,p=class{constructor(){this.entities=new 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OpenRAG"}),(0,i.jsx)(d.Ay,{})]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"install-openrag",children:"Install OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"For this quickstart, install OpenRAG with the automatic installer script and basic setup:"}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a directory to store the OpenRAG configuration files, and then change to that directory:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"mkdir openrag-workspace\ncd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.a,{href:"https://docs.openr.ag/files/run_openrag_with_prereqs.sh",children:"Download the OpenRAG install script"}),", move it to your OpenRAG directory, and then run it:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"bash run_openrag_with_prereqs.sh\n"})}),"\n",(0,i.jsxs)(n.p,{children:["This script installs OpenRAG and its dependencies, including Docker or Podman, and it creates a ",(0,i.jsx)(n.code,{children:".env"})," file and ",(0,i.jsx)(n.code,{children:"docker-compose"})," files in the current working directory.\nYou might be prompted to install certain dependencies if they aren't already present in your environment.\nThis process can take a few minutes.\nOnce the environment is ready, OpenRAG starts."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Basic Setup"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Create passwords for your OpenRAG installation's OpenSearch and Langflow services. You can click ",(0,i.jsx)(n.strong,{children:"Generate Passwords"})," to automatically generate passwords."]}),"\n",(0,i.jsxs)(n.p,{children:["The OpenSearch password is required. The Langflow admin password is optional.\nIf you don't generate a Langflow admin password, Langflow runs in ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required."]}),"\n",(0,i.jsxs)(n.p,{children:["Your passwords are saved in the ",(0,i.jsx)(n.code,{children:".env"})," file that is used to start OpenRAG.\nYou can find this file in your OpenRAG installation directory."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Save Configuration"}),", and then click ",(0,i.jsx)(n.strong,{children:"Start All Services"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"Wait a few minutes while the startup process pulls and runs the necessary container images.\nProceed when you see the following messages in the terminal user interface (TUI):"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"Services started successfully\nCommand completed successfully\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To open the OpenRAG application, go to the TUI main menu, and then click ",(0,i.jsx)(n.strong,{children:"Open App"}),".\nAlternatively, in your browser, navigate to ",(0,i.jsx)(n.code,{children:"localhost:3000"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Select the ",(0,i.jsx)(n.strong,{children:"OpenAI"})," model provider, enter your OpenAI API key, and then click ",(0,i.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"For this quickstart, you can use the default options for the model settings."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click through the overview slides for a brief introduction to OpenRAG and basic setup, or click ",(0,i.jsx)(o.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Skip overview"}),".\nYou can complete this quickstart without going through the overview."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"chat-with-documents",children:"Load and chat with documents"}),"\n",(0,i.jsxs)(n.p,{children:["OpenRAG's knowledge base chat is powered by the ",(0,i.jsx)(n.a,{href:"/agents",children:"OpenRAG OpenSearch Agent"}),".\nSome documents are included by default to get you started, and you can load your own documents."]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["In OpenRAG, click ",(0,i.jsx)(o.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Chat"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["For this quickstart, ask the agent what documents are available.\nFor example: ",(0,i.jsx)(n.code,{children:"What documents are available to you?"})]}),"\n",(0,i.jsx)(n.p,{children:"The agent responds with a summary of OpenRAG's default documents."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To verify the agent's response, click ",(0,i.jsx)(o.A,{name:"Library","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Knowledge"})," to view the documents stored in the OpenRAG OpenSearch vector database.\nYou can click a document to view the chunks of the document as they are stored in the database."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Add Knowledge"})," to add your own documents to your OpenRAG knowledge base."]}),"\n",(0,i.jsxs)(n.p,{children:["For this quickstart, use either the ",(0,i.jsx)(o.A,{name:"File","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"File"})," or ",(0,i.jsx)(o.A,{name:"Folder","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Folder"})," upload options to load documents from your local machine.\n",(0,i.jsx)(n.strong,{children:"Folder"})," uploads an entire directory.\nThe default directory is the ",(0,i.jsx)(n.code,{children:"/openrag-documents"})," subdirectory in your OpenRAG installation directory."]}),"\n",(0,i.jsxs)(n.p,{children:["For information about the cloud storage provider options, see ",(0,i.jsx)(n.a,{href:"/knowledge#oauth-ingestion",children:"Ingest files through OAuth connectors"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Return to the ",(0,i.jsx)(n.strong,{children:"Chat"})," window, and then ask a question related to the documents that you just uploaded."]}),"\n",(0,i.jsx)(n.p,{children:"If the agent's response doesn't seem to reference your documents correctly, try the following:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(o.A,{name:"Gear","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Function Call: search_documents (tool_call)"})," to view the log of tool calls made by the agent. This is helpful for troubleshooting because it shows you how the agent used particular tools."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(o.A,{name:"Library","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Knowledge"})," to confirm that the documents are present in the OpenRAG OpenSearch vector database, and then click each document to see how the document was chunked.\nIf a document was chunked improperly, you might need to tweak the ingestion or modify and reupload the document."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"})," to modify the knowledge ingestion settings."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["For more information about knowledge bases and knowledge ingestion, see ",(0,i.jsx)(n.a,{href:"/knowledge",children:"OpenSearch in OpenRAG"}),"."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"change-components",children:"Change the language model and chat settings"}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To change the knowledge ingestion settings, agent behavior, or language model, click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Settings"})," page provides quick access to commonly used parameters like the ",(0,i.jsx)(n.strong,{children:"Language model"})," and ",(0,i.jsx)(n.strong,{children:"Agent Instructions"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["For greater insight into the underlying ",(0,i.jsx)(n.a,{href:"/agents",children:"Langflow flow"})," that drives the OpenRAG chat, click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"})," and then click ",(0,i.jsx)(n.strong,{children:"Proceed"})," to launch the Langflow visual editor in a new browser window."]}),"\n",(0,i.jsxs)(n.p,{children:["If Langflow requests login information, enter the ",(0,i.jsx)(n.code,{children:"LANGFLOW_SUPERUSER"})," and ",(0,i.jsx)(n.code,{children:"LANGFLOW_SUPERUSER_PASSWORD"})," from the ",(0,i.jsx)(n.code,{children:".env"})," file in your OpenRAG installation directory."]}),"\n",(0,i.jsx)(n.p,{children:"The OpenRAG OpenSearch Agent flow opens in a new browser window."}),"\n",(0,i.jsx)(n.p,{children:(0,i.jsx)(n.img,{alt:"OpenRAG OpenSearch Agent flow",src:s(3982).A+"",width:"4084",height:"2176"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["For this quickstart, try changing the model.\nClick the ",(0,i.jsx)(n.strong,{children:"Language Model"})," component, and then change the ",(0,i.jsx)(n.strong,{children:"Model Name"})," to a different OpenAI model."]}),"\n",(0,i.jsxs)(n.p,{children:["When editing built-in flows, you can click ",(0,i.jsx)(n.strong,{children:"Restore flow"})," to revert the flow to its initial state."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Press ",(0,i.jsx)("kbd",{children:"Command"}),"+",(0,i.jsx)("kbd",{children:"S"})," (",(0,i.jsx)("kbd",{children:"Ctrl"}),"+",(0,i.jsx)("kbd",{children:"S"}),") to save your changes."]}),"\n",(0,i.jsx)(n.p,{children:"You can close the Langflow browser window, or leave it open if you want to continue experimenting with the flow editor."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Switch to your OpenRAG browser window, and then click ",(0,i.jsx)(o.A,{name:"Plus","aria-hidden":"true"})," in the ",(0,i.jsx)(n.strong,{children:"Conversations"})," tab to start a new conversation.\nThis ensures that the chat doesn't persist any context from the previous conversation with the original model."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Ask the same question you asked in ",(0,i.jsx)(n.a,{href:"#chat-with-documents",children:"Load and chat with documents"})," to see how the response differs from the original model."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"integrate-openrag-into-an-application",children:"Integrate OpenRAG into an application"}),"\n",(0,i.jsxs)(n.p,{children:["Langflow in OpenRAG includes pre-built flows that you can integrate into your applications using the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Langflow API"}),".\nYou can use these flows as-is or modify them to better suit your needs, as demonstrated in ",(0,i.jsx)(n.a,{href:"#change-components",children:"Change the language model and chat settings"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"You can send and receive requests with the Langflow API using Python, TypeScript, or curl."}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Open the OpenRAG OpenSearch Agent flow in the Langflow visual editor: From the ",(0,i.jsx)(n.strong,{children:"Chat"})," window, click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),", and then click ",(0,i.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Create a ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"}),", which is a user-specific token required to send requests to the Langflow server.\nThis key doesn't grant access to OpenRAG."]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["In the Langflow visual editor, click your user icon in the header, and then select ",(0,i.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:["Click ",(0,i.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,i.jsx)(o.A,{name:"Plus","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Add New"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:["Name your key, and then click ",(0,i.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n",(0,i.jsx)(n.li,{children:"Copy the API key and store it securely."}),"\n",(0,i.jsxs)(n.li,{children:["Exit the Langflow ",(0,i.jsx)(n.strong,{children:"Settings"})," page to return to the visual editor."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Share"}),", and then select ",(0,i.jsx)(n.strong,{children:"API access"})," to get pregenerated code snippets that call the Langflow API and run the flow."]}),"\n",(0,i.jsxs)(n.p,{children:["These code snippets construct API requests with your Langflow server URL (",(0,i.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"}),"), the flow to run (",(0,i.jsx)(n.code,{children:"FLOW_ID"}),"), required headers (",(0,i.jsx)(n.code,{children:"LANGFLOW_API_KEY"}),", ",(0,i.jsx)(n.code,{children:"Content-Type"}),"), and a payload containing the required inputs to run the flow, including a default chat input message."]}),"\n",(0,i.jsx)(n.p,{children:"In production, you would modify the inputs to suit your application logic. For example, you could replace the default chat input message with dynamic user input."}),"\n",(0,i.jsxs)(a.A,{children:[(0,i.jsx)(l.A,{value:"python",label:"Python",children:(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:'import requests\nimport os\nimport uuid\n\napi_key = \'LANGFLOW_API_KEY\'\nurl = "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" # The complete API endpoint URL for this flow\n\n# Request payload configuration\npayload = {\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n}\npayload["session_id"] = str(uuid.uuid4())\n\nheaders = {"x-api-key": api_key}\n\ntry:\n # Send API request\n response = requests.request("POST", url, json=payload, headers=headers)\n response.raise_for_status() # Raise exception for bad status codes\n\n # Print response\n print(response.text)\n\nexcept requests.exceptions.RequestException as e:\n print(f"Error making API request: {e}")\nexcept ValueError as e:\n print(f"Error parsing response: {e}")\n'})})}),(0,i.jsx)(l.A,{value:"typescript",label:"TypeScript",children:(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-typescript",children:'const crypto = require(\'crypto\');\nconst apiKey = \'LANGFLOW_API_KEY\';\nconst payload = {\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n};\npayload.session_id = crypto.randomUUID();\n\nconst options = {\n method: \'POST\',\n headers: {\n \'Content-Type\': \'application/json\',\n "x-api-key": apiKey\n },\n body: JSON.stringify(payload)\n};\n\nfetch(\'http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID\', options)\n .then(response => response.json())\n .then(response => console.warn(response))\n .catch(err => console.error(err));\n'})})}),(0,i.jsx)(l.A,{value:"curl",label:"curl",children:(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:'curl --request POST \\\n --url \'http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID?stream=false\' \\\n --header \'Content-Type: application/json\' \\\n --header "x-api-key: LANGFLOW_API_KEY" \\\n --data \'{\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n }\'\n'})})})]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Copy your preferred snippet, and then run it:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.strong,{children:"Python"}),": Paste the snippet into a ",(0,i.jsx)(n.code,{children:".py"})," file, save it, and then run it with ",(0,i.jsx)(n.code,{children:"python filename.py"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.strong,{children:"TypeScript"}),": Paste the snippet into a ",(0,i.jsx)(n.code,{children:".ts"})," file, save it, and then run it with ",(0,i.jsx)(n.code,{children:"ts-node filename.ts"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.strong,{children:"curl"}),": Paste and run snippet directly in your terminal."]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.p,{children:"If the request is successful, the response includes many details about the flow run, including the session ID, inputs, outputs, components, durations, and more."}),"\n",(0,i.jsxs)(n.p,{children:["In production, you won't pass the raw response to the user in its entirety.\nInstead, you extract and reformat relevant fields for different use cases, as demonstrated in the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/quickstart#extract-data-from-the-response",children:"Langflow quickstart"}),".\nFor example, you could pass the chat output text to a front-end user-facing application, and store specific fields in logs and backend data stores for monitoring, chat history, or analytics.\nYou could also pass the output from one flow as input to another flow."]}),"\n",(0,i.jsx)(n.h2,{id:"next-steps",children:"Next steps"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Reinstall OpenRAG with your preferred settings"}),": This quickstart used a minimal setup to demonstrate OpenRAG's core functionality.\nIt is recommended that you reinstall OpenRAG with your preferred configuration because some settings are immutable after initial setup.\nFor all installation options, see ",(0,i.jsx)(n.a,{href:"/install",children:"Install OpenRAG with TUI"})," and ",(0,i.jsx)(n.a,{href:"/docker",children:"Install OpenRAG with containers"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Learn more about OpenRAG"}),": Explore OpenRAG and the OpenRAG documentation to learn more about its features and functionality."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Learn more about Langflow"}),": For a deep dive on the Langflow API and visual editor, see the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/",children:"Langflow documentation"}),"."]}),"\n"]}),"\n"]})]})}function g(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(x,{...e})}):x(e)}},3862:(e,n,s)=>{s.d(n,{Ay:()=>a,RM:()=>r});var t=s(4848),i=s(8453);const r=[];function o(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,i.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install",children:"Install WSL"})," with the Ubuntu distribution using WSL 2:"]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-powershell",children:"wsl --install -d Ubuntu\n"})}),"\n",(0,t.jsxs)(n.p,{children:["For new installations, the ",(0,t.jsx)(n.code,{children:"wsl --install"})," command uses WSL 2 and Ubuntu by default."]}),"\n",(0,t.jsxs)(n.p,{children:["For existing WSL installations, you can ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#change-the-default-linux-distribution-installed",children:"change the distribution"})," and ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2",children:"check the WSL version"}),"."]}),"\n",(0,t.jsx)(n.admonition,{title:"Known limitation",type:"warning",children:(0,t.jsx)(n.p,{children:"OpenRAG isn't compatible with nested virtualization, which can cause networking issues.\nDon't install OpenRAG on a WSL distribution that is installed inside a Windows VM.\nInstead, install OpenRAG on your base OS or a non-nested Linux 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When you reach the Docker Desktop ",(0,t.jsx)(n.strong,{children:"WSL integration"})," settings, make sure your Ubuntu distribution is enabled, and then click ",(0,t.jsx)(n.strong,{children:"Apply & Restart"})," to enable Docker support in WSL."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Install and run OpenRAG from within your WSL Ubuntu distribution."}),"\n"]}),"\n"]}),"\n",(0,t.jsx)("br",{}),"\n",(0,t.jsxs)(n.p,{children:["If you encounter issues with port forwarding or the Windows Firewall, you might need to adjust the ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/security/operating-system-security/network-security/windows-firewall/hyper-v-firewall",children:"Hyper-V firewall settings"})," to allow communication between your WSL distribution and the Windows host. 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providers, see the complete ",(0,i.jsx)(n.a,{href:"/install",children:"installation guide"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.a,{href:"https://www.python.org/downloads/release/python-3100/",children:"Python"})," version 3.13 or later."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Microsoft Windows only: To run OpenRAG on Windows, you must use the Windows Subsystem for Linux (WSL)."}),"\n",(0,i.jsxs)(t,{children:[(0,i.jsx)("summary",{children:"Install WSL for OpenRAG"}),(0,i.jsx)(a.Ay,{})]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"install-openrag",children:"Install OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"For this quickstart, install OpenRAG with the automatic installer script and basic setup:"}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a directory to store the OpenRAG configuration files, and then change to that directory:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"mkdir openrag-workspace\ncd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.a,{href:"https://docs.openr.ag/files/run_openrag_with_prereqs.sh",children:"Download the OpenRAG install script"}),", move it to your OpenRAG directory, and then run it:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"bash run_openrag_with_prereqs.sh\n"})}),"\n",(0,i.jsxs)(n.p,{children:["This script installs OpenRAG and its dependencies, including Docker or Podman, and it creates a ",(0,i.jsx)(n.code,{children:".env"})," file and ",(0,i.jsx)(n.code,{children:"docker-compose"})," files in the current working directory.\nYou might be prompted to install certain dependencies if they aren't already present in your environment.\nThis process can take a few minutes.\nOnce the environment is ready, OpenRAG starts."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Basic Setup"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Create passwords for your OpenRAG installation's OpenSearch and Langflow services. You can click ",(0,i.jsx)(n.strong,{children:"Generate Passwords"})," to automatically generate passwords."]}),"\n",(0,i.jsxs)(n.p,{children:["The OpenSearch password is required. The Langflow admin password is optional.\nIf you don't generate a Langflow admin password, Langflow runs in ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required."]}),"\n",(0,i.jsxs)(n.p,{children:["Your passwords are saved in the ",(0,i.jsx)(n.code,{children:".env"})," file that is used to start OpenRAG.\nYou can find this file in your OpenRAG installation directory."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Save Configuration"}),", and then click ",(0,i.jsx)(n.strong,{children:"Start All Services"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"Wait a few minutes while the startup process pulls and runs the necessary container images.\nProceed when you see the following messages in the terminal user interface (TUI):"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"Services started successfully\nCommand completed successfully\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To open the OpenRAG application, go to the TUI main menu, and then click ",(0,i.jsx)(n.strong,{children:"Open App"}),".\nAlternatively, in your browser, navigate to ",(0,i.jsx)(n.code,{children:"localhost:3000"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Select the ",(0,i.jsx)(n.strong,{children:"OpenAI"})," model provider, enter your OpenAI API key, and then click ",(0,i.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"For this quickstart, you can use the default options for the model settings."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click through the overview slides for a brief introduction to OpenRAG and basic setup, or click ",(0,i.jsx)(o.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Skip overview"}),".\nYou can complete this quickstart without going through the overview."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"chat-with-documents",children:"Load and chat with documents"}),"\n",(0,i.jsxs)(n.p,{children:["Use the ",(0,i.jsxs)(n.a,{href:"/chat",children:["OpenRAG ",(0,i.jsx)(n.strong,{children:"Chat"})]})," to explore the documents in your OpenRAG database using natural language queries.\nSome documents are included by default to get you started, and you can load your own documents."]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["In OpenRAG, click ",(0,i.jsx)(o.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Chat"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["For this quickstart, ask the agent what documents are available.\nFor example: ",(0,i.jsx)(n.code,{children:"What documents are available to you?"})]}),"\n",(0,i.jsx)(n.p,{children:"The agent responds with a summary of OpenRAG's default documents."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To verify the agent's response, click ",(0,i.jsx)(o.A,{name:"Library","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Knowledge"})," to view the documents stored in the OpenRAG OpenSearch vector database.\nYou can click a document to view the chunks of the document as they are stored in the database."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Add Knowledge"})," to add your own documents to your OpenRAG knowledge base."]}),"\n",(0,i.jsxs)(n.p,{children:["For this quickstart, use either the ",(0,i.jsx)(o.A,{name:"File","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"File"})," or ",(0,i.jsx)(o.A,{name:"Folder","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Folder"})," upload options to load documents from your local machine.\n",(0,i.jsx)(n.strong,{children:"Folder"})," uploads an entire directory.\nThe default directory is the ",(0,i.jsx)(n.code,{children:"/openrag-documents"})," subdirectory in your OpenRAG installation directory."]}),"\n",(0,i.jsxs)(n.p,{children:["For information about the cloud storage provider options, see ",(0,i.jsx)(n.a,{href:"/ingestion#oauth-ingestion",children:"Ingest files with OAuth connectors"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Return to the ",(0,i.jsx)(n.strong,{children:"Chat"})," window, and then ask a question related to the documents that you just uploaded."]}),"\n",(0,i.jsx)(n.p,{children:"If the agent's response doesn't seem to reference your documents correctly, try the following:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(o.A,{name:"Gear","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Function Call: search_documents (tool_call)"})," to view the log of tool calls made by the agent. This is helpful for troubleshooting because it shows you how the agent used particular tools."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(o.A,{name:"Library","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Knowledge"})," to confirm that the documents are present in the OpenRAG OpenSearch vector database, and then click each document to see how the document was chunked.\nIf a document was chunked improperly, you might need to tweak the ingestion or modify and reupload the document."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"})," to modify the knowledge ingestion settings."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["For more information, see ",(0,i.jsx)(n.a,{href:"/knowledge",children:"Configure knowledge"})," and ",(0,i.jsx)(n.a,{href:"/ingestion",children:"Ingest knowledge"}),"."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"change-components",children:"Change the language model and chat settings"}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To change the knowledge ingestion settings, agent behavior, or language model, click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Settings"})," page provides quick access to commonly used parameters like the ",(0,i.jsx)(n.strong,{children:"Language model"})," and ",(0,i.jsx)(n.strong,{children:"Agent Instructions"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["For greater insight into the underlying ",(0,i.jsx)(n.a,{href:"/agents",children:"Langflow flow"})," that drives the OpenRAG chat, click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"})," and then click ",(0,i.jsx)(n.strong,{children:"Proceed"})," to launch the Langflow visual editor in a new browser window."]}),"\n",(0,i.jsxs)(n.p,{children:["If Langflow requests login information, enter the ",(0,i.jsx)(n.code,{children:"LANGFLOW_SUPERUSER"})," and ",(0,i.jsx)(n.code,{children:"LANGFLOW_SUPERUSER_PASSWORD"})," from the ",(0,i.jsx)(n.code,{children:".env"})," file in your OpenRAG installation directory."]}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"OpenRAG OpenSearch Agent"})," flow opens in a new browser window."]}),"\n",(0,i.jsx)(n.p,{children:(0,i.jsx)(n.img,{alt:"OpenRAG OpenSearch Agent flow",src:s(3982).A+"",width:"4084",height:"2176"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["For this quickstart, try changing the model.\nClick the ",(0,i.jsx)(n.strong,{children:"Language Model"})," component, and then change the ",(0,i.jsx)(n.strong,{children:"Model Name"})," to a different OpenAI model."]}),"\n",(0,i.jsxs)(n.p,{children:["After you edit a built-in flow, you can click ",(0,i.jsx)(n.strong,{children:"Restore flow"})," on the ",(0,i.jsx)(n.strong,{children:"Settings"})," page to revert the flow to its original state when you first installed OpenRAG."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Press ",(0,i.jsx)("kbd",{children:"Command"}),"+",(0,i.jsx)("kbd",{children:"S"})," (",(0,i.jsx)("kbd",{children:"Ctrl"}),"+",(0,i.jsx)("kbd",{children:"S"}),") to save your changes."]}),"\n",(0,i.jsx)(n.p,{children:"You can close the Langflow browser window, or leave it open if you want to continue experimenting with the flow editor."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Switch to your OpenRAG browser window, and then click ",(0,i.jsx)(o.A,{name:"Plus","aria-hidden":"true"})," in the ",(0,i.jsx)(n.strong,{children:"Conversations"})," tab to start a new conversation.\nThis ensures that the chat doesn't persist any context from the previous conversation with the original model."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Ask the same question you asked in ",(0,i.jsx)(n.a,{href:"#chat-with-documents",children:"Load and chat with documents"})," to see how the response differs from the original model."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"integrate-openrag-into-an-application",children:"Integrate OpenRAG into an application"}),"\n",(0,i.jsxs)(n.p,{children:["Langflow in OpenRAG includes pre-built flows that you can integrate into your applications using the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Langflow API"}),".\nYou can use these flows as-is or modify them to better suit your needs, as demonstrated in ",(0,i.jsx)(n.a,{href:"#change-components",children:"Change the language model and chat settings"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"You can send and receive requests with the Langflow API using Python, TypeScript, or curl."}),"\n",(0,i.jsx)(l.Ay,{}),"\n",(0,i.jsx)(n.h2,{id:"next-steps",children:"Next steps"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Reinstall OpenRAG with your preferred settings"}),": This quickstart used a minimal setup to demonstrate OpenRAG's core functionality.\nIt is recommended that you reinstall OpenRAG with your preferred configuration because some settings are immutable after initial setup.\nFor all installation options, see ",(0,i.jsx)(n.a,{href:"/install",children:"Install OpenRAG with TUI"})," and ",(0,i.jsx)(n.a,{href:"/docker",children:"Install OpenRAG with containers"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.strong,{children:"Learn more about OpenRAG"}),": Explore OpenRAG and the OpenRAG documentation to learn more about its features and 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2:"]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-powershell",children:"wsl --install -d Ubuntu\n"})}),"\n",(0,t.jsxs)(n.p,{children:["For new installations, the ",(0,t.jsx)(n.code,{children:"wsl --install"})," command uses WSL 2 and Ubuntu by default."]}),"\n",(0,t.jsxs)(n.p,{children:["For existing WSL installations, you can ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#change-the-default-linux-distribution-installed",children:"change the distribution"})," and ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2",children:"check the WSL version"}),"."]}),"\n",(0,t.jsx)(n.admonition,{title:"Known limitation",type:"warning",children:(0,t.jsx)(n.p,{children:"OpenRAG isn't compatible with nested virtualization, which can cause networking issues.\nDon't install OpenRAG on a WSL distribution that is installed inside a Windows VM.\nInstead, install OpenRAG on your base OS or a non-nested Linux VM."})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#ways-to-run-multiple-linux-distributions-with-wsl",children:"Start your WSL Ubuntu distribution"})," if it doesn't start automatically."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/setup/environment#set-up-your-linux-username-and-password",children:"Set up a username and password for your WSL distribution"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers",children:"Install Docker Desktop for Windows with WSL 2"}),". When you reach the Docker Desktop ",(0,t.jsx)(n.strong,{children:"WSL integration"})," settings, make sure your Ubuntu distribution is enabled, and then click ",(0,t.jsx)(n.strong,{children:"Apply & Restart"})," to enable Docker support in WSL."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Install and run OpenRAG from within your WSL Ubuntu distribution."}),"\n"]}),"\n"]}),"\n",(0,t.jsx)("br",{}),"\n",(0,t.jsxs)(n.p,{children:["If you encounter issues with port forwarding or the Windows Firewall, you might need to adjust the ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/security/operating-system-security/network-security/windows-firewall/hyper-v-firewall",children:"Hyper-V firewall settings"})," to allow communication between your WSL distribution and the Windows host. For more troubleshooting advice for networking issues, see ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/troubleshooting#common-issues",children:"Troubleshooting WSL common issues"}),"."]})]})}function a(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(o,{...e})}):o(e)}},3982:(e,n,s)=>{s.d(n,{A:()=>t});const t=s.p+"assets/images/opensearch-agent-flow-f3b279e02425cd043002eb7749067108.png"},7224:(e,n,s)=>{s.d(n,{Ay:()=>d,RM:()=>l});var t=s(4848),i=s(8453),r=s(1610),o=s(1470),a=s(9365);const l=[];function c(e){const n={a:"a",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,i.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Open the ",(0,t.jsx)(n.strong,{children:"OpenRAG OpenSearch Agent"})," flow in the Langflow visual editor: From the ",(0,t.jsx)(n.strong,{children:"Chat"})," window, click ",(0,t.jsx)(r.A,{name:"Settings2","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Settings"}),", click ",(0,t.jsx)(n.strong,{children:"Edit in Langflow"}),", and then click ",(0,t.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Create a ",(0,t.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"}),", which is a user-specific token required to send requests to the Langflow server.\nThis key doesn't grant access to OpenRAG."]}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["In the Langflow visual editor, click your user icon in the header, and then select ",(0,t.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add New"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Name your key, and then click ",(0,t.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n",(0,t.jsx)(n.li,{children:"Copy the API key and store it securely."}),"\n",(0,t.jsxs)(n.li,{children:["Exit the Langflow ",(0,t.jsx)(n.strong,{children:"Settings"})," page to return to the visual editor."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Share"}),", and then select ",(0,t.jsx)(n.strong,{children:"API access"})," to get pregenerated code snippets that call the Langflow API and run the flow."]}),"\n",(0,t.jsxs)(n.p,{children:["These code snippets construct API requests with your Langflow server URL (",(0,t.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"}),"), the flow to run (",(0,t.jsx)(n.code,{children:"FLOW_ID"}),"), required headers (",(0,t.jsx)(n.code,{children:"LANGFLOW_API_KEY"}),", ",(0,t.jsx)(n.code,{children:"Content-Type"}),"), and a payload containing the required inputs to run the flow, including a default chat input message."]}),"\n",(0,t.jsx)(n.p,{children:"In production, you would modify the inputs to suit your application logic. For example, you could replace the default chat input message with dynamic user input."}),"\n",(0,t.jsxs)(o.A,{children:[(0,t.jsx)(a.A,{value:"python",label:"Python",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-python",children:'import requests\nimport os\nimport uuid\n\napi_key = \'LANGFLOW_API_KEY\'\nurl = "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" # The complete API endpoint URL for this flow\n\n# Request payload configuration\npayload = {\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n}\npayload["session_id"] = str(uuid.uuid4())\n\nheaders = {"x-api-key": api_key}\n\ntry:\n # Send API request\n response = requests.request("POST", url, json=payload, headers=headers)\n response.raise_for_status() # Raise exception for bad status codes\n\n # Print response\n print(response.text)\n\nexcept requests.exceptions.RequestException as e:\n print(f"Error making API request: {e}")\nexcept ValueError as e:\n print(f"Error parsing response: {e}")\n'})})}),(0,t.jsx)(a.A,{value:"typescript",label:"TypeScript",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-typescript",children:'const crypto = require(\'crypto\');\nconst apiKey = \'LANGFLOW_API_KEY\';\nconst payload = {\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n};\npayload.session_id = crypto.randomUUID();\n\nconst options = {\n method: \'POST\',\n headers: {\n \'Content-Type\': \'application/json\',\n "x-api-key": apiKey\n },\n body: JSON.stringify(payload)\n};\n\nfetch(\'http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID\', options)\n .then(response => response.json())\n .then(response => console.warn(response))\n .catch(err => console.error(err));\n'})})}),(0,t.jsx)(a.A,{value:"curl",label:"curl",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:'curl --request POST \\\n --url \'http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID?stream=false\' \\\n --header \'Content-Type: application/json\' \\\n --header "x-api-key: LANGFLOW_API_KEY" \\\n --data \'{\n "output_type": "chat",\n "input_type": "chat",\n "input_value": "hello world!"\n }\'\n'})})})]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Copy your preferred snippet, and then run it:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Python"}),": Paste the snippet into a ",(0,t.jsx)(n.code,{children:".py"})," file, save it, and then run it with ",(0,t.jsx)(n.code,{children:"python filename.py"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"TypeScript"}),": Paste the snippet into a ",(0,t.jsx)(n.code,{children:".ts"})," file, save it, and then run it with ",(0,t.jsx)(n.code,{children:"ts-node filename.ts"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"curl"}),": Paste and run snippet directly in your terminal."]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,t.jsx)(n.p,{children:"If the request is successful, the response includes many details about the flow run, including the session ID, inputs, outputs, components, durations, and more."}),"\n",(0,t.jsxs)(n.p,{children:["In production, you won't pass the raw response to the user in its entirety.\nInstead, you extract and reformat relevant fields for different use cases, as demonstrated in the ",(0,t.jsx)(n.a,{href:"https://docs.langflow.org/quickstart#extract-data-from-the-response",children:"Langflow quickstart"}),".\nFor example, you could pass the chat output text to a front-end user-facing application, and store specific fields in logs and backend data stores for monitoring, chat history, or analytics.\nYou could also pass the output from one flow as input to another flow."]})]})}function d(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(c,{...e})}):c(e)}}}]); \ No newline at end of file diff --git a/assets/js/c8078f0a.0b3241eb.js b/assets/js/c8078f0a.0b3241eb.js deleted file mode 100644 index 930d8fca..00000000 --- a/assets/js/c8078f0a.0b3241eb.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[9026],{9196:(e,n,r)=>{r.r(n),r.d(n,{assets:()=>c,contentTitle:()=>t,default:()=>a,frontMatter:()=>l,metadata:()=>i,toc:()=>o});const i=JSON.parse('{"id":"reference/configuration","title":"Environment variables","description":"OpenRAG recognizes environment variables from the following sources:","source":"@site/docs/reference/configuration.mdx","sourceDirName":"reference","slug":"/reference/configuration","permalink":"/reference/configuration","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/reference/configuration.mdx","tags":[],"version":"current","frontMatter":{"title":"Environment variables","slug":"/reference/configuration"},"sidebar":"tutorialSidebar","previous":{"title":"Docling in OpenRAG","permalink":"/ingestion"},"next":{"title":"Troubleshoot OpenRAG","permalink":"/support/troubleshoot"}}');var s=r(4848),d=r(8453);r(1610),r(1470),r(9365);const l={title:"Environment variables",slug:"/reference/configuration"},t=void 0,c={},o=[{value:"Configure environment variables",id:"configure-environment-variables",level:2},{value:"Set environment variables",id:"set-environment-variables",level:3},{value:"Supported environment variables",id:"supported-environment-variables",level:2},{value:"AI provider settings",id:"ai-provider-settings",level:3},{value:"Document processing",id:"document-processing",level:3},{value:"Langflow settings",id:"langflow-settings",level:3},{value:"OAuth provider settings",id:"oauth-provider-settings",level:3},{value:"OpenSearch settings",id:"opensearch-settings",level:3},{value:"System settings",id:"system-settings",level:3},{value:"Langflow runtime overrides",id:"langflow-runtime-overrides",level:2},{value:"Default values and fallbacks",id:"default-values-and-fallbacks",level:2},{value:"OpenRAG configuration defaults",id:"openrag-configuration-defaults",level:3},{value:"System configuration defaults",id:"system-configuration-defaults",level:3}];function h(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",table:"table",tbody:"tbody",td:"td",th:"th",thead:"thead",tr:"tr",ul:"ul",...(0,d.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(n.p,{children:"OpenRAG recognizes environment variables from the following sources:"}),"\n",(0,s.jsxs)(n.ul,{children:["\n",(0,s.jsxs)(n.li,{children:[(0,s.jsx)(n.a,{href:"#configure-environment-variables",children:"Environment variables"}),": Values set in the ",(0,s.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,s.jsxs)(n.li,{children:[(0,s.jsx)(n.a,{href:"#langflow-runtime-overrides",children:"Langflow runtime overrides"}),": Langflow components can set environment variables at runtime."]}),"\n",(0,s.jsxs)(n.li,{children:[(0,s.jsx)(n.a,{href:"#default-values-and-fallbacks",children:"Default or fallback values"}),": These values are default or fallback values if OpenRAG doesn't find a value."]}),"\n"]}),"\n",(0,s.jsx)(n.h2,{id:"configure-environment-variables",children:"Configure environment variables"}),"\n",(0,s.jsxs)(n.p,{children:["Environment variables are set in a ",(0,s.jsx)(n.code,{children:".env"})," file in the root of your OpenRAG project directory."]}),"\n",(0,s.jsxs)(n.p,{children:["For an example ",(0,s.jsx)(n.code,{children:".env"})," file, see ",(0,s.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/.env.example",children:[(0,s.jsx)(n.code,{children:".env.example"})," in the OpenRAG repository"]}),"."]}),"\n",(0,s.jsxs)(n.p,{children:["The Docker Compose files are populated with values from your ",(0,s.jsx)(n.code,{children:".env"}),", so you don't need to edit the Docker Compose files manually."]}),"\n",(0,s.jsx)(n.p,{children:"Environment variables always take precedence over other variables."}),"\n",(0,s.jsx)(n.h3,{id:"set-environment-variables",children:"Set environment variables"}),"\n",(0,s.jsx)(n.p,{children:"To set environment variables, do the following."}),"\n",(0,s.jsxs)(n.ol,{children:["\n",(0,s.jsx)(n.li,{children:"Stop OpenRAG."}),"\n",(0,s.jsxs)(n.li,{children:["Set the values in the ",(0,s.jsx)(n.code,{children:".env"})," file:","\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{className:"language-bash",children:"LOG_LEVEL=DEBUG\nLOG_FORMAT=json\nSERVICE_NAME=openrag-dev\n"})}),"\n"]}),"\n",(0,s.jsx)(n.li,{children:"Start OpenRAG."}),"\n"]}),"\n",(0,s.jsxs)(n.p,{children:["Updating provider API keys or provider endpoints in the ",(0,s.jsx)(n.code,{children:".env"})," file will not take effect after ",(0,s.jsx)(n.a,{href:"/install#application-onboarding",children:"Application onboarding"}),". To change these values, you must:"]}),"\n",(0,s.jsxs)(n.ol,{children:["\n",(0,s.jsx)(n.li,{children:"Stop OpenRAG."}),"\n",(0,s.jsxs)(n.li,{children:["Remove the containers:","\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{children:"docker-compose down\n"})}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["Update the values in your ",(0,s.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,s.jsxs)(n.li,{children:["Start OpenRAG containers.","\n",(0,s.jsx)(n.pre,{children:(0,s.jsx)(n.code,{children:"docker-compose up -d\n"})}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["Complete ",(0,s.jsx)(n.a,{href:"/install#application-onboarding",children:"Application onboarding"})," again."]}),"\n"]}),"\n",(0,s.jsx)(n.h2,{id:"supported-environment-variables",children:"Supported environment variables"}),"\n",(0,s.jsx)(n.p,{children:"All OpenRAG configuration can be controlled through environment variables."}),"\n",(0,s.jsx)(n.h3,{id:"ai-provider-settings",children:"AI provider settings"}),"\n",(0,s.jsxs)(n.p,{children:["Configure which AI models and providers OpenRAG uses for language processing and embeddings.\nFor more information, see ",(0,s.jsx)(n.a,{href:"/install#application-onboarding",children:"Application onboarding"}),"."]}),"\n",(0,s.jsxs)(n.table,{children:[(0,s.jsx)(n.thead,{children:(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.th,{children:"Variable"}),(0,s.jsx)(n.th,{children:"Default"}),(0,s.jsx)(n.th,{children:"Description"})]})}),(0,s.jsxs)(n.tbody,{children:[(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"EMBEDDING_MODEL"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"text-embedding-3-small"})}),(0,s.jsx)(n.td,{children:"Embedding model for vector search."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"LLM_MODEL"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"gpt-4o-mini"})}),(0,s.jsx)(n.td,{children:"Language model for the chat agent."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"MODEL_PROVIDER"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"openai"})}),(0,s.jsx)(n.td,{children:"Model provider, such as OpenAI or IBM watsonx.ai."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"OPENAI_API_KEY"})}),(0,s.jsx)(n.td,{children:"-"}),(0,s.jsx)(n.td,{children:"Your OpenAI API key. Optional. Can be provided during application onboarding when installing OpenRAG."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"PROVIDER_API_KEY"})}),(0,s.jsx)(n.td,{children:"-"}),(0,s.jsx)(n.td,{children:"API key for the model provider."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"PROVIDER_ENDPOINT"})}),(0,s.jsx)(n.td,{children:"-"}),(0,s.jsx)(n.td,{children:"Custom provider endpoint. Only used for IBM or Ollama providers."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"PROVIDER_PROJECT_ID"})}),(0,s.jsx)(n.td,{children:"-"}),(0,s.jsx)(n.td,{children:"Project ID for providers. Only required for the IBM watsonx.ai provider."})]})]})]}),"\n",(0,s.jsx)(n.h3,{id:"document-processing",children:"Document processing"}),"\n",(0,s.jsxs)(n.p,{children:["Control how OpenRAG processes and ingests documents into your knowledge base.\nFor more information, see ",(0,s.jsx)(n.a,{href:"/ingestion",children:"Ingestion"}),"."]}),"\n",(0,s.jsxs)(n.table,{children:[(0,s.jsx)(n.thead,{children:(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.th,{children:"Variable"}),(0,s.jsx)(n.th,{children:"Default"}),(0,s.jsx)(n.th,{children:"Description"})]})}),(0,s.jsxs)(n.tbody,{children:[(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"CHUNK_OVERLAP"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"200"})}),(0,s.jsx)(n.td,{children:"Overlap between chunks."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"CHUNK_SIZE"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"1000"})}),(0,s.jsx)(n.td,{children:"Text chunk size for document processing."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"DISABLE_INGEST_WITH_LANGFLOW"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"false"})}),(0,s.jsx)(n.td,{children:"Disable Langflow ingestion pipeline."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"DOCLING_OCR_ENGINE"})}),(0,s.jsx)(n.td,{children:"-"}),(0,s.jsx)(n.td,{children:"OCR engine for document processing."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"OCR_ENABLED"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"false"})}),(0,s.jsx)(n.td,{children:"Enable OCR for image processing."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"OPENRAG_DOCUMENTS_PATHS"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"./openrag-documents"})}),(0,s.jsx)(n.td,{children:"Document paths for ingestion."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"PICTURE_DESCRIPTIONS_ENABLED"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"false"})}),(0,s.jsx)(n.td,{children:"Enable picture descriptions."})]})]})]}),"\n",(0,s.jsx)(n.h3,{id:"langflow-settings",children:"Langflow settings"}),"\n",(0,s.jsx)(n.p,{children:"Configure Langflow authentication."}),"\n",(0,s.jsxs)(n.table,{children:[(0,s.jsx)(n.thead,{children:(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.th,{children:"Variable"}),(0,s.jsx)(n.th,{children:"Default"}),(0,s.jsx)(n.th,{children:"Description"})]})}),(0,s.jsxs)(n.tbody,{children:[(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"LANGFLOW_AUTO_LOGIN"})}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"False"})}),(0,s.jsx)(n.td,{children:"Enable auto-login for Langflow."})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"LANGFLOW_CHAT_FLOW_ID"})}),(0,s.jsx)(n.td,{children:"pre-filled"}),(0,s.jsxs)(n.td,{children:["This value is pre-filled. 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sources:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"#configure-environment-variables",children:"Environment variables"}),": Values set in the ",(0,r.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"#langflow-runtime-overrides",children:"Langflow runtime overrides"}),": Langflow components can set environment variables at runtime."]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)(n.a,{href:"#default-values-and-fallbacks",children:"Default or fallback values"}),": These values are default or fallback values if OpenRAG doesn't find a value."]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"configure-environment-variables",children:"Configure environment variables"}),"\n",(0,r.jsxs)(n.p,{children:["Environment variables are set in a ",(0,r.jsx)(n.code,{children:".env"})," file in the root of your OpenRAG project directory."]}),"\n",(0,r.jsxs)(n.p,{children:["For an example ",(0,r.jsx)(n.code,{children:".env"})," file, see ",(0,r.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/.env.example",children:[(0,r.jsx)(n.code,{children:".env.example"})," in the OpenRAG repository"]}),"."]}),"\n",(0,r.jsxs)(n.p,{children:["The Docker Compose files are populated with values from your ",(0,r.jsx)(n.code,{children:".env"}),", so you don't need to edit the Docker Compose files manually."]}),"\n",(0,r.jsx)(n.p,{children:"Environment variables always take precedence over other variables."}),"\n",(0,r.jsx)(n.h3,{id:"set-environment-variables",children:"Set environment variables"}),"\n",(0,r.jsxs)(n.p,{children:["After you start OpenRAG, you must ",(0,r.jsx)(n.a,{href:"/install#tui-container-management",children:"stop and restart OpenRAG containers"})," to apply any changes you make to the ",(0,r.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,r.jsx)(n.p,{children:"To set mutable environment variables, do the following:"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Stop OpenRAG with the TUI or Docker Compose."}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Set the values in the ",(0,r.jsx)(n.code,{children:".env"})," file:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"LOG_LEVEL=DEBUG\nLOG_FORMAT=json\nSERVICE_NAME=openrag-dev\n"})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Start OpenRAG with the TUI or Docker Compose."}),"\n"]}),"\n"]}),"\n",(0,r.jsxs)(n.p,{children:["Certain environment variables that you set during ",(0,r.jsx)(n.a,{href:"/install#application-onboarding",children:"application onboarding"}),", such as provider API keys and provider endpoints, require resetting the containers after modifying the ",(0,r.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,r.jsxs)(n.p,{children:["To change immutable variables with TUI-managed 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The values in your ",(0,r.jsx)(n.code,{children:".env"})," file are automatically populated."]}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"supported-environment-variables",children:"Supported environment variables"}),"\n",(0,r.jsx)(n.p,{children:"All OpenRAG configuration can be controlled through environment variables."}),"\n",(0,r.jsx)(n.h3,{id:"ai-provider-settings",children:"AI provider settings"}),"\n",(0,r.jsxs)(n.p,{children:["Configure which models and providers OpenRAG uses to generate text and embeddings.\nThese are initially set during ",(0,r.jsx)(n.a,{href:"/install#application-onboarding",children:"application onboarding"}),".\nSome values are immutable and can only be changed by recreating the OpenRAG containers, as explained in ",(0,r.jsx)(n.a,{href:"#set-environment-variables",children:"Set environment variables"}),"."]}),"\n",(0,r.jsxs)(n.table,{children:[(0,r.jsx)(n.thead,{children:(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.th,{children:"Variable"}),(0,r.jsx)(n.th,{children:"Default"}),(0,r.jsx)(n.th,{children:"Description"})]})}),(0,r.jsxs)(n.tbody,{children:[(0,r.jsxs)(n.tr,{children:[(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"EMBEDDING_MODEL"})}),(0,r.jsx)(n.td,{children:(0,r.jsx)(n.code,{children:"text-embedding-3-small"})}),(0,r.jsx)(n.td,{children:"Embedding model for generating vector embeddings for documents in the knowledge base and similarity search queries. 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These are runtime variables populated from OAuth login."]}),"\n",(0,i.jsxs)(n.li,{children:["The ",(0,i.jsx)(n.strong,{children:"Create Data"})," component combines the secret inputs into a structured data object that will be associated with the document embeddings."]}),"\n",(0,i.jsxs)(n.li,{children:["The ",(0,i.jsxs)(n.a,{href:"https://docs.langflow.org/components-embedding-models",children:[(0,i.jsx)(n.strong,{children:"Embedding Model"})," component"]})," generates vector embeddings using OpenAI's ",(0,i.jsx)(n.code,{children:"text-embedding-3-small"})," model. The embedding model is selected at [Application onboarding] and cannot be changed."]}),"\n",(0,i.jsxs)(n.li,{children:["The ",(0,i.jsxs)(n.a,{href:"https://docs.langflow.org/bundles-elastic#opensearch",children:[(0,i.jsx)(n.strong,{children:"OpenSearch"})," component"]})," stores the processed documents and their embeddings in the ",(0,i.jsx)(n.code,{children:"documents"})," index at ",(0,i.jsx)(n.code,{children:"https://opensearch:9200"}),". By default, the component is authenticated with a JWT token, but you can also select ",(0,i.jsx)(n.code,{children:"basic"})," auth mode, and enter your OpenSearch admin username and password."]}),"\n"]}),"\n",(0,i.jsx)(r.Ay,{}),"\n",(0,i.jsx)(n.h3,{id:"url-flow",children:"OpenSearch URL Ingestion flow"}),"\n",(0,i.jsxs)(n.p,{children:["An additional knowledge ingestion flow is included in OpenRAG, where it is used as an MCP tool by the ",(0,i.jsx)(n.a,{href:"/agents#flow",children:(0,i.jsx)(n.strong,{children:"Open Search Agent flow"})}),".\nThe agent calls this component to fetch web content, and the results are ingested into OpenSearch."]}),"\n",(0,i.jsxs)(n.p,{children:["For more on using MCP clients in Langflow, see ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/mcp-client",children:"MCP clients"}),".",(0,i.jsx)(n.br,{}),"\n","To connect additional MCP servers to the MCP client, see ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/mcp-tutorial",children:"Connect to MCP servers from your application"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"use-openrag-default-ingestion-instead-of-docling-serve",children:"Use OpenRAG default ingestion instead of Docling serve"}),"\n",(0,i.jsxs)(n.p,{children:["If you want to use OpenRAG's built-in pipeline instead of Docling serve, set ",(0,i.jsx)(n.code,{children:"DISABLE_INGEST_WITH_LANGFLOW=true"})," in ",(0,i.jsx)(n.a,{href:"/reference/configuration#document-processing",children:"Environment variables"}),"."]}),"\n",(0,i.jsx)(n.p,{children:"The built-in pipeline still uses the Docling processor, but uses it directly without the Docling Serve API."}),"\n",(0,i.jsxs)(n.p,{children:["For more information, see ",(0,i.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/models/processors.py#L58",children:[(0,i.jsx)(n.code,{children:"processors.py"})," in the OpenRAG repository"]}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"performance-expectations",children:"Performance expectations"}),"\n",(0,i.jsx)(n.p,{children:"On a local VM with 7 vCPUs and 8 GiB RAM, OpenRAG ingested approximately 5.03 GB across 1,083 files in about 42 minutes.\nThis equates to approximately 2.4 documents per second."}),"\n",(0,i.jsx)(n.p,{children:"You can generally expect equal or better performance on developer laptops and significantly faster on servers.\nThroughput scales with CPU cores, memory, storage speed, and configuration choices such as embedding model, chunk size and overlap, and concurrency."}),"\n",(0,i.jsx)(n.p,{children:"This test returned 12 errors (approximately 1.1%).\nAll errors were file-specific, and they didn't stop the pipeline."}),"\n",(0,i.jsx)(n.p,{children:"Ingestion dataset:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:"Total files: 1,083 items mounted"}),"\n",(0,i.jsx)(n.li,{children:"Total size on disk: 5,026,474,862 bytes (approximately 5.03 GB)"}),"\n"]}),"\n",(0,i.jsx)(n.p,{children:"Hardware specifications:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:"Machine: Apple M4 Pro"}),"\n",(0,i.jsxs)(n.li,{children:["Podman VM:","\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["Name: ",(0,i.jsx)(n.code,{children:"podman-machine-default"})]}),"\n",(0,i.jsxs)(n.li,{children:["Type: ",(0,i.jsx)(n.code,{children:"applehv"})]}),"\n",(0,i.jsx)(n.li,{children:"vCPUs: 7"}),"\n",(0,i.jsx)(n.li,{children:"Memory: 8 GiB"}),"\n",(0,i.jsx)(n.li,{children:"Disk size: 100 GiB"}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.p,{children:"Test results:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-text",children:"2025-09-24T22:40:45.542190Z /app/src/main.py:231 Ingesting default documents when ready disable_langflow_ingest=False\n2025-09-24T22:40:45.546385Z /app/src/main.py:270 Using Langflow ingestion pipeline for default documents file_count=1082\n...\n2025-09-24T23:19:44.866365Z /app/src/main.py:351 Langflow ingestion completed success_count=1070 error_count=12 total_files=1082\n"})}),"\n",(0,i.jsx)(n.p,{children:"Elapsed time: ~42 minutes 15 seconds (2,535 seconds)"}),"\n",(0,i.jsx)(n.p,{children:"Throughput: ~2.4 documents/second"})]})}function p(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(h,{...e})}):h(e)}}}]); \ No newline at end of file diff --git a/assets/js/ca2c3c0c.e8524bce.js b/assets/js/ca2c3c0c.e8524bce.js new file mode 100644 index 00000000..c4fc04de --- /dev/null +++ b/assets/js/ca2c3c0c.e8524bce.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[6919],{5421:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>x,contentTitle:()=>g,default:()=>m,frontMatter:()=>u,metadata:()=>o,toc:()=>j});const o=JSON.parse('{"id":"core-components/ingestion","title":"Ingest knowledge","description":"Upload documents to your OpenRAG OpenSearch instance to populate your knowledge base with unique content, such as your own company documents, research papers, or websites.","source":"@site/docs/core-components/ingestion.mdx","sourceDirName":"core-components","slug":"/ingestion","permalink":"/ingestion","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/core-components/ingestion.mdx","tags":[],"version":"current","frontMatter":{"title":"Ingest knowledge","slug":"/ingestion"},"sidebar":"tutorialSidebar","previous":{"title":"Configure knowledge","permalink":"/knowledge"},"next":{"title":"Filter knowledge","permalink":"/knowledge-filters"}}');var t=s(4848),i=s(8453),r=s(1610),l=s(1470),c=s(9365),d=s(8401);const a=[];function h(e){const n={a:"a",code:"code",li:"li",p:"p",strong:"strong",ul:"ul",...(0,i.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,t.jsxs)(s,{children:[(0,t.jsx)("summary",{children:"About the OpenSearch Ingestion flow"}),(0,t.jsxs)(n.p,{children:["When you upload documents locally or with OAuth connectors, the ",(0,t.jsx)(n.strong,{children:"OpenSearch Ingestion"})," flow runs in the background.\nBy default, this flow uses Docling Serve to import and process documents."]}),(0,t.jsxs)(n.p,{children:["Like all ",(0,t.jsx)(n.a,{href:"/agents",children:"OpenRAG flows"}),", you can ",(0,t.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"inspect the flow in Langflow"}),", and you can customize it if you want to change the knowledge ingestion settings."]}),(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"OpenSearch Ingestion"})," flow is comprised of several components that work together to process and store documents in your knowledge base:"]}),(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/bundles-docling#docling-serve",children:[(0,t.jsx)(n.strong,{children:"Docling Serve"})," component"]}),": Ingests files and processes them by connecting to OpenRAG's local Docling Serve service. The output is ",(0,t.jsx)(n.code,{children:"DoclingDocument"})," data that contains the extracted text and metadata from the documents."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/bundles-docling#export-doclingdocument",children:[(0,t.jsx)(n.strong,{children:"Export DoclingDocument"})," component"]}),": Exports processed ",(0,t.jsx)(n.code,{children:"DoclingDocument"})," data to Markdown format with image placeholders. This conversion standardizes the document data in preparation for further processing."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/components-processing#dataframe-operations",children:[(0,t.jsx)(n.strong,{children:"DataFrame Operations"})," component"]}),": Three of these components run sequentially to add metadata to the document data: ",(0,t.jsx)(n.code,{children:"filename"}),", ",(0,t.jsx)(n.code,{children:"file_size"}),", and ",(0,t.jsx)(n.code,{children:"mimetype"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/components-processing#split-text",children:[(0,t.jsx)(n.strong,{children:"Split Text"})," component"]}),": Splits the processed text into chunks, based on the configured ",(0,t.jsx)(n.a,{href:"/knowledge#knowledge-ingestion-settings",children:"chunk size and overlap settings"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Secret Input"})," component: If needed, four of these components securely fetch the ",(0,t.jsx)(n.a,{href:"/knowledge#auth",children:"OAuth authentication"})," configuration variables: ",(0,t.jsx)(n.code,{children:"CONNECTOR_TYPE"}),", ",(0,t.jsx)(n.code,{children:"OWNER"}),", ",(0,t.jsx)(n.code,{children:"OWNER_EMAIL"}),", and ",(0,t.jsx)(n.code,{children:"OWNER_NAME"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Create Data"})," component: Combines the authentication credentials from the ",(0,t.jsx)(n.strong,{children:"Secret Input"})," components into a structured data object that is associated with the document embeddings."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/components-embedding-models",children:[(0,t.jsx)(n.strong,{children:"Embedding Model"})," component"]}),": Generates vector embeddings using your selected ",(0,t.jsx)(n.a,{href:"/knowledge#set-the-embedding-model-and-dimensions",children:"embedding model"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/bundles-elastic#opensearch",children:[(0,t.jsx)(n.strong,{children:"OpenSearch"})," component"]}),": Stores the processed documents and their embeddings in a ",(0,t.jsx)(n.code,{children:"documents"})," index of your OpenRAG ",(0,t.jsx)(n.a,{href:"/knowledge",children:"OpenSearch knowledge base"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["The default address for the OpenSearch instance is ",(0,t.jsx)(n.code,{children:"https://opensearch:9200"}),". To change this address, edit the ",(0,t.jsx)(n.code,{children:"OPENSEARCH_PORT"})," ",(0,t.jsx)(n.a,{href:"/reference/configuration#opensearch-settings",children:"environment variable"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["The default authentication method is JSON Web Token (JWT) authentication. If you ",(0,t.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"edit the flow"}),", you can select ",(0,t.jsx)(n.code,{children:"basic"})," auth mode, which uses the ",(0,t.jsx)(n.code,{children:"OPENSEARCH_USERNAME"})," and ",(0,t.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})," ",(0,t.jsx)(n.a,{href:"/reference/configuration#opensearch-settings",children:"environment variables"})," for authentication instead of JWT."]}),"\n"]}),"\n"]})]})}function p(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(h,{...e})}):h(e)}const u={title:"Ingest knowledge",slug:"/ingestion"},g=void 0,x={},j=[{value:"Ingest local files and folders",id:"ingest-local-files-and-folders",level:2},...a,{value:"Ingest local files temporarily",id:"ingest-local-files-temporarily",level:2},...d.RM,{value:"Ingest files with OAuth connectors",id:"oauth-ingestion",level:2},{value:"Enable OAuth connectors",id:"enable-oauth-connectors",level:3},{value:"Authenticate and ingest files from cloud storage",id:"authenticate-and-ingest-files-from-cloud-storage",level:3},...a,{value:"Ingest knowledge from URLs",id:"url-flow",level:2},{value:"Monitor ingestion",id:"monitor-ingestion",level:2},{value:"Ingestion performance expectations",id:"ingestion-performance-expectations",level:3},{value:"Troubleshoot ingestion",id:"troubleshoot-ingestion",level:2},{value:"See also",id:"see-also",level:2}];function f(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,i.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(n.p,{children:["Upload documents to your ",(0,t.jsx)(n.a,{href:"/knowledge",children:"OpenRAG OpenSearch instance"})," to populate your knowledge base with unique content, such as your own company documents, research papers, or websites.\nDocuments are processed through OpenRAG's knowledge ingestion flows with Docling."]}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG can ingest knowledge from direct file uploads, URLs, and OAuth authenticated connectors."}),"\n",(0,t.jsxs)(n.p,{children:["Knowledge ingestion is powered by OpenRAG's built-in knowledge ingestion flows that use Docling to process documents before storing the documents in your OpenSearch database.\nDuring ingestion, documents are broken into smaller chunks of content that are then embedded using your selected ",(0,t.jsx)(n.a,{href:"/knowledge#set-the-embedding-model-and-dimensions",children:"embedding model"}),".\nThen, the chunks, embeddings, and associated metadata (which connects chunks of the same document) are stored in your OpenSearch database."]}),"\n",(0,t.jsxs)(n.p,{children:["To modify chunking behavior and other ingestion settings, see ",(0,t.jsx)(n.a,{href:"/knowledge#knowledge-ingestion-settings",children:"Knowledge ingestion settings"})," and ",(0,t.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"Inspect and modify flows"}),"."]}),"\n",(0,t.jsx)(n.h2,{id:"ingest-local-files-and-folders",children:"Ingest local files and folders"}),"\n",(0,t.jsx)(n.p,{children:"You can upload files and folders from your local machine to your knowledge base:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"})," to view your OpenSearch knowledge base."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Add Knowledge"})," to add your own documents to your OpenRAG knowledge base."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To upload one file, click ",(0,t.jsx)(r.A,{name:"File","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"File"}),". 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Each user must separately authorize OpenRAG to access their own cloud storage. When a user connects a cloud storage service, they are redirected to authenticate with that service provider and grant OpenRAG permission to sync documents from their personal cloud storage."}),"\n",(0,t.jsx)(n.h3,{id:"enable-oauth-connectors",children:"Enable OAuth connectors"}),"\n",(0,t.jsx)(n.p,{children:"Before users can connect their own cloud storage accounts, you must configure the provider's OAuth credentials in OpenRAG. Typically, this requires that you register OpenRAG as an OAuth application in your cloud provider, and then obtain the app's OAuth credentials, such as a client ID and secret key.\nTo enable multiple connectors, you must register an app and generate credentials for each provider."}),"\n",(0,t.jsxs)(l.A,{children:[(0,t.jsxs)(c.A,{value:"TUI",label:"TUI Advanced Setup",default:!0,children:[(0,t.jsxs)(n.p,{children:["If you use the TUI to manage your OpenRAG containers, provide OAuth credentials in the ",(0,t.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),(0,t.jsxs)(n.p,{children:["You can do this during ",(0,t.jsx)(n.a,{href:"/install#setup",children:"installation"}),", or you can add the credentials afterwards:"]}),(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["If OpenRAG is running, stop it: Go to ",(0,t.jsx)(n.a,{href:"/install#tui-container-management",children:(0,t.jsx)(n.strong,{children:"Status"})}),", and then click ",(0,t.jsx)(n.strong,{children:"Stop Services"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Advanced Setup"}),", and then add the OAuth credentials for the cloud storage providers that you want to use:"]}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Amazon"}),": Provide your AWS Access Key ID and AWS Secret Access Key with access to your S3 instance. For more information, see the AWS documentation on ",(0,t.jsx)(n.a,{href:"https://docs.aws.amazon.com/singlesignon/latest/userguide/manage-your-applications.html",children:"Configuring access to AWS applications"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Google"}),": Provide your Google OAuth Client ID and Google OAuth Client Secret. You can generate these in the ",(0,t.jsx)(n.a,{href:"https://console.cloud.google.com/apis/credentials",children:"Google Cloud Console"}),". For more information, see the ",(0,t.jsx)(n.a,{href:"https://developers.google.com/identity/protocols/oauth2",children:"Google OAuth client documentation"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Microsoft"}),": For the Microsoft OAuth Client ID and Microsoft OAuth Client Secret, provide ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/app-registration?view=odsp-graph-online",children:"Azure application registration credentials for SharePoint and OneDrive"}),". For more information, see the ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth",children:"Microsoft Graph OAuth client documentation"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"The OpenRAG TUI presents redirect URIs for your OAuth app that you must register with your OAuth provider.\nThese are the URLs your OAuth provider will redirect back to after users authenticate and grant access to their cloud storage."}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG regenerates the ",(0,t.jsx)(n.a,{href:"/reference/configuration",children:(0,t.jsx)(n.code,{children:".env"})})," file with the given credentials."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Start Container Services"}),"."]}),"\n"]}),"\n"]})]}),(0,t.jsxs)(c.A,{value:"env",label:"Docker Compose .env file",children:[(0,t.jsxs)(n.p,{children:["If you ",(0,t.jsx)(n.a,{href:"/docker",children:"install OpenRAG with self-managed containers"}),", set OAuth credentials in the ",(0,t.jsx)(n.code,{children:".env"})," file for Docker Compose."]}),(0,t.jsxs)(n.p,{children:["You can do this during ",(0,t.jsx)(n.a,{href:"/docker#install-openrag-with-docker-compose",children:"initial set up"}),", or you can add the credentials afterwards:"]}),(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Stop your OpenRAG deployment."}),"\n",(0,t.jsxs)(l.A,{children:[(0,t.jsx)(c.A,{value:"podman",label:"Podman",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"podman stop --all\n"})})}),(0,t.jsx)(c.A,{value:"docker",label:"Docker",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker stop $(docker ps -q)\n"})})})]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Edit the ",(0,t.jsx)(n.code,{children:".env"})," file for Docker Compose to add the OAuth credentials for the cloud storage providers that you want to use:"]}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Amazon"}),": Provide your AWS Access Key ID and AWS Secret Access Key with access to your S3 instance. For more information, see the AWS documentation on ",(0,t.jsx)(n.a,{href:"https://docs.aws.amazon.com/singlesignon/latest/userguide/manage-your-applications.html",children:"Configuring access to AWS applications"}),"."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-env",children:"AWS_ACCESS_KEY_ID=\nAWS_SECRET_ACCESS_KEY=\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Google"}),": Provide your Google OAuth Client ID and Google OAuth Client Secret. You can generate these in the ",(0,t.jsx)(n.a,{href:"https://console.cloud.google.com/apis/credentials",children:"Google Cloud Console"}),". For more information, see the ",(0,t.jsx)(n.a,{href:"https://developers.google.com/identity/protocols/oauth2",children:"Google OAuth client documentation"}),"."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-env",children:"GOOGLE_OAUTH_CLIENT_ID=\nGOOGLE_OAUTH_CLIENT_SECRET=\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Microsoft"}),": For the Microsoft OAuth Client ID and Microsoft OAuth Client Secret, provide ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/app-registration?view=odsp-graph-online",children:"Azure application registration credentials for SharePoint and OneDrive"}),". For more information, see the ",(0,t.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth",children:"Microsoft Graph OAuth client documentation"}),"."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-env",children:"MICROSOFT_GRAPH_OAUTH_CLIENT_ID=\nMICROSOFT_GRAPH_OAUTH_CLIENT_SECRET=\n"})}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Save the ",(0,t.jsx)(n.code,{children:".env"})," file."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Restart your OpenRAG deployment:"}),"\n",(0,t.jsxs)(l.A,{children:[(0,t.jsx)(c.A,{value:"podman",label:"Podman",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"podman-compose up -d\n"})})}),(0,t.jsx)(c.A,{value:"docker",label:"Docker",children:(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker-compose up -d\n"})})})]}),"\n"]}),"\n"]})]})]}),"\n",(0,t.jsx)(n.h3,{id:"authenticate-and-ingest-files-from-cloud-storage",children:"Authenticate and ingest files from cloud storage"}),"\n",(0,t.jsxs)(n.p,{children:["After you start OpenRAG with OAuth connectors enabled, each user is prompted to authenticate with the OAuth provider upon accessing your OpenRAG instance.\nIndividual authentication is required to access a user's cloud storage from your OpenRAG instance.\nFor example, if a user navigates to the default OpenRAG URL at ",(0,t.jsx)(n.code,{children:"http://localhost:3000"}),", they are redirected to the OAuth provider's sign-in page.\nAfter authenticating and granting the required permissions for OpenRAG, the user is redirected back to OpenRAG."]}),"\n",(0,t.jsx)(n.p,{children:"To ingest knowledge with an OAuth connector, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"})," to view your OpenSearch knowledge base."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then select a storage provider."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["On the ",(0,t.jsx)(n.strong,{children:"Add Cloud Knowledge"})," page, click ",(0,t.jsx)(n.strong,{children:"Add Files"}),", and then select the files and folders to ingest from the connected storage."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(n.strong,{children:"Ingest Files"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["The selected files are processed in the background through the ",(0,t.jsx)(n.strong,{children:"OpenSearch Ingestion"})," flow."]}),"\n",(0,t.jsx)(p,{}),"\n",(0,t.jsxs)(n.p,{children:["You can ",(0,t.jsx)(n.a,{href:"#monitor-ingestion",children:"monitor ingestion"})," to see the progress of the uploads and check for failed uploads."]}),"\n",(0,t.jsx)(n.h2,{id:"url-flow",children:"Ingest knowledge from URLs"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"OpenSearch URL Ingestion"})," flow is used to ingest web content from URLs.\nThis flow isn't directly accessible from the OpenRAG user interface.\nInstead, this flow is called by the ",(0,t.jsxs)(n.a,{href:"/chat#flow",children:[(0,t.jsx)(n.strong,{children:"OpenRAG OpenSearch Agent"})," flow"]})," as a Model Context Protocol (MCP) tool.\nThe agent can call this component to fetch web content from a given URL, and then ingest that content into your OpenSearch knowledge base."]}),"\n",(0,t.jsxs)(n.p,{children:["Like all OpenRAG flows, you can ",(0,t.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"inspect the flow in Langflow"}),", and you can customize it."]}),"\n",(0,t.jsxs)(n.p,{children:["For more information about MCP in Langflow, see the Langflow documentation on ",(0,t.jsx)(n.a,{href:"https://docs.langflow.org/mcp-client",children:"MCP clients"})," and ",(0,t.jsx)(n.a,{href:"https://docs.langflow.org/mcp-tutorial",children:"MCP servers"}),"."]}),"\n",(0,t.jsx)(n.h2,{id:"monitor-ingestion",children:"Monitor ingestion"}),"\n",(0,t.jsx)(n.p,{children:"Document ingestion tasks run in the background."}),"\n",(0,t.jsxs)(n.p,{children:["In the OpenRAG user interface, a badge is shown on ",(0,t.jsx)(r.A,{name:"Bell","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Tasks"})," when OpenRAG tasks are active.\nClick ",(0,t.jsx)(r.A,{name:"Bell","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Tasks"})," to inspect and cancel tasks:"]}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Active Tasks"}),": All tasks that are ",(0,t.jsx)(n.strong,{children:"Pending"}),", ",(0,t.jsx)(n.strong,{children:"Running"}),", or ",(0,t.jsx)(n.strong,{children:"Processing"}),".\nFor each active task, depending on its state, you can find the task ID, start time, duration, number of files processed, and the total files enqueued for processing."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Pending"}),": The task is queued and waiting to start."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Running"}),": The task is actively processing files."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Processing"}),": The task is performing ingestion operations."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"Failed"}),": Something went wrong during ingestion, or the task was manually canceled.\nFor troubleshooting advice, see ",(0,t.jsx)(n.a,{href:"#troubleshoot-ingestion",children:"Troubleshoot ingestion"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["To stop an active task, click ",(0,t.jsx)(r.A,{name:"X","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Cancel"}),". Canceling a task stops processing immediately and marks the task as ",(0,t.jsx)(n.strong,{children:"Failed"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"ingestion-performance-expectations",children:"Ingestion performance expectations"}),"\n",(0,t.jsx)(n.p,{children:"The following performance test was conducted with Docling Serve."}),"\n",(0,t.jsx)(n.p,{children:"On a local VM with 7 vCPUs and 8 GiB RAM, OpenRAG ingested approximately 5.03 GB across 1,083 files in about 42 minutes.\nThis equates to approximately 2.4 documents per second."}),"\n",(0,t.jsx)(n.p,{children:"You can generally expect equal or better performance on developer laptops, and significantly faster performance on servers.\nThroughput scales with CPU cores, memory, storage speed, and configuration choices, such as the embedding model, chunk size, overlap, and concurrency."}),"\n",(0,t.jsx)(n.p,{children:"This test returned 12 error, approximately 1.1 percent of the total files ingested.\nAll errors were file-specific, and they didn't stop the pipeline."}),"\n",(0,t.jsxs)(s,{children:[(0,t.jsx)("summary",{children:"Ingestion performance test details"}),(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Ingestion dataset:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Total files: 1,083 items mounted"}),"\n",(0,t.jsx)(n.li,{children:"Total size on disk: 5,026,474,862 bytes (approximately 5.03 GB)"}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Hardware specifications:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Machine: Apple M4 Pro"}),"\n",(0,t.jsxs)(n.li,{children:["Podman VM:","\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Name: podman-machine-default"}),"\n",(0,t.jsx)(n.li,{children:"Type: applehv"}),"\n",(0,t.jsx)(n.li,{children:"vCPUs: 7"}),"\n",(0,t.jsx)(n.li,{children:"Memory: 8 GiB"}),"\n",(0,t.jsx)(n.li,{children:"Disk size: 100 GiB"}),"\n"]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Test results:"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-text",children:"2025-09-24T22:40:45.542190Z /app/src/main.py:231 Ingesting default documents when ready disable_langflow_ingest=False\n2025-09-24T22:40:45.546385Z /app/src/main.py:270 Using Langflow ingestion pipeline for default documents file_count=1082\n...\n2025-09-24T23:19:44.866365Z /app/src/main.py:351 Langflow ingestion completed success_count=1070 error_count=12 total_files=1082\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Elapsed time: Approximately 42 minutes 15 seconds (2,535 seconds)"}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Throughput: Approximately 2.4 documents per second"}),"\n"]}),"\n"]})]}),"\n",(0,t.jsx)(n.h2,{id:"troubleshoot-ingestion",children:"Troubleshoot ingestion"}),"\n",(0,t.jsx)(n.p,{children:"If an ingestion task fails, do the following:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Make sure you are uploading supported file types."}),"\n",(0,t.jsx)(n.li,{children:"Split excessively large files into smaller files before uploading."}),"\n",(0,t.jsx)(n.li,{children:"Remove unusual embedded content, such as videos or animations, before uploading. Although Docling can replace some non-text content with placeholders during ingestion, some embedded content might cause errors."}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["If the OpenRAG ",(0,t.jsx)(n.strong,{children:"Chat"})," doesn't seem to use your documents correctly, ",(0,t.jsx)(n.a,{href:"#browse-knowledge",children:"browse your knowledge base"})," to confirm that the documents are uploaded in full, and the chunks are correct."]}),"\n",(0,t.jsxs)(n.p,{children:["If the documents are present and well-formed, check your ",(0,t.jsx)(n.a,{href:"/knowledge-filters",children:"knowledge filters"}),".\nIf a global filter is applied, make sure the expected documents are included in the global filter.\nIf the global filter excludes any documents, the agent cannot access those documents unless you apply a chat-level filter or change the global filter."]}),"\n",(0,t.jsx)(n.p,{children:"If text is missing or incorrectly processed, you need to reupload the documents after modifying the ingestion parameters or the documents themselves.\nFor example:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:"Break combined documents into separate files for better metadata context."}),"\n",(0,t.jsxs)(n.li,{children:["Make sure scanned documents are legible enough for extraction, and enable the ",(0,t.jsx)(n.strong,{children:"OCR"})," option. Poorly scanned documents might require additional preparation or rescanning before ingestion."]}),"\n",(0,t.jsxs)(n.li,{children:["Adjust the ",(0,t.jsx)(n.strong,{children:"Chunk Size"})," and ",(0,t.jsx)(n.strong,{children:"Chunk Overlap"})," settings to better suit your documents. Larger chunks provide more context but can include irrelevant information, while smaller chunks yield more precise semantic search but can lack context."]}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["For more information about modifying ingestion parameters and flows, see ",(0,t.jsx)(n.a,{href:"/knowledge#knowledge-ingestion-settings",children:"Knowledge ingestion settings"}),"."]}),"\n",(0,t.jsx)(n.h2,{id:"see-also",children:"See also"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"/knowledge",children:"Configure knowledge"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"/knowledge-filters",children:"Filter knowledge"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"/chat",children:"Chat with knowledge"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"/agents#inspect-and-modify-flows",children:"Inspect and modify flows"})}),"\n"]})]})}function m(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(f,{...e})}):f(e)}},8401:(e,n,s)=>{s.d(n,{Ay:()=>c,RM:()=>r});var o=s(4848),t=s(8453),i=s(1610);const r=[];function l(e){const n={p:"p",strong:"strong",...(0,t.R)(),...e.components};return(0,o.jsxs)(n.p,{children:["When using the OpenRAG ",(0,o.jsx)(n.strong,{children:"Chat"}),", click ",(0,o.jsx)(i.A,{name:"Plus","aria-hidden":"true"})," in the chat input field to upload a file to the current chat session.\nFiles added this way are processed and made available to the agent for the current conversation only.\nThese files aren't stored in the knowledge base permanently."]})}function c(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(l,{...e})}):l(e)}}}]); \ No newline at end of file diff --git a/assets/js/common.3a9d628e.js b/assets/js/common.0dd27f1f.js similarity index 69% rename from assets/js/common.3a9d628e.js rename to assets/js/common.0dd27f1f.js index a3d611d2..485dba40 100644 --- a/assets/js/common.3a9d628e.js +++ b/assets/js/common.0dd27f1f.js @@ -1,2 +1,2 @@ -/*! 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lusIcon:()=>im,MessageSquareQuote:()=>om,MessageSquareQuoteIcon:()=>om,MessageSquareReply:()=>cm,MessageSquareReplyIcon:()=>cm,MessageSquareShare:()=>sm,MessageSquareShareIcon:()=>sm,MessageSquareText:()=>hm,MessageSquareTextIcon:()=>hm,MessageSquareWarning:()=>dm,MessageSquareWarningIcon:()=>dm,MessageSquareX:()=>lm,MessageSquareXIcon:()=>lm,MessagesSquare:()=>pm,MessagesSquareIcon:()=>pm,Mic:()=>fm,Mic2:()=>km,Mic2Icon:()=>km,MicIcon:()=>fm,MicOff:()=>ym,MicOffIcon:()=>ym,MicVocal:()=>km,MicVocalIcon:()=>km,Microchip:()=>mm,MicrochipIcon:()=>mm,Microscope:()=>gm,MicroscopeIcon:()=>gm,Microwave:()=>Mm,MicrowaveIcon:()=>Mm,Milestone:()=>vm,MilestoneIcon:()=>vm,Milk:()=>Lm,MilkIcon:()=>Lm,MilkOff:()=>xm,MilkOffIcon:()=>xm,Minimize:()=>Am,Minimize2:()=>wm,Minimize2Icon:()=>wm,MinimizeIcon:()=>Am,Minus:()=>Im,MinusCircle:()=>Yi,MinusCircleIcon:()=>Yi,MinusIcon:()=>Im,MinusSquare:()=>NA,MinusSquareIcon:()=>NA,Monitor:()=>Dm,MonitorCheck:()=>Cm,MonitorCheckIcon:()=>Cm,MonitorCog:()=>bm,MonitorCogIcon:()=>bm,MonitorDot:()=>Sm,MonitorDotIcon:()=>Sm,MonitorDown:()=>Tm,MonitorDownIcon:()=>Tm,MonitorIcon:()=>Dm,MonitorOff:()=>Rm,MonitorOffIcon:()=>Rm,MonitorPause:()=>Pm,MonitorPauseIcon:()=>Pm,MonitorPlay:()=>qm,MonitorPlayIcon:()=>qm,MonitorSmartphone:()=>Em,MonitorSmartphoneIcon:()=>Em,MonitorSpeaker:()=>$m,MonitorSpeakerIcon:()=>$m,MonitorStop:()=>zm,MonitorStopIcon:()=>zm,MonitorUp:()=>Hm,MonitorUpIcon:()=>Hm,MonitorX:()=>Om,MonitorXIcon:()=>Om,Moon:()=>Vm,MoonIcon:()=>Vm,MoonStar:()=>Nm,MoonStarIcon:()=>Nm,MoreHorizontal:()=>xh,MoreHorizontalIcon:()=>xh,MoreVertical:()=>vh,MoreVerticalIcon:()=>vh,Mountain:()=>Bm,MountainIcon:()=>Bm,MountainSnow:()=>jm,MountainSnowIcon:()=>jm,Mouse:()=>Km,MouseIcon:()=>Km,MouseOff:()=>Fm,MouseOffIcon:()=>Fm,MousePointer:()=>Wm,MousePointer2:()=>_m,MousePointer2Icon:()=>_m,MousePointerBan:()=>Um,MousePointerBanIcon:()=>Um,MousePointerClick:()=>Gm,MousePointerClickIcon:()=>Gm,MousePointerIcon:()=>Wm,MousePointerSquareDashed:()=>SA,MousePointerSquareDashedIcon:()=>SA,Move:()=>sg,Move3D:()=>Zm,Move3DIcon:()=>Zm,Move3d:()=>Zm,Move3dIcon:()=>Zm,MoveDiagonal:()=>Ym,MoveDiagonal2:()=>Xm,MoveDiagonal2Icon:()=>Xm,MoveDiagonalIcon:()=>Ym,MoveDown:()=>eg,MoveDownIcon:()=>eg,MoveDownLeft:()=>Qm,MoveDownLeftIcon:()=>Qm,MoveDownRight:()=>Jm,MoveDownRightIcon:()=>Jm,MoveHorizontal:()=>tg,MoveHorizontalIcon:()=>tg,MoveIcon:()=>sg,MoveLeft:()=>ag,MoveLeftIcon:()=>ag,MoveRight:()=>rg,MoveRightIcon:()=>rg,MoveUp:()=>og,MoveUpIcon:()=>og,MoveUpLeft:()=>ng,MoveUpLeftIcon:()=>ng,MoveUpRight:()=>ig,MoveUpRightIcon:()=>ig,MoveVertical:()=>cg,MoveVerticalIcon:()=>cg,Music:()=>ug,Music2:()=>hg,Music2Icon:()=>hg,Music3:()=>dg,Music3Icon:()=>dg,Music4:()=>lg,Music4Icon:()=>lg,MusicIcon:()=>ug,Navigation:()=>fg,Navigation2:()=>yg,Navigation2Icon:()=>yg,Navigation2Off:()=>pg,Navigation2OffIcon:()=>pg,NavigationIcon:()=>fg,NavigationOff:()=>kg,NavigationOffIcon:()=>kg,Network:()=>mg,NetworkIcon:()=>mg,Newspaper:()=>gg,NewspaperIcon:()=>gg,Nfc:()=>Mg,NfcIcon:()=>Mg,NonBinary:()=>vg,NonBinaryIcon:()=>vg,Notebook:()=>Ag,NotebookIcon:()=>Ag,NotebookPen:()=>xg,NotebookPenIcon:()=>xg,NotebookTabs:()=>Lg,NotebookTabsIcon:()=>Lg,NotebookText:()=>wg,NotebookTextIcon:()=>wg,NotepadText:()=>Cg,NotepadTextDashed:()=>Ig,NotepadTextDashedIcon:()=>Ig,NotepadTextIcon:()=>Cg,Nut:()=>Sg,NutIcon:()=>Sg,NutOff:()=>bg,NutOffIcon:()=>bg,Octagon:()=>Eg,OctagonAlert:()=>Tg,OctagonAlertIcon:()=>Tg,OctagonIcon:()=>Eg,OctagonMinus:()=>Rg,OctagonMinusIcon:()=>Rg,OctagonPause:()=>Pg,OctagonPauseIcon:()=>Pg,OctagonX:()=>qg,OctagonXIcon:()=>qg,Omega:()=>$g,OmegaIcon:()=>$g,Option:()=>zg,OptionIcon:()=>zg,Orbit:()=>Hg,OrbitIcon:()=>Hg,Origami:()=>Og,OrigamiIcon:()=>Og,Outdent:()=>Ik,OutdentIcon:()=>Ik,Package:()=>Ug,Package2:()=>Dg,Package2Icon:()=>Dg,PackageCheck:()=>Ng,PackageCheckIcon:()=>Ng,PackageIcon:()=>Ug,PackageMinus:()=>Vg,PackageMinusIcon:()=>Vg,PackageOpen:()=>jg,PackageOpenIcon:()=>jg,PackagePlus:()=>Fg,PackagePlusIcon:()=>Fg,PackageSearch:()=>Bg,PackageSearchIcon:()=>Bg,PackageX:()=>_g,PackageXIcon:()=>_g,PaintBucket:()=>Gg,PaintBucketIcon:()=>Gg,PaintRoller:()=>Wg,PaintRollerIcon:()=>Wg,Paintbrush:()=>Zg,Paintbrush2:()=>Kg,Paintbrush2Icon:()=>Kg,PaintbrushIcon:()=>Zg,PaintbrushVertical:()=>Kg,PaintbrushVerticalIcon:()=>Kg,Palette:()=>Xg,PaletteIcon:()=>Xg,Palmtree:()=>fb,PalmtreeIcon:()=>fb,Panda:()=>Yg,PandaIcon:()=>Yg,PanelBottom:()=>tM,PanelBottomClose:()=>Qg,PanelBottomCloseIcon:()=>Qg,PanelBottomDashed:()=>Jg,PanelBottomDashedIcon:()=>Jg,PanelBottomIcon:()=>tM,PanelBottomInactive:()=>Jg,PanelBottomInactiveIcon:()=>Jg,PanelBottomOpen:()=>eM,PanelBottomOpenIcon:()=>eM,PanelLeft:()=>oM,PanelLeftClose:()=>aM,PanelLeftCloseIcon:()=>aM,PanelLeftDashed:()=>rM,PanelLeftDashedIcon:()=>rM,PanelLeftIcon:()=>oM,PanelLeftInactive:()=>rM,PanelLeftInactiveIcon:()=>rM,PanelLeftOpen:()=>nM,PanelLeftOpenIcon:()=>nM,PanelLeftRightDashed:()=>iM,PanelLeftRightDashedIcon:()=>iM,PanelRight:()=>dM,PanelRightClose:()=>cM,PanelRightCloseIcon:()=>cM,PanelRightDashed:()=>sM,PanelRightDashedIcon:()=>sM,PanelRightIcon:()=>dM,PanelRightInactive:()=>sM,PanelRightInactiveIcon:()=>sM,PanelRightOpen:()=>hM,PanelRightOpenIcon:()=>hM,PanelTop:()=>kM,PanelTopBottomDashed:()=>uM,PanelTopBottomDashedIcon:()=>uM,PanelTopClose:()=>lM,PanelTopCloseIcon:()=>lM,PanelTopDashed:()=>pM,PanelTopDashedIcon:()=>pM,PanelTopIcon:()=>kM,PanelTopInactive:()=>pM,PanelTopInactiveIcon:()=>pM,PanelTopOpen:()=>yM,PanelTopOpenIcon:()=>yM,PanelsLeftBottom:()=>fM,PanelsLeftBottomIcon:()=>fM,PanelsLeftRight:()=>Sc,PanelsLeftRightIcon:()=>Sc,PanelsRightBottom:()=>mM,PanelsRightBottomIcon:()=>mM,PanelsTopBottom:()=>Vx,PanelsTopBottomIcon:()=>Vx,PanelsTopLeft:()=>MM,PanelsTopLeftIcon:()=>MM,Paperclip:()=>gM,PaperclipIcon:()=>gM,Parentheses:()=>vM,ParenthesesIcon:()=>vM,ParkingCircle:()=>eo,ParkingCircleIcon:()=>eo,ParkingCircleOff:()=>Ji,ParkingCircleOffIcon:()=>Ji,ParkingMeter:()=>xM,ParkingMeterIcon:()=>xM,ParkingSquare:()=>FA,ParkingSquareIcon:()=>FA,ParkingSquareOff:()=>jA,ParkingSquareOffIcon:()=>jA,PartyPopper:()=>LM,PartyPopperIcon:()=>LM,Pause:()=>wM,PauseCircle:()=>to,PauseCircleIcon:()=>to,PauseIcon:()=>wM,PauseOctagon:()=>Pg,PauseOctagonIcon:()=>Pg,PawPrint:()=>AM,PawPrintIcon:()=>AM,PcCase:()=>IM,PcCaseIcon:()=>IM,Pen:()=>TM,PenBox:()=>_A,PenBoxIcon:()=>_A,PenIcon:()=>TM,PenLine:()=>CM,PenLineIcon:()=>CM,PenOff:()=>SM,PenOffIcon:()=>SM,PenSquare:()=>_A,PenSquareIcon:()=>_A,PenTool:()=>bM,PenToolIcon:()=>bM,Pencil:()=>EM,PencilIcon:()=>EM,PencilLine:()=>PM,PencilLineIcon:()=>PM,PencilOff:()=>RM,PencilOffIcon:()=>RM,PencilRuler:()=>qM,PencilRulerIcon:()=>qM,Pentagon:()=>zM,PentagonIcon:()=>zM,Percent:()=>$M,PercentCircle:()=>ao,PercentCircleIcon:()=>ao,PercentDiamond:()=>Ss,PercentDiamondIcon:()=>Ss,PercentIcon:()=>$M,PercentSquare:()=>UA,PercentSquareIcon:()=>UA,PersonStanding:()=>HM,PersonStandingIcon:()=>HM,PhilippinePeso:()=>OM,PhilippinePesoIcon:()=>OM,Phone:()=>_M,PhoneCall:()=>DM,PhoneCallIcon:()=>DM,PhoneForwarded:()=>NM,PhoneForwardedIcon:()=>NM,PhoneIcon:()=>_M,PhoneIncoming:()=>VM,PhoneIncomingIcon:()=>VM,PhoneMissed:()=>jM,PhoneMissedIcon:()=>jM,PhoneOff:()=>FM,PhoneOffIcon:()=>FM,PhoneOutgoing:()=>BM,PhoneOutgoingIcon:()=>BM,Pi:()=>UM,PiIcon:()=>UM,PiSquare:()=>GA,PiSquareIcon:()=>GA,Piano:()=>GM,PianoIcon:()=>GM,Pickaxe:()=>WM,PickaxeIcon:()=>WM,PictureInPicture:()=>ZM,PictureInPicture2:()=>KM,PictureInPicture2Icon:()=>KM,PictureInPictureIcon:()=>ZM,PieChart:()=>Jn,PieChartIcon:()=>Jn,PiggyBank:()=>XM,PiggyBankIcon:()=>XM,Pilcrow:()=>ev,PilcrowIcon:()=>ev,PilcrowLeft:()=>YM,PilcrowLeftIcon:()=>YM,PilcrowRight:()=>QM,PilcrowRightIcon:()=>QM,PilcrowSquare:()=>WA,PilcrowSquareIcon:()=>WA,Pill:()=>tv,PillBottle:()=>JM,PillBottleIcon:()=>JM,PillIcon:()=>tv,Pin:()=>rv,PinIcon:()=>rv,PinOff:()=>av,PinOffIcon:()=>av,Pipette:()=>nv,PipetteIcon:()=>nv,Pizza:()=>iv,PizzaIcon:()=>iv,Plane:()=>hv,PlaneIcon:()=>hv,PlaneLanding:()=>ov,PlaneLandingIcon:()=>ov,PlaneTakeoff:()=>cv,PlaneTakeoffIcon:()=>cv,Play:()=>sv,PlayCircle:()=>ro,PlayCircleIcon:()=>ro,PlayIcon:()=>sv,PlaySquare:()=>ZA,PlaySquareIcon:()=>ZA,Plug:()=>uv,Plug2:()=>dv,Plug2Icon:()=>dv,PlugIcon:()=>uv,PlugZap:()=>lv,PlugZap2:()=>lv,PlugZap2Icon:()=>lv,PlugZapIcon:()=>lv,Plus:()=>pv,PlusCircle:()=>no,PlusCircleIcon:()=>no,PlusIcon:()=>pv,PlusSquare:()=>KA,PlusSquareIcon:()=>KA,Pocket:()=>kv,PocketIcon:()=>kv,PocketKnife:()=>yv,PocketKnifeIcon:()=>yv,Podcast:()=>fv,PodcastIcon:()=>fv,Pointer:()=>gv,PointerIcon:()=>gv,PointerOff:()=>mv,PointerOffIcon:()=>mv,Popcorn:()=>Mv,PopcornIcon:()=>Mv,Popsicle:()=>vv,PopsicleIcon:()=>vv,PoundSterling:()=>Lv,PoundSterlingIcon:()=>Lv,Power:()=>Av,PowerCircle:()=>oo,PowerCircleIcon:()=>oo,PowerIcon:()=>Av,PowerOff:()=>xv,PowerOffIcon:()=>xv,PowerSquare:()=>XA,PowerSquareIcon:()=>XA,Presentation:()=>wv,PresentationIcon:()=>wv,Printer:()=>Cv,PrinterCheck:()=>Iv,PrinterCheckIcon:()=>Iv,PrinterIcon:()=>Cv,Projector:()=>bv,ProjectorIcon:()=>bv,Proportions:()=>Sv,ProportionsIcon:()=>Sv,Puzzle:()=>Tv,PuzzleIcon:()=>Tv,Pyramid:()=>Rv,PyramidIcon:()=>Rv,QrCode:()=>Pv,QrCodeIcon:()=>Pv,Quote:()=>qv,QuoteIcon:()=>qv,Rabbit:()=>Ev,RabbitIcon:()=>Ev,Radar:()=>$v,RadarIcon:()=>$v,Radiation:()=>zv,RadiationIcon:()=>zv,Radical:()=>Hv,RadicalIcon:()=>Hv,Radio:()=>Vv,RadioIcon:()=>Vv,RadioReceiver:()=>Dv,RadioReceiverIcon:()=>Dv,RadioTower:()=>Ov,RadioTowerIcon:()=>Ov,Radius:()=>Nv,RadiusIcon:()=>Nv,RailSymbol:()=>jv,RailSymbolIcon:()=>jv,Rainbow:()=>Fv,RainbowIcon:()=>Fv,Rat:()=>Bv,RatIcon:()=>Bv,Ratio:()=>_v,RatioIcon:()=>_v,Receipt:()=>ex,ReceiptCent:()=>Uv,ReceiptCentIcon:()=>Uv,ReceiptEuro:()=>Gv,ReceiptEuroIcon:()=>Gv,ReceiptIcon:()=>ex,ReceiptIndianRupee:()=>Wv,ReceiptIndianRupeeIcon:()=>Wv,ReceiptJapaneseYen:()=>Kv,ReceiptJapaneseYenIcon:()=>Kv,ReceiptPoundSterling:()=>Zv,ReceiptPoundSterlingIcon:()=>Zv,ReceiptRussianRuble:()=>Xv,ReceiptRussianRubleIcon:()=>Xv,ReceiptSwissFranc:()=>Yv,ReceiptSwissFrancIcon:()=>Yv,ReceiptText:()=>Jv,ReceiptTextIcon:()=>Jv,ReceiptTurkishLira:()=>Qv,ReceiptTurkishLiraIcon:()=>Qv,RectangleCircle:()=>tx,RectangleCircleIcon:()=>tx,RectangleEllipsis:()=>ax,RectangleEllipsisIcon:()=>ax,RectangleGoggles:()=>rx,RectangleGogglesIcon:()=>rx,RectangleHorizontal:()=>nx,RectangleHorizontalIcon:()=>nx,RectangleVertical:()=>ix,RectangleVerticalIcon:()=>ix,Recycle:()=>ox,RecycleIcon:()=>ox,Redo:()=>hx,Redo2:()=>cx,Redo2Icon:()=>cx,RedoDot:()=>sx,RedoDotIcon:()=>sx,RedoIcon:()=>hx,RefreshCcw:()=>lx,RefreshCcwDot:()=>dx,RefreshCcwDotIcon:()=>dx,RefreshCcwIcon:()=>lx,RefreshCw:()=>px,RefreshCwIcon:()=>px,RefreshCwOff:()=>ux,RefreshCwOffIcon:()=>ux,Refrigerator:()=>yx,RefrigeratorIcon:()=>yx,Regex:()=>kx,RegexIcon:()=>kx,RemoveFormatting:()=>fx,RemoveFormattingIcon:()=>fx,Repeat:()=>gx,Repeat1:()=>Mx,Repeat1Icon:()=>Mx,Repeat2:()=>mx,Repeat2Icon:()=>mx,RepeatIcon:()=>gx,Replace:()=>Lx,ReplaceAll:()=>vx,ReplaceAllIcon:()=>vx,ReplaceIcon:()=>Lx,Reply:()=>wx,ReplyAll:()=>xx,ReplyAllIcon:()=>xx,ReplyIcon:()=>wx,Rewind:()=>Ax,RewindIcon:()=>Ax,Ribbon:()=>Ix,RibbonIcon:()=>Ix,Rocket:()=>Cx,RocketIcon:()=>Cx,RockingChair:()=>bx,RockingChairIcon:()=>bx,RollerCoaster:()=>Sx,RollerCoasterIcon:()=>Sx,Rose:()=>Tx,RoseIcon:()=>Tx,Rotate3D:()=>Rx,Rotate3DIcon:()=>Rx,Rotate3d:()=>Rx,Rotate3dIcon:()=>Rx,RotateCcw:()=>Ex,RotateCcwIcon:()=>Ex,RotateCcwKey:()=>Px,RotateCcwKeyIcon:()=>Px,RotateCcwSquare:()=>qx,RotateCcwSquareIcon:()=>qx,RotateCw:()=>zx,RotateCwIcon:()=>zx,RotateCwSquare:()=>$x,RotateCwSquareIcon:()=>$x,Route:()=>Ox,RouteIcon:()=>Ox,RouteOff:()=>Hx,RouteOffIcon:()=>Hx,Router:()=>Nx,RouterIcon:()=>Nx,Rows:()=>Dx,Rows2:()=>Dx,Rows2Icon:()=>Dx,Rows3:()=>Vx,Rows3Icon:()=>Vx,Rows4:()=>jx,Rows4Icon:()=>jx,RowsIcon:()=>Dx,Rss:()=>Fx,RssIcon:()=>Fx,Ruler:()=>_x,RulerDimensionLine:()=>Bx,RulerDimensionLineIcon:()=>Bx,RulerIcon:()=>_x,RussianRuble:()=>Gx,RussianRubleIcon:()=>Gx,Sailboat:()=>Ux,SailboatIcon:()=>Ux,Salad:()=>Wx,SaladIcon:()=>Wx,Sandwich:()=>Kx,SandwichIcon:()=>Kx,Satellite:()=>Yx,SatelliteDish:()=>Zx,SatelliteDishIcon:()=>Zx,SatelliteIcon:()=>Yx,SaudiRiyal:()=>Xx,SaudiRiyalIcon:()=>Xx,Save:()=>eL,SaveAll:()=>Qx,SaveAllIcon:()=>Qx,SaveIcon:()=>eL,SaveOff:()=>Jx,SaveOffIcon:()=>Jx,Scale:()=>aL,Scale3D:()=>tL,Scale3DIcon:()=>tL,Scale3d:()=>tL,Scale3dIcon:()=>tL,ScaleIcon:()=>aL,Scaling:()=>rL,ScalingIcon:()=>rL,Scan:()=>uL,ScanBarcode:()=>nL,ScanBarcodeIcon:()=>nL,ScanEye:()=>iL,ScanEyeIcon:()=>iL,ScanFace:()=>oL,ScanFaceIcon:()=>oL,ScanHeart:()=>cL,ScanHeartIcon:()=>cL,ScanIcon:()=>uL,ScanLine:()=>sL,ScanLineIcon:()=>sL,ScanQrCode:()=>hL,ScanQrCodeIcon:()=>hL,ScanSearch:()=>dL,ScanSearchIcon:()=>dL,ScanText:()=>lL,ScanTextIcon:()=>lL,ScatterChart:()=>ei,ScatterChartIcon:()=>ei,School:()=>pL,School2:()=>Zb,School2Icon:()=>Zb,SchoolIcon:()=>pL,Scissors:()=>kL,ScissorsIcon:()=>kL,ScissorsLineDashed:()=>yL,ScissorsLineDashedIcon:()=>yL,ScissorsSquare:()=>eI,ScissorsSquareDashedBottom:()=>fA,ScissorsSquareDashedBottomIcon:()=>fA,ScissorsSquareIcon:()=>eI,ScreenShare:()=>mL,ScreenShareIcon:()=>mL,ScreenShareOff:()=>fL,ScreenShareOffIcon:()=>fL,Scroll:()=>ML,ScrollIcon:()=>ML,ScrollText:()=>gL,ScrollTextIcon:()=>gL,Search:()=>AL,SearchCheck:()=>vL,SearchCheckIcon:()=>vL,SearchCode:()=>xL,SearchCodeIcon:()=>xL,SearchIcon:()=>AL,SearchSlash:()=>LL,SearchSlashIcon:()=>LL,SearchX:()=>wL,SearchXIcon:()=>wL,Section:()=>IL,SectionIcon:()=>IL,Send:()=>SL,SendHorizonal:()=>CL,SendHorizonalIcon:()=>CL,SendHorizontal:()=>CL,SendHorizontalIcon:()=>CL,SendIcon:()=>SL,SendToBack:()=>bL,SendToBackIcon:()=>bL,SeparatorHorizontal:()=>TL,SeparatorHorizontalIcon:()=>TL,SeparatorVertical:()=>RL,SeparatorVerticalIcon:()=>RL,Server:()=>$L,ServerCog:()=>PL,ServerCogIcon:()=>PL,ServerCrash:()=>qL,ServerCrashIcon:()=>qL,ServerIcon:()=>$L,ServerOff:()=>EL,ServerOffIcon:()=>EL,Settings:()=>zL,Settings2:()=>HL,Settings2Icon:()=>HL,SettingsIcon:()=>zL,Shapes:()=>NL,ShapesIcon:()=>NL,Share:()=>DL,Share2:()=>OL,Share2Icon:()=>OL,ShareIcon:()=>DL,Sheet:()=>VL,SheetIcon:()=>VL,Shell:()=>jL,ShellIcon:()=>jL,Shield:()=>JL,ShieldAlert:()=>FL,ShieldAlertIcon:()=>FL,ShieldBan:()=>BL,ShieldBanIcon:()=>BL,ShieldCheck:()=>_L,ShieldCheckIcon:()=>_L,ShieldClose:()=>QL,ShieldCloseIcon:()=>QL,ShieldEllipsis:()=>UL,ShieldEllipsisIcon:()=>UL,ShieldHalf:()=>GL,ShieldHalfIcon:()=>GL,ShieldIcon:()=>JL,ShieldMinus:()=>WL,ShieldMinusIcon:()=>WL,ShieldOff:()=>KL,ShieldOffIcon:()=>KL,ShieldPlus:()=>ZL,ShieldPlusIcon:()=>ZL,ShieldQuestion:()=>XL,ShieldQuestionIcon:()=>XL,ShieldQuestionMark:()=>XL,ShieldQuestionMarkIcon:()=>XL,ShieldUser:()=>YL,ShieldUserIcon:()=>YL,ShieldX:()=>QL,ShieldXIcon:()=>QL,Ship:()=>tw,ShipIcon:()=>tw,ShipWheel:()=>ew,ShipWheelIcon:()=>ew,Shirt:()=>aw,ShirtIcon:()=>aw,ShoppingBag:()=>rw,ShoppingBagIcon:()=>rw,ShoppingBasket:()=>nw,ShoppingBasketIcon:()=>nw,ShoppingCart:()=>iw,ShoppingCartIcon:()=>iw,Shovel:()=>ow,ShovelIcon:()=>ow,ShowerHead:()=>cw,ShowerHeadIcon:()=>cw,Shredder:()=>sw,ShredderIcon:()=>sw,Shrimp:()=>hw,ShrimpIcon:()=>hw,Shrink:()=>dw,ShrinkIcon:()=>dw,Shrub:()=>lw,ShrubIcon:()=>lw,Shuffle:()=>uw,ShuffleIco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a=this.computeRuleType(e),r=this.wrapper.DEFINE_RULE(Vt(e.name),this.startImplementation(a,t).bind(this));return this.allRules.set(e.name,r),e.entry&&(this.mainRule=r),r}computeRuleType(e){if(!e.fragment){if((0,n.Xq)(e))return Dt;{const t=(0,n.PV)(e);return null!=t?t:e.name}}}parse(e,t={}){this.nodeBuilder.buildRootNode(e);const a=this.lexerResult=this.lexer.tokenize(e);this.wrapper.input=a.tokens;const r=t.rule?this.allRules.get(t.rule):this.mainRule;if(!r)throw new Error(t.rule?`No rule found with name '${t.rule}'`:"No main rule available.");const n=r.call(this.wrapper,{});return this.nodeBuilder.addHiddenNodes(a.hidden),this.unorderedGroups.clear(),this.lexerResult=void 0,{value:n,lexerErrors:a.errors,lexerReport:a.report,parserErrors:this.wrapper.errors}}startImplementation(e,t){return a=>{const r=!this.isRecording()&&void 0!==e;if(r){const t={$type:e};this.stack.push(t),e===Dt&&(t.value="")}let n;try{n=t(a)}catch(i){n=void 0}return void 0===n&&r&&(n=this.construct()),n}}extractHiddenTokens(e){const t=this.lexerResult.hidden;if(!t.length)return[];const a=e.startOffset;for(let r=0;ra)return t.splice(0,r)}return t.splice(0,t.length)}consume(e,t,a){const r=this.wrapper.wrapConsume(e,t);if(!this.isRecording()&&this.isValidToken(r)){const e=this.extractHiddenTokens(r);this.nodeBuilder.addHiddenNodes(e);const t=this.nodeBuilder.buildLeafNode(r,a),{assignment:n,isCrossRef:i}=this.getAssignment(a),c=this.current;if(n){const e=(0,o.wb)(a)?r.image:this.converter.convert(r.image,t);this.assign(n.operator,n.feature,e,t,i)}else if(Nt(c)){let e=r.image;(0,o.wb)(a)||(e=this.converter.convert(e,t).toString()),c.value+=e}}}isValidToken(e){return!e.isInsertedInRecovery&&!isNaN(e.startOffset)&&"number"==typeof e.endOffset&&!isNaN(e.endOffset)}subrule(e,t,a,r,n){let i;this.isRecording()||a||(i=this.nodeBuilder.buildCompositeNode(r));const o=this.wrapper.wrapSubrule(e,t,n);!this.isRecording()&&i&&i.length>0&&this.performSubruleAssignment(o,r,i)}performSubruleAssignment(e,t,a){const{assignment:r,isCrossRef:n}=this.getAssignment(t);if(r)this.assign(r.operator,r.feature,e,a,n);else if(!r){const t=this.current;if(Nt(t))t.value+=e.toString();else if("object"==typeof e&&e){const a=this.assignWithoutOverride(e,t);this.stack.pop(),this.stack.push(a)}}}action(e,t){if(!this.isRecording()){let a=this.current;if(t.feature&&t.operator){a=this.construct(),this.nodeBuilder.removeNode(a.$cstNode);this.nodeBuilder.buildCompositeNode(t).content.push(a.$cstNode);const r={$type:e};this.stack.push(r),this.assign(t.operator,t.feature,a,a.$cstNode,!1)}else a.$type=e}}construct(){if(this.isRecording())return;const e=this.current;return(0,St.SD)(e),this.nodeBuilder.construct(e),this.stack.pop(),Nt(e)?this.converter.convert(e.value,e.$cstNode):((0,St.OP)(this.astReflection,e),e)}getAssignment(e){if(!this.assignmentMap.has(e)){const t=(0,St.XG)(e,o.wh);this.assignmentMap.set(e,{assignment:t,isCrossRef:!!t&&(0,o._c)(t.terminal)})}return this.assignmentMap.get(e)}assign(e,t,a,r,n){const i=this.current;let o;switch(o=n&&"string"==typeof a?this.linker.buildReference(i,t,r,a):a,e){case"=":i[t]=o;break;case"?=":i[t]=!0;break;case"+=":Array.isArray(i[t])||(i[t]=[]),i[t].push(o)}}assignWithoutOverride(e,t){for(const[r,n]of Object.entries(t)){const t=e[r];void 0===t?e[r]=n:Array.isArray(t)&&Array.isArray(n)&&(n.push(...t),e[r]=n)}const a=e.$cstNode;return a&&(a.astNode=void 0,e.$cstNode=void 0),e}get definitionErrors(){return this.wrapper.definitionErrors}}class Bt{buildMismatchTokenMessage(e){return c.my.buildMismatchTokenMessage(e)}buildNotAllInputParsedMessage(e){return c.my.buildNotAllInputParsedMessage(e)}buildNoViableAltMessage(e){return c.my.buildNoViableAltMessage(e)}buildEarlyExitMessage(e){return c.my.buildEarlyExitMessage(e)}}class _t extends Bt{buildMismatchTokenMessage({expected:e,actual:t}){return`Expecting ${e.LABEL?"`"+e.LABEL+"`":e.name.endsWith(":KW")?`keyword '${e.name.substring(0,e.name.length-3)}'`:`token of type '${e.name}'`} but found \`${t.image}\`.`}buildNotAllInputParsedMessage({firstRedundant:e}){return`Expecting end of file but found \`${e.image}\`.`}}class Ut extends jt{constructor(){super(...arguments),this.tokens=[],this.elementStack=[],this.lastElementStack=[],this.nextTokenIndex=0,this.stackSize=0}action(){}construct(){}parse(e){this.resetState();const t=this.lexer.tokenize(e,{mode:"partial"});return this.tokens=t.tokens,this.wrapper.input=[...this.tokens],this.mainRule.call(this.wrapper,{}),this.unorderedGroups.clear(),{tokens:this.tokens,elementStack:[...this.lastElementStack],tokenIndex:this.nextTokenIndex}}rule(e,t){const a=this.wrapper.DEFINE_RULE(Vt(e.name),this.startImplementation(t).bind(this));return this.allRules.set(e.name,a),e.entry&&(this.mainRule=a),a}resetState(){this.elementStack=[],this.lastElementStack=[],this.nextTokenIndex=0,this.stackSize=0}startImplementation(e){return t=>{const a=this.keepStackSize();try{e(t)}finally{this.resetStackSize(a)}}}removeUnexpectedElements(){this.elementStack.splice(this.stackSize)}keepStackSize(){const e=this.elementStack.length;return this.stackSize=e,e}resetStackSize(e){this.removeUnexpectedElements(),this.stackSize=e}consume(e,t,a){this.wrapper.wrapConsume(e,t),this.isRecording()||(this.lastElementStack=[...this.elementStack,a],this.nextTokenIndex=this.currIdx+1)}subrule(e,t,a,r,n){this.before(r),this.wrapper.wrapSubrule(e,t,n),this.after(r)}before(e){this.isRecording()||this.elementStack.push(e)}after(e){if(!this.isRecording()){const t=this.elementStack.lastIndexOf(e);t>=0&&this.elementStack.splice(t)}}get currIdx(){return this.wrapper.currIdx}}const Gt={recoveryEnabled:!0,nodeLocationTracking:"full",skipValidations:!0,errorMessageProvider:new _t};class Wt extends c.jr{constructor(e,t){const a=t&&"maxLookahead"in t;super(e,Object.assign(Object.assign(Object.assign({},Gt),{lookaheadStrategy:a?new c.T6({maxLookahead:t.maxLookahead}):new B({logging:t.skipValidations?()=>{}:void 0})}),t))}get IS_RECORDING(){return this.RECORDING_PHASE}DEFINE_RULE(e,t){return this.RULE(e,t)}wrapSelfAnalysis(){this.performSelfAnalysis()}wrapConsume(e,t){return this.consume(e,t)}wrapSubrule(e,t,a){return this.subrule(e,t,{ARGS:[a]})}wrapOr(e,t){this.or(e,t)}wrapOption(e,t){this.option(e,t)}wrapMany(e,t){this.many(e,t)}wrapAtLeastOne(e,t){this.atLeastOne(e,t)}}var Kt=a(1564),Zt=a(1719);function Xt(e,t,a){return function(e,t){const a=(0,n.YV)(t,!1),r=(0,Zt.Td)(t.rules).filter(o.s7).filter(e=>a.has(e));for(const n of r){const t=Object.assign(Object.assign({},e),{consume:1,optional:1,subrule:1,many:1,or:1});e.parser.rule(n,Yt(t,n.definition))}}({parser:t,tokens:a,ruleNames:new Map},e),t}function Yt(e,t,a=!1){let r;if((0,o.wb)(t))r=function(e,t){const a=e.consume++,r=e.tokens[t.value];if(!r)throw new Error("Could not find token for keyword: "+t.value);return()=>e.parser.consume(a,r,t)}(e,t);else if((0,o.ve)(t))r=function(e,t){const a=(0,n.Uz)(t);return()=>e.parser.action(a,t)}(e,t);else if((0,o.wh)(t))r=Yt(e,t.terminal);else if((0,o._c)(t))r=ea(e,t);else if((0,o.$g)(t))r=function(e,t){const a=t.rule.ref;if((0,o.s7)(a)){const r=e.subrule++,n=a.fragment,i=t.arguments.length>0?function(e,t){const a=t.map(e=>Qt(e.value));return t=>{const r={};for(let n=0;n({});return o=>e.parser.subrule(r,aa(e,a),n,t,i(o))}if((0,o.rE)(a)){const r=e.consume++,n=ra(e,a.name);return()=>e.parser.consume(r,n,t)}if(!a)throw new Kt.W(t.$cstNode,`Undefined rule: ${t.rule.$refText}`);(0,Kt.d)(a)}(e,t);else if((0,o.jp)(t))r=function(e,t){if(1===t.elements.length)return Yt(e,t.elements[0]);{const a=[];for(const n of t.elements){const t={ALT:Yt(e,n,!0)},r=Jt(n);r&&(t.GATE=Qt(r)),a.push(t)}const r=e.or++;return t=>e.parser.alternatives(r,a.map(e=>{const a={ALT:()=>e.ALT(t)},r=e.GATE;return r&&(a.GATE=()=>r(t)),a}))}}(e,t);else if((0,o.cY)(t))r=function(e,t){if(1===t.elements.length)return Yt(e,t.elements[0]);const a=[];for(const c of t.elements){const t={ALT:Yt(e,c,!0)},r=Jt(c);r&&(t.GATE=Qt(r)),a.push(t)}const r=e.or++,n=(e,t)=>`uGroup_${e}_${t.getRuleStack().join("-")}`,i=t=>e.parser.alternatives(r,a.map((a,i)=>{const o={ALT:()=>!0},c=e.parser;o.ALT=()=>{if(a.ALT(t),!c.isRecording()){const e=n(r,c);c.unorderedGroups.get(e)||c.unorderedGroups.set(e,[]);const t=c.unorderedGroups.get(e);void 0===(null==t?void 0:t[i])&&(t[i]=!0)}};const s=a.GATE;return o.GATE=s?()=>s(t):()=>{const e=c.unorderedGroups.get(n(r,c));return!(null==e?void 0:e[i])},o})),o=ta(e,Jt(t),i,"*");return t=>{o(t),e.parser.isRecording()||e.parser.unorderedGroups.delete(n(r,e.parser))}}(e,t);else if((0,o.IZ)(t))r=function(e,t){const a=t.elements.map(t=>Yt(e,t));return e=>a.forEach(t=>t(e))}(e,t);else{if(!(0,o.FO)(t))throw new Kt.W(t.$cstNode,`Unexpected element type: ${t.$type}`);{const a=e.consume++;r=()=>e.parser.consume(a,c.LT,t)}}return ta(e,a?void 0:Jt(t),r,t.cardinality)}function Qt(e){if((0,o.RP)(e)){const t=Qt(e.left),a=Qt(e.right);return e=>t(e)||a(e)}if((0,o.Tu)(e)){const t=Qt(e.left),a=Qt(e.right);return e=>t(e)&&a(e)}if((0,o.Ct)(e)){const t=Qt(e.value);return e=>!t(e)}if((0,o.TF)(e)){const t=e.parameter.ref.name;return e=>void 0!==e&&!0===e[t]}if((0,o.Cz)(e)){const t=Boolean(e.true);return()=>t}(0,Kt.d)(e)}function Jt(e){if((0,o.IZ)(e))return e.guardCondition}function ea(e,t,a=t.terminal){if(a){if((0,o.$g)(a)&&(0,o.s7)(a.rule.ref)){const r=a.rule.ref,n=e.subrule++;return a=>e.parser.subrule(n,aa(e,r),!1,t,a)}if((0,o.$g)(a)&&(0,o.rE)(a.rule.ref)){const r=e.consume++,n=ra(e,a.rule.ref.name);return()=>e.parser.consume(r,n,t)}if((0,o.wb)(a)){const r=e.consume++,n=ra(e,a.value);return()=>e.parser.consume(r,n,t)}throw new Error("Could not build cross reference parser")}{if(!t.type.ref)throw new Error("Could not resolve reference to type: "+t.type.$refText);const a=(0,n.U5)(t.type.ref),r=null==a?void 0:a.terminal;if(!r)throw new Error("Could not find name assignment for type: "+(0,n.Uz)(t.type.ref));return ea(e,t,r)}}function ta(e,t,a,r){const n=t&&Qt(t);if(!r){if(n){const t=e.or++;return r=>e.parser.alternatives(t,[{ALT:()=>a(r),GATE:()=>n(r)},{ALT:(0,c.mT)(),GATE:()=>!n(r)}])}return a}if("*"===r){const t=e.many++;return r=>e.parser.many(t,{DEF:()=>a(r),GATE:n?()=>n(r):void 0})}if("+"===r){const t=e.many++;if(n){const r=e.or++;return i=>e.parser.alternatives(r,[{ALT:()=>e.parser.atLeastOne(t,{DEF:()=>a(i)}),GATE:()=>n(i)},{ALT:(0,c.mT)(),GATE:()=>!n(i)}])}return r=>e.parser.atLeastOne(t,{DEF:()=>a(r)})}if("?"===r){const t=e.optional++;return r=>e.parser.optional(t,{DEF:()=>a(r),GATE:n?()=>n(r):void 0})}(0,Kt.d)(r)}function aa(e,t){const a=function(e,t){if((0,o.s7)(t))return t.name;if(e.ruleNames.has(t))return e.ruleNames.get(t);{let a=t,r=a.$container,n=t.$type;for(;!(0,o.s7)(r);){if((0,o.IZ)(r)||(0,o.jp)(r)||(0,o.cY)(r)){n=r.elements.indexOf(a).toString()+":"+n}a=r,r=r.$container}return n=r.name+":"+n,e.ruleNames.set(t,n),n}}(e,t),r=e.parser.getRule(a);if(!r)throw new Error(`Rule "${a}" not found."`);return r}function ra(e,t){const a=e.tokens[t];if(!a)throw new Error(`Token "${t}" not found."`);return a}function na(e){const t=function(e){const t=e.Grammar,a=e.parser.Lexer,r=new Ft(e);return Xt(t,r,a.definition)}(e);return t.finalize(),t}var ia=a(1945),oa=a(5033),ca=a(9850),sa=a(2479);let ha=0,da=10;const la=Symbol("OperationCancelled");function ua(e){return e===la}async function pa(e){if(e===ca.XO.None)return;const t=performance.now();if(t-ha>=da&&(ha=t,await new Promise(e=>{"undefined"==typeof setImmediate?setTimeout(e,0):setImmediate(e)}),ha=performance.now()),e.isCancellationRequested)throw la}class ya{constructor(){this.promise=new Promise((e,t)=>{this.resolve=t=>(e(t),this),this.reject=e=>(t(e),this)})}}class ka{constructor(e,t,a,r){this._uri=e,this._languageId=t,this._version=a,this._content=r,this._lineOffsets=void 0}get uri(){return this._uri}get languageId(){return this._languageId}get version(){return this._version}getText(e){if(e){const t=this.offsetAt(e.start),a=this.offsetAt(e.end);return this._content.substring(t,a)}return this._content}update(e,t){for(const a of e)if(ka.isIncremental(a)){const e=va(a.range),t=this.offsetAt(e.start),r=this.offsetAt(e.end);this._content=this._content.substring(0,t)+a.text+this._content.substring(r,this._content.length);const n=Math.max(e.start.line,0),i=Math.max(e.end.line,0);let o=this._lineOffsets;const c=ga(a.text,!1,t);if(i-n===c.length)for(let a=0,h=c.length;ae?r=n:a=n+1}const n=a-1;return{line:n,character:(e=this.ensureBeforeEOL(e,t[n]))-t[n]}}offsetAt(e){const t=this.getLineOffsets();if(e.line>=t.length)return this._content.length;if(e.line<0)return 0;const a=t[e.line];if(e.character<=0)return a;const r=e.line+1t&&Ma(this._content.charCodeAt(e-1));)e--;return e}get lineCount(){return this.getLineOffsets().length}static isIncremental(e){const t=e;return null!=t&&"string"==typeof t.text&&void 0!==t.range&&(void 0===t.rangeLength||"number"==typeof t.rangeLength)}static isFull(e){const t=e;return null!=t&&"string"==typeof t.text&&void 0===t.range&&void 0===t.rangeLength}}var fa;function ma(e,t){if(e.length<=1)return e;const a=e.length/2|0,r=e.slice(0,a),n=e.slice(a);ma(r,t),ma(n,t);let i=0,o=0,c=0;for(;ia.line||t.line===a.line&&t.character>a.character?{start:a,end:t}:e}function xa(e){const t=va(e.range);return t!==e.range?{newText:e.newText,range:t}:e}!function(e){e.create=function(e,t,a,r){return new ka(e,t,a,r)},e.update=function(e,t,a){if(e instanceof ka)return e.update(t,a),e;throw new Error("TextDocument.update: document must be created by TextDocument.create")},e.applyEdits=function(e,t){const a=e.getText(),r=ma(t.map(xa),(e,t)=>{const a=e.range.start.line-t.range.start.line;return 0===a?e.range.start.character-t.range.start.character:a});let n=0;const i=[];for(const o of r){const t=e.offsetAt(o.range.start);if(tn&&i.push(a.substring(n,t)),o.newText.length&&i.push(o.newText),n=e.offsetAt(o.range.end)}return i.push(a.substr(n)),i.join("")}}(fa||(fa={}));var La,wa=a(7608);!function(e){e[e.Changed=0]="Changed",e[e.Parsed=1]="Parsed",e[e.IndexedContent=2]="IndexedContent",e[e.ComputedScopes=3]="ComputedScopes",e[e.Linked=4]="Linked",e[e.IndexedReferences=5]="IndexedReferences",e[e.Validated=6]="Validated"}(La||(La={}));class Aa{constructor(e){this.serviceRegistry=e.ServiceRegistry,this.textDocuments=e.workspace.TextDocuments,this.fileSystemProvider=e.workspace.FileSystemProvider}async fromUri(e,t=ca.XO.None){const a=await this.fileSystemProvider.readFile(e);return this.createAsync(e,a,t)}fromTextDocument(e,t,a){return t=null!=t?t:wa.r.parse(e.uri),ca.XO.is(a)?this.createAsync(t,e,a):this.create(t,e,a)}fromString(e,t,a){return ca.XO.is(a)?this.createAsync(t,e,a):this.create(t,e,a)}fromModel(e,t){return this.create(t,{$model:e})}create(e,t,a){if("string"==typeof t){const r=this.parse(e,t,a);return this.createLangiumDocument(r,e,void 0,t)}if("$model"in t){const a={value:t.$model,parserErrors:[],lexerErrors:[]};return this.createLangiumDocument(a,e)}{const r=this.parse(e,t.getText(),a);return this.createLangiumDocument(r,e,t)}}async createAsync(e,t,a){if("string"==typeof t){const r=await this.parseAsync(e,t,a);return this.createLangiumDocument(r,e,void 0,t)}{const r=await this.parseAsync(e,t.getText(),a);return this.createLangiumDocument(r,e,t)}}createLangiumDocument(e,t,a,r){let n;if(a)n={parseResult:e,uri:t,state:La.Parsed,references:[],textDocument:a};else{const a=this.createTextDocumentGetter(t,r);n={parseResult:e,uri:t,state:La.Parsed,references:[],get textDocument(){return a()}}}return e.value.$document=n,n}async update(e,t){var a,r;const n=null===(a=e.parseResult.value.$cstNode)||void 0===a?void 0:a.root.fullText,i=null===(r=this.textDocuments)||void 0===r?void 0:r.get(e.uri.toString()),o=i?i.getText():await this.fileSystemProvider.readFile(e.uri);if(i)Object.defineProperty(e,"textDocument",{value:i});else{const t=this.createTextDocumentGetter(e.uri,o);Object.defineProperty(e,"textDocument",{get:t})}return n!==o&&(e.parseResult=await this.parseAsync(e.uri,o,t),e.parseResult.value.$document=e),e.state=La.Parsed,e}parse(e,t,a){return this.serviceRegistry.getServices(e).parser.LangiumParser.parse(t,a)}parseAsync(e,t,a){return this.serviceRegistry.getServices(e).parser.AsyncParser.parse(t,a)}createTextDocumentGetter(e,t){const a=this.serviceRegistry;let r;return()=>null!=r?r:r=fa.create(e.toString(),a.getServices(e).LanguageMetaData.languageId,0,null!=t?t:"")}}class Ia{constructor(e){this.documentMap=new Map,this.langiumDocumentFactory=e.workspace.LangiumDocumentFactory,this.serviceRegistry=e.ServiceRegistry}get all(){return(0,Zt.Td)(this.documentMap.values())}addDocument(e){const t=e.uri.toString();if(this.documentMap.has(t))throw new Error(`A document with the URI '${t}' is already present.`);this.documentMap.set(t,e)}getDocument(e){const t=e.toString();return this.documentMap.get(t)}async getOrCreateDocument(e,t){let a=this.getDocument(e);return a||(a=await this.langiumDocumentFactory.fromUri(e,t),this.addDocument(a),a)}createDocument(e,t,a){if(a)return this.langiumDocumentFactory.fromString(t,e,a).then(e=>(this.addDocument(e),e));{const a=this.langiumDocumentFactory.fromString(t,e);return this.addDocument(a),a}}hasDocument(e){return this.documentMap.has(e.toString())}invalidateDocument(e){const t=e.toString(),a=this.documentMap.get(t);if(a){this.serviceRegistry.getServices(e).references.Linker.unlink(a),a.state=La.Changed,a.precomputedScopes=void 0,a.diagnostics=void 0}return a}deleteDocument(e){const t=e.toString(),a=this.documentMap.get(t);return a&&(a.state=La.Changed,this.documentMap.delete(t)),a}}const Ca=Symbol("ref_resolving");class ba{constructor(e){this.reflection=e.shared.AstReflection,this.langiumDocuments=()=>e.shared.workspace.LangiumDocuments,this.scopeProvider=e.references.ScopeProvider,this.astNodeLocator=e.workspace.AstNodeLocator}async link(e,t=ca.XO.None){for(const a of(0,St.jm)(e.parseResult.value))await pa(t),(0,St.DM)(a).forEach(t=>this.doLink(t,e))}doLink(e,t){var a;const r=e.reference;if(void 0===r._ref){r._ref=Ca;try{const t=this.getCandidate(e);if((0,sa.Zl)(t))r._ref=t;else if(r._nodeDescription=t,this.langiumDocuments().hasDocument(t.documentUri)){const a=this.loadAstNode(t);r._ref=null!=a?a:this.createLinkingError(e,t)}else r._ref=void 0}catch(n){console.error(`An error occurred while resolving reference to '${r.$refText}':`,n);const t=null!==(a=n.message)&&void 0!==a?a:String(n);r._ref=Object.assign(Object.assign({},e),{message:`An error occurred while resolving reference to '${r.$refText}': ${t}`})}t.references.push(r)}}unlink(e){for(const t of e.references)delete t._ref,delete t._nodeDescription;e.references=[]}getCandidate(e){const t=this.scopeProvider.getScope(e).getElement(e.reference.$refText);return null!=t?t:this.createLinkingError(e)}buildReference(e,t,a,r){const n=this,i={$refNode:a,$refText:r,get ref(){var a;if((0,sa.ng)(this._ref))return this._ref;if((0,sa.Nr)(this._nodeDescription)){const a=n.loadAstNode(this._nodeDescription);this._ref=null!=a?a:n.createLinkingError({reference:i,container:e,property:t},this._nodeDescription)}else if(void 0===this._ref){this._ref=Ca;const r=(0,St.cQ)(e).$document,o=n.getLinkedNode({reference:i,container:e,property:t});if(o.error&&r&&r.statee.length>0),i=r.split("/").filter(e=>e.length>0);let o=0;for(;o=e.end)return t.ref}if(a){const t=this.nameProvider.getNameNode(a);if(t&&(t===e||(0,r.pO)(e,t)))return a}}}findDeclarationNode(e){const t=this.findDeclaration(e);if(null==t?void 0:t.$cstNode){const e=this.nameProvider.getNameNode(t);return null!=e?e:t.$cstNode}}findReferences(e,t){const a=[];if(t.includeDeclaration){const t=this.getReferenceToSelf(e);t&&a.push(t)}let r=this.index.findAllReferences(e,this.nodeLocator.getAstNodePath(e));return t.documentUri&&(r=r.filter(e=>Ta.equals(e.sourceUri,t.documentUri))),a.push(...r),(0,Zt.Td)(a)}getReferenceToSelf(e){const t=this.nameProvider.getNameNode(e);if(t){const a=(0,St.YE)(e),n=this.nodeLocator.getAstNodePath(e);return{sourceUri:a.uri,sourcePath:n,targetUri:a.uri,targetPath:n,segment:(0,r.SX)(t),local:!0}}}}class Pa{constructor(e){if(this.map=new Map,e)for(const[t,a]of e)this.add(t,a)}get size(){return Zt.iD.sum((0,Zt.Td)(this.map.values()).map(e=>e.length))}clear(){this.map.clear()}delete(e,t){if(void 0===t)return this.map.delete(e);{const a=this.map.get(e);if(a){const r=a.indexOf(t);if(r>=0)return 1===a.length?this.map.delete(e):a.splice(r,1),!0}return!1}}get(e){var t;return null!==(t=this.map.get(e))&&void 0!==t?t:[]}has(e,t){if(void 0===t)return this.map.has(e);{const a=this.map.get(e);return!!a&&a.indexOf(t)>=0}}add(e,t){return this.map.has(e)?this.map.get(e).push(t):this.map.set(e,[t]),this}addAll(e,t){return this.map.has(e)?this.map.get(e).push(...t):this.map.set(e,Array.from(t)),this}forEach(e){this.map.forEach((t,a)=>t.forEach(t=>e(t,a,this)))}[Symbol.iterator](){return this.entries().iterator()}entries(){return(0,Zt.Td)(this.map.entries()).flatMap(([e,t])=>t.map(t=>[e,t]))}keys(){return(0,Zt.Td)(this.map.keys())}values(){return(0,Zt.Td)(this.map.values()).flat()}entriesGroupedByKey(){return(0,Zt.Td)(this.map.entries())}}class qa{get size(){return this.map.size}constructor(e){if(this.map=new Map,this.inverse=new Map,e)for(const[t,a]of e)this.set(t,a)}clear(){this.map.clear(),this.inverse.clear()}set(e,t){return this.map.set(e,t),this.inverse.set(t,e),this}get(e){return this.map.get(e)}getKey(e){return this.inverse.get(e)}delete(e){const t=this.map.get(e);return void 0!==t&&(this.map.delete(e),this.inverse.delete(t),!0)}}class Ea{constructor(e){this.nameProvider=e.references.NameProvider,this.descriptions=e.workspace.AstNodeDescriptionProvider}async computeExports(e,t=ca.XO.None){return this.computeExportsForNode(e.parseResult.value,e,void 0,t)}async computeExportsForNode(e,t,a=St.VN,r=ca.XO.None){const n=[];this.exportNode(e,n,t);for(const i of a(e))await pa(r),this.exportNode(i,n,t);return n}exportNode(e,t,a){const r=this.nameProvider.getName(e);r&&t.push(this.descriptions.createDescription(e,r,a))}async computeLocalScopes(e,t=ca.XO.None){const a=e.parseResult.value,r=new Pa;for(const n of(0,St.Uo)(a))await pa(t),this.processNode(n,e,r);return r}processNode(e,t,a){const r=e.$container;if(r){const n=this.nameProvider.getName(e);n&&a.add(r,this.descriptions.createDescription(e,n,t))}}}class $a{constructor(e,t,a){var r;this.elements=e,this.outerScope=t,this.caseInsensitive=null!==(r=null==a?void 0:a.caseInsensitive)&&void 0!==r&&r}getAllElements(){return this.outerScope?this.elements.concat(this.outerScope.getAllElements()):this.elements}getElement(e){const t=this.caseInsensitive?this.elements.find(t=>t.name.toLowerCase()===e.toLowerCase()):this.elements.find(t=>t.name===e);return t||(this.outerScope?this.outerScope.getElement(e):void 0)}}class za{constructor(e,t,a){var r;this.elements=new Map,this.caseInsensitive=null!==(r=null==a?void 0:a.caseInsensitive)&&void 0!==r&&r;for(const n of e){const e=this.caseInsensitive?n.name.toLowerCase():n.name;this.elements.set(e,n)}this.outerScope=t}getElement(e){const t=this.caseInsensitive?e.toLowerCase():e,a=this.elements.get(t);return a||(this.outerScope?this.outerScope.getElement(e):void 0)}getAllElements(){let e=(0,Zt.Td)(this.elements.values());return this.outerScope&&(e=e.concat(this.outerScope.getAllElements())),e}}class Ha{constructor(){this.toDispose=[],this.isDisposed=!1}onDispose(e){this.toDispose.push(e)}dispose(){this.throwIfDisposed(),this.clear(),this.isDisposed=!0,this.toDispose.forEach(e=>e.dispose())}throwIfDisposed(){if(this.isDisposed)throw new Error("This cache has already been disposed")}}class Oa extends Ha{constructor(){super(...arguments),this.cache=new Map}has(e){return this.throwIfDisposed(),this.cache.has(e)}set(e,t){this.throwIfDisposed(),this.cache.set(e,t)}get(e,t){if(this.throwIfDisposed(),this.cache.has(e))return this.cache.get(e);if(t){const a=t();return this.cache.set(e,a),a}}delete(e){return this.throwIfDisposed(),this.cache.delete(e)}clear(){this.throwIfDisposed(),this.cache.clear()}}class Da extends Ha{constructor(e){super(),this.cache=new Map,this.converter=null!=e?e:e=>e}has(e,t){return this.throwIfDisposed(),this.cacheForContext(e).has(t)}set(e,t,a){this.throwIfDisposed(),this.cacheForContext(e).set(t,a)}get(e,t,a){this.throwIfDisposed();const r=this.cacheForContext(e);if(r.has(t))return r.get(t);if(a){const e=a();return r.set(t,e),e}}delete(e,t){return this.throwIfDisposed(),this.cacheForContext(e).delete(t)}clear(e){if(this.throwIfDisposed(),e){const t=this.converter(e);this.cache.delete(t)}else this.cache.clear()}cacheForContext(e){const t=this.converter(e);let a=this.cache.get(t);return a||(a=new Map,this.cache.set(t,a)),a}}class Na extends Oa{constructor(e,t){super(),t?(this.toDispose.push(e.workspace.DocumentBuilder.onBuildPhase(t,()=>{this.clear()})),this.toDispose.push(e.workspace.DocumentBuilder.onUpdate((e,t)=>{t.length>0&&this.clear()}))):this.toDispose.push(e.workspace.DocumentBuilder.onUpdate(()=>{this.clear()}))}}class Va{constructor(e){this.reflection=e.shared.AstReflection,this.nameProvider=e.references.NameProvider,this.descriptions=e.workspace.AstNodeDescriptionProvider,this.indexManager=e.shared.workspace.IndexManager,this.globalScopeCache=new Na(e.shared)}getScope(e){const t=[],a=this.reflection.getReferenceType(e),r=(0,St.YE)(e.container).precomputedScopes;if(r){let n=e.container;do{const e=r.get(n);e.length>0&&t.push((0,Zt.Td)(e).filter(e=>this.reflection.isSubtype(e.type,a))),n=n.$container}while(n)}let n=this.getGlobalScope(a,e);for(let i=t.length-1;i>=0;i--)n=this.createScope(t[i],n);return n}createScope(e,t,a){return new $a((0,Zt.Td)(e),t,a)}createScopeForNodes(e,t,a){const r=(0,Zt.Td)(e).map(e=>{const t=this.nameProvider.getName(e);if(t)return this.descriptions.createDescription(e,t)}).nonNullable();return new $a(r,t,a)}getGlobalScope(e,t){return this.globalScopeCache.get(e,()=>new za(this.indexManager.allElements(e)))}}function ja(e){return"object"==typeof e&&!!e&&("$ref"in e||"$error"in e)}class Fa{constructor(e){this.ignoreProperties=new Set(["$container","$containerProperty","$containerIndex","$document","$cstNode"]),this.langiumDocuments=e.shared.workspace.LangiumDocuments,this.astNodeLocator=e.workspace.AstNodeLocator,this.nameProvider=e.references.NameProvider,this.commentProvider=e.documentation.CommentProvider}serialize(e,t){const a=null!=t?t:{},r=null==t?void 0:t.replacer,n=(e,t)=>this.replacer(e,t,a),i=r?(e,t)=>r(e,t,n):n;try{return this.currentDocument=(0,St.YE)(e),JSON.stringify(e,i,null==t?void 0:t.space)}finally{this.currentDocument=void 0}}deserialize(e,t){const a=null!=t?t:{},r=JSON.parse(e);return this.linkNode(r,r,a),r}replacer(e,t,{refText:a,sourceText:r,textRegions:n,comments:i,uriConverter:o}){var c,s,h,d;if(!this.ignoreProperties.has(e)){if((0,sa.A_)(t)){const e=t.ref,r=a?t.$refText:void 0;if(e){const a=(0,St.YE)(e);let n="";this.currentDocument&&this.currentDocument!==a&&(n=o?o(a.uri,t):a.uri.toString());return{$ref:`${n}#${this.astNodeLocator.getAstNodePath(e)}`,$refText:r}}return{$error:null!==(s=null===(c=t.error)||void 0===c?void 0:c.message)&&void 0!==s?s:"Could not resolve reference",$refText:r}}if((0,sa.ng)(t)){let a;if(n&&(a=this.addAstNodeRegionWithAssignmentsTo(Object.assign({},t)),e&&!t.$document||!(null==a?void 0:a.$textRegion)||(a.$textRegion.documentURI=null===(h=this.currentDocument)||void 0===h?void 0:h.uri.toString())),r&&!e&&(null!=a||(a=Object.assign({},t)),a.$sourceText=null===(d=t.$cstNode)||void 0===d?void 0:d.text),i){null!=a||(a=Object.assign({},t));const e=this.commentProvider.getComment(t);e&&(a.$comment=e.replace(/\r/g,""))}return null!=a?a:t}return t}}addAstNodeRegionWithAssignmentsTo(e){const t=e=>({offset:e.offset,end:e.end,length:e.length,range:e.range});if(e.$cstNode){const a=(e.$textRegion=t(e.$cstNode)).assignments={};return Object.keys(e).filter(e=>!e.startsWith("$")).forEach(r=>{const i=(0,n.Bd)(e.$cstNode,r).map(t);0!==i.length&&(a[r]=i)}),e}}linkNode(e,t,a,r,n,i){for(const[c,s]of Object.entries(e))if(Array.isArray(s))for(let r=0;r{await this.handleException(()=>e.call(t,a,r,n),"An error occurred during validation",r,a)}}async handleException(e,t,a,r){try{await e()}catch(n){if(ua(n))throw n;console.error(`${t}:`,n),n instanceof Error&&n.stack&&console.error(n.stack);a("error",`${t}: ${n instanceof Error?n.message:String(n)}`,{node:r})}}addEntry(e,t){if("AstNode"!==e)for(const a of this.reflection.getAllSubTypes(e))this.entries.add(a,t);else this.entries.add("AstNode",t)}getChecks(e,t){let a=(0,Zt.Td)(this.entries.get(e)).concat(this.entries.get("AstNode"));return t&&(a=a.filter(e=>t.includes(e.category))),a.map(e=>e.check)}registerBeforeDocument(e,t=this){this.entriesBefore.push(this.wrapPreparationException(e,"An error occurred during set-up of the validation",t))}registerAfterDocument(e,t=this){this.entriesAfter.push(this.wrapPreparationException(e,"An error occurred during tear-down of the validation",t))}wrapPreparationException(e,t,a){return async(r,n,i,o)=>{await this.handleException(()=>e.call(a,r,n,i,o),t,n,r)}}get checksBefore(){return this.entriesBefore}get checksAfter(){return this.entriesAfter}}class Ka{constructor(e){this.validationRegistry=e.validation.ValidationRegistry,this.metadata=e.LanguageMetaData}async validateDocument(e,t={},a=ca.XO.None){const r=e.parseResult,n=[];if(await pa(a),!t.categories||t.categories.includes("built-in")){if(this.processLexingErrors(r,n,t),t.stopAfterLexingErrors&&n.some(e=>{var t;return(null===(t=e.data)||void 0===t?void 0:t.code)===Ga.LexingError}))return n;if(this.processParsingErrors(r,n,t),t.stopAfterParsingErrors&&n.some(e=>{var t;return(null===(t=e.data)||void 0===t?void 0:t.code)===Ga.ParsingError}))return n;if(this.processLinkingErrors(e,n,t),t.stopAfterLinkingErrors&&n.some(e=>{var t;return(null===(t=e.data)||void 0===t?void 0:t.code)===Ga.LinkingError}))return n}try{n.push(...await this.validateAst(r.value,t,a))}catch(i){if(ua(i))throw i;console.error("An error occurred during validation:",i)}return await pa(a),n}processLexingErrors(e,t,a){var r,n,i;const o=[...e.lexerErrors,...null!==(n=null===(r=e.lexerReport)||void 0===r?void 0:r.diagnostics)&&void 0!==n?n:[]];for(const c of o){const e=null!==(i=c.severity)&&void 0!==i?i:"error",a={severity:Xa(e),range:{start:{line:c.line-1,character:c.column-1},end:{line:c.line-1,character:c.column+c.length-1}},message:c.message,data:Ya(e),source:this.getSource()};t.push(a)}}processParsingErrors(e,t,a){for(const n of e.parserErrors){let e;if(isNaN(n.token.startOffset)){if("previousToken"in n){const t=n.previousToken;if(isNaN(t.startOffset)){const t={line:0,character:0};e={start:t,end:t}}else{const a={line:t.endLine-1,character:t.endColumn};e={start:a,end:a}}}}else e=(0,r.wf)(n.token);if(e){const a={severity:Xa("error"),range:e,message:n.message,data:_a(Ga.ParsingError),source:this.getSource()};t.push(a)}}}processLinkingErrors(e,t,a){for(const r of e.references){const e=r.error;if(e){const a={node:e.container,property:e.property,index:e.index,data:{code:Ga.LinkingError,containerType:e.container.$type,property:e.property,refText:e.reference.$refText}};t.push(this.toDiagnostic("error",e.message,a))}}}async validateAst(e,t,a=ca.XO.None){const r=[],n=(e,t,a)=>{r.push(this.toDiagnostic(e,t,a))};return await this.validateAstBefore(e,t,n,a),await this.validateAstNodes(e,t,n,a),await this.validateAstAfter(e,t,n,a),r}async validateAstBefore(e,t,a,r=ca.XO.None){var n;const i=this.validationRegistry.checksBefore;for(const o of i)await pa(r),await o(e,a,null!==(n=t.categories)&&void 0!==n?n:[],r)}async validateAstNodes(e,t,a,r=ca.XO.None){await Promise.all((0,St.jm)(e).map(async e=>{await pa(r);const n=this.validationRegistry.getChecks(e.$type,t.categories);for(const t of n)await t(e,a,r)}))}async validateAstAfter(e,t,a,r=ca.XO.None){var n;const i=this.validationRegistry.checksAfter;for(const o of i)await pa(r),await o(e,a,null!==(n=t.categories)&&void 0!==n?n:[],r)}toDiagnostic(e,t,a){return{message:t,range:Za(a),severity:Xa(e),code:a.code,codeDescription:a.codeDescription,tags:a.tags,relatedInformation:a.relatedInformation,data:a.data,source:this.getSource()}}getSource(){return this.metadata.languageId}}function Za(e){if(e.range)return e.range;let t;return"string"==typeof e.property?t=(0,n.qO)(e.node.$cstNode,e.property,e.index):"string"==typeof e.keyword&&(t=(0,n.SS)(e.node.$cstNode,e.keyword,e.index)),null!=t||(t=e.node.$cstNode),t?t.range:{start:{line:0,character:0},end:{line:0,character:0}}}function Xa(e){switch(e){case"error":return 1;case"warning":return 2;case"info":return 3;case"hint":return 4;default:throw new Error("Invalid diagnostic severity: "+e)}}function Ya(e){switch(e){case"error":return _a(Ga.LexingError);case"warning":return _a(Ga.LexingWarning);case"info":return _a(Ga.LexingInfo);case"hint":return _a(Ga.LexingHint);default:throw new Error("Invalid diagnostic severity: "+e)}}!function(e){e.LexingError="lexing-error",e.LexingWarning="lexing-warning",e.LexingInfo="lexing-info",e.LexingHint="lexing-hint",e.ParsingError="parsing-error",e.LinkingError="linking-error"}(Ga||(Ga={}));class Qa{constructor(e){this.astNodeLocator=e.workspace.AstNodeLocator,this.nameProvider=e.references.NameProvider}createDescription(e,t,a){const n=null!=a?a:(0,St.YE)(e);null!=t||(t=this.nameProvider.getName(e));const i=this.astNodeLocator.getAstNodePath(e);if(!t)throw new Error(`Node at path ${i} has no name.`);let o;const c=()=>{var t;return null!=o?o:o=(0,r.SX)(null!==(t=this.nameProvider.getNameNode(e))&&void 0!==t?t:e.$cstNode)};return{node:e,name:t,get nameSegment(){return c()},selectionSegment:(0,r.SX)(e.$cstNode),type:e.$type,documentUri:n.uri,path:i}}}class Ja{constructor(e){this.nodeLocator=e.workspace.AstNodeLocator}async createDescriptions(e,t=ca.XO.None){const a=[],r=e.parseResult.value;for(const n of(0,St.jm)(r))await pa(t),(0,St.DM)(n).filter(e=>!(0,sa.Zl)(e)).forEach(e=>{const t=this.createDescription(e);t&&a.push(t)});return a}createDescription(e){const t=e.reference.$nodeDescription,a=e.reference.$refNode;if(!t||!a)return;const n=(0,St.YE)(e.container).uri;return{sourceUri:n,sourcePath:this.nodeLocator.getAstNodePath(e.container),targetUri:t.documentUri,targetPath:t.path,segment:(0,r.SX)(a),local:Ta.equals(t.documentUri,n)}}}class er{constructor(){this.segmentSeparator="/",this.indexSeparator="@"}getAstNodePath(e){if(e.$container){const t=this.getAstNodePath(e.$container),a=this.getPathSegment(e);return t+this.segmentSeparator+a}return""}getPathSegment({$containerProperty:e,$containerIndex:t}){if(!e)throw new Error("Missing '$containerProperty' in AST node.");return void 0!==t?e+this.indexSeparator+t:e}getAstNode(e,t){return t.split(this.segmentSeparator).reduce((e,t)=>{if(!e||0===t.length)return e;const a=t.indexOf(this.indexSeparator);if(a>0){const r=t.substring(0,a),n=parseInt(t.substring(a+1)),i=e[r];return null==i?void 0:i[n]}return e[t]},e)}}var tr,ar=a(2676);class rr{constructor(e){this._ready=new ya,this.settings={},this.workspaceConfig=!1,this.onConfigurationSectionUpdateEmitter=new ar.Emitter,this.serviceRegistry=e.ServiceRegistry}get ready(){return this._ready.promise}initialize(e){var t,a;this.workspaceConfig=null!==(a=null===(t=e.capabilities.workspace)||void 0===t?void 0:t.configuration)&&void 0!==a&&a}async initialized(e){if(this.workspaceConfig){if(e.register){const t=this.serviceRegistry.all;e.register({section:t.map(e=>this.toSectionName(e.LanguageMetaData.languageId))})}if(e.fetchConfiguration){const t=this.serviceRegistry.all.map(e=>({section:this.toSectionName(e.LanguageMetaData.languageId)})),a=await e.fetchConfiguration(t);t.forEach((e,t)=>{this.updateSectionConfiguration(e.section,a[t])})}}this._ready.resolve()}updateConfiguration(e){e.settings&&Object.keys(e.settings).forEach(t=>{const a=e.settings[t];this.updateSectionConfiguration(t,a),this.onConfigurationSectionUpdateEmitter.fire({section:t,configuration:a})})}updateSectionConfiguration(e,t){this.settings[e]=t}async getConfiguration(e,t){await this.ready;const a=this.toSectionName(e);if(this.settings[a])return this.settings[a][t]}toSectionName(e){return`${e}`}get onConfigurationSectionUpdate(){return this.onConfigurationSectionUpdateEmitter.event}}!function(e){e.create=function(e){return{dispose:async()=>await e()}}}(tr||(tr={}));class nr{constructor(e){this.updateBuildOptions={validation:{categories:["built-in","fast"]}},this.updateListeners=[],this.buildPhaseListeners=new Pa,this.documentPhaseListeners=new Pa,this.buildState=new Map,this.documentBuildWaiters=new Map,this.currentState=La.Changed,this.langiumDocuments=e.workspace.LangiumDocuments,this.langiumDocumentFactory=e.workspace.LangiumDocumentFactory,this.textDocuments=e.workspace.TextDocuments,this.indexManager=e.workspace.IndexManager,this.serviceRegistry=e.ServiceRegistry}async build(e,t={},a=ca.XO.None){var r,n;for(const i of e){const e=i.uri.toString();if(i.state===La.Validated){if("boolean"==typeof t.validation&&t.validation)i.state=La.IndexedReferences,i.diagnostics=void 0,this.buildState.delete(e);else if("object"==typeof t.validation){const a=this.buildState.get(e),o=null===(r=null==a?void 0:a.result)||void 0===r?void 0:r.validationChecks;if(o){const r=(null!==(n=t.validation.categories)&&void 0!==n?n:Ua.all).filter(e=>!o.includes(e));r.length>0&&(this.buildState.set(e,{completed:!1,options:{validation:Object.assign(Object.assign({},t.validation),{categories:r})},result:a.result}),i.state=La.IndexedReferences)}}}else this.buildState.delete(e)}this.currentState=La.Changed,await this.emitUpdate(e.map(e=>e.uri),[]),await this.buildDocuments(e,t,a)}async update(e,t,a=ca.XO.None){this.currentState=La.Changed;for(const i of t)this.langiumDocuments.deleteDocument(i),this.buildState.delete(i.toString()),this.indexManager.remove(i);for(const i of e){if(!this.langiumDocuments.invalidateDocument(i)){const e=this.langiumDocumentFactory.fromModel({$type:"INVALID"},i);e.state=La.Changed,this.langiumDocuments.addDocument(e)}this.buildState.delete(i.toString())}const r=(0,Zt.Td)(e).concat(t).map(e=>e.toString()).toSet();this.langiumDocuments.all.filter(e=>!r.has(e.uri.toString())&&this.shouldRelink(e,r)).forEach(e=>{this.serviceRegistry.getServices(e.uri).references.Linker.unlink(e),e.state=Math.min(e.state,La.ComputedScopes),e.diagnostics=void 0}),await this.emitUpdate(e,t),await pa(a);const n=this.sortDocuments(this.langiumDocuments.all.filter(e=>{var t;return e.statea(e,t)))}sortDocuments(e){let t=0,a=e.length-1;for(;t=0&&!this.hasTextDocument(e[a]);)a--;tvoid 0!==e.error)||this.indexManager.isAffected(e,t)}onUpdate(e){return this.updateListeners.push(e),tr.create(()=>{const t=this.updateListeners.indexOf(e);t>=0&&this.updateListeners.splice(t,1)})}async buildDocuments(e,t,a){this.prepareBuild(e,t),await this.runCancelable(e,La.Parsed,a,e=>this.langiumDocumentFactory.update(e,a)),await this.runCancelable(e,La.IndexedContent,a,e=>this.indexManager.updateContent(e,a)),await this.runCancelable(e,La.ComputedScopes,a,async e=>{const t=this.serviceRegistry.getServices(e.uri).references.ScopeComputation;e.precomputedScopes=await t.computeLocalScopes(e,a)}),await this.runCancelable(e,La.Linked,a,e=>this.serviceRegistry.getServices(e.uri).references.Linker.link(e,a)),await this.runCancelable(e,La.IndexedReferences,a,e=>this.indexManager.updateReferences(e,a));const r=e.filter(e=>this.shouldValidate(e));await this.runCancelable(r,La.Validated,a,e=>this.validate(e,a));for(const n of e){const e=this.buildState.get(n.uri.toString());e&&(e.completed=!0)}}prepareBuild(e,t){for(const a of e){const e=a.uri.toString(),r=this.buildState.get(e);r&&!r.completed||this.buildState.set(e,{completed:!1,options:t,result:null==r?void 0:r.result})}}async runCancelable(e,t,a,r){const n=e.filter(e=>e.statee.state===t);await this.notifyBuildPhase(i,t,a),this.currentState=t}onBuildPhase(e,t){return this.buildPhaseListeners.add(e,t),tr.create(()=>{this.buildPhaseListeners.delete(e,t)})}onDocumentPhase(e,t){return this.documentPhaseListeners.add(e,t),tr.create(()=>{this.documentPhaseListeners.delete(e,t)})}waitUntil(e,t,a){let r;if(t&&"path"in t?r=t:a=t,null!=a||(a=ca.XO.None),r){const t=this.langiumDocuments.getDocument(r);if(t&&t.state>e)return Promise.resolve(r)}return this.currentState>=e?Promise.resolve(void 0):a.isCancellationRequested?Promise.reject(la):new Promise((t,n)=>{const i=this.onBuildPhase(e,()=>{if(i.dispose(),o.dispose(),r){const e=this.langiumDocuments.getDocument(r);t(null==e?void 0:e.uri)}else t(void 0)}),o=a.onCancellationRequested(()=>{i.dispose(),o.dispose(),n(la)})})}async notifyDocumentPhase(e,t,a){const r=this.documentPhaseListeners.get(t).slice();for(const i of r)try{await i(e,a)}catch(n){if(!ua(n))throw n}}async notifyBuildPhase(e,t,a){if(0===e.length)return;const r=this.buildPhaseListeners.get(t).slice();for(const n of r)await pa(a),await n(e,a)}shouldValidate(e){return Boolean(this.getBuildOptions(e).validation)}async validate(e,t){var a,r;const n=this.serviceRegistry.getServices(e.uri).validation.DocumentValidator,i=this.getBuildOptions(e).validation,o="object"==typeof i?i:void 0,c=await n.validateDocument(e,o,t);e.diagnostics?e.diagnostics.push(...c):e.diagnostics=c;const s=this.buildState.get(e.uri.toString());if(s){null!==(a=s.result)&&void 0!==a||(s.result={});const e=null!==(r=null==o?void 0:o.categories)&&void 0!==r?r:Ua.all;s.result.validationChecks?s.result.validationChecks.push(...e):s.result.validationChecks=[...e]}}getBuildOptions(e){var t,a;return null!==(a=null===(t=this.buildState.get(e.uri.toString()))||void 0===t?void 0:t.options)&&void 0!==a?a:{}}}class ir{constructor(e){this.symbolIndex=new Map,this.symbolByTypeIndex=new Da,this.referenceIndex=new Map,this.documents=e.workspace.LangiumDocuments,this.serviceRegistry=e.ServiceRegistry,this.astReflection=e.AstReflection}findAllReferences(e,t){const a=(0,St.YE)(e).uri,r=[];return this.referenceIndex.forEach(e=>{e.forEach(e=>{Ta.equals(e.targetUri,a)&&e.targetPath===t&&r.push(e)})}),(0,Zt.Td)(r)}allElements(e,t){let a=(0,Zt.Td)(this.symbolIndex.keys());return t&&(a=a.filter(e=>!t||t.has(e))),a.map(t=>this.getFileDescriptions(t,e)).flat()}getFileDescriptions(e,t){var a;if(!t)return null!==(a=this.symbolIndex.get(e))&&void 0!==a?a:[];const r=this.symbolByTypeIndex.get(e,t,()=>{var a;return(null!==(a=this.symbolIndex.get(e))&&void 0!==a?a:[]).filter(e=>this.astReflection.isSubtype(e.type,t))});return r}remove(e){const t=e.toString();this.symbolIndex.delete(t),this.symbolByTypeIndex.clear(t),this.referenceIndex.delete(t)}async updateContent(e,t=ca.XO.None){const a=this.serviceRegistry.getServices(e.uri),r=await a.references.ScopeComputation.computeExports(e,t),n=e.uri.toString();this.symbolIndex.set(n,r),this.symbolByTypeIndex.clear(n)}async updateReferences(e,t=ca.XO.None){const a=this.serviceRegistry.getServices(e.uri),r=await a.workspace.ReferenceDescriptionProvider.createDescriptions(e,t);this.referenceIndex.set(e.uri.toString(),r)}isAffected(e,t){const a=this.referenceIndex.get(e.uri.toString());return!!a&&a.some(e=>!e.local&&t.has(e.targetUri.toString()))}}class or{constructor(e){this.initialBuildOptions={},this._ready=new ya,this.serviceRegistry=e.ServiceRegistry,this.langiumDocuments=e.workspace.LangiumDocuments,this.documentBuilder=e.workspace.DocumentBuilder,this.fileSystemProvider=e.workspace.FileSystemProvider,this.mutex=e.workspace.WorkspaceLock}get ready(){return this._ready.promise}get workspaceFolders(){return this.folders}initialize(e){var t;this.folders=null!==(t=e.workspaceFolders)&&void 0!==t?t:void 0}initialized(e){return this.mutex.write(e=>{var t;return this.initializeWorkspace(null!==(t=this.folders)&&void 0!==t?t:[],e)})}async initializeWorkspace(e,t=ca.XO.None){const a=await this.performStartup(e);await pa(t),await this.documentBuilder.build(a,this.initialBuildOptions,t)}async performStartup(e){const t=this.serviceRegistry.all.flatMap(e=>e.LanguageMetaData.fileExtensions),a=[],r=e=>{a.push(e),this.langiumDocuments.hasDocument(e.uri)||this.langiumDocuments.addDocument(e)};return await this.loadAdditionalDocuments(e,r),await Promise.all(e.map(e=>[e,this.getRootFolder(e)]).map(async e=>this.traverseFolder(...e,t,r))),this._ready.resolve(),a}loadAdditionalDocuments(e,t){return Promise.resolve()}getRootFolder(e){return wa.r.parse(e.uri)}async traverseFolder(e,t,a,r){const n=await this.fileSystemProvider.readDirectory(t);await Promise.all(n.map(async t=>{if(this.includeEntry(e,t,a))if(t.isDirectory)await this.traverseFolder(e,t.uri,a,r);else if(t.isFile){const e=await this.langiumDocuments.getOrCreateDocument(t.uri);r(e)}}))}includeEntry(e,t,a){const r=Ta.basename(t.uri);if(r.startsWith("."))return!1;if(t.isDirectory)return"node_modules"!==r&&"out"!==r;if(t.isFile){const e=Ta.extname(t.uri);return a.includes(e)}return!1}}class cr{buildUnexpectedCharactersMessage(e,t,a,r,n){return c.PW.buildUnexpectedCharactersMessage(e,t,a,r,n)}buildUnableToPopLexerModeMessage(e){return c.PW.buildUnableToPopLexerModeMessage(e)}}const sr={mode:"full"};class hr{constructor(e){this.errorMessageProvider=e.parser.LexerErrorMessageProvider,this.tokenBuilder=e.parser.TokenBuilder;const t=this.tokenBuilder.buildTokens(e.Grammar,{caseInsensitive:e.LanguageMetaData.caseInsensitive});this.tokenTypes=this.toTokenTypeDictionary(t);const a=lr(t)?Object.values(t):t,r="production"===e.LanguageMetaData.mode;this.chevrotainLexer=new c.JG(a,{positionTracking:"full",skipValidations:r,errorMessageProvider:this.errorMessageProvider})}get definition(){return this.tokenTypes}tokenize(e,t=sr){var a,r,n;const i=this.chevrotainLexer.tokenize(e);return{tokens:i.tokens,errors:i.errors,hidden:null!==(a=i.groups.hidden)&&void 0!==a?a:[],report:null===(n=(r=this.tokenBuilder).flushLexingReport)||void 0===n?void 0:n.call(r,e)}}toTokenTypeDictionary(e){if(lr(e))return e;const t=dr(e)?Object.values(e.modes).flat():e,a={};return t.forEach(e=>a[e.name]=e),a}}function dr(e){return e&&"modes"in e&&"defaultMode"in e}function lr(e){return!function(e){return Array.isArray(e)&&(0===e.length||"name"in e[0])}(e)&&!dr(e)}function ur(e,t,a){let r,n;"string"==typeof e?(n=t,r=a):(n=e.range.start,r=t),n||(n=se.create(0,0));const i=function(e){var t,a,r;const n=[];let i=e.position.line,o=e.position.character;for(let c=0;c=d.length){if(n.length>0){const e=se.create(i,o);n.push({type:"break",content:"",range:he.create(e,e)})}}else{yr.lastIndex=l;const e=yr.exec(d);if(e){const t=e[0],a=e[1],r=se.create(i,o+l),c=se.create(i,o+l+t.length);n.push({type:"tag",content:a,range:he.create(r,c)}),l+=t.length,l=Mr(d,l)}if(l0&&"break"===n[n.length-1].type)return n.slice(0,-1);return n}({lines:pr(e),position:n,options:Cr(r)});return function(e){var t,a,r,n;const i=se.create(e.position.line,e.position.character);if(0===e.tokens.length)return new Sr([],he.create(i,i));const o=[];for(;e.index0&&n.push({type:"text",content:t.substring(i,e),range:he.create(se.create(a,i+r),se.create(a,e+r))});let s=o.length+1;const h=c[1];if(n.push({type:"inline-tag",content:h,range:he.create(se.create(a,i+s+r),se.create(a,i+s+h.length+r))}),s+=h.length,4===c.length){s+=c[2].length;const e=c[3];n.push({type:"text",content:e,range:he.create(se.create(a,i+s+r),se.create(a,i+s+e.length+r))})}else n.push({type:"text",content:"",range:he.create(se.create(a,i+s+r),se.create(a,i+s+r))});i=e+c[0].length}const o=t.substring(i);o.length>0&&n.push({type:"text",content:o,range:he.create(se.create(a,i+r),se.create(a,i+r+o.length))})}return n}const mr=/\S/,gr=/\s*$/;function Mr(e,t){const a=e.substring(t).match(mr);return a?t+a.index:e.length}function vr(e){const t=e.match(gr);if(t&&"number"==typeof t.index)return t.index}function xr(e,t){const a=e.tokens[e.index];return"tag"===a.type?Ar(e,!1):"text"===a.type||"inline-tag"===a.type?Lr(e):(function(e,t){if(t){const a=new Pr("",e.range);"inlines"in t?t.inlines.push(a):t.content.inlines.push(a)}}(a,t),void e.index++)}function Lr(e){let t=e.tokens[e.index];const a=t;let r=t;const n=[];for(;t&&"break"!==t.type&&"tag"!==t.type;)n.push(wr(e)),r=t,t=e.tokens[e.index];return new Rr(n,he.create(a.range.start,r.range.end))}function wr(e){return"inline-tag"===e.tokens[e.index].type?Ar(e,!0):Ir(e)}function Ar(e,t){const a=e.tokens[e.index++],r=a.content.substring(1),n=e.tokens[e.index];if("text"===(null==n?void 0:n.type)){if(t){const n=Ir(e);return new Tr(r,new Rr([n],n.range),t,he.create(a.range.start,n.range.end))}{const n=Lr(e);return new Tr(r,n,t,he.create(a.range.start,n.range.end))}}{const e=a.range;return new Tr(r,new Rr([],e),t,e)}}function Ir(e){const t=e.tokens[e.index++];return new Pr(t.content,t.range)}function Cr(e){if(!e)return Cr({start:"/**",end:"*/",line:"*"});const{start:t,end:a,line:r}=e;return{start:br(t,!0),end:br(a,!1),line:br(r,!0)}}function br(e,t){if("string"==typeof e||"object"==typeof e){const a="string"==typeof e?(0,i.Nt)(e):e.source;return t?new RegExp(`^\\s*${a}`):new RegExp(`\\s*${a}\\s*$`)}return e}class Sr{constructor(e,t){this.elements=e,this.range=t}getTag(e){return this.getAllTags().find(t=>t.name===e)}getTags(e){return this.getAllTags().filter(t=>t.name===e)}getAllTags(){return this.elements.filter(e=>"name"in e)}toString(){let e="";for(const t of this.elements)if(0===e.length)e=t.toString();else{const a=t.toString();e+=qr(e)+a}return e.trim()}toMarkdown(e){let t="";for(const a of this.elements)if(0===t.length)t=a.toMarkdown(e);else{const r=a.toMarkdown(e);t+=qr(t)+r}return t.trim()}}class Tr{constructor(e,t,a,r){this.name=e,this.content=t,this.inline=a,this.range=r}toString(){let e=`@${this.name}`;const t=this.content.toString();return 1===this.content.inlines.length?e=`${e} ${t}`:this.content.inlines.length>1&&(e=`${e}\n${t}`),this.inline?`{${e}}`:e}toMarkdown(e){var t,a;return null!==(a=null===(t=null==e?void 0:e.renderTag)||void 0===t?void 0:t.call(e,this))&&void 0!==a?a:this.toMarkdownDefault(e)}toMarkdownDefault(e){const t=this.content.toMarkdown(e);if(this.inline){const a=function(e,t,a){var r,n;if("linkplain"===e||"linkcode"===e||"link"===e){const i=t.indexOf(" ");let o=t;if(i>0){const e=Mr(t,i);o=t.substring(e),t=t.substring(0,i)}("linkcode"===e||"link"===e&&"code"===a.link)&&(o=`\`${o}\``);const c=null!==(n=null===(r=a.renderLink)||void 0===r?void 0:r.call(a,t,o))&&void 0!==n?n:function(e,t){try{return wa.r.parse(e,!0),`[${t}](${e})`}catch(r){return e}}(t,o);return c}return}(this.name,t,null!=e?e:{});if("string"==typeof a)return a}let a="";"italic"===(null==e?void 0:e.tag)||void 0===(null==e?void 0:e.tag)?a="*":"bold"===(null==e?void 0:e.tag)?a="**":"bold-italic"===(null==e?void 0:e.tag)&&(a="***");let r=`${a}@${this.name}${a}`;return 1===this.content.inlines.length?r=`${r} \u2014 ${t}`:this.content.inlines.length>1&&(r=`${r}\n${t}`),this.inline?`{${r}}`:r}}class Rr{constructor(e,t){this.inlines=e,this.range=t}toString(){let e="";for(let t=0;ta.range.start.line&&(e+="\n")}return e}toMarkdown(e){let t="";for(let a=0;ar.range.start.line&&(t+="\n")}return t}}class Pr{constructor(e,t){this.text=e,this.range=t}toString(){return this.text}toMarkdown(){return this.text}}function qr(e){return e.endsWith("\n")?"\n":"\n\n"}class Er{constructor(e){this.indexManager=e.shared.workspace.IndexManager,this.commentProvider=e.documentation.CommentProvider}getDocumentation(e){const t=this.commentProvider.getComment(e);if(t&&function(e,t){const a=Cr(t),r=pr(e);if(0===r.length)return!1;const n=r[0],i=r[r.length-1],o=a.start,c=a.end;return Boolean(null==o?void 0:o.exec(n))&&Boolean(null==c?void 0:c.exec(i))}(t)){return ur(t).toMarkdown({renderLink:(t,a)=>this.documentationLinkRenderer(e,t,a),renderTag:t=>this.documentationTagRenderer(e,t)})}}documentationLinkRenderer(e,t,a){var r;const n=null!==(r=this.findNameInPrecomputedScopes(e,t))&&void 0!==r?r:this.findNameInGlobalScope(e,t);if(n&&n.nameSegment){const e=n.nameSegment.range.start.line+1,t=n.nameSegment.range.start.character+1;return`[${a}](${n.documentUri.with({fragment:`L${e},${t}`}).toString()})`}}documentationTagRenderer(e,t){}findNameInPrecomputedScopes(e,t){const a=(0,St.YE)(e).precomputedScopes;if(!a)return;let r=e;do{const e=a.get(r).find(e=>e.name===t);if(e)return e;r=r.$container}while(r)}findNameInGlobalScope(e,t){return this.indexManager.allElements().find(e=>e.name===t)}}class $r{constructor(e){this.grammarConfig=()=>e.parser.GrammarConfig}getComment(e){var t;return function(e){return"string"==typeof e.$comment}(e)?e.$comment:null===(t=(0,r.v)(e.$cstNode,this.grammarConfig().multilineCommentRules))||void 0===t?void 0:t.text}}class zr{constructor(e){this.syncParser=e.parser.LangiumParser}parse(e,t){return Promise.resolve(this.syncParser.parse(e))}}class Hr{constructor(){this.previousTokenSource=new ca.Qi,this.writeQueue=[],this.readQueue=[],this.done=!0}write(e){this.cancelWrite();const t=(ha=performance.now(),new ca.Qi);return this.previousTokenSource=t,this.enqueue(this.writeQueue,e,t.token)}read(e){return this.enqueue(this.readQueue,e)}enqueue(e,t,a=ca.XO.None){const r=new ya,n={action:t,deferred:r,cancellationToken:a};return e.push(n),this.performNextOperation(),r.promise}async performNextOperation(){if(!this.done)return;const e=[];if(this.writeQueue.length>0)e.push(this.writeQueue.shift());else{if(!(this.readQueue.length>0))return;e.push(...this.readQueue.splice(0,this.readQueue.length))}this.done=!1,await Promise.all(e.map(async({action:e,deferred:t,cancellationToken:a})=>{try{const r=await Promise.resolve().then(()=>e(a));t.resolve(r)}catch(r){ua(r)?t.resolve(void 0):t.reject(r)}})),this.done=!0,this.performNextOperation()}cancelWrite(){this.previousTokenSource.cancel()}}class Or{constructor(e){this.grammarElementIdMap=new qa,this.tokenTypeIdMap=new qa,this.grammar=e.Grammar,this.lexer=e.parser.Lexer,this.linker=e.references.Linker}dehydrate(e){return{lexerErrors:e.lexerErrors,lexerReport:e.lexerReport?this.dehydrateLexerReport(e.lexerReport):void 0,parserErrors:e.parserErrors.map(e=>Object.assign(Object.assign({},e),{message:e.message})),value:this.dehydrateAstNode(e.value,this.createDehyrationContext(e.value))}}dehydrateLexerReport(e){return e}createDehyrationContext(e){const t=new Map,a=new Map;for(const r of(0,St.jm)(e))t.set(r,{});if(e.$cstNode)for(const n of(0,r.NS)(e.$cstNode))a.set(n,{});return{astNodes:t,cstNodes:a}}dehydrateAstNode(e,t){const a=t.astNodes.get(e);a.$type=e.$type,a.$containerIndex=e.$containerIndex,a.$containerProperty=e.$containerProperty,void 0!==e.$cstNode&&(a.$cstNode=this.dehydrateCstNode(e.$cstNode,t));for(const[r,n]of Object.entries(e))if(!r.startsWith("$"))if(Array.isArray(n)){const e=[];a[r]=e;for(const a of 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processing`,()=>{if(this.modes.push(a),!1===this.config.skipValidations&&this.TRACE_INIT("validatePatterns",()=>{this.lexerDefinitionErrors=this.lexerDefinitionErrors.concat(it(e,d))}),(0,i.A)(this.lexerDefinitionErrors)){let r;St(e),this.TRACE_INIT("analyzeTokenTypes",()=>{r=nt(e,{lineTerminatorCharacters:this.config.lineTerminatorCharacters,positionTracking:t.positionTracking,ensureOptimizations:t.ensureOptimizations,safeMode:t.safeMode,tracer:this.TRACE_INIT})}),this.patternIdxToConfig[a]=r.patternIdxToConfig,this.charCodeToPatternIdxToConfig[a]=r.charCodeToPatternIdxToConfig,this.emptyGroups=x({},this.emptyGroups,r.emptyGroups),this.hasCustom=r.hasCustom||this.hasCustom,this.canModeBeOptimized[a]=r.canBeOptimized}})}),this.defaultMode=a.defaultMode,!(0,i.A)(this.lexerDefinitionErrors)&&!this.config.deferDefinitionErrorsHandling){const e=(0,o.A)(this.lexerDefinitionErrors,e=>e.message).join("-----------------------\n");throw new Error("Errors detected in definition of Lexer:\n"+e)}(0,r.A)(this.lexerDefinitionWarning,e=>{je(e.message)}),this.TRACE_INIT("Choosing sub-methods implementations",()=>{if(rt?(this.chopInput=vt.A,this.match=this.matchWithTest):(this.updateLastIndex=xt.A,this.match=this.matchWithExec),n&&(this.handleModes=xt.A),!1===this.trackStartLines&&(this.computeNewColumn=vt.A),!1===this.trackEndLines&&(this.updateTokenEndLineColumnLocation=xt.A),/full/i.test(this.config.positionTracking))this.createTokenInstance=this.createFullToken;else if(/onlyStart/i.test(this.config.positionTracking))this.createTokenInstance=this.createStartOnlyToken;else{if(!/onlyOffset/i.test(this.config.positionTracking))throw Error(`Invalid config option: "${this.config.positionTracking}"`);this.createTokenInstance=this.createOffsetOnlyToken}this.hasCustom?(this.addToken=this.addTokenUsingPush,this.handlePayload=this.handlePayloadWithCustom):(this.addToken=this.addTokenUsingMemberAccess,this.handlePayload=this.handlePayloadNoCustom)}),this.TRACE_INIT("Failed Optimization Warnings",()=>{const e=(0,Ce.A)(this.canModeBeOptimized,(e,t,a)=>(!1===t&&e.push(a),e),[]);if(t.ensureOptimizations&&!(0,i.A)(e))throw Error(`Lexer Modes: < ${e.join(", ")} > cannot be optimized.\n\t Disable the "ensureOptimizations" lexer config flag to silently ignore this and run the lexer in an un-optimized mode.\n\t Or inspect the console log for details on how to resolve these issues.`)}),this.TRACE_INIT("clearRegExpParserCache",()=>{Fe={}}),this.TRACE_INIT("toFastProperties",()=>{h(this)})})}tokenize(e,t=this.defaultMode){if(!(0,i.A)(this.lexerDefinitionErrors)){const e=(0,o.A)(this.lexerDefinitionErrors,e=>e.message).join("-----------------------\n");throw new Error("Unable to Tokenize because Errors detected in definition of Lexer:\n"+e)}return this.tokenizeInternal(e,t)}tokenizeInternal(e,t){let a,n,i,o,c,s,h,d,l,u,p,y,k,f,m;const g=e,v=g.length;let x=0,L=0;const w=this.hasCustom?0:Math.floor(e.length/10),A=new Array(w),I=[];let C=this.trackStartLines?1:void 0,b=this.trackStartLines?1:void 0;const S=function(e){const t={},a=(0,M.A)(e);return(0,r.A)(a,a=>{const r=e[a];if(!(0,Y.A)(r))throw Error("non exhaustive match");t[a]=[]}),t}(this.emptyGroups),T=this.trackStartLines,R=this.config.lineTerminatorsPattern;let P=0,q=[],E=[];const $=[],z=[];let H;function O(){return q}function D(e){const t=Mt(e),a=E[t];return void 0===a?z:a}Object.freeze(z);const N=e=>{if(1===$.length&&void 0===e.tokenType.PUSH_MODE){const t=this.config.errorMessageProvider.buildUnableToPopLexerModeMessage(e);I.push({offset:e.startOffset,line:e.startLine,column:e.startColumn,length:e.image.length,message:t})}else{$.pop();const e=(0,Lt.A)($);q=this.patternIdxToConfig[e],E=this.charCodeToPatternIdxToConfig[e],P=q.length;const t=this.canModeBeOptimized[e]&&!1===this.config.safeMode;H=E&&t?D:O}};function V(e){$.push(e),E=this.charCodeToPatternIdxToConfig[e],q=this.patternIdxToConfig[e],P=q.length,P=q.length;const t=this.canModeBeOptimized[e]&&!1===this.config.safeMode;H=E&&t?D:O}let j;V.call(this,t);const F=this.config.recoveryEnabled;for(;xs.length){s=o,h=d,j=t;break}}}break}}if(null!==s){if(l=s.length,u=j.group,void 0!==u&&(p=j.tokenTypeIdx,y=this.createTokenInstance(s,x,p,j.tokenType,C,b,l),this.handlePayload(y,h),!1===u?L=this.addToken(A,L,y):S[u].push(y)),e=this.chopInput(e,l),x+=l,b=this.computeNewColumn(b,l),!0===T&&!0===j.canLineTerminator){let e,t,a=0;R.lastIndex=0;do{e=R.test(s),!0===e&&(t=R.lastIndex-1,a++)}while(!0===e);0!==a&&(C+=a,b=l-t,this.updateTokenEndLineColumnLocation(y,u,t,a,C,b,l))}this.handleModes(j,N,V,y)}else{const t=x,a=C,r=b;let i=!1===F;for(;!1===i&&x`Expecting ${Dt(e)?`--\x3e ${Ot(e)} <--`:`token of type --\x3e ${e.name} <--`} but found --\x3e '${t.image}' <--`,buildNotAllInputParsedMessage:({firstRedundant:e,ruleName:t})=>"Redundant input, expecting EOF but found: "+e.image,buildNoViableAltMessage({expectedPathsPerAlt:e,actual:t,previous:a,customUserDescription:r,ruleName:n}){const i="Expecting: ",c="\nbut found: '"+De(t).image+"'";if(r)return i+r+c;{const t=(0,Ce.A)(e,(e,t)=>e.concat(t),[]),a=(0,o.A)(t,e=>`[${(0,o.A)(e,e=>Ot(e)).join(", ")}]`);return i+`one of these possible Token sequences:\n${(0,o.A)(a,(e,t)=>` ${t+1}. ${e}`).join("\n")}`+c}},buildEarlyExitMessage({expectedIterationPaths:e,actual:t,customUserDescription:a,ruleName:r}){const n="Expecting: ",i="\nbut found: '"+De(t).image+"'";if(a)return n+a+i;return n+`expecting at least one iteration which starts with one of these possible Token sequences::\n <${(0,o.A)(e,e=>`[${(0,o.A)(e,e=>Ot(e)).join(",")}]`).join(" ,")}>`+i}};Object.freeze(Qt);const Jt={buildRuleNotFoundError:(e,t)=>"Invalid grammar, reference to a rule which is not defined: ->"+t.nonTerminalName+"<-\ninside top level rule: ->"+e.name+"<-"},ea={buildDuplicateFoundError(e,t){const a=e.name,r=De(t),n=r.idx,i=ce(r),o=(c=r)instanceof U?c.terminalType.name:c instanceof H?c.nonTerminalName:"";var c;let s=`->${i}${n>0?n:""}<- ${o?`with argument: ->${o}<-`:""}\n appears more than once (${t.length} times) in the top level rule: ->${a}<-. \n For further details see: https://chevrotain.io/docs/FAQ.html#NUMERICAL_SUFFIXES \n `;return s=s.replace(/[ \t]+/g," "),s=s.replace(/\s\s+/g,"\n"),s},buildNamespaceConflictError:e=>`Namespace conflict found in grammar.\nThe grammar has both a Terminal(Token) and a Non-Terminal(Rule) named: <${e.name}>.\nTo resolve this make sure each Terminal and Non-Terminal names are unique\nThis is easy to accomplish by using the convention that Terminal names start with an uppercase letter\nand Non-Terminal names start with a lower case letter.`,buildAlternationPrefixAmbiguityError(e){const t=(0,o.A)(e.prefixPath,e=>Ot(e)).join(", "),a=0===e.alternation.idx?"":e.alternation.idx;return`Ambiguous alternatives: <${e.ambiguityIndices.join(" ,")}> due to common lookahead prefix\nin inside <${e.topLevelRule.name}> Rule,\n<${t}> may appears as a prefix path in all these alternatives.\nSee: https://chevrotain.io/docs/guide/resolving_grammar_errors.html#COMMON_PREFIX\nFor Further details.`},buildAlternationAmbiguityError(e){const t=(0,o.A)(e.prefixPath,e=>Ot(e)).join(", "),a=0===e.alternation.idx?"":e.alternation.idx;let r=`Ambiguous Alternatives Detected: <${e.ambiguityIndices.join(" ,")}> in inside <${e.topLevelRule.name}> Rule,\n<${t}> may appears as a prefix path in all these alternatives.\n`;return r+="See: https://chevrotain.io/docs/guide/resolving_grammar_errors.html#AMBIGUOUS_ALTERNATIVES\nFor Further details.",r},buildEmptyRepetitionError(e){let t=ce(e.repetition);0!==e.repetition.idx&&(t+=e.repetition.idx);return`The repetition <${t}> within Rule <${e.topLevelRule.name}> can never consume any tokens.\nThis could lead to an infinite loop.`},buildTokenNameError:e=>"deprecated",buildEmptyAlternationError:e=>`Ambiguous empty alternative: <${e.emptyChoiceIdx+1}> in inside <${e.topLevelRule.name}> Rule.\nOnly the last alternative may be an empty alternative.`,buildTooManyAlternativesError:e=>`An Alternation cannot have more than 256 alternatives:\n inside <${e.topLevelRule.name}> Rule.\n has ${e.alternation.definition.length+1} alternatives.`,buildLeftRecursionError(e){const t=e.topLevelRule.name;return`Left Recursion found in grammar.\nrule: <${t}> can be invoked from itself (directly or indirectly)\nwithout consuming any Tokens. The grammar path that causes this is: \n ${`${t} --\x3e ${(0,o.A)(e.leftRecursionPath,e=>e.name).concat([t]).join(" --\x3e ")}`}\n To fix this refactor your grammar to remove the left recursion.\nsee: https://en.wikipedia.org/wiki/LL_parser#Left_factoring.`},buildInvalidRuleNameError:e=>"deprecated",buildDuplicateRuleNameError(e){let t;t=e.topLevelRule instanceof O?e.topLevelRule.name:e.topLevelRule;return`Duplicate definition, rule: ->${t}<- is already defined in the grammar: ->${e.grammarName}<-`}};class ta extends W{constructor(e,t){super(),this.nameToTopRule=e,this.errMsgProvider=t,this.errors=[]}resolveRefs(){(0,r.A)((0,n.A)(this.nameToTopRule),e=>{this.currTopLevel=e,e.accept(this)})}visitNonTerminal(e){const t=this.nameToTopRule[e.nonTerminalName];if(t)e.referencedRule=t;else{const t=this.errMsgProvider.buildRuleNotFoundError(this.currTopLevel,e);this.errors.push({message:t,type:qr.UNRESOLVED_SUBRULE_REF,ruleName:this.currTopLevel.name,unresolvedRefName:e.nonTerminalName})}}}var aa=a(8139),ra=a(2528);const na=function(e,t,a,r){for(var n=-1,i=null==e?0:e.length;++n{!1===(0,i.A)(e.definition)&&(n=c(e.definition))}),n;if(!(t instanceof U))throw Error("non exhaustive match");a.push(t.terminalType)}}o++}return n.push({partialPath:a,suffixDef:u(e,o)}),n}function ga(e,t,a,r){const n="EXIT_NONE_TERMINAL",o=[n],c="EXIT_ALTERNATIVE";let h=!1;const d=t.length,l=d-r-1,p=[],y=[];for(y.push({idx:-1,def:e,ruleStack:[],occurrenceStack:[]});!(0,i.A)(y);){const e=y.pop();if(e===c){h&&(0,Lt.A)(y).idx<=l&&y.pop();continue}const r=e.def,k=e.idx,f=e.ruleStack,m=e.occurrenceStack;if((0,i.A)(r))continue;const g=r[0];if(g===n){const e={idx:k,def:u(r),ruleStack:ha(f),occurrenceStack:ha(m)};y.push(e)}else if(g instanceof U)if(k=0;t--){const e={idx:k,def:g.definition[t].definition.concat(u(r)),ruleStack:f,occurrenceStack:m};y.push(e),y.push(c)}else if(g instanceof D)y.push({idx:k,def:g.definition.concat(u(r)),ruleStack:f,occurrenceStack:m});else{if(!(g instanceof O))throw Error("non exhaustive match");y.push(Ma(g,k,f,m))}}return p}function Ma(e,t,a,r){const n=(0,s.A)(a);n.push(e.name);const i=(0,s.A)(r);return i.push(1),{idx:t,def:e.definition,ruleStack:n,occurrenceStack:i}}var va;function xa(e){if(e instanceof N||"Option"===e)return va.OPTION;if(e instanceof F||"Repetition"===e)return va.REPETITION;if(e instanceof V||"RepetitionMandatory"===e)return va.REPETITION_MANDATORY;if(e instanceof j||"RepetitionMandatoryWithSeparator"===e)return va.REPETITION_MANDATORY_WITH_SEPARATOR;if(e instanceof B||"RepetitionWithSeparator"===e)return va.REPETITION_WITH_SEPARATOR;if(e instanceof _||"Alternation"===e)return va.ALTERNATION;throw Error("non exhaustive match")}function La(e){const{occurrence:t,rule:a,prodType:r,maxLookahead:n}=e,i=xa(r);return i===va.ALTERNATION?Pa(t,a,n):qa(t,a,i,n)}function wa(e,t,a,n){const i=e.length,s=ie(e,e=>ie(e,e=>1===e.length));if(t)return function(t){const r=(0,o.A)(t,e=>e.GATE);for(let n=0;n(0,ue.A)(e)),a=(0,Ce.A)(t,(e,t,a)=>((0,r.A)(t,t=>{(0,c.A)(e,t.tokenTypeIdx)||(e[t.tokenTypeIdx]=a),(0,r.A)(t.categoryMatches,t=>{(0,c.A)(e,t)||(e[t]=a)})}),e),{});return function(){const e=this.LA(1);return a[e.tokenTypeIdx]}}return function(){for(let t=0;t1===e.length),o=e.length;if(n&&!a){const t=(0,ue.A)(e);if(1===t.length&&(0,i.A)(t[0].categoryMatches)){const e=t[0].tokenTypeIdx;return function(){return this.LA(1).tokenTypeIdx===e}}{const e=(0,Ce.A)(t,(e,t,a)=>(e[t.tokenTypeIdx]=!0,(0,r.A)(t.categoryMatches,t=>{e[t]=!0}),e),[]);return function(){const t=this.LA(1);return!0===e[t.tokenTypeIdx]}}}return function(){e:for(let a=0;ama([e],1)),n=ba(a.length),c=(0,o.A)(a,e=>{const t={};return(0,r.A)(e,e=>{const a=Sa(e.partialPath);(0,r.A)(a,e=>{t[e]=!0})}),t});let s=a;for(let o=1;o<=t;o++){const e=s;s=ba(e.length);for(let a=0;a{const t=Sa(e.partialPath);(0,r.A)(t,e=>{c[a][e]=!0})})}}}}return n}function Pa(e,t,a,r){const n=new Ca(e,va.ALTERNATION,r);return t.accept(n),Ra(n.result,a)}function qa(e,t,a,r){const n=new Ca(e,a);t.accept(n);const i=n.result,o=new Ia(t,e,a).startWalking();return Ra([new D({definition:i}),new D({definition:o})],r)}function Ea(e,t){e:for(let a=0;aie(e,e=>ie(e,e=>(0,i.A)(e.categoryMatches))))}function za(e,t,a,i){const c=(0,aa.A)(e,e=>function(e,t){const a=new Da;e.accept(a);const r=a.allProductions,i=sa(r,Ha),c=C(i,e=>e.length>1),s=(0,o.A)((0,n.A)(c),a=>{const r=De(a),n=t.buildDuplicateFoundError(e,a),i=ce(r),o={message:n,type:qr.DUPLICATE_PRODUCTIONS,ruleName:e.name,dslName:i,occurrence:r.idx},c=Oa(r);return c&&(o.parameter=c),o});return s}(e,a)),s=function(e,t,a){const n=[],i=(0,o.A)(t,e=>e.name);return(0,r.A)(e,e=>{const t=e.name;if(ae(i,t)){const r=a.buildNamespaceConflictError(e);n.push({message:r,type:qr.CONFLICT_TOKENS_RULES_NAMESPACE,ruleName:t})}}),n}(e,t,a),h=(0,aa.A)(e,e=>function(e,t){const a=new ja;e.accept(a);const r=a.alternations,n=(0,aa.A)(r,a=>a.definition.length>255?[{message:t.buildTooManyAlternativesError({topLevelRule:e,alternation:a}),type:qr.TOO_MANY_ALTS,ruleName:e.name,occurrence:a.idx}]:[]);return n}(e,a)),d=(0,aa.A)(e,t=>function(e,t,a,r){const n=[],i=(0,Ce.A)(t,(t,a)=>a.name===e.name?t+1:t,0);if(i>1){const t=r.buildDuplicateRuleNameError({topLevelRule:e,grammarName:a});n.push({message:t,type:qr.DUPLICATE_RULE_NAME,ruleName:e.name})}return n}(t,e,i,a));return c.concat(s,h,d)}function Ha(e){return`${ce(e)}_#_${e.idx}_#_${Oa(e)}`}function Oa(e){return e instanceof U?e.terminalType.name:e instanceof H?e.nonTerminalName:""}class Da extends W{constructor(){super(...arguments),this.allProductions=[]}visitNonTerminal(e){this.allProductions.push(e)}visitOption(e){this.allProductions.push(e)}visitRepetitionWithSeparator(e){this.allProductions.push(e)}visitRepetitionMandatory(e){this.allProductions.push(e)}visitRepetitionMandatoryWithSeparator(e){this.allProductions.push(e)}visitRepetition(e){this.allProductions.push(e)}visitAlternation(e){this.allProductions.push(e)}visitTerminal(e){this.allProductions.push(e)}}function Na(e,t,a,r=[]){const n=[],o=Va(t.definition);if((0,i.A)(o))return[];{const t=e.name;ae(o,e)&&n.push({message:a.buildLeftRecursionError({topLevelRule:e,leftRecursionPath:r}),type:qr.LEFT_RECURSION,ruleName:t});const i=He(o,r.concat([e])),c=(0,aa.A)(i,t=>{const n=(0,s.A)(r);return n.push(t),Na(e,t,a,n)});return n.concat(c)}}function Va(e){let t=[];if((0,i.A)(e))return t;const a=De(e);if(a instanceof H)t.push(a.referencedRule);else if(a instanceof D||a instanceof N||a instanceof V||a instanceof j||a instanceof B||a instanceof F)t=t.concat(Va(a.definition));else if(a instanceof _)t=(0,ue.A)((0,o.A)(a.definition,e=>Va(e.definition)));else if(!(a instanceof U))throw Error("non exhaustive match");const r=oe(a),n=e.length>1;if(r&&n){const a=u(e);return t.concat(Va(a))}return t}class ja extends W{constructor(){super(...arguments),this.alternations=[]}visitAlternation(e){this.alternations.push(e)}}function Fa(e,t,a){const n=new ja;e.accept(n);let i=n.alternations;i=Le(i,e=>!0===e.ignoreAmbiguities);const c=(0,aa.A)(i,n=>{const i=n.idx,c=n.maxLookahead||t,s=Pa(i,e,c,n),h=function(e,t,a,n){const i=[],c=(0,Ce.A)(e,(a,n,o)=>(!0===t.definition[o].ignoreAmbiguities||(0,r.A)(n,n=>{const c=[o];(0,r.A)(e,(e,a)=>{o!==a&&Ea(e,n)&&!0!==t.definition[a].ignoreAmbiguities&&c.push(a)}),c.length>1&&!Ea(i,n)&&(i.push(n),a.push({alts:c,path:n}))}),a),[]),s=(0,o.A)(c,e=>{const r=(0,o.A)(e.alts,e=>e+1);return{message:n.buildAlternationAmbiguityError({topLevelRule:a,alternation:t,ambiguityIndices:r,prefixPath:e.path}),type:qr.AMBIGUOUS_ALTS,ruleName:a.name,occurrence:t.idx,alternatives:e.alts}});return s}(s,n,e,a),d=function(e,t,a,r){const n=(0,Ce.A)(e,(e,t,a)=>{const r=(0,o.A)(t,e=>({idx:a,path:e}));return e.concat(r)},[]),i=Oe((0,aa.A)(n,e=>{if(!0===t.definition[e.idx].ignoreAmbiguities)return[];const i=e.idx,c=e.path,s=(0,be.A)(n,e=>{return!0!==t.definition[e.idx].ignoreAmbiguities&&e.idx{const a=r[t];return e===a||a.categoryMatchesMap[e.tokenTypeIdx]}));var a,r});return(0,o.A)(s,e=>{const n=[e.idx+1,i+1],o=0===t.idx?"":t.idx;return{message:r.buildAlternationPrefixAmbiguityError({topLevelRule:a,alternation:t,ambiguityIndices:n,prefixPath:e.path}),type:qr.AMBIGUOUS_PREFIX_ALTS,ruleName:a.name,occurrence:o,alternatives:n}})}));return i}(s,n,e,a);return h.concat(d)});return c}class Ba extends W{constructor(){super(...arguments),this.allProductions=[]}visitRepetitionWithSeparator(e){this.allProductions.push(e)}visitRepetitionMandatory(e){this.allProductions.push(e)}visitRepetitionMandatoryWithSeparator(e){this.allProductions.push(e)}visitRepetition(e){this.allProductions.push(e)}}function _a(e){const t=(0,ge.A)(e,{errMsgProvider:Jt}),a={};return(0,r.A)(e.rules,e=>{a[e.name]=e}),function(e,t){const a=new ta(e,t);return a.resolveRefs(),a.errors}(a,t.errMsgProvider)}const Ua="MismatchedTokenException",Ga="NoViableAltException",Wa="EarlyExitException",Ka="NotAllInputParsedException",Za=[Ua,Ga,Wa,Ka];function Xa(e){return ae(Za,e.name)}Object.freeze(Za);class Ya extends Error{constructor(e,t){super(e),this.token=t,this.resyncedTokens=[],Object.setPrototypeOf(this,new.target.prototype),Error.captureStackTrace&&Error.captureStackTrace(this,this.constructor)}}class Qa extends Ya{constructor(e,t,a){super(e,t),this.previousToken=a,this.name=Ua}}class Ja extends Ya{constructor(e,t,a){super(e,t),this.previousToken=a,this.name=Ga}}class er extends Ya{constructor(e,t){super(e,t),this.name=Ka}}class tr extends Ya{constructor(e,t,a){super(e,t),this.previousToken=a,this.name=Wa}}const ar={},rr="InRuleRecoveryException";class nr extends Error{constructor(e){super(e),this.name=rr}}function ir(e,t,a,r,n,i,o){const c=this.getKeyForAutomaticLookahead(r,n);let s=this.firstAfterRepMap[c];if(void 0===s){const e=this.getCurrRuleFullName();s=new i(this.getGAstProductions()[e],n).startWalking(),this.firstAfterRepMap[c]=s}let h=s.token,d=s.occurrence;const l=s.isEndOfRule;1===this.RULE_STACK.length&&l&&void 0===h&&(h=Zt,d=1),void 0!==h&&void 0!==d&&this.shouldInRepetitionRecoveryBeTried(h,d,o)&&this.tryInRepetitionRecovery(e,t,a,h)}const or=1024,cr=1280,sr=1536;function hr(e,t,a){return a|t|e}class dr{constructor(e){var t;this.maxLookahead=null!==(t=null==e?void 0:e.maxLookahead)&&void 0!==t?t:Rr.maxLookahead}validate(e){const t=this.validateNoLeftRecursion(e.rules);if((0,i.A)(t)){const a=this.validateEmptyOrAlternatives(e.rules),r=this.validateAmbiguousAlternationAlternatives(e.rules,this.maxLookahead),n=this.validateSomeNonEmptyLookaheadPath(e.rules,this.maxLookahead);return[...t,...a,...r,...n]}return t}validateNoLeftRecursion(e){return(0,aa.A)(e,e=>Na(e,e,ea))}validateEmptyOrAlternatives(e){return(0,aa.A)(e,e=>function(e,t){const a=new ja;e.accept(a);const r=a.alternations;return(0,aa.A)(r,a=>{const r=ha(a.definition);return(0,aa.A)(r,(r,n)=>{const o=ga([r],[],At,1);return(0,i.A)(o)?[{message:t.buildEmptyAlternationError({topLevelRule:e,alternation:a,emptyChoiceIdx:n}),type:qr.NONE_LAST_EMPTY_ALT,ruleName:e.name,occurrence:a.idx,alternative:n+1}]:[]})})}(e,ea))}validateAmbiguousAlternationAlternatives(e,t){return(0,aa.A)(e,e=>Fa(e,t,ea))}validateSomeNonEmptyLookaheadPath(e,t){return function(e,t,a){const n=[];return(0,r.A)(e,e=>{const o=new Ba;e.accept(o);const c=o.allProductions;(0,r.A)(c,r=>{const o=xa(r),c=r.maxLookahead||t,s=qa(r.idx,e,o,c)[0];if((0,i.A)((0,ue.A)(s))){const t=a.buildEmptyRepetitionError({topLevelRule:e,repetition:r});n.push({message:t,type:qr.NO_NON_EMPTY_LOOKAHEAD,ruleName:e.name})}})}),n}(e,t,ea)}buildLookaheadForAlternation(e){return function(e,t,a,r,n,i){const o=Pa(e,t,a);return i(o,r,$a(o)?It:At,n)}(e.prodOccurrence,e.rule,e.maxLookahead,e.hasPredicates,e.dynamicTokensEnabled,wa)}buildLookaheadForOptional(e){return function(e,t,a,r,n,i){const o=qa(e,t,n,a),c=$a(o)?It:At;return i(o[0],c,r)}(e.prodOccurrence,e.rule,e.maxLookahead,e.dynamicTokensEnabled,xa(e.prodType),Aa)}}const lr=new class extends W{constructor(){super(...arguments),this.dslMethods={option:[],alternation:[],repetition:[],repetitionWithSeparator:[],repetitionMandatory:[],repetitionMandatoryWithSeparator:[]}}reset(){this.dslMethods={option:[],alternation:[],repetition:[],repetitionWithSeparator:[],repetitionMandatory:[],repetitionMandatoryWithSeparator:[]}}visitOption(e){this.dslMethods.option.push(e)}visitRepetitionWithSeparator(e){this.dslMethods.repetitionWithSeparator.push(e)}visitRepetitionMandatory(e){this.dslMethods.repetitionMandatory.push(e)}visitRepetitionMandatoryWithSeparator(e){this.dslMethods.repetitionMandatoryWithSeparator.push(e)}visitRepetition(e){this.dslMethods.repetition.push(e)}visitAlternation(e){this.dslMethods.alternation.push(e)}};function ur(e,t){!0===isNaN(e.startOffset)?(e.startOffset=t.startOffset,e.endOffset=t.endOffset):e.endOffset!1===(0,we.A)(e[t])),r=(0,o.A)(a,t=>({msg:`Missing visitor method: <${t}> on ${e.constructor.name} CST Visitor.`,type:mr.MISSING_METHOD,methodName:t}));return Oe(r)}(e,t);return a}(this,t);if(!(0,i.A)(e)){const t=(0,o.A)(e,e=>e.msg);throw Error(`Errors Detected in CST Visitor <${this.constructor.name}>:\n\t${t.join("\n\n").replace(/\n/g,"\n\t")}`)}}};return(a.prototype=r).constructor=a,a._RULE_NAMES=t,a}var mr;!function(e){e[e.REDUNDANT_METHOD=0]="REDUNDANT_METHOD",e[e.MISSING_METHOD=1]="MISSING_METHOD"}(mr||(mr={}));var gr=a(3149);const Mr={description:"This Object indicates the Parser is during Recording Phase"};Object.freeze(Mr);const vr=!0,xr=Math.pow(2,8)-1,Lr=Kt({name:"RECORDING_PHASE_TOKEN",pattern:Ht.NA});St([Lr]);const wr=Xt(Lr,"This IToken indicates the Parser is in Recording Phase\n\tSee: https://chevrotain.io/docs/guide/internals.html#grammar-recording for details",-1,-1,-1,-1,-1,-1);Object.freeze(wr);const Ar={name:"This CSTNode indicates the Parser is in Recording Phase\n\tSee: https://chevrotain.io/docs/guide/internals.html#grammar-recording for details",children:{}};function Ir(e,t,a,r=!1){Sr(a);const n=(0,Lt.A)(this.recordingProdStack),i=(0,we.A)(t)?t:t.DEF,o=new e({definition:[],idx:a});return r&&(o.separator=t.SEP),(0,c.A)(t,"MAX_LOOKAHEAD")&&(o.maxLookahead=t.MAX_LOOKAHEAD),this.recordingProdStack.push(o),i.call(this),n.definition.push(o),this.recordingProdStack.pop(),Mr}function Cr(e,t){Sr(t);const a=(0,Lt.A)(this.recordingProdStack),n=!1===(0,Y.A)(e),i=!1===n?e:e.DEF,o=new _({definition:[],idx:t,ignoreAmbiguities:n&&!0===e.IGNORE_AMBIGUITIES});(0,c.A)(e,"MAX_LOOKAHEAD")&&(o.maxLookahead=e.MAX_LOOKAHEAD);const s=J(i,e=>(0,we.A)(e.GATE));return o.hasPredicates=s,a.definition.push(o),(0,r.A)(i,e=>{const t=new D({definition:[]});o.definition.push(t),(0,c.A)(e,"IGNORE_AMBIGUITIES")?t.ignoreAmbiguities=e.IGNORE_AMBIGUITIES:(0,c.A)(e,"GATE")&&(t.ignoreAmbiguities=!0),this.recordingProdStack.push(t),e.ALT.call(this),this.recordingProdStack.pop()}),Mr}function br(e){return 0===e?"":`${e}`}function Sr(e){if(e<0||e>xr){const t=new Error(`Invalid DSL Method idx value: <${e}>\n\tIdx value must be a none negative value smaller than ${xr+1}`);throw t.KNOWN_RECORDER_ERROR=!0,t}}const Tr=Xt(Zt,"",NaN,NaN,NaN,NaN,NaN,NaN);Object.freeze(Tr);const Rr=Object.freeze({recoveryEnabled:!1,maxLookahead:3,dynamicTokensEnabled:!1,outputCst:!0,errorMessageProvider:Qt,nodeLocationTracking:"none",traceInitPerf:!1,skipValidations:!1}),Pr=Object.freeze({recoveryValueFunc:()=>{},resyncEnabled:!0});var qr,Er;function $r(e=void 0){return function(){return e}}!function(e){e[e.INVALID_RULE_NAME=0]="INVALID_RULE_NAME",e[e.DUPLICATE_RULE_NAME=1]="DUPLICATE_RULE_NAME",e[e.INVALID_RULE_OVERRIDE=2]="INVALID_RULE_OVERRIDE",e[e.DUPLICATE_PRODUCTIONS=3]="DUPLICATE_PRODUCTIONS",e[e.UNRESOLVED_SUBRULE_REF=4]="UNRESOLVED_SUBRULE_REF",e[e.LEFT_RECURSION=5]="LEFT_RECURSION",e[e.NONE_LAST_EMPTY_ALT=6]="NONE_LAST_EMPTY_ALT",e[e.AMBIGUOUS_ALTS=7]="AMBIGUOUS_ALTS",e[e.CONFLICT_TOKENS_RULES_NAMESPACE=8]="CONFLICT_TOKENS_RULES_NAMESPACE",e[e.INVALID_TOKEN_NAME=9]="INVALID_TOKEN_NAME",e[e.NO_NON_EMPTY_LOOKAHEAD=10]="NO_NON_EMPTY_LOOKAHEAD",e[e.AMBIGUOUS_PREFIX_ALTS=11]="AMBIGUOUS_PREFIX_ALTS",e[e.TOO_MANY_ALTS=12]="TOO_MANY_ALTS",e[e.CUSTOM_LOOKAHEAD_VALIDATION=13]="CUSTOM_LOOKAHEAD_VALIDATION"}(qr||(qr={}));class zr{static performSelfAnalysis(e){throw Error("The **static** `performSelfAnalysis` method has been deprecated.\t\nUse the **instance** method with the same name instead.")}performSelfAnalysis(){this.TRACE_INIT("performSelfAnalysis",()=>{let e;this.selfAnalysisDone=!0;const t=this.className;this.TRACE_INIT("toFastProps",()=>{h(this)}),this.TRACE_INIT("Grammar Recording",()=>{try{this.enableRecording(),(0,r.A)(this.definedRulesNames,e=>{const t=this[e].originalGrammarAction;let a;this.TRACE_INIT(`${e} Rule`,()=>{a=this.topLevelRuleRecord(e,t)}),this.gastProductionsCache[e]=a})}finally{this.disableRecording()}});let a=[];if(this.TRACE_INIT("Grammar Resolving",()=>{a=_a({rules:(0,n.A)(this.gastProductionsCache)}),this.definitionErrors=this.definitionErrors.concat(a)}),this.TRACE_INIT("Grammar Validations",()=>{if((0,i.A)(a)&&!1===this.skipValidations){const a=(e={rules:(0,n.A)(this.gastProductionsCache),tokenTypes:(0,n.A)(this.tokensMap),errMsgProvider:ea,grammarName:t},za((e=(0,ge.A)(e,{errMsgProvider:ea})).rules,e.tokenTypes,e.errMsgProvider,e.grammarName)),r=function(e){const t=e.lookaheadStrategy.validate({rules:e.rules,tokenTypes:e.tokenTypes,grammarName:e.grammarName});return(0,o.A)(t,e=>Object.assign({type:qr.CUSTOM_LOOKAHEAD_VALIDATION},e))}({lookaheadStrategy:this.lookaheadStrategy,rules:(0,n.A)(this.gastProductionsCache),tokenTypes:(0,n.A)(this.tokensMap),grammarName:t});this.definitionErrors=this.definitionErrors.concat(a,r)}var e}),(0,i.A)(this.definitionErrors)&&(this.recoveryEnabled&&this.TRACE_INIT("computeAllProdsFollows",()=>{const e=function(e){const t={};return(0,r.A)(e,e=>{const a=new ke(e).startWalking();x(t,a)}),t}((0,n.A)(this.gastProductionsCache));this.resyncFollows=e}),this.TRACE_INIT("ComputeLookaheadFunctions",()=>{var e,t;null===(t=(e=this.lookaheadStrategy).initialize)||void 0===t||t.call(e,{rules:(0,n.A)(this.gastProductionsCache)}),this.preComputeLookaheadFunctions((0,n.A)(this.gastProductionsCache))})),!zr.DEFER_DEFINITION_ERRORS_HANDLING&&!(0,i.A)(this.definitionErrors))throw e=(0,o.A)(this.definitionErrors,e=>e.message),new Error(`Parser Definition Errors detected:\n ${e.join("\n-------------------------------\n")}`)})}constructor(e,t){this.definitionErrors=[],this.selfAnalysisDone=!1;const a=this;if(a.initErrorHandler(t),a.initLexerAdapter(),a.initLooksAhead(t),a.initRecognizerEngine(e,t),a.initRecoverable(t),a.initTreeBuilder(t),a.initContentAssist(),a.initGastRecorder(t),a.initPerformanceTracer(t),(0,c.A)(t,"ignoredIssues"))throw new Error("The IParserConfig property has been deprecated.\n\tPlease use the flag on the relevant DSL method instead.\n\tSee: https://chevrotain.io/docs/guide/resolving_grammar_errors.html#IGNORING_AMBIGUITIES\n\tFor further details.");this.skipValidations=(0,c.A)(t,"skipValidations")?t.skipValidations:Rr.skipValidations}}zr.DEFER_DEFINITION_ERRORS_HANDLING=!1,Er=zr,[class{initRecoverable(e){this.firstAfterRepMap={},this.resyncFollows={},this.recoveryEnabled=(0,c.A)(e,"recoveryEnabled")?e.recoveryEnabled:Rr.recoveryEnabled,this.recoveryEnabled&&(this.attemptInRepetitionRecovery=ir)}getTokenToInsert(e){const t=Xt(e,"",NaN,NaN,NaN,NaN,NaN,NaN);return t.isInsertedInRecovery=!0,t}canTokenTypeBeInsertedInRecovery(e){return!0}canTokenTypeBeDeletedInRecovery(e){return!0}tryInRepetitionRecovery(e,t,a,r){const n=this.findReSyncTokenType(),i=this.exportLexerState(),o=[];let c=!1;const s=this.LA(1);let h=this.LA(1);const d=()=>{const e=this.LA(0),t=this.errorMessageProvider.buildMismatchTokenMessage({expected:r,actual:s,previous:e,ruleName:this.getCurrRuleFullName()}),a=new Qa(t,s,this.LA(0));a.resyncedTokens=ha(o),this.SAVE_ERROR(a)};for(;!c;){if(this.tokenMatcher(h,r))return void d();if(a.call(this))return d(),void e.apply(this,t);this.tokenMatcher(h,n)?c=!0:(h=this.SKIP_TOKEN(),this.addToResyncTokens(h,o))}this.importLexerState(i)}shouldInRepetitionRecoveryBeTried(e,t,a){return!1!==a&&!this.tokenMatcher(this.LA(1),e)&&!this.isBackTracking()&&!this.canPerformInRuleRecovery(e,this.getFollowsForInRuleRecovery(e,t))}getFollowsForInRuleRecovery(e,t){const a=this.getCurrentGrammarPath(e,t);return this.getNextPossibleTokenTypes(a)}tryInRuleRecovery(e,t){if(this.canRecoverWithSingleTokenInsertion(e,t))return this.getTokenToInsert(e);if(this.canRecoverWithSingleTokenDeletion(e)){const e=this.SKIP_TOKEN();return this.consumeToken(),e}throw new nr("sad sad panda")}canPerformInRuleRecovery(e,t){return this.canRecoverWithSingleTokenInsertion(e,t)||this.canRecoverWithSingleTokenDeletion(e)}canRecoverWithSingleTokenInsertion(e,t){if(!this.canTokenTypeBeInsertedInRecovery(e))return!1;if((0,i.A)(t))return!1;const a=this.LA(1);return void 0!==(0,Ne.A)(t,e=>this.tokenMatcher(a,e))}canRecoverWithSingleTokenDeletion(e){return!!this.canTokenTypeBeDeletedInRecovery(e)&&this.tokenMatcher(this.LA(2),e)}isInCurrentRuleReSyncSet(e){const t=this.getCurrFollowKey(),a=this.getFollowSetFromFollowKey(t);return ae(a,e)}findReSyncTokenType(){const e=this.flattenFollowSet();let t=this.LA(1),a=2;for(;;){const r=(0,Ne.A)(e,e=>Yt(t,e));if(void 0!==r)return r;t=this.LA(a),a++}}getCurrFollowKey(){if(1===this.RULE_STACK.length)return ar;const e=this.getLastExplicitRuleShortName(),t=this.getLastExplicitRuleOccurrenceIndex(),a=this.getPreviousExplicitRuleShortName();return{ruleName:this.shortRuleNameToFullName(e),idxInCallingRule:t,inRule:this.shortRuleNameToFullName(a)}}buildFullFollowKeyStack(){const e=this.RULE_STACK,t=this.RULE_OCCURRENCE_STACK;return(0,o.A)(e,(a,r)=>0===r?ar:{ruleName:this.shortRuleNameToFullName(a),idxInCallingRule:t[r],inRule:this.shortRuleNameToFullName(e[r-1])})}flattenFollowSet(){const e=(0,o.A)(this.buildFullFollowKeyStack(),e=>this.getFollowSetFromFollowKey(e));return(0,ue.A)(e)}getFollowSetFromFollowKey(e){if(e===ar)return[Zt];const t=e.ruleName+e.idxInCallingRule+ye+e.inRule;return this.resyncFollows[t]}addToResyncTokens(e,t){return this.tokenMatcher(e,Zt)||t.push(e),t}reSyncTo(e){const t=[];let a=this.LA(1);for(;!1===this.tokenMatcher(a,e);)a=this.SKIP_TOKEN(),this.addToResyncTokens(a,t);return ha(t)}attemptInRepetitionRecovery(e,t,a,r,n,i,o){}getCurrentGrammarPath(e,t){return{ruleStack:this.getHumanReadableRuleStack(),occurrenceStack:(0,s.A)(this.RULE_OCCURRENCE_STACK),lastTok:e,lastTokOccurrence:t}}getHumanReadableRuleStack(){return(0,o.A)(this.RULE_STACK,e=>this.shortRuleNameToFullName(e))}},class{initLooksAhead(e){this.dynamicTokensEnabled=(0,c.A)(e,"dynamicTokensEnabled")?e.dynamicTokensEnabled:Rr.dynamicTokensEnabled,this.maxLookahead=(0,c.A)(e,"maxLookahead")?e.maxLookahead:Rr.maxLookahead,this.lookaheadStrategy=(0,c.A)(e,"lookaheadStrategy")?e.lookaheadStrategy:new dr({maxLookahead:this.maxLookahead}),this.lookAheadFuncsCache=new Map}preComputeLookaheadFunctions(e){(0,r.A)(e,e=>{this.TRACE_INIT(`${e.name} Rule Lookahead`,()=>{const{alternation:t,repetition:a,option:n,repetitionMandatory:i,repetitionMandatoryWithSeparator:o,repetitionWithSeparator:c}=function(e){lr.reset(),e.accept(lr);const t=lr.dslMethods;return lr.reset(),t}(e);(0,r.A)(t,t=>{const a=0===t.idx?"":t.idx;this.TRACE_INIT(`${ce(t)}${a}`,()=>{const a=this.lookaheadStrategy.buildLookaheadForAlternation({prodOccurrence:t.idx,rule:e,maxLookahead:t.maxLookahead||this.maxLookahead,hasPredicates:t.hasPredicates,dynamicTokensEnabled:this.dynamicTokensEnabled}),r=hr(this.fullRuleNameToShort[e.name],256,t.idx);this.setLaFuncCache(r,a)})}),(0,r.A)(a,t=>{this.computeLookaheadFunc(e,t.idx,768,"Repetition",t.maxLookahead,ce(t))}),(0,r.A)(n,t=>{this.computeLookaheadFunc(e,t.idx,512,"Option",t.maxLookahead,ce(t))}),(0,r.A)(i,t=>{this.computeLookaheadFunc(e,t.idx,or,"RepetitionMandatory",t.maxLookahead,ce(t))}),(0,r.A)(o,t=>{this.computeLookaheadFunc(e,t.idx,sr,"RepetitionMandatoryWithSeparator",t.maxLookahead,ce(t))}),(0,r.A)(c,t=>{this.computeLookaheadFunc(e,t.idx,cr,"RepetitionWithSeparator",t.maxLookahead,ce(t))})})})}computeLookaheadFunc(e,t,a,r,n,i){this.TRACE_INIT(`${i}${0===t?"":t}`,()=>{const i=this.lookaheadStrategy.buildLookaheadForOptional({prodOccurrence:t,rule:e,maxLookahead:n||this.maxLookahead,dynamicTokensEnabled:this.dynamicTokensEnabled,prodType:r}),o=hr(this.fullRuleNameToShort[e.name],a,t);this.setLaFuncCache(o,i)})}getKeyForAutomaticLookahead(e,t){return hr(this.getLastExplicitRuleShortName(),e,t)}getLaFuncFromCache(e){return this.lookAheadFuncsCache.get(e)}setLaFuncCache(e,t){this.lookAheadFuncsCache.set(e,t)}},class{initTreeBuilder(e){if(this.CST_STACK=[],this.outputCst=e.outputCst,this.nodeLocationTracking=(0,c.A)(e,"nodeLocationTracking")?e.nodeLocationTracking:Rr.nodeLocationTracking,this.outputCst)if(/full/i.test(this.nodeLocationTracking))this.recoveryEnabled?(this.setNodeLocationFromToken=pr,this.setNodeLocationFromNode=pr,this.cstPostRule=xt.A,this.setInitialNodeLocation=this.setInitialNodeLocationFullRecovery):(this.setNodeLocationFromToken=xt.A,this.setNodeLocationFromNode=xt.A,this.cstPostRule=this.cstPostRuleFull,this.setInitialNodeLocation=this.setInitialNodeLocationFullRegular);else if(/onlyOffset/i.test(this.nodeLocationTracking))this.recoveryEnabled?(this.setNodeLocationFromToken=ur,this.setNodeLocationFromNode=ur,this.cstPostRule=xt.A,this.setInitialNodeLocation=this.setInitialNodeLocationOnlyOffsetRecovery):(this.setNodeLocationFromToken=xt.A,this.setNodeLocationFromNode=xt.A,this.cstPostRule=this.cstPostRuleOnlyOffset,this.setInitialNodeLocation=this.setInitialNodeLocationOnlyOffsetRegular);else{if(!/none/i.test(this.nodeLocationTracking))throw Error(`Invalid config option: "${e.nodeLocationTracking}"`);this.setNodeLocationFromToken=xt.A,this.setNodeLocationFromNode=xt.A,this.cstPostRule=xt.A,this.setInitialNodeLocation=xt.A}else this.cstInvocationStateUpdate=xt.A,this.cstFinallyStateUpdate=xt.A,this.cstPostTerminal=xt.A,this.cstPostNonTerminal=xt.A,this.cstPostRule=xt.A}setInitialNodeLocationOnlyOffsetRecovery(e){e.location={startOffset:NaN,endOffset:NaN}}setInitialNodeLocationOnlyOffsetRegular(e){e.location={startOffset:this.LA(1).startOffset,endOffset:NaN}}setInitialNodeLocationFullRecovery(e){e.location={startOffset:NaN,startLine:NaN,startColumn:NaN,endOffset:NaN,endLine:NaN,endColumn:NaN}}setInitialNodeLocationFullRegular(e){const t=this.LA(1);e.location={startOffset:t.startOffset,startLine:t.startLine,startColumn:t.startColumn,endOffset:NaN,endLine:NaN,endColumn:NaN}}cstInvocationStateUpdate(e){const t={name:e,children:Object.create(null)};this.setInitialNodeLocation(t),this.CST_STACK.push(t)}cstFinallyStateUpdate(){this.CST_STACK.pop()}cstPostRuleFull(e){const t=this.LA(0),a=e.location;a.startOffset<=t.startOffset==1?(a.endOffset=t.endOffset,a.endLine=t.endLine,a.endColumn=t.endColumn):(a.startOffset=NaN,a.startLine=NaN,a.startColumn=NaN)}cstPostRuleOnlyOffset(e){const t=this.LA(0),a=e.location;a.startOffset<=t.startOffset==1?a.endOffset=t.endOffset:a.startOffset=NaN}cstPostTerminal(e,t){const a=this.CST_STACK[this.CST_STACK.length-1];var r,n,i;n=t,i=e,void 0===(r=a).children[i]?r.children[i]=[n]:r.children[i].push(n),this.setNodeLocationFromToken(a.location,t)}cstPostNonTerminal(e,t){const a=this.CST_STACK[this.CST_STACK.length-1];!function(e,t,a){void 0===e.children[t]?e.children[t]=[a]:e.children[t].push(a)}(a,t,e),this.setNodeLocationFromNode(a.location,e.location)}getBaseCstVisitorConstructor(){if((0,fe.A)(this.baseCstVisitorConstructor)){const e=fr(this.className,(0,M.A)(this.gastProductionsCache));return this.baseCstVisitorConstructor=e,e}return this.baseCstVisitorConstructor}getBaseCstVisitorConstructorWithDefaults(){if((0,fe.A)(this.baseCstVisitorWithDefaultsConstructor)){const e=function(e,t,a){const n=function(){};yr(n,e+"BaseSemanticsWithDefaults");const i=Object.create(a.prototype);return(0,r.A)(t,e=>{i[e]=kr}),(n.prototype=i).constructor=n,n}(this.className,(0,M.A)(this.gastProductionsCache),this.getBaseCstVisitorConstructor());return this.baseCstVisitorWithDefaultsConstructor=e,e}return this.baseCstVisitorWithDefaultsConstructor}getLastExplicitRuleShortName(){const e=this.RULE_STACK;return e[e.length-1]}getPreviousExplicitRuleShortName(){const e=this.RULE_STACK;return e[e.length-2]}getLastExplicitRuleOccurrenceIndex(){const e=this.RULE_OCCURRENCE_STACK;return e[e.length-1]}},class{initLexerAdapter(){this.tokVector=[],this.tokVectorLength=0,this.currIdx=-1}set input(e){if(!0!==this.selfAnalysisDone)throw Error("Missing invocation at the end of the Parser's constructor.");this.reset(),this.tokVector=e,this.tokVectorLength=e.length}get input(){return this.tokVector}SKIP_TOKEN(){return this.currIdx<=this.tokVector.length-2?(this.consumeToken(),this.LA(1)):Tr}LA(e){const t=this.currIdx+e;return t<0||this.tokVectorLength<=t?Tr:this.tokVector[t]}consumeToken(){this.currIdx++}exportLexerState(){return this.currIdx}importLexerState(e){this.currIdx=e}resetLexerState(){this.currIdx=-1}moveToTerminatedState(){this.currIdx=this.tokVector.length-1}getLexerPosition(){return this.exportLexerState()}},class{initRecognizerEngine(e,t){if(this.className=this.constructor.name,this.shortRuleNameToFull={},this.fullRuleNameToShort={},this.ruleShortNameIdx=256,this.tokenMatcher=It,this.subruleIdx=0,this.definedRulesNames=[],this.tokensMap={},this.isBackTrackingStack=[],this.RULE_STACK=[],this.RULE_OCCURRENCE_STACK=[],this.gastProductionsCache={},(0,c.A)(t,"serializedGrammar"))throw Error("The Parser's configuration can no longer contain a property.\n\tSee: https://chevrotain.io/docs/changes/BREAKING_CHANGES.html#_6-0-0\n\tFor Further details.");if((0,Y.A)(e)){if((0,i.A)(e))throw Error("A Token Vocabulary cannot be empty.\n\tNote that the first argument for the parser constructor\n\tis no longer a Token vector (since v4.0).");if("number"==typeof e[0].startOffset)throw Error("The Parser constructor no longer accepts a token vector as the first argument.\n\tSee: https://chevrotain.io/docs/changes/BREAKING_CHANGES.html#_4-0-0\n\tFor Further details.")}if((0,Y.A)(e))this.tokensMap=(0,Ce.A)(e,(e,t)=>(e[t.name]=t,e),{});else if((0,c.A)(e,"modes")&&ie((0,ue.A)((0,n.A)(e.modes)),qt)){const t=(0,ue.A)((0,n.A)(e.modes)),a=le(t);this.tokensMap=(0,Ce.A)(a,(e,t)=>(e[t.name]=t,e),{})}else{if(!(0,gr.A)(e))throw new Error(" argument must be An Array of Token constructors, A dictionary of Token constructors or an IMultiModeLexerDefinition");this.tokensMap=(0,s.A)(e)}this.tokensMap.EOF=Zt;const a=(0,c.A)(e,"modes")?(0,ue.A)((0,n.A)(e.modes)):(0,n.A)(e),r=ie(a,e=>(0,i.A)(e.categoryMatches));this.tokenMatcher=r?It:At,St((0,n.A)(this.tokensMap))}defineRule(e,t,a){if(this.selfAnalysisDone)throw Error(`Grammar rule <${e}> may not be defined after the 'performSelfAnalysis' method has been called'\nMake sure that all grammar rule definitions are done before 'performSelfAnalysis' is called.`);const r=(0,c.A)(a,"resyncEnabled")?a.resyncEnabled:Pr.resyncEnabled,n=(0,c.A)(a,"recoveryValueFunc")?a.recoveryValueFunc:Pr.recoveryValueFunc,i=this.ruleShortNameIdx<<12;let o;return this.ruleShortNameIdx++,this.shortRuleNameToFull[i]=e,this.fullRuleNameToShort[e]=i,o=!0===this.outputCst?function(...a){try{this.ruleInvocationStateUpdate(i,e,this.subruleIdx),t.apply(this,a);const r=this.CST_STACK[this.CST_STACK.length-1];return this.cstPostRule(r),r}catch(o){return this.invokeRuleCatch(o,r,n)}finally{this.ruleFinallyStateUpdate()}}:function(...a){try{return this.ruleInvocationStateUpdate(i,e,this.subruleIdx),t.apply(this,a)}catch(o){return this.invokeRuleCatch(o,r,n)}finally{this.ruleFinallyStateUpdate()}},Object.assign(o,{ruleName:e,originalGrammarAction:t})}invokeRuleCatch(e,t,a){const r=1===this.RULE_STACK.length,n=t&&!this.isBackTracking()&&this.recoveryEnabled;if(Xa(e)){const t=e;if(n){const r=this.findReSyncTokenType();if(this.isInCurrentRuleReSyncSet(r)){if(t.resyncedTokens=this.reSyncTo(r),this.outputCst){const e=this.CST_STACK[this.CST_STACK.length-1];return e.recoveredNode=!0,e}return a(e)}if(this.outputCst){const e=this.CST_STACK[this.CST_STACK.length-1];e.recoveredNode=!0,t.partialCstResult=e}throw t}if(r)return this.moveToTerminatedState(),a(e);throw t}throw e}optionInternal(e,t){const a=this.getKeyForAutomaticLookahead(512,t);return this.optionInternalLogic(e,t,a)}optionInternalLogic(e,t,a){let r,n=this.getLaFuncFromCache(a);if("function"!=typeof e){r=e.DEF;const t=e.GATE;if(void 0!==t){const e=n;n=()=>t.call(this)&&e.call(this)}}else r=e;if(!0===n.call(this))return r.call(this)}atLeastOneInternal(e,t){const a=this.getKeyForAutomaticLookahead(or,e);return this.atLeastOneInternalLogic(e,t,a)}atLeastOneInternalLogic(e,t,a){let r,n=this.getLaFuncFromCache(a);if("function"!=typeof t){r=t.DEF;const e=t.GATE;if(void 0!==e){const t=n;n=()=>e.call(this)&&t.call(this)}}else r=t;if(!0!==n.call(this))throw this.raiseEarlyExitException(e,va.REPETITION_MANDATORY,t.ERR_MSG);{let e=this.doSingleRepetition(r);for(;!0===n.call(this)&&!0===e;)e=this.doSingleRepetition(r)}this.attemptInRepetitionRecovery(this.atLeastOneInternal,[e,t],n,or,e,ka)}atLeastOneSepFirstInternal(e,t){const a=this.getKeyForAutomaticLookahead(sr,e);this.atLeastOneSepFirstInternalLogic(e,t,a)}atLeastOneSepFirstInternalLogic(e,t,a){const r=t.DEF,n=t.SEP;if(!0!==this.getLaFuncFromCache(a).call(this))throw this.raiseEarlyExitException(e,va.REPETITION_MANDATORY_WITH_SEPARATOR,t.ERR_MSG);{r.call(this);const t=()=>this.tokenMatcher(this.LA(1),n);for(;!0===this.tokenMatcher(this.LA(1),n);)this.CONSUME(n),r.call(this);this.attemptInRepetitionRecovery(this.repetitionSepSecondInternal,[e,n,t,r,fa],t,sr,e,fa)}}manyInternal(e,t){const a=this.getKeyForAutomaticLookahead(768,e);return this.manyInternalLogic(e,t,a)}manyInternalLogic(e,t,a){let r,n=this.getLaFuncFromCache(a);if("function"!=typeof t){r=t.DEF;const e=t.GATE;if(void 0!==e){const t=n;n=()=>e.call(this)&&t.call(this)}}else r=t;let i=!0;for(;!0===n.call(this)&&!0===i;)i=this.doSingleRepetition(r);this.attemptInRepetitionRecovery(this.manyInternal,[e,t],n,768,e,pa,i)}manySepFirstInternal(e,t){const a=this.getKeyForAutomaticLookahead(cr,e);this.manySepFirstInternalLogic(e,t,a)}manySepFirstInternalLogic(e,t,a){const r=t.DEF,n=t.SEP;if(!0===this.getLaFuncFromCache(a).call(this)){r.call(this);const t=()=>this.tokenMatcher(this.LA(1),n);for(;!0===this.tokenMatcher(this.LA(1),n);)this.CONSUME(n),r.call(this);this.attemptInRepetitionRecovery(this.repetitionSepSecondInternal,[e,n,t,r,ya],t,cr,e,ya)}}repetitionSepSecondInternal(e,t,a,r,n){for(;a();)this.CONSUME(t),r.call(this);this.attemptInRepetitionRecovery(this.repetitionSepSecondInternal,[e,t,a,r,n],a,sr,e,n)}doSingleRepetition(e){const t=this.getLexerPosition();return e.call(this),this.getLexerPosition()>t}orInternal(e,t){const a=this.getKeyForAutomaticLookahead(256,t),r=(0,Y.A)(e)?e:e.DEF,n=this.getLaFuncFromCache(a).call(this,r);if(void 0!==n)return r[n].ALT.call(this);this.raiseNoAltException(t,e.ERR_MSG)}ruleFinallyStateUpdate(){if(this.RULE_STACK.pop(),this.RULE_OCCURRENCE_STACK.pop(),this.cstFinallyStateUpdate(),0===this.RULE_STACK.length&&!1===this.isAtEndOfInput()){const e=this.LA(1),t=this.errorMessageProvider.buildNotAllInputParsedMessage({firstRedundant:e,ruleName:this.getCurrRuleFullName()});this.SAVE_ERROR(new er(t,e))}}subruleInternal(e,t,a){let r;try{const n=void 0!==a?a.ARGS:void 0;return this.subruleIdx=t,r=e.apply(this,n),this.cstPostNonTerminal(r,void 0!==a&&void 0!==a.LABEL?a.LABEL:e.ruleName),r}catch(n){throw this.subruleInternalError(n,a,e.ruleName)}}subruleInternalError(e,t,a){throw Xa(e)&&void 0!==e.partialCstResult&&(this.cstPostNonTerminal(e.partialCstResult,void 0!==t&&void 0!==t.LABEL?t.LABEL:a),delete e.partialCstResult),e}consumeInternal(e,t,a){let r;try{const t=this.LA(1);!0===this.tokenMatcher(t,e)?(this.consumeToken(),r=t):this.consumeInternalError(e,t,a)}catch(n){r=this.consumeInternalRecovery(e,t,n)}return this.cstPostTerminal(void 0!==a&&void 0!==a.LABEL?a.LABEL:e.name,r),r}consumeInternalError(e,t,a){let r;const n=this.LA(0);throw r=void 0!==a&&a.ERR_MSG?a.ERR_MSG:this.errorMessageProvider.buildMismatchTokenMessage({expected:e,actual:t,previous:n,ruleName:this.getCurrRuleFullName()}),this.SAVE_ERROR(new Qa(r,t,n))}consumeInternalRecovery(e,t,a){if(!this.recoveryEnabled||"MismatchedTokenException"!==a.name||this.isBackTracking())throw a;{const n=this.getFollowsForInRuleRecovery(e,t);try{return this.tryInRuleRecovery(e,n)}catch(r){throw r.name===rr?a:r}}}saveRecogState(){const e=this.errors,t=(0,s.A)(this.RULE_STACK);return{errors:e,lexerState:this.exportLexerState(),RULE_STACK:t,CST_STACK:this.CST_STACK}}reloadRecogState(e){this.errors=e.errors,this.importLexerState(e.lexerState),this.RULE_STACK=e.RULE_STACK}ruleInvocationStateUpdate(e,t,a){this.RULE_OCCURRENCE_STACK.push(a),this.RULE_STACK.push(e),this.cstInvocationStateUpdate(t)}isBackTracking(){return 0!==this.isBackTrackingStack.length}getCurrRuleFullName(){const e=this.getLastExplicitRuleShortName();return this.shortRuleNameToFull[e]}shortRuleNameToFullName(e){return this.shortRuleNameToFull[e]}isAtEndOfInput(){return this.tokenMatcher(this.LA(1),Zt)}reset(){this.resetLexerState(),this.subruleIdx=0,this.isBackTrackingStack=[],this.errors=[],this.RULE_STACK=[],this.CST_STACK=[],this.RULE_OCCURRENCE_STACK=[]}},class{ACTION(e){return e.call(this)}consume(e,t,a){return this.consumeInternal(t,e,a)}subrule(e,t,a){return this.subruleInternal(t,e,a)}option(e,t){return this.optionInternal(t,e)}or(e,t){return this.orInternal(t,e)}many(e,t){return this.manyInternal(e,t)}atLeastOne(e,t){return this.atLeastOneInternal(e,t)}CONSUME(e,t){return this.consumeInternal(e,0,t)}CONSUME1(e,t){return this.consumeInternal(e,1,t)}CONSUME2(e,t){return this.consumeInternal(e,2,t)}CONSUME3(e,t){return this.consumeInternal(e,3,t)}CONSUME4(e,t){return this.consumeInternal(e,4,t)}CONSUME5(e,t){return this.consumeInternal(e,5,t)}CONSUME6(e,t){return this.consumeInternal(e,6,t)}CONSUME7(e,t){return this.consumeInternal(e,7,t)}CONSUME8(e,t){return this.consumeInternal(e,8,t)}CONSUME9(e,t){return this.consumeInternal(e,9,t)}SUBRULE(e,t){return this.subruleInternal(e,0,t)}SUBRULE1(e,t){return this.subruleInternal(e,1,t)}SUBRULE2(e,t){return this.subruleInternal(e,2,t)}SUBRULE3(e,t){return this.subruleInternal(e,3,t)}SUBRULE4(e,t){return this.subruleInternal(e,4,t)}SUBRULE5(e,t){return this.subruleInternal(e,5,t)}SUBRULE6(e,t){return this.subruleInternal(e,6,t)}SUBRULE7(e,t){return this.subruleInternal(e,7,t)}SUBRULE8(e,t){return this.subruleInternal(e,8,t)}SUBRULE9(e,t){return this.subruleInternal(e,9,t)}OPTION(e){return this.optionInternal(e,0)}OPTION1(e){return this.optionInternal(e,1)}OPTION2(e){return this.optionInternal(e,2)}OPTION3(e){return this.optionInternal(e,3)}OPTION4(e){return this.optionInternal(e,4)}OPTION5(e){return this.optionInternal(e,5)}OPTION6(e){return this.optionInternal(e,6)}OPTION7(e){return this.optionInternal(e,7)}OPTION8(e){return this.optionInternal(e,8)}OPTION9(e){return this.optionInternal(e,9)}OR(e){return this.orInternal(e,0)}OR1(e){return this.orInternal(e,1)}OR2(e){return this.orInternal(e,2)}OR3(e){return this.orInternal(e,3)}OR4(e){return this.orInternal(e,4)}OR5(e){return this.orInternal(e,5)}OR6(e){return this.orInternal(e,6)}OR7(e){return this.orInternal(e,7)}OR8(e){return this.orInternal(e,8)}OR9(e){return this.orInternal(e,9)}MANY(e){this.manyInternal(0,e)}MANY1(e){this.manyInternal(1,e)}MANY2(e){this.manyInternal(2,e)}MANY3(e){this.manyInternal(3,e)}MANY4(e){this.manyInternal(4,e)}MANY5(e){this.manyInternal(5,e)}MANY6(e){this.manyInternal(6,e)}MANY7(e){this.manyInternal(7,e)}MANY8(e){this.manyInternal(8,e)}MANY9(e){this.manyInternal(9,e)}MANY_SEP(e){this.manySepFirstInternal(0,e)}MANY_SEP1(e){this.manySepFirstInternal(1,e)}MANY_SEP2(e){this.manySepFirstInternal(2,e)}MANY_SEP3(e){this.manySepFirstInternal(3,e)}MANY_SEP4(e){this.manySepFirstInternal(4,e)}MANY_SEP5(e){this.manySepFirstInternal(5,e)}MANY_SEP6(e){this.manySepFirstInternal(6,e)}MANY_SEP7(e){this.manySepFirstInternal(7,e)}MANY_SEP8(e){this.manySepFirstInternal(8,e)}MANY_SEP9(e){this.manySepFirstInternal(9,e)}AT_LEAST_ONE(e){this.atLeastOneInternal(0,e)}AT_LEAST_ONE1(e){return this.atLeastOneInternal(1,e)}AT_LEAST_ONE2(e){this.atLeastOneInternal(2,e)}AT_LEAST_ONE3(e){this.atLeastOneInternal(3,e)}AT_LEAST_ONE4(e){this.atLeastOneInternal(4,e)}AT_LEAST_ONE5(e){this.atLeastOneInternal(5,e)}AT_LEAST_ONE6(e){this.atLeastOneInternal(6,e)}AT_LEAST_ONE7(e){this.atLeastOneInternal(7,e)}AT_LEAST_ONE8(e){this.atLeastOneInternal(8,e)}AT_LEAST_ONE9(e){this.atLeastOneInternal(9,e)}AT_LEAST_ONE_SEP(e){this.atLeastOneSepFirstInternal(0,e)}AT_LEAST_ONE_SEP1(e){this.atLeastOneSepFirstInternal(1,e)}AT_LEAST_ONE_SEP2(e){this.atLeastOneSepFirstInternal(2,e)}AT_LEAST_ONE_SEP3(e){this.atLeastOneSepFirstInternal(3,e)}AT_LEAST_ONE_SEP4(e){this.atLeastOneSepFirstInternal(4,e)}AT_LEAST_ONE_SEP5(e){this.atLeastOneSepFirstInternal(5,e)}AT_LEAST_ONE_SEP6(e){this.atLeastOneSepFirstInternal(6,e)}AT_LEAST_ONE_SEP7(e){this.atLeastOneSepFirstInternal(7,e)}AT_LEAST_ONE_SEP8(e){this.atLeastOneSepFirstInternal(8,e)}AT_LEAST_ONE_SEP9(e){this.atLeastOneSepFirstInternal(9,e)}RULE(e,t,a=Pr){if(ae(this.definedRulesNames,e)){const t={message:ea.buildDuplicateRuleNameError({topLevelRule:e,grammarName:this.className}),type:qr.DUPLICATE_RULE_NAME,ruleName:e};this.definitionErrors.push(t)}this.definedRulesNames.push(e);const r=this.defineRule(e,t,a);return this[e]=r,r}OVERRIDE_RULE(e,t,a=Pr){const r=function(e,t,a){const r=[];let n;return ae(t,e)||(n=`Invalid rule override, rule: ->${e}<- cannot be overridden in the grammar: ->${a}<-as it is not defined in any of the super grammars `,r.push({message:n,type:qr.INVALID_RULE_OVERRIDE,ruleName:e})),r}(e,this.definedRulesNames,this.className);this.definitionErrors=this.definitionErrors.concat(r);const n=this.defineRule(e,t,a);return this[e]=n,n}BACKTRACK(e,t){return function(){this.isBackTrackingStack.push(1);const a=this.saveRecogState();try{return e.apply(this,t),!0}catch(r){if(Xa(r))return!1;throw r}finally{this.reloadRecogState(a),this.isBackTrackingStack.pop()}}}getGAstProductions(){return this.gastProductionsCache}getSerializedGastProductions(){return e=(0,n.A)(this.gastProductionsCache),(0,o.A)(e,G);var e}},class{initErrorHandler(e){this._errors=[],this.errorMessageProvider=(0,c.A)(e,"errorMessageProvider")?e.errorMessageProvider:Rr.errorMessageProvider}SAVE_ERROR(e){if(Xa(e))return e.context={ruleStack:this.getHumanReadableRuleStack(),ruleOccurrenceStack:(0,s.A)(this.RULE_OCCURRENCE_STACK)},this._errors.push(e),e;throw Error("Trying to save an Error which is not a RecognitionException")}get errors(){return(0,s.A)(this._errors)}set errors(e){this._errors=e}raiseEarlyExitException(e,t,a){const r=this.getCurrRuleFullName(),n=qa(e,this.getGAstProductions()[r],t,this.maxLookahead)[0],i=[];for(let c=1;c<=this.maxLookahead;c++)i.push(this.LA(c));const o=this.errorMessageProvider.buildEarlyExitMessage({expectedIterationPaths:n,actual:i,previous:this.LA(0),customUserDescription:a,ruleName:r});throw this.SAVE_ERROR(new tr(o,this.LA(1),this.LA(0)))}raiseNoAltException(e,t){const a=this.getCurrRuleFullName(),r=Pa(e,this.getGAstProductions()[a],this.maxLookahead),n=[];for(let c=1;c<=this.maxLookahead;c++)n.push(this.LA(c));const i=this.LA(0),o=this.errorMessageProvider.buildNoViableAltMessage({expectedPathsPerAlt:r,actual:n,previous:i,customUserDescription:t,ruleName:this.getCurrRuleFullName()});throw this.SAVE_ERROR(new Ja(o,this.LA(1),i))}},class{initContentAssist(){}computeContentAssist(e,t){const a=this.gastProductionsCache[e];if((0,fe.A)(a))throw Error(`Rule ->${e}<- does not exist in this grammar.`);return ga([a],t,this.tokenMatcher,this.maxLookahead)}getNextPossibleTokenTypes(e){const t=De(e.ruleStack),a=this.getGAstProductions()[t];return new la(a,e).startWalking()}},class{initGastRecorder(e){this.recordingProdStack=[],this.RECORDING_PHASE=!1}enableRecording(){this.RECORDING_PHASE=!0,this.TRACE_INIT("Enable Recording",()=>{for(let e=0;e<10;e++){const t=e>0?e:"";this[`CONSUME${t}`]=function(t,a){return this.consumeInternalRecord(t,e,a)},this[`SUBRULE${t}`]=function(t,a){return this.subruleInternalRecord(t,e,a)},this[`OPTION${t}`]=function(t){return this.optionInternalRecord(t,e)},this[`OR${t}`]=function(t){return this.orInternalRecord(t,e)},this[`MANY${t}`]=function(t){this.manyInternalRecord(e,t)},this[`MANY_SEP${t}`]=function(t){this.manySepFirstInternalRecord(e,t)},this[`AT_LEAST_ONE${t}`]=function(t){this.atLeastOneInternalRecord(e,t)},this[`AT_LEAST_ONE_SEP${t}`]=function(t){this.atLeastOneSepFirstInternalRecord(e,t)}}this.consume=function(e,t,a){return this.consumeInternalRecord(t,e,a)},this.subrule=function(e,t,a){return this.subruleInternalRecord(t,e,a)},this.option=function(e,t){return this.optionInternalRecord(t,e)},this.or=function(e,t){return this.orInternalRecord(t,e)},this.many=function(e,t){this.manyInternalRecord(e,t)},this.atLeastOne=function(e,t){this.atLeastOneInternalRecord(e,t)},this.ACTION=this.ACTION_RECORD,this.BACKTRACK=this.BACKTRACK_RECORD,this.LA=this.LA_RECORD})}disableRecording(){this.RECORDING_PHASE=!1,this.TRACE_INIT("Deleting Recording methods",()=>{const e=this;for(let t=0;t<10;t++){const a=t>0?t:"";delete e[`CONSUME${a}`],delete e[`SUBRULE${a}`],delete e[`OPTION${a}`],delete e[`OR${a}`],delete e[`MANY${a}`],delete e[`MANY_SEP${a}`],delete e[`AT_LEAST_ONE${a}`],delete e[`AT_LEAST_ONE_SEP${a}`]}delete e.consume,delete e.subrule,delete e.option,delete e.or,delete e.many,delete e.atLeastOne,delete e.ACTION,delete e.BACKTRACK,delete e.LA})}ACTION_RECORD(e){}BACKTRACK_RECORD(e,t){return()=>!0}LA_RECORD(e){return Tr}topLevelRuleRecord(e,t){try{const a=new O({definition:[],name:e});return 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lusIcon:()=>im,MessageSquareQuote:()=>om,MessageSquareQuoteIcon:()=>om,MessageSquareReply:()=>cm,MessageSquareReplyIcon:()=>cm,MessageSquareShare:()=>sm,MessageSquareShareIcon:()=>sm,MessageSquareText:()=>hm,MessageSquareTextIcon:()=>hm,MessageSquareWarning:()=>dm,MessageSquareWarningIcon:()=>dm,MessageSquareX:()=>lm,MessageSquareXIcon:()=>lm,MessagesSquare:()=>pm,MessagesSquareIcon:()=>pm,Mic:()=>fm,Mic2:()=>km,Mic2Icon:()=>km,MicIcon:()=>fm,MicOff:()=>ym,MicOffIcon:()=>ym,MicVocal:()=>km,MicVocalIcon:()=>km,Microchip:()=>mm,MicrochipIcon:()=>mm,Microscope:()=>gm,MicroscopeIcon:()=>gm,Microwave:()=>Mm,MicrowaveIcon:()=>Mm,Milestone:()=>vm,MilestoneIcon:()=>vm,Milk:()=>Lm,MilkIcon:()=>Lm,MilkOff:()=>xm,MilkOffIcon:()=>xm,Minimize:()=>Am,Minimize2:()=>wm,Minimize2Icon:()=>wm,MinimizeIcon:()=>Am,Minus:()=>Im,MinusCircle:()=>Yi,MinusCircleIcon:()=>Yi,MinusIcon:()=>Im,MinusSquare:()=>NA,MinusSquareIcon:()=>NA,Monitor:()=>Dm,MonitorCheck:()=>Cm,MonitorCheckIcon:()=>Cm,MonitorCog:()=>bm,MonitorCogIcon:()=>bm,MonitorDot:()=>Sm,MonitorDotIcon:()=>Sm,MonitorDown:()=>Tm,MonitorDownIcon:()=>Tm,MonitorIcon:()=>Dm,MonitorOff:()=>Rm,MonitorOffIcon:()=>Rm,MonitorPause:()=>Pm,MonitorPauseIcon:()=>Pm,MonitorPlay:()=>qm,MonitorPlayIcon:()=>qm,MonitorSmartphone:()=>Em,MonitorSmartphoneIcon:()=>Em,MonitorSpeaker:()=>$m,MonitorSpeakerIcon:()=>$m,MonitorStop:()=>zm,MonitorStopIcon:()=>zm,MonitorUp:()=>Hm,MonitorUpIcon:()=>Hm,MonitorX:()=>Om,MonitorXIcon:()=>Om,Moon:()=>Vm,MoonIcon:()=>Vm,MoonStar:()=>Nm,MoonStarIcon:()=>Nm,MoreHorizontal:()=>xh,MoreHorizontalIcon:()=>xh,MoreVertical:()=>vh,MoreVerticalIcon:()=>vh,Mountain:()=>Bm,MountainIcon:()=>Bm,MountainSnow:()=>jm,MountainSnowIcon:()=>jm,Mouse:()=>Km,MouseIcon:()=>Km,MouseOff:()=>Fm,MouseOffIcon:()=>Fm,MousePointer:()=>Wm,MousePointer2:()=>_m,MousePointer2Icon:()=>_m,MousePointerBan:()=>Um,MousePointerBanIcon:()=>Um,MousePointerClick:()=>Gm,MousePointerClickIcon:()=>Gm,MousePointerIcon:()=>Wm,MousePointerSquareDashed:()=>SA,MousePointerSquareDashedIcon:()=>SA,Move:()=>sg,Move3D:()=>Zm,Move3DIcon:()=>Zm,Move3d:()=>Zm,Move3dIcon:()=>Zm,MoveDiagonal:()=>Ym,MoveDiagonal2:()=>Xm,MoveDiagonal2Icon:()=>Xm,MoveDiagonalIcon:()=>Ym,MoveDown:()=>eg,MoveDownIcon:()=>eg,MoveDownLeft:()=>Qm,MoveDownLeftIcon:()=>Qm,MoveDownRight:()=>Jm,MoveDownRightIcon:()=>Jm,MoveHorizontal:()=>tg,MoveHorizontalIcon:()=>tg,MoveIcon:()=>sg,MoveLeft:()=>ag,MoveLeftIcon:()=>ag,MoveRight:()=>rg,MoveRightIcon:()=>rg,MoveUp:()=>og,MoveUpIcon:()=>og,MoveUpLeft:()=>ng,MoveUpLeftIcon:()=>ng,MoveUpRight:()=>ig,MoveUpRightIcon:()=>ig,MoveVertical:()=>cg,MoveVerticalIcon:()=>cg,Music:()=>ug,Music2:()=>hg,Music2Icon:()=>hg,Music3:()=>dg,Music3Icon:()=>dg,Music4:()=>lg,Music4Icon:()=>lg,MusicIcon:()=>ug,Navigation:()=>fg,Navigation2:()=>yg,Navigation2Icon:()=>yg,Navigation2Off:()=>pg,Navigation2OffIcon:()=>pg,NavigationIcon:()=>fg,NavigationOff:()=>kg,NavigationOffIcon:()=>kg,Network:()=>mg,NetworkIcon:()=>mg,Newspaper:()=>gg,NewspaperIcon:()=>gg,Nfc:()=>Mg,NfcIcon:()=>Mg,NonBinary:()=>vg,NonBinaryIcon:()=>vg,Notebook:()=>Ag,NotebookIcon:()=>Ag,NotebookPen:()=>xg,NotebookPenIcon:()=>xg,NotebookTabs:()=>Lg,NotebookTabsIcon:()=>Lg,NotebookText:()=>wg,NotebookTextIcon:()=>wg,NotepadText:()=>Cg,NotepadTextDashed:()=>Ig,NotepadTextDashedIcon:()=>Ig,NotepadTextIcon:()=>Cg,Nut:()=>Sg,NutIcon:()=>Sg,NutOff:()=>bg,NutOffIcon:()=>bg,Octagon:()=>Eg,OctagonAlert:()=>Tg,OctagonAlertIcon:()=>Tg,OctagonIcon:()=>Eg,OctagonMinus:()=>Rg,OctagonMinusIcon:()=>Rg,OctagonPause:()=>Pg,OctagonPauseIcon:()=>Pg,OctagonX:()=>qg,OctagonXIcon:()=>qg,Omega:()=>$g,OmegaIcon:()=>$g,Option:()=>zg,OptionIcon:()=>zg,Orbit:()=>Hg,OrbitIcon:()=>Hg,Origami:()=>Og,OrigamiIcon:()=>Og,Outdent:()=>Ik,OutdentIcon:()=>Ik,Package:()=>Ug,Package2:()=>Dg,Package2Icon:()=>Dg,PackageCheck:()=>Ng,PackageCheckIcon:()=>Ng,PackageIcon:()=>Ug,PackageMinus:()=>Vg,PackageMinusIcon:()=>Vg,PackageOpen:()=>jg,PackageOpenIcon:()=>jg,PackagePlus:()=>Fg,PackagePlusIcon:()=>Fg,PackageSearch:()=>Bg,PackageSearchIcon:()=>Bg,PackageX:()=>_g,PackageXIcon:()=>_g,PaintBucket:()=>Gg,PaintBucketIcon:()=>Gg,PaintRoller:()=>Wg,PaintRollerIcon:()=>Wg,Paintbrush:()=>Zg,Paintbrush2:()=>Kg,Paintbrush2Icon:()=>Kg,PaintbrushIcon:()=>Zg,PaintbrushVertical:()=>Kg,PaintbrushVerticalIcon:()=>Kg,Palette:()=>Xg,PaletteIcon:()=>Xg,Palmtree:()=>fb,PalmtreeIcon:()=>fb,Panda:()=>Yg,PandaIcon:()=>Yg,PanelBottom:()=>tM,PanelBottomClose:()=>Qg,PanelBottomCloseIcon:()=>Qg,PanelBottomDashed:()=>Jg,PanelBottomDashedIcon:()=>Jg,PanelBottomIcon:()=>tM,PanelBottomInactive:()=>Jg,PanelBottomInactiveIcon:()=>Jg,PanelBottomOpen:()=>eM,PanelBottomOpenIcon:()=>eM,PanelLeft:()=>oM,PanelLeftClose:()=>aM,PanelLeftCloseIcon:()=>aM,PanelLeftDashed:()=>rM,PanelLeftDashedIcon:()=>rM,PanelLeftIcon:()=>oM,PanelLeftInactive:()=>rM,PanelLeftInactiveIcon:()=>rM,PanelLeftOpen:()=>nM,PanelLeftOpenIcon:()=>nM,PanelLeftRightDashed:()=>iM,PanelLeftRightDashedIcon:()=>iM,PanelRight:()=>dM,PanelRightClose:()=>cM,PanelRightCloseIcon:()=>cM,PanelRightDashed:()=>sM,PanelRightDashedIcon:()=>sM,PanelRightIcon:()=>dM,PanelRightInactive:()=>sM,PanelRightInactiveIcon:()=>sM,PanelRightOpen:()=>hM,PanelRightOpenIcon:()=>hM,PanelTop:()=>kM,PanelTopBottomDashed:()=>uM,PanelTopBottomDashedIcon:()=>uM,PanelTopClose:()=>lM,PanelTopCloseIcon:()=>lM,PanelTopDashed:()=>pM,PanelTopDashedIcon:()=>pM,PanelTopIcon:()=>kM,PanelTopInactive:()=>pM,PanelTopInactiveIcon:()=>pM,PanelTopOpen:()=>yM,PanelTopOpenIcon:()=>yM,PanelsLeftBottom:()=>fM,PanelsLeftBottomIcon:()=>fM,PanelsLeftRight:()=>Sc,PanelsLeftRightIcon:()=>Sc,PanelsRightBottom:()=>mM,PanelsRightBottomIcon:()=>mM,PanelsTopBottom:()=>Vx,PanelsTopBottomIcon:()=>Vx,PanelsTopLeft:()=>MM,PanelsTopLeftIcon:()=>MM,Paperclip:()=>gM,PaperclipIcon:()=>gM,Parentheses:()=>vM,ParenthesesIcon:()=>vM,ParkingCircle:()=>eo,ParkingCircleIcon:()=>eo,ParkingCircleOff:()=>Ji,ParkingCircleOffIcon:()=>Ji,ParkingMeter:()=>xM,ParkingMeterIcon:()=>xM,ParkingSquare:()=>FA,ParkingSquareIcon:()=>FA,ParkingSquareOff:()=>jA,ParkingSquareOffIcon:()=>jA,PartyPopper:()=>LM,PartyPopperIcon:()=>LM,Pause:()=>wM,PauseCircle:()=>to,PauseCircleIcon:()=>to,PauseIcon:()=>wM,PauseOctagon:()=>Pg,PauseOctagonIcon:()=>Pg,PawPrint:()=>AM,PawPrintIcon:()=>AM,PcCase:()=>IM,PcCaseIcon:()=>IM,Pen:()=>TM,PenBox:()=>_A,PenBoxIcon:()=>_A,PenIcon:()=>TM,PenLine:()=>CM,PenLineIcon:()=>CM,PenOff:()=>SM,PenOffIcon:()=>SM,PenSquare:()=>_A,PenSquareIcon:()=>_A,PenTool:()=>bM,PenToolIcon:()=>bM,Pencil:()=>EM,PencilIcon:()=>EM,PencilLine:()=>PM,PencilLineIcon:()=>PM,PencilOff:()=>RM,PencilOffIcon:()=>RM,PencilRuler:()=>qM,PencilRulerIcon:()=>qM,Pentagon:()=>zM,PentagonIcon:()=>zM,Percent:()=>$M,PercentCircle:()=>ao,PercentCircleIcon:()=>ao,PercentDiamond:()=>Ss,PercentDiamondIcon:()=>Ss,PercentIcon:()=>$M,PercentSquare:()=>UA,PercentSquareIcon:()=>UA,PersonStanding:()=>HM,PersonStandingIcon:()=>HM,PhilippinePeso:()=>OM,PhilippinePesoIcon:()=>OM,Phone:()=>_M,PhoneCall:()=>DM,PhoneCallIcon:()=>DM,PhoneForwarded:()=>NM,PhoneForwardedIcon:()=>NM,PhoneIcon:()=>_M,PhoneIncoming:()=>VM,PhoneIncomingIcon:()=>VM,PhoneMissed:()=>jM,PhoneMissedIcon:()=>jM,PhoneOff:()=>FM,PhoneOffIcon:()=>FM,PhoneOutgoing:()=>BM,PhoneOutgoingIcon:()=>BM,Pi:()=>UM,PiIcon:()=>UM,PiSquare:()=>GA,PiSquareIcon:()=>GA,Piano:()=>GM,PianoIcon:()=>GM,Pickaxe:()=>WM,PickaxeIcon:()=>WM,PictureInPicture:()=>ZM,PictureInPicture2:()=>KM,PictureInPicture2Icon:()=>KM,PictureInPictureIcon:()=>ZM,PieChart:()=>Jn,PieChartIcon:()=>Jn,PiggyBank:()=>XM,PiggyBankIcon:()=>XM,Pilcrow:()=>ev,PilcrowIcon:()=>ev,PilcrowLeft:()=>YM,PilcrowLeftIcon:()=>YM,PilcrowRight:()=>QM,PilcrowRightIcon:()=>QM,PilcrowSquare:()=>WA,PilcrowSquareIcon:()=>WA,Pill:()=>tv,PillBottle:()=>JM,PillBottleIcon:()=>JM,PillIcon:()=>tv,Pin:()=>rv,PinIcon:()=>rv,PinOff:()=>av,PinOffIcon:()=>av,Pipette:()=>nv,PipetteIcon:()=>nv,Pizza:()=>iv,PizzaIcon:()=>iv,Plane:()=>hv,PlaneIcon:()=>hv,PlaneLanding:()=>ov,PlaneLandingIcon:()=>ov,PlaneTakeoff:()=>cv,PlaneTakeoffIcon:()=>cv,Play:()=>sv,PlayCircle:()=>ro,PlayCircleIcon:()=>ro,PlayIcon:()=>sv,PlaySquare:()=>ZA,PlaySquareIcon:()=>ZA,Plug:()=>uv,Plug2:()=>dv,Plug2Icon:()=>dv,PlugIcon:()=>uv,PlugZap:()=>lv,PlugZap2:()=>lv,PlugZap2Icon:()=>lv,PlugZapIcon:()=>lv,Plus:()=>pv,PlusCircle:()=>no,PlusCircleIcon:()=>no,PlusIcon:()=>pv,PlusSquare:()=>KA,PlusSquareIcon:()=>KA,Pocket:()=>kv,PocketIcon:()=>kv,PocketKnife:()=>yv,PocketKnifeIcon:()=>yv,Podcast:()=>fv,PodcastIcon:()=>fv,Pointer:()=>gv,PointerIcon:()=>gv,PointerOff:()=>mv,PointerOffIcon:()=>mv,Popcorn:()=>Mv,PopcornIcon:()=>Mv,Popsicle:()=>vv,PopsicleIcon:()=>vv,PoundSterling:()=>Lv,PoundSterlingIcon:()=>Lv,Power:()=>Av,PowerCircle:()=>oo,PowerCircleIcon:()=>oo,PowerIcon:()=>Av,PowerOff:()=>xv,PowerOffIcon:()=>xv,PowerSquare:()=>XA,PowerSquareIcon:()=>XA,Presentation:()=>wv,PresentationIcon:()=>wv,Printer:()=>Cv,PrinterCheck:()=>Iv,PrinterCheckIcon:()=>Iv,PrinterIcon:()=>Cv,Projector:()=>bv,ProjectorIcon:()=>bv,Proportions:()=>Sv,ProportionsIcon:()=>Sv,Puzzle:()=>Tv,PuzzleIcon:()=>Tv,Pyramid:()=>Rv,PyramidIcon:()=>Rv,QrCode:()=>Pv,QrCodeIcon:()=>Pv,Quote:()=>qv,QuoteIcon:()=>qv,Rabbit:()=>Ev,RabbitIcon:()=>Ev,Radar:()=>$v,RadarIcon:()=>$v,Radiation:()=>zv,RadiationIcon:()=>zv,Radical:()=>Hv,RadicalIcon:()=>Hv,Radio:()=>Vv,RadioIcon:()=>Vv,RadioReceiver:()=>Dv,RadioReceiverIcon:()=>Dv,RadioTower:()=>Ov,RadioTowerIcon:()=>Ov,Radius:()=>Nv,RadiusIcon:()=>Nv,RailSymbol:()=>jv,RailSymbolIcon:()=>jv,Rainbow:()=>Fv,RainbowIcon:()=>Fv,Rat:()=>Bv,RatIcon:()=>Bv,Ratio:()=>_v,RatioIcon:()=>_v,Receipt:()=>ex,ReceiptCent:()=>Uv,ReceiptCentIcon:()=>Uv,ReceiptEuro:()=>Gv,ReceiptEuroIcon:()=>Gv,ReceiptIcon:()=>ex,ReceiptIndianRupee:()=>Wv,ReceiptIndianRupeeIcon:()=>Wv,ReceiptJapaneseYen:()=>Kv,ReceiptJapaneseYenIcon:()=>Kv,ReceiptPoundSterling:()=>Zv,ReceiptPoundSterlingIcon:()=>Zv,ReceiptRussianRuble:()=>Xv,ReceiptRussianRubleIcon:()=>Xv,ReceiptSwissFranc:()=>Yv,ReceiptSwissFrancIcon:()=>Yv,ReceiptText:()=>Jv,ReceiptTextIcon:()=>Jv,ReceiptTurkishLira:()=>Qv,ReceiptTurkishLiraIcon:()=>Qv,RectangleCircle:()=>tx,RectangleCircleIcon:()=>tx,RectangleEllipsis:()=>ax,RectangleEllipsisIcon:()=>ax,RectangleGoggles:()=>rx,RectangleGogglesIcon:()=>rx,RectangleHorizontal:()=>nx,RectangleHorizontalIcon:()=>nx,RectangleVertical:()=>ix,RectangleVerticalIcon:()=>ix,Recycle:()=>ox,RecycleIcon:()=>ox,Redo:()=>hx,Redo2:()=>cx,Redo2Icon:()=>cx,RedoDot:()=>sx,RedoDotIcon:()=>sx,RedoIcon:()=>hx,RefreshCcw:()=>lx,RefreshCcwDot:()=>dx,RefreshCcwDotIcon:()=>dx,RefreshCcwIcon:()=>lx,RefreshCw:()=>px,RefreshCwIcon:()=>px,RefreshCwOff:()=>ux,RefreshCwOffIcon:()=>ux,Refrigerator:()=>yx,RefrigeratorIcon:()=>yx,Regex:()=>kx,RegexIcon:()=>kx,RemoveFormatting:()=>fx,RemoveFormattingIcon:()=>fx,Repeat:()=>gx,Repeat1:()=>Mx,Repeat1Icon:()=>Mx,Repeat2:()=>mx,Repeat2Icon:()=>mx,RepeatIcon:()=>gx,Replace:()=>Lx,ReplaceAll:()=>vx,ReplaceAllIcon:()=>vx,ReplaceIcon:()=>Lx,Reply:()=>wx,ReplyAll:()=>xx,ReplyAllIcon:()=>xx,ReplyIcon:()=>wx,Rewind:()=>Ax,RewindIcon:()=>Ax,Ribbon:()=>Ix,RibbonIcon:()=>Ix,Rocket:()=>Cx,RocketIcon:()=>Cx,RockingChair:()=>bx,RockingChairIcon:()=>bx,RollerCoaster:()=>Sx,RollerCoasterIcon:()=>Sx,Rose:()=>Tx,RoseIcon:()=>Tx,Rotate3D:()=>Rx,Rotate3DIcon:()=>Rx,Rotate3d:()=>Rx,Rotate3dIcon:()=>Rx,RotateCcw:()=>Ex,RotateCcwIcon:()=>Ex,RotateCcwKey:()=>Px,RotateCcwKeyIcon:()=>Px,RotateCcwSquare:()=>qx,RotateCcwSquareIcon:()=>qx,RotateCw:()=>zx,RotateCwIcon:()=>zx,RotateCwSquare:()=>$x,RotateCwSquareIcon:()=>$x,Route:()=>Ox,RouteIcon:()=>Ox,RouteOff:()=>Hx,RouteOffIcon:()=>Hx,Router:()=>Nx,RouterIcon:()=>Nx,Rows:()=>Dx,Rows2:()=>Dx,Rows2Icon:()=>Dx,Rows3:()=>Vx,Rows3Icon:()=>Vx,Rows4:()=>jx,Rows4Icon:()=>jx,RowsIcon:()=>Dx,Rss:()=>Fx,RssIcon:()=>Fx,Ruler:()=>_x,RulerDimensionLine:()=>Bx,RulerDimensionLineIcon:()=>Bx,RulerIcon:()=>_x,RussianRuble:()=>Gx,RussianRubleIcon:()=>Gx,Sailboat:()=>Ux,SailboatIcon:()=>Ux,Salad:()=>Wx,SaladIcon:()=>Wx,Sandwich:()=>Kx,SandwichIcon:()=>Kx,Satellite:()=>Yx,SatelliteDish:()=>Zx,SatelliteDishIcon:()=>Zx,SatelliteIcon:()=>Yx,SaudiRiyal:()=>Xx,SaudiRiyalIcon:()=>Xx,Save:()=>eL,SaveAll:()=>Qx,SaveAllIcon:()=>Qx,SaveIcon:()=>eL,SaveOff:()=>Jx,SaveOffIcon:()=>Jx,Scale:()=>aL,Scale3D:()=>tL,Scale3DIcon:()=>tL,Scale3d:()=>tL,Scale3dIcon:()=>tL,ScaleIcon:()=>aL,Scaling:()=>rL,ScalingIcon:()=>rL,Scan:()=>uL,ScanBarcode:()=>nL,ScanBarcodeIcon:()=>nL,ScanEye:()=>iL,ScanEyeIcon:()=>iL,ScanFace:()=>oL,ScanFaceIcon:()=>oL,ScanHeart:()=>cL,ScanHeartIcon:()=>cL,ScanIcon:()=>uL,ScanLine:()=>sL,ScanLineIcon:()=>sL,ScanQrCode:()=>hL,ScanQrCodeIcon:()=>hL,ScanSearch:()=>dL,ScanSearchIcon:()=>dL,ScanText:()=>lL,ScanTextIcon:()=>lL,ScatterChart:()=>ei,ScatterChartIcon:()=>ei,School:()=>pL,School2:()=>Zb,School2Icon:()=>Zb,SchoolIcon:()=>pL,Scissors:()=>kL,ScissorsIcon:()=>kL,ScissorsLineDashed:()=>yL,ScissorsLineDashedIcon:()=>yL,ScissorsSquare:()=>eI,ScissorsSquareDashedBottom:()=>fA,ScissorsSquareDashedBottomIcon:()=>fA,ScissorsSquareIcon:()=>eI,ScreenShare:()=>mL,ScreenShareIcon:()=>mL,ScreenShareOff:()=>fL,ScreenShareOffIcon:()=>fL,Scroll:()=>ML,ScrollIcon:()=>ML,ScrollText:()=>gL,ScrollTextIcon:()=>gL,Search:()=>AL,SearchCheck:()=>vL,SearchCheckIcon:()=>vL,SearchCode:()=>xL,SearchCodeIcon:()=>xL,SearchIcon:()=>AL,SearchSlash:()=>LL,SearchSlashIcon:()=>LL,SearchX:()=>wL,SearchXIcon:()=>wL,Section:()=>IL,SectionIcon:()=>IL,Send:()=>SL,SendHorizonal:()=>CL,SendHorizonalIcon:()=>CL,SendHorizontal:()=>CL,SendHorizontalIcon:()=>CL,SendIcon:()=>SL,SendToBack:()=>bL,SendToBackIcon:()=>bL,SeparatorHorizontal:()=>TL,SeparatorHorizontalIcon:()=>TL,SeparatorVertical:()=>RL,SeparatorVerticalIcon:()=>RL,Server:()=>$L,ServerCog:()=>PL,ServerCogIcon:()=>PL,ServerCrash:()=>qL,ServerCrashIcon:()=>qL,ServerIcon:()=>$L,ServerOff:()=>EL,ServerOffIcon:()=>EL,Settings:()=>zL,Settings2:()=>HL,Settings2Icon:()=>HL,SettingsIcon:()=>zL,Shapes:()=>NL,ShapesIcon:()=>NL,Share:()=>DL,Share2:()=>OL,Share2Icon:()=>OL,ShareIcon:()=>DL,Sheet:()=>VL,SheetIcon:()=>VL,Shell:()=>jL,ShellIcon:()=>jL,Shield:()=>JL,ShieldAlert:()=>FL,ShieldAlertIcon:()=>FL,ShieldBan:()=>BL,ShieldBanIcon:()=>BL,ShieldCheck:()=>_L,ShieldCheckIcon:()=>_L,ShieldClose:()=>QL,ShieldCloseIcon:()=>QL,ShieldEllipsis:()=>UL,ShieldEllipsisIcon:()=>UL,ShieldHalf:()=>GL,ShieldHalfIcon:()=>GL,ShieldIcon:()=>JL,ShieldMinus:()=>WL,ShieldMinusIcon:()=>WL,ShieldOff:()=>KL,ShieldOffIcon:()=>KL,ShieldPlus:()=>ZL,ShieldPlusIcon:()=>ZL,ShieldQuestion:()=>XL,ShieldQuestionIcon:()=>XL,ShieldQuestionMark:()=>XL,ShieldQuestionMarkIcon:()=>XL,ShieldUser:()=>YL,ShieldUserIcon:()=>YL,ShieldX:()=>QL,ShieldXIcon:()=>QL,Ship:()=>tw,ShipIcon:()=>tw,ShipWheel:()=>ew,ShipWheelIcon:()=>ew,Shirt:()=>aw,ShirtIcon:()=>aw,ShoppingBag:()=>rw,ShoppingBagIcon:()=>rw,ShoppingBasket:()=>nw,ShoppingBasketIcon:()=>nw,ShoppingCart:()=>iw,ShoppingCartIcon:()=>iw,Shovel:()=>ow,ShovelIcon:()=>ow,ShowerHead:()=>cw,ShowerHeadIcon:()=>cw,Shredder:()=>sw,ShredderIcon:()=>sw,Shrimp:()=>hw,ShrimpIcon:()=>hw,Shrink:()=>dw,ShrinkIcon:()=>dw,Shrub:()=>lw,ShrubIcon:()=>lw,Shuffle:()=>uw,ShuffleIco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a=this.computeRuleType(e),r=this.wrapper.DEFINE_RULE(Vt(e.name),this.startImplementation(a,t).bind(this));return this.allRules.set(e.name,r),e.entry&&(this.mainRule=r),r}computeRuleType(e){if(!e.fragment){if((0,n.Xq)(e))return Dt;{const t=(0,n.PV)(e);return null!=t?t:e.name}}}parse(e,t={}){this.nodeBuilder.buildRootNode(e);const a=this.lexerResult=this.lexer.tokenize(e);this.wrapper.input=a.tokens;const r=t.rule?this.allRules.get(t.rule):this.mainRule;if(!r)throw new Error(t.rule?`No rule found with name '${t.rule}'`:"No main rule available.");const n=r.call(this.wrapper,{});return this.nodeBuilder.addHiddenNodes(a.hidden),this.unorderedGroups.clear(),this.lexerResult=void 0,{value:n,lexerErrors:a.errors,lexerReport:a.report,parserErrors:this.wrapper.errors}}startImplementation(e,t){return a=>{const r=!this.isRecording()&&void 0!==e;if(r){const t={$type:e};this.stack.push(t),e===Dt&&(t.value="")}let n;try{n=t(a)}catch(i){n=void 0}return void 0===n&&r&&(n=this.construct()),n}}extractHiddenTokens(e){const t=this.lexerResult.hidden;if(!t.length)return[];const a=e.startOffset;for(let r=0;ra)return t.splice(0,r)}return t.splice(0,t.length)}consume(e,t,a){const r=this.wrapper.wrapConsume(e,t);if(!this.isRecording()&&this.isValidToken(r)){const e=this.extractHiddenTokens(r);this.nodeBuilder.addHiddenNodes(e);const t=this.nodeBuilder.buildLeafNode(r,a),{assignment:n,isCrossRef:i}=this.getAssignment(a),c=this.current;if(n){const e=(0,o.wb)(a)?r.image:this.converter.convert(r.image,t);this.assign(n.operator,n.feature,e,t,i)}else if(Nt(c)){let e=r.image;(0,o.wb)(a)||(e=this.converter.convert(e,t).toString()),c.value+=e}}}isValidToken(e){return!e.isInsertedInRecovery&&!isNaN(e.startOffset)&&"number"==typeof e.endOffset&&!isNaN(e.endOffset)}subrule(e,t,a,r,n){let i;this.isRecording()||a||(i=this.nodeBuilder.buildCompositeNode(r));const o=this.wrapper.wrapSubrule(e,t,n);!this.isRecording()&&i&&i.length>0&&this.performSubruleAssignment(o,r,i)}performSubruleAssignment(e,t,a){const{assignment:r,isCrossRef:n}=this.getAssignment(t);if(r)this.assign(r.operator,r.feature,e,a,n);else if(!r){const t=this.current;if(Nt(t))t.value+=e.toString();else if("object"==typeof e&&e){const a=this.assignWithoutOverride(e,t);this.stack.pop(),this.stack.push(a)}}}action(e,t){if(!this.isRecording()){let a=this.current;if(t.feature&&t.operator){a=this.construct(),this.nodeBuilder.removeNode(a.$cstNode);this.nodeBuilder.buildCompositeNode(t).content.push(a.$cstNode);const r={$type:e};this.stack.push(r),this.assign(t.operator,t.feature,a,a.$cstNode,!1)}else a.$type=e}}construct(){if(this.isRecording())return;const e=this.current;return(0,St.SD)(e),this.nodeBuilder.construct(e),this.stack.pop(),Nt(e)?this.converter.convert(e.value,e.$cstNode):((0,St.OP)(this.astReflection,e),e)}getAssignment(e){if(!this.assignmentMap.has(e)){const t=(0,St.XG)(e,o.wh);this.assignmentMap.set(e,{assignment:t,isCrossRef:!!t&&(0,o._c)(t.terminal)})}return this.assignmentMap.get(e)}assign(e,t,a,r,n){const i=this.current;let o;switch(o=n&&"string"==typeof a?this.linker.buildReference(i,t,r,a):a,e){case"=":i[t]=o;break;case"?=":i[t]=!0;break;case"+=":Array.isArray(i[t])||(i[t]=[]),i[t].push(o)}}assignWithoutOverride(e,t){for(const[r,n]of Object.entries(t)){const t=e[r];void 0===t?e[r]=n:Array.isArray(t)&&Array.isArray(n)&&(n.push(...t),e[r]=n)}const a=e.$cstNode;return a&&(a.astNode=void 0,e.$cstNode=void 0),e}get definitionErrors(){return this.wrapper.definitionErrors}}class Bt{buildMismatchTokenMessage(e){return c.my.buildMismatchTokenMessage(e)}buildNotAllInputParsedMessage(e){return c.my.buildNotAllInputParsedMessage(e)}buildNoViableAltMessage(e){return c.my.buildNoViableAltMessage(e)}buildEarlyExitMessage(e){return c.my.buildEarlyExitMessage(e)}}class _t extends Bt{buildMismatchTokenMessage({expected:e,actual:t}){return`Expecting ${e.LABEL?"`"+e.LABEL+"`":e.name.endsWith(":KW")?`keyword '${e.name.substring(0,e.name.length-3)}'`:`token of type '${e.name}'`} but found \`${t.image}\`.`}buildNotAllInputParsedMessage({firstRedundant:e}){return`Expecting end of file but found \`${e.image}\`.`}}class Ut extends jt{constructor(){super(...arguments),this.tokens=[],this.elementStack=[],this.lastElementStack=[],this.nextTokenIndex=0,this.stackSize=0}action(){}construct(){}parse(e){this.resetState();const t=this.lexer.tokenize(e,{mode:"partial"});return this.tokens=t.tokens,this.wrapper.input=[...this.tokens],this.mainRule.call(this.wrapper,{}),this.unorderedGroups.clear(),{tokens:this.tokens,elementStack:[...this.lastElementStack],tokenIndex:this.nextTokenIndex}}rule(e,t){const a=this.wrapper.DEFINE_RULE(Vt(e.name),this.startImplementation(t).bind(this));return this.allRules.set(e.name,a),e.entry&&(this.mainRule=a),a}resetState(){this.elementStack=[],this.lastElementStack=[],this.nextTokenIndex=0,this.stackSize=0}startImplementation(e){return t=>{const a=this.keepStackSize();try{e(t)}finally{this.resetStackSize(a)}}}removeUnexpectedElements(){this.elementStack.splice(this.stackSize)}keepStackSize(){const e=this.elementStack.length;return this.stackSize=e,e}resetStackSize(e){this.removeUnexpectedElements(),this.stackSize=e}consume(e,t,a){this.wrapper.wrapConsume(e,t),this.isRecording()||(this.lastElementStack=[...this.elementStack,a],this.nextTokenIndex=this.currIdx+1)}subrule(e,t,a,r,n){this.before(r),this.wrapper.wrapSubrule(e,t,n),this.after(r)}before(e){this.isRecording()||this.elementStack.push(e)}after(e){if(!this.isRecording()){const t=this.elementStack.lastIndexOf(e);t>=0&&this.elementStack.splice(t)}}get currIdx(){return this.wrapper.currIdx}}const Gt={recoveryEnabled:!0,nodeLocationTracking:"full",skipValidations:!0,errorMessageProvider:new _t};class Wt extends c.jr{constructor(e,t){const a=t&&"maxLookahead"in t;super(e,Object.assign(Object.assign(Object.assign({},Gt),{lookaheadStrategy:a?new c.T6({maxLookahead:t.maxLookahead}):new B({logging:t.skipValidations?()=>{}:void 0})}),t))}get IS_RECORDING(){return this.RECORDING_PHASE}DEFINE_RULE(e,t){return this.RULE(e,t)}wrapSelfAnalysis(){this.performSelfAnalysis()}wrapConsume(e,t){return this.consume(e,t)}wrapSubrule(e,t,a){return this.subrule(e,t,{ARGS:[a]})}wrapOr(e,t){this.or(e,t)}wrapOption(e,t){this.option(e,t)}wrapMany(e,t){this.many(e,t)}wrapAtLeastOne(e,t){this.atLeastOne(e,t)}}var Kt=a(1564),Zt=a(1719);function Xt(e,t,a){return function(e,t){const a=(0,n.YV)(t,!1),r=(0,Zt.Td)(t.rules).filter(o.s7).filter(e=>a.has(e));for(const n of r){const t=Object.assign(Object.assign({},e),{consume:1,optional:1,subrule:1,many:1,or:1});e.parser.rule(n,Yt(t,n.definition))}}({parser:t,tokens:a,ruleNames:new Map},e),t}function Yt(e,t,a=!1){let r;if((0,o.wb)(t))r=function(e,t){const a=e.consume++,r=e.tokens[t.value];if(!r)throw new Error("Could not find token for keyword: "+t.value);return()=>e.parser.consume(a,r,t)}(e,t);else if((0,o.ve)(t))r=function(e,t){const a=(0,n.Uz)(t);return()=>e.parser.action(a,t)}(e,t);else if((0,o.wh)(t))r=Yt(e,t.terminal);else if((0,o._c)(t))r=ea(e,t);else if((0,o.$g)(t))r=function(e,t){const a=t.rule.ref;if((0,o.s7)(a)){const r=e.subrule++,n=a.fragment,i=t.arguments.length>0?function(e,t){const a=t.map(e=>Qt(e.value));return t=>{const r={};for(let n=0;n({});return o=>e.parser.subrule(r,aa(e,a),n,t,i(o))}if((0,o.rE)(a)){const r=e.consume++,n=ra(e,a.name);return()=>e.parser.consume(r,n,t)}if(!a)throw new Kt.W(t.$cstNode,`Undefined rule: ${t.rule.$refText}`);(0,Kt.d)(a)}(e,t);else if((0,o.jp)(t))r=function(e,t){if(1===t.elements.length)return Yt(e,t.elements[0]);{const a=[];for(const n of t.elements){const t={ALT:Yt(e,n,!0)},r=Jt(n);r&&(t.GATE=Qt(r)),a.push(t)}const r=e.or++;return t=>e.parser.alternatives(r,a.map(e=>{const a={ALT:()=>e.ALT(t)},r=e.GATE;return r&&(a.GATE=()=>r(t)),a}))}}(e,t);else if((0,o.cY)(t))r=function(e,t){if(1===t.elements.length)return Yt(e,t.elements[0]);const a=[];for(const c of t.elements){const t={ALT:Yt(e,c,!0)},r=Jt(c);r&&(t.GATE=Qt(r)),a.push(t)}const r=e.or++,n=(e,t)=>`uGroup_${e}_${t.getRuleStack().join("-")}`,i=t=>e.parser.alternatives(r,a.map((a,i)=>{const o={ALT:()=>!0},c=e.parser;o.ALT=()=>{if(a.ALT(t),!c.isRecording()){const e=n(r,c);c.unorderedGroups.get(e)||c.unorderedGroups.set(e,[]);const t=c.unorderedGroups.get(e);void 0===(null==t?void 0:t[i])&&(t[i]=!0)}};const s=a.GATE;return o.GATE=s?()=>s(t):()=>{const e=c.unorderedGroups.get(n(r,c));return!(null==e?void 0:e[i])},o})),o=ta(e,Jt(t),i,"*");return t=>{o(t),e.parser.isRecording()||e.parser.unorderedGroups.delete(n(r,e.parser))}}(e,t);else if((0,o.IZ)(t))r=function(e,t){const a=t.elements.map(t=>Yt(e,t));return e=>a.forEach(t=>t(e))}(e,t);else{if(!(0,o.FO)(t))throw new Kt.W(t.$cstNode,`Unexpected element type: ${t.$type}`);{const a=e.consume++;r=()=>e.parser.consume(a,c.LT,t)}}return ta(e,a?void 0:Jt(t),r,t.cardinality)}function Qt(e){if((0,o.RP)(e)){const t=Qt(e.left),a=Qt(e.right);return e=>t(e)||a(e)}if((0,o.Tu)(e)){const t=Qt(e.left),a=Qt(e.right);return e=>t(e)&&a(e)}if((0,o.Ct)(e)){const t=Qt(e.value);return e=>!t(e)}if((0,o.TF)(e)){const t=e.parameter.ref.name;return e=>void 0!==e&&!0===e[t]}if((0,o.Cz)(e)){const t=Boolean(e.true);return()=>t}(0,Kt.d)(e)}function Jt(e){if((0,o.IZ)(e))return e.guardCondition}function ea(e,t,a=t.terminal){if(a){if((0,o.$g)(a)&&(0,o.s7)(a.rule.ref)){const r=a.rule.ref,n=e.subrule++;return a=>e.parser.subrule(n,aa(e,r),!1,t,a)}if((0,o.$g)(a)&&(0,o.rE)(a.rule.ref)){const r=e.consume++,n=ra(e,a.rule.ref.name);return()=>e.parser.consume(r,n,t)}if((0,o.wb)(a)){const r=e.consume++,n=ra(e,a.value);return()=>e.parser.consume(r,n,t)}throw new Error("Could not build cross reference parser")}{if(!t.type.ref)throw new Error("Could not resolve reference to type: "+t.type.$refText);const a=(0,n.U5)(t.type.ref),r=null==a?void 0:a.terminal;if(!r)throw new Error("Could not find name assignment for type: "+(0,n.Uz)(t.type.ref));return ea(e,t,r)}}function ta(e,t,a,r){const n=t&&Qt(t);if(!r){if(n){const t=e.or++;return r=>e.parser.alternatives(t,[{ALT:()=>a(r),GATE:()=>n(r)},{ALT:(0,c.mT)(),GATE:()=>!n(r)}])}return a}if("*"===r){const t=e.many++;return r=>e.parser.many(t,{DEF:()=>a(r),GATE:n?()=>n(r):void 0})}if("+"===r){const t=e.many++;if(n){const r=e.or++;return i=>e.parser.alternatives(r,[{ALT:()=>e.parser.atLeastOne(t,{DEF:()=>a(i)}),GATE:()=>n(i)},{ALT:(0,c.mT)(),GATE:()=>!n(i)}])}return r=>e.parser.atLeastOne(t,{DEF:()=>a(r)})}if("?"===r){const t=e.optional++;return r=>e.parser.optional(t,{DEF:()=>a(r),GATE:n?()=>n(r):void 0})}(0,Kt.d)(r)}function aa(e,t){const a=function(e,t){if((0,o.s7)(t))return t.name;if(e.ruleNames.has(t))return e.ruleNames.get(t);{let a=t,r=a.$container,n=t.$type;for(;!(0,o.s7)(r);){if((0,o.IZ)(r)||(0,o.jp)(r)||(0,o.cY)(r)){n=r.elements.indexOf(a).toString()+":"+n}a=r,r=r.$container}return n=r.name+":"+n,e.ruleNames.set(t,n),n}}(e,t),r=e.parser.getRule(a);if(!r)throw new Error(`Rule "${a}" not found."`);return r}function ra(e,t){const a=e.tokens[t];if(!a)throw new Error(`Token "${t}" not found."`);return a}function na(e){const t=function(e){const t=e.Grammar,a=e.parser.Lexer,r=new Ft(e);return Xt(t,r,a.definition)}(e);return t.finalize(),t}var ia=a(1945),oa=a(5033),ca=a(9850),sa=a(2479);let ha=0,da=10;const la=Symbol("OperationCancelled");function ua(e){return e===la}async function pa(e){if(e===ca.XO.None)return;const t=performance.now();if(t-ha>=da&&(ha=t,await new Promise(e=>{"undefined"==typeof setImmediate?setTimeout(e,0):setImmediate(e)}),ha=performance.now()),e.isCancellationRequested)throw la}class ya{constructor(){this.promise=new Promise((e,t)=>{this.resolve=t=>(e(t),this),this.reject=e=>(t(e),this)})}}class ka{constructor(e,t,a,r){this._uri=e,this._languageId=t,this._version=a,this._content=r,this._lineOffsets=void 0}get uri(){return this._uri}get languageId(){return this._languageId}get version(){return this._version}getText(e){if(e){const t=this.offsetAt(e.start),a=this.offsetAt(e.end);return this._content.substring(t,a)}return this._content}update(e,t){for(const a of e)if(ka.isIncremental(a)){const e=va(a.range),t=this.offsetAt(e.start),r=this.offsetAt(e.end);this._content=this._content.substring(0,t)+a.text+this._content.substring(r,this._content.length);const n=Math.max(e.start.line,0),i=Math.max(e.end.line,0);let o=this._lineOffsets;const c=ga(a.text,!1,t);if(i-n===c.length)for(let a=0,h=c.length;ae?r=n:a=n+1}const n=a-1;return{line:n,character:(e=this.ensureBeforeEOL(e,t[n]))-t[n]}}offsetAt(e){const t=this.getLineOffsets();if(e.line>=t.length)return this._content.length;if(e.line<0)return 0;const a=t[e.line];if(e.character<=0)return a;const r=e.line+1t&&Ma(this._content.charCodeAt(e-1));)e--;return e}get lineCount(){return this.getLineOffsets().length}static isIncremental(e){const t=e;return null!=t&&"string"==typeof t.text&&void 0!==t.range&&(void 0===t.rangeLength||"number"==typeof t.rangeLength)}static isFull(e){const t=e;return null!=t&&"string"==typeof t.text&&void 0===t.range&&void 0===t.rangeLength}}var fa;function ma(e,t){if(e.length<=1)return e;const a=e.length/2|0,r=e.slice(0,a),n=e.slice(a);ma(r,t),ma(n,t);let i=0,o=0,c=0;for(;ia.line||t.line===a.line&&t.character>a.character?{start:a,end:t}:e}function xa(e){const t=va(e.range);return t!==e.range?{newText:e.newText,range:t}:e}!function(e){e.create=function(e,t,a,r){return new ka(e,t,a,r)},e.update=function(e,t,a){if(e instanceof ka)return e.update(t,a),e;throw new Error("TextDocument.update: document must be created by TextDocument.create")},e.applyEdits=function(e,t){const a=e.getText(),r=ma(t.map(xa),(e,t)=>{const a=e.range.start.line-t.range.start.line;return 0===a?e.range.start.character-t.range.start.character:a});let n=0;const i=[];for(const o of r){const t=e.offsetAt(o.range.start);if(tn&&i.push(a.substring(n,t)),o.newText.length&&i.push(o.newText),n=e.offsetAt(o.range.end)}return i.push(a.substr(n)),i.join("")}}(fa||(fa={}));var La,wa=a(7608);!function(e){e[e.Changed=0]="Changed",e[e.Parsed=1]="Parsed",e[e.IndexedContent=2]="IndexedContent",e[e.ComputedScopes=3]="ComputedScopes",e[e.Linked=4]="Linked",e[e.IndexedReferences=5]="IndexedReferences",e[e.Validated=6]="Validated"}(La||(La={}));class Aa{constructor(e){this.serviceRegistry=e.ServiceRegistry,this.textDocuments=e.workspace.TextDocuments,this.fileSystemProvider=e.workspace.FileSystemProvider}async fromUri(e,t=ca.XO.None){const a=await this.fileSystemProvider.readFile(e);return this.createAsync(e,a,t)}fromTextDocument(e,t,a){return t=null!=t?t:wa.r.parse(e.uri),ca.XO.is(a)?this.createAsync(t,e,a):this.create(t,e,a)}fromString(e,t,a){return ca.XO.is(a)?this.createAsync(t,e,a):this.create(t,e,a)}fromModel(e,t){return this.create(t,{$model:e})}create(e,t,a){if("string"==typeof t){const r=this.parse(e,t,a);return this.createLangiumDocument(r,e,void 0,t)}if("$model"in t){const a={value:t.$model,parserErrors:[],lexerErrors:[]};return this.createLangiumDocument(a,e)}{const r=this.parse(e,t.getText(),a);return this.createLangiumDocument(r,e,t)}}async createAsync(e,t,a){if("string"==typeof t){const r=await this.parseAsync(e,t,a);return this.createLangiumDocument(r,e,void 0,t)}{const r=await this.parseAsync(e,t.getText(),a);return this.createLangiumDocument(r,e,t)}}createLangiumDocument(e,t,a,r){let n;if(a)n={parseResult:e,uri:t,state:La.Parsed,references:[],textDocument:a};else{const a=this.createTextDocumentGetter(t,r);n={parseResult:e,uri:t,state:La.Parsed,references:[],get textDocument(){return a()}}}return e.value.$document=n,n}async update(e,t){var a,r;const n=null===(a=e.parseResult.value.$cstNode)||void 0===a?void 0:a.root.fullText,i=null===(r=this.textDocuments)||void 0===r?void 0:r.get(e.uri.toString()),o=i?i.getText():await this.fileSystemProvider.readFile(e.uri);if(i)Object.defineProperty(e,"textDocument",{value:i});else{const t=this.createTextDocumentGetter(e.uri,o);Object.defineProperty(e,"textDocument",{get:t})}return n!==o&&(e.parseResult=await this.parseAsync(e.uri,o,t),e.parseResult.value.$document=e),e.state=La.Parsed,e}parse(e,t,a){return this.serviceRegistry.getServices(e).parser.LangiumParser.parse(t,a)}parseAsync(e,t,a){return this.serviceRegistry.getServices(e).parser.AsyncParser.parse(t,a)}createTextDocumentGetter(e,t){const a=this.serviceRegistry;let r;return()=>null!=r?r:r=fa.create(e.toString(),a.getServices(e).LanguageMetaData.languageId,0,null!=t?t:"")}}class Ia{constructor(e){this.documentMap=new Map,this.langiumDocumentFactory=e.workspace.LangiumDocumentFactory,this.serviceRegistry=e.ServiceRegistry}get all(){return(0,Zt.Td)(this.documentMap.values())}addDocument(e){const t=e.uri.toString();if(this.documentMap.has(t))throw new Error(`A document with the URI '${t}' is already present.`);this.documentMap.set(t,e)}getDocument(e){const t=e.toString();return this.documentMap.get(t)}async getOrCreateDocument(e,t){let a=this.getDocument(e);return a||(a=await this.langiumDocumentFactory.fromUri(e,t),this.addDocument(a),a)}createDocument(e,t,a){if(a)return this.langiumDocumentFactory.fromString(t,e,a).then(e=>(this.addDocument(e),e));{const a=this.langiumDocumentFactory.fromString(t,e);return this.addDocument(a),a}}hasDocument(e){return this.documentMap.has(e.toString())}invalidateDocument(e){const t=e.toString(),a=this.documentMap.get(t);if(a){this.serviceRegistry.getServices(e).references.Linker.unlink(a),a.state=La.Changed,a.precomputedScopes=void 0,a.diagnostics=void 0}return a}deleteDocument(e){const t=e.toString(),a=this.documentMap.get(t);return a&&(a.state=La.Changed,this.documentMap.delete(t)),a}}const Ca=Symbol("ref_resolving");class ba{constructor(e){this.reflection=e.shared.AstReflection,this.langiumDocuments=()=>e.shared.workspace.LangiumDocuments,this.scopeProvider=e.references.ScopeProvider,this.astNodeLocator=e.workspace.AstNodeLocator}async link(e,t=ca.XO.None){for(const a of(0,St.jm)(e.parseResult.value))await pa(t),(0,St.DM)(a).forEach(t=>this.doLink(t,e))}doLink(e,t){var a;const r=e.reference;if(void 0===r._ref){r._ref=Ca;try{const t=this.getCandidate(e);if((0,sa.Zl)(t))r._ref=t;else if(r._nodeDescription=t,this.langiumDocuments().hasDocument(t.documentUri)){const a=this.loadAstNode(t);r._ref=null!=a?a:this.createLinkingError(e,t)}else r._ref=void 0}catch(n){console.error(`An error occurred while resolving reference to '${r.$refText}':`,n);const t=null!==(a=n.message)&&void 0!==a?a:String(n);r._ref=Object.assign(Object.assign({},e),{message:`An error occurred while resolving reference to '${r.$refText}': ${t}`})}t.references.push(r)}}unlink(e){for(const t of e.references)delete t._ref,delete t._nodeDescription;e.references=[]}getCandidate(e){const t=this.scopeProvider.getScope(e).getElement(e.reference.$refText);return null!=t?t:this.createLinkingError(e)}buildReference(e,t,a,r){const n=this,i={$refNode:a,$refText:r,get ref(){var a;if((0,sa.ng)(this._ref))return this._ref;if((0,sa.Nr)(this._nodeDescription)){const a=n.loadAstNode(this._nodeDescription);this._ref=null!=a?a:n.createLinkingError({reference:i,container:e,property:t},this._nodeDescription)}else if(void 0===this._ref){this._ref=Ca;const r=(0,St.cQ)(e).$document,o=n.getLinkedNode({reference:i,container:e,property:t});if(o.error&&r&&r.statee.length>0),i=r.split("/").filter(e=>e.length>0);let o=0;for(;o=e.end)return t.ref}if(a){const t=this.nameProvider.getNameNode(a);if(t&&(t===e||(0,r.pO)(e,t)))return a}}}findDeclarationNode(e){const t=this.findDeclaration(e);if(null==t?void 0:t.$cstNode){const e=this.nameProvider.getNameNode(t);return null!=e?e:t.$cstNode}}findReferences(e,t){const a=[];if(t.includeDeclaration){const t=this.getReferenceToSelf(e);t&&a.push(t)}let r=this.index.findAllReferences(e,this.nodeLocator.getAstNodePath(e));return t.documentUri&&(r=r.filter(e=>Ta.equals(e.sourceUri,t.documentUri))),a.push(...r),(0,Zt.Td)(a)}getReferenceToSelf(e){const t=this.nameProvider.getNameNode(e);if(t){const a=(0,St.YE)(e),n=this.nodeLocator.getAstNodePath(e);return{sourceUri:a.uri,sourcePath:n,targetUri:a.uri,targetPath:n,segment:(0,r.SX)(t),local:!0}}}}class Pa{constructor(e){if(this.map=new Map,e)for(const[t,a]of e)this.add(t,a)}get size(){return Zt.iD.sum((0,Zt.Td)(this.map.values()).map(e=>e.length))}clear(){this.map.clear()}delete(e,t){if(void 0===t)return this.map.delete(e);{const a=this.map.get(e);if(a){const r=a.indexOf(t);if(r>=0)return 1===a.length?this.map.delete(e):a.splice(r,1),!0}return!1}}get(e){var t;return null!==(t=this.map.get(e))&&void 0!==t?t:[]}has(e,t){if(void 0===t)return this.map.has(e);{const a=this.map.get(e);return!!a&&a.indexOf(t)>=0}}add(e,t){return this.map.has(e)?this.map.get(e).push(t):this.map.set(e,[t]),this}addAll(e,t){return this.map.has(e)?this.map.get(e).push(...t):this.map.set(e,Array.from(t)),this}forEach(e){this.map.forEach((t,a)=>t.forEach(t=>e(t,a,this)))}[Symbol.iterator](){return this.entries().iterator()}entries(){return(0,Zt.Td)(this.map.entries()).flatMap(([e,t])=>t.map(t=>[e,t]))}keys(){return(0,Zt.Td)(this.map.keys())}values(){return(0,Zt.Td)(this.map.values()).flat()}entriesGroupedByKey(){return(0,Zt.Td)(this.map.entries())}}class qa{get size(){return this.map.size}constructor(e){if(this.map=new Map,this.inverse=new Map,e)for(const[t,a]of e)this.set(t,a)}clear(){this.map.clear(),this.inverse.clear()}set(e,t){return this.map.set(e,t),this.inverse.set(t,e),this}get(e){return this.map.get(e)}getKey(e){return this.inverse.get(e)}delete(e){const t=this.map.get(e);return void 0!==t&&(this.map.delete(e),this.inverse.delete(t),!0)}}class Ea{constructor(e){this.nameProvider=e.references.NameProvider,this.descriptions=e.workspace.AstNodeDescriptionProvider}async computeExports(e,t=ca.XO.None){return this.computeExportsForNode(e.parseResult.value,e,void 0,t)}async computeExportsForNode(e,t,a=St.VN,r=ca.XO.None){const n=[];this.exportNode(e,n,t);for(const i of a(e))await pa(r),this.exportNode(i,n,t);return n}exportNode(e,t,a){const r=this.nameProvider.getName(e);r&&t.push(this.descriptions.createDescription(e,r,a))}async computeLocalScopes(e,t=ca.XO.None){const a=e.parseResult.value,r=new Pa;for(const n of(0,St.Uo)(a))await pa(t),this.processNode(n,e,r);return r}processNode(e,t,a){const r=e.$container;if(r){const n=this.nameProvider.getName(e);n&&a.add(r,this.descriptions.createDescription(e,n,t))}}}class $a{constructor(e,t,a){var r;this.elements=e,this.outerScope=t,this.caseInsensitive=null!==(r=null==a?void 0:a.caseInsensitive)&&void 0!==r&&r}getAllElements(){return this.outerScope?this.elements.concat(this.outerScope.getAllElements()):this.elements}getElement(e){const t=this.caseInsensitive?this.elements.find(t=>t.name.toLowerCase()===e.toLowerCase()):this.elements.find(t=>t.name===e);return t||(this.outerScope?this.outerScope.getElement(e):void 0)}}class za{constructor(e,t,a){var r;this.elements=new Map,this.caseInsensitive=null!==(r=null==a?void 0:a.caseInsensitive)&&void 0!==r&&r;for(const n of e){const e=this.caseInsensitive?n.name.toLowerCase():n.name;this.elements.set(e,n)}this.outerScope=t}getElement(e){const t=this.caseInsensitive?e.toLowerCase():e,a=this.elements.get(t);return a||(this.outerScope?this.outerScope.getElement(e):void 0)}getAllElements(){let e=(0,Zt.Td)(this.elements.values());return this.outerScope&&(e=e.concat(this.outerScope.getAllElements())),e}}class Ha{constructor(){this.toDispose=[],this.isDisposed=!1}onDispose(e){this.toDispose.push(e)}dispose(){this.throwIfDisposed(),this.clear(),this.isDisposed=!0,this.toDispose.forEach(e=>e.dispose())}throwIfDisposed(){if(this.isDisposed)throw new Error("This cache has already been disposed")}}class Oa extends Ha{constructor(){super(...arguments),this.cache=new Map}has(e){return this.throwIfDisposed(),this.cache.has(e)}set(e,t){this.throwIfDisposed(),this.cache.set(e,t)}get(e,t){if(this.throwIfDisposed(),this.cache.has(e))return this.cache.get(e);if(t){const a=t();return this.cache.set(e,a),a}}delete(e){return this.throwIfDisposed(),this.cache.delete(e)}clear(){this.throwIfDisposed(),this.cache.clear()}}class Da extends Ha{constructor(e){super(),this.cache=new Map,this.converter=null!=e?e:e=>e}has(e,t){return this.throwIfDisposed(),this.cacheForContext(e).has(t)}set(e,t,a){this.throwIfDisposed(),this.cacheForContext(e).set(t,a)}get(e,t,a){this.throwIfDisposed();const r=this.cacheForContext(e);if(r.has(t))return r.get(t);if(a){const e=a();return r.set(t,e),e}}delete(e,t){return this.throwIfDisposed(),this.cacheForContext(e).delete(t)}clear(e){if(this.throwIfDisposed(),e){const t=this.converter(e);this.cache.delete(t)}else this.cache.clear()}cacheForContext(e){const t=this.converter(e);let a=this.cache.get(t);return a||(a=new Map,this.cache.set(t,a)),a}}class Na extends Oa{constructor(e,t){super(),t?(this.toDispose.push(e.workspace.DocumentBuilder.onBuildPhase(t,()=>{this.clear()})),this.toDispose.push(e.workspace.DocumentBuilder.onUpdate((e,t)=>{t.length>0&&this.clear()}))):this.toDispose.push(e.workspace.DocumentBuilder.onUpdate(()=>{this.clear()}))}}class Va{constructor(e){this.reflection=e.shared.AstReflection,this.nameProvider=e.references.NameProvider,this.descriptions=e.workspace.AstNodeDescriptionProvider,this.indexManager=e.shared.workspace.IndexManager,this.globalScopeCache=new Na(e.shared)}getScope(e){const t=[],a=this.reflection.getReferenceType(e),r=(0,St.YE)(e.container).precomputedScopes;if(r){let n=e.container;do{const e=r.get(n);e.length>0&&t.push((0,Zt.Td)(e).filter(e=>this.reflection.isSubtype(e.type,a))),n=n.$container}while(n)}let n=this.getGlobalScope(a,e);for(let i=t.length-1;i>=0;i--)n=this.createScope(t[i],n);return n}createScope(e,t,a){return new $a((0,Zt.Td)(e),t,a)}createScopeForNodes(e,t,a){const r=(0,Zt.Td)(e).map(e=>{const t=this.nameProvider.getName(e);if(t)return this.descriptions.createDescription(e,t)}).nonNullable();return new $a(r,t,a)}getGlobalScope(e,t){return this.globalScopeCache.get(e,()=>new za(this.indexManager.allElements(e)))}}function ja(e){return"object"==typeof e&&!!e&&("$ref"in e||"$error"in e)}class Fa{constructor(e){this.ignoreProperties=new Set(["$container","$containerProperty","$containerIndex","$document","$cstNode"]),this.langiumDocuments=e.shared.workspace.LangiumDocuments,this.astNodeLocator=e.workspace.AstNodeLocator,this.nameProvider=e.references.NameProvider,this.commentProvider=e.documentation.CommentProvider}serialize(e,t){const a=null!=t?t:{},r=null==t?void 0:t.replacer,n=(e,t)=>this.replacer(e,t,a),i=r?(e,t)=>r(e,t,n):n;try{return this.currentDocument=(0,St.YE)(e),JSON.stringify(e,i,null==t?void 0:t.space)}finally{this.currentDocument=void 0}}deserialize(e,t){const a=null!=t?t:{},r=JSON.parse(e);return this.linkNode(r,r,a),r}replacer(e,t,{refText:a,sourceText:r,textRegions:n,comments:i,uriConverter:o}){var c,s,h,d;if(!this.ignoreProperties.has(e)){if((0,sa.A_)(t)){const e=t.ref,r=a?t.$refText:void 0;if(e){const a=(0,St.YE)(e);let n="";this.currentDocument&&this.currentDocument!==a&&(n=o?o(a.uri,t):a.uri.toString());return{$ref:`${n}#${this.astNodeLocator.getAstNodePath(e)}`,$refText:r}}return{$error:null!==(s=null===(c=t.error)||void 0===c?void 0:c.message)&&void 0!==s?s:"Could not resolve reference",$refText:r}}if((0,sa.ng)(t)){let a;if(n&&(a=this.addAstNodeRegionWithAssignmentsTo(Object.assign({},t)),e&&!t.$document||!(null==a?void 0:a.$textRegion)||(a.$textRegion.documentURI=null===(h=this.currentDocument)||void 0===h?void 0:h.uri.toString())),r&&!e&&(null!=a||(a=Object.assign({},t)),a.$sourceText=null===(d=t.$cstNode)||void 0===d?void 0:d.text),i){null!=a||(a=Object.assign({},t));const e=this.commentProvider.getComment(t);e&&(a.$comment=e.replace(/\r/g,""))}return null!=a?a:t}return t}}addAstNodeRegionWithAssignmentsTo(e){const t=e=>({offset:e.offset,end:e.end,length:e.length,range:e.range});if(e.$cstNode){const a=(e.$textRegion=t(e.$cstNode)).assignments={};return Object.keys(e).filter(e=>!e.startsWith("$")).forEach(r=>{const i=(0,n.Bd)(e.$cstNode,r).map(t);0!==i.length&&(a[r]=i)}),e}}linkNode(e,t,a,r,n,i){for(const[c,s]of Object.entries(e))if(Array.isArray(s))for(let r=0;r{await this.handleException(()=>e.call(t,a,r,n),"An error occurred during validation",r,a)}}async handleException(e,t,a,r){try{await e()}catch(n){if(ua(n))throw n;console.error(`${t}:`,n),n instanceof Error&&n.stack&&console.error(n.stack);a("error",`${t}: ${n instanceof Error?n.message:String(n)}`,{node:r})}}addEntry(e,t){if("AstNode"!==e)for(const a of this.reflection.getAllSubTypes(e))this.entries.add(a,t);else this.entries.add("AstNode",t)}getChecks(e,t){let a=(0,Zt.Td)(this.entries.get(e)).concat(this.entries.get("AstNode"));return t&&(a=a.filter(e=>t.includes(e.category))),a.map(e=>e.check)}registerBeforeDocument(e,t=this){this.entriesBefore.push(this.wrapPreparationException(e,"An error occurred during set-up of the validation",t))}registerAfterDocument(e,t=this){this.entriesAfter.push(this.wrapPreparationException(e,"An error occurred during tear-down of the validation",t))}wrapPreparationException(e,t,a){return async(r,n,i,o)=>{await this.handleException(()=>e.call(a,r,n,i,o),t,n,r)}}get checksBefore(){return this.entriesBefore}get checksAfter(){return this.entriesAfter}}class Ka{constructor(e){this.validationRegistry=e.validation.ValidationRegistry,this.metadata=e.LanguageMetaData}async validateDocument(e,t={},a=ca.XO.None){const r=e.parseResult,n=[];if(await pa(a),!t.categories||t.categories.includes("built-in")){if(this.processLexingErrors(r,n,t),t.stopAfterLexingErrors&&n.some(e=>{var t;return(null===(t=e.data)||void 0===t?void 0:t.code)===Ga.LexingError}))return n;if(this.processParsingErrors(r,n,t),t.stopAfterParsingErrors&&n.some(e=>{var t;return(null===(t=e.data)||void 0===t?void 0:t.code)===Ga.ParsingError}))return n;if(this.processLinkingErrors(e,n,t),t.stopAfterLinkingErrors&&n.some(e=>{var t;return(null===(t=e.data)||void 0===t?void 0:t.code)===Ga.LinkingError}))return n}try{n.push(...await this.validateAst(r.value,t,a))}catch(i){if(ua(i))throw i;console.error("An error occurred during validation:",i)}return await pa(a),n}processLexingErrors(e,t,a){var r,n,i;const o=[...e.lexerErrors,...null!==(n=null===(r=e.lexerReport)||void 0===r?void 0:r.diagnostics)&&void 0!==n?n:[]];for(const c of o){const e=null!==(i=c.severity)&&void 0!==i?i:"error",a={severity:Xa(e),range:{start:{line:c.line-1,character:c.column-1},end:{line:c.line-1,character:c.column+c.length-1}},message:c.message,data:Ya(e),source:this.getSource()};t.push(a)}}processParsingErrors(e,t,a){for(const n of e.parserErrors){let e;if(isNaN(n.token.startOffset)){if("previousToken"in n){const t=n.previousToken;if(isNaN(t.startOffset)){const t={line:0,character:0};e={start:t,end:t}}else{const a={line:t.endLine-1,character:t.endColumn};e={start:a,end:a}}}}else e=(0,r.wf)(n.token);if(e){const a={severity:Xa("error"),range:e,message:n.message,data:_a(Ga.ParsingError),source:this.getSource()};t.push(a)}}}processLinkingErrors(e,t,a){for(const r of e.references){const e=r.error;if(e){const a={node:e.container,property:e.property,index:e.index,data:{code:Ga.LinkingError,containerType:e.container.$type,property:e.property,refText:e.reference.$refText}};t.push(this.toDiagnostic("error",e.message,a))}}}async validateAst(e,t,a=ca.XO.None){const r=[],n=(e,t,a)=>{r.push(this.toDiagnostic(e,t,a))};return await this.validateAstBefore(e,t,n,a),await this.validateAstNodes(e,t,n,a),await this.validateAstAfter(e,t,n,a),r}async validateAstBefore(e,t,a,r=ca.XO.None){var n;const i=this.validationRegistry.checksBefore;for(const o of i)await pa(r),await o(e,a,null!==(n=t.categories)&&void 0!==n?n:[],r)}async validateAstNodes(e,t,a,r=ca.XO.None){await Promise.all((0,St.jm)(e).map(async e=>{await pa(r);const n=this.validationRegistry.getChecks(e.$type,t.categories);for(const t of n)await t(e,a,r)}))}async validateAstAfter(e,t,a,r=ca.XO.None){var n;const i=this.validationRegistry.checksAfter;for(const o of i)await pa(r),await o(e,a,null!==(n=t.categories)&&void 0!==n?n:[],r)}toDiagnostic(e,t,a){return{message:t,range:Za(a),severity:Xa(e),code:a.code,codeDescription:a.codeDescription,tags:a.tags,relatedInformation:a.relatedInformation,data:a.data,source:this.getSource()}}getSource(){return this.metadata.languageId}}function Za(e){if(e.range)return e.range;let t;return"string"==typeof e.property?t=(0,n.qO)(e.node.$cstNode,e.property,e.index):"string"==typeof e.keyword&&(t=(0,n.SS)(e.node.$cstNode,e.keyword,e.index)),null!=t||(t=e.node.$cstNode),t?t.range:{start:{line:0,character:0},end:{line:0,character:0}}}function Xa(e){switch(e){case"error":return 1;case"warning":return 2;case"info":return 3;case"hint":return 4;default:throw new Error("Invalid diagnostic severity: "+e)}}function Ya(e){switch(e){case"error":return _a(Ga.LexingError);case"warning":return _a(Ga.LexingWarning);case"info":return _a(Ga.LexingInfo);case"hint":return _a(Ga.LexingHint);default:throw new Error("Invalid diagnostic severity: "+e)}}!function(e){e.LexingError="lexing-error",e.LexingWarning="lexing-warning",e.LexingInfo="lexing-info",e.LexingHint="lexing-hint",e.ParsingError="parsing-error",e.LinkingError="linking-error"}(Ga||(Ga={}));class Qa{constructor(e){this.astNodeLocator=e.workspace.AstNodeLocator,this.nameProvider=e.references.NameProvider}createDescription(e,t,a){const n=null!=a?a:(0,St.YE)(e);null!=t||(t=this.nameProvider.getName(e));const i=this.astNodeLocator.getAstNodePath(e);if(!t)throw new Error(`Node at path ${i} has no name.`);let o;const c=()=>{var t;return null!=o?o:o=(0,r.SX)(null!==(t=this.nameProvider.getNameNode(e))&&void 0!==t?t:e.$cstNode)};return{node:e,name:t,get nameSegment(){return c()},selectionSegment:(0,r.SX)(e.$cstNode),type:e.$type,documentUri:n.uri,path:i}}}class Ja{constructor(e){this.nodeLocator=e.workspace.AstNodeLocator}async createDescriptions(e,t=ca.XO.None){const a=[],r=e.parseResult.value;for(const n of(0,St.jm)(r))await pa(t),(0,St.DM)(n).filter(e=>!(0,sa.Zl)(e)).forEach(e=>{const t=this.createDescription(e);t&&a.push(t)});return a}createDescription(e){const t=e.reference.$nodeDescription,a=e.reference.$refNode;if(!t||!a)return;const n=(0,St.YE)(e.container).uri;return{sourceUri:n,sourcePath:this.nodeLocator.getAstNodePath(e.container),targetUri:t.documentUri,targetPath:t.path,segment:(0,r.SX)(a),local:Ta.equals(t.documentUri,n)}}}class er{constructor(){this.segmentSeparator="/",this.indexSeparator="@"}getAstNodePath(e){if(e.$container){const t=this.getAstNodePath(e.$container),a=this.getPathSegment(e);return t+this.segmentSeparator+a}return""}getPathSegment({$containerProperty:e,$containerIndex:t}){if(!e)throw new Error("Missing '$containerProperty' in AST node.");return void 0!==t?e+this.indexSeparator+t:e}getAstNode(e,t){return t.split(this.segmentSeparator).reduce((e,t)=>{if(!e||0===t.length)return e;const a=t.indexOf(this.indexSeparator);if(a>0){const r=t.substring(0,a),n=parseInt(t.substring(a+1)),i=e[r];return null==i?void 0:i[n]}return e[t]},e)}}var tr,ar=a(2676);class rr{constructor(e){this._ready=new ya,this.settings={},this.workspaceConfig=!1,this.onConfigurationSectionUpdateEmitter=new ar.Emitter,this.serviceRegistry=e.ServiceRegistry}get ready(){return this._ready.promise}initialize(e){var t,a;this.workspaceConfig=null!==(a=null===(t=e.capabilities.workspace)||void 0===t?void 0:t.configuration)&&void 0!==a&&a}async initialized(e){if(this.workspaceConfig){if(e.register){const t=this.serviceRegistry.all;e.register({section:t.map(e=>this.toSectionName(e.LanguageMetaData.languageId))})}if(e.fetchConfiguration){const t=this.serviceRegistry.all.map(e=>({section:this.toSectionName(e.LanguageMetaData.languageId)})),a=await e.fetchConfiguration(t);t.forEach((e,t)=>{this.updateSectionConfiguration(e.section,a[t])})}}this._ready.resolve()}updateConfiguration(e){e.settings&&Object.keys(e.settings).forEach(t=>{const a=e.settings[t];this.updateSectionConfiguration(t,a),this.onConfigurationSectionUpdateEmitter.fire({section:t,configuration:a})})}updateSectionConfiguration(e,t){this.settings[e]=t}async getConfiguration(e,t){await this.ready;const a=this.toSectionName(e);if(this.settings[a])return this.settings[a][t]}toSectionName(e){return`${e}`}get onConfigurationSectionUpdate(){return this.onConfigurationSectionUpdateEmitter.event}}!function(e){e.create=function(e){return{dispose:async()=>await e()}}}(tr||(tr={}));class nr{constructor(e){this.updateBuildOptions={validation:{categories:["built-in","fast"]}},this.updateListeners=[],this.buildPhaseListeners=new Pa,this.documentPhaseListeners=new Pa,this.buildState=new Map,this.documentBuildWaiters=new Map,this.currentState=La.Changed,this.langiumDocuments=e.workspace.LangiumDocuments,this.langiumDocumentFactory=e.workspace.LangiumDocumentFactory,this.textDocuments=e.workspace.TextDocuments,this.indexManager=e.workspace.IndexManager,this.serviceRegistry=e.ServiceRegistry}async build(e,t={},a=ca.XO.None){var r,n;for(const i of e){const e=i.uri.toString();if(i.state===La.Validated){if("boolean"==typeof t.validation&&t.validation)i.state=La.IndexedReferences,i.diagnostics=void 0,this.buildState.delete(e);else if("object"==typeof t.validation){const a=this.buildState.get(e),o=null===(r=null==a?void 0:a.result)||void 0===r?void 0:r.validationChecks;if(o){const r=(null!==(n=t.validation.categories)&&void 0!==n?n:Ua.all).filter(e=>!o.includes(e));r.length>0&&(this.buildState.set(e,{completed:!1,options:{validation:Object.assign(Object.assign({},t.validation),{categories:r})},result:a.result}),i.state=La.IndexedReferences)}}}else this.buildState.delete(e)}this.currentState=La.Changed,await this.emitUpdate(e.map(e=>e.uri),[]),await this.buildDocuments(e,t,a)}async update(e,t,a=ca.XO.None){this.currentState=La.Changed;for(const i of t)this.langiumDocuments.deleteDocument(i),this.buildState.delete(i.toString()),this.indexManager.remove(i);for(const i of e){if(!this.langiumDocuments.invalidateDocument(i)){const e=this.langiumDocumentFactory.fromModel({$type:"INVALID"},i);e.state=La.Changed,this.langiumDocuments.addDocument(e)}this.buildState.delete(i.toString())}const r=(0,Zt.Td)(e).concat(t).map(e=>e.toString()).toSet();this.langiumDocuments.all.filter(e=>!r.has(e.uri.toString())&&this.shouldRelink(e,r)).forEach(e=>{this.serviceRegistry.getServices(e.uri).references.Linker.unlink(e),e.state=Math.min(e.state,La.ComputedScopes),e.diagnostics=void 0}),await this.emitUpdate(e,t),await pa(a);const n=this.sortDocuments(this.langiumDocuments.all.filter(e=>{var t;return e.statea(e,t)))}sortDocuments(e){let t=0,a=e.length-1;for(;t=0&&!this.hasTextDocument(e[a]);)a--;tvoid 0!==e.error)||this.indexManager.isAffected(e,t)}onUpdate(e){return this.updateListeners.push(e),tr.create(()=>{const t=this.updateListeners.indexOf(e);t>=0&&this.updateListeners.splice(t,1)})}async buildDocuments(e,t,a){this.prepareBuild(e,t),await this.runCancelable(e,La.Parsed,a,e=>this.langiumDocumentFactory.update(e,a)),await this.runCancelable(e,La.IndexedContent,a,e=>this.indexManager.updateContent(e,a)),await this.runCancelable(e,La.ComputedScopes,a,async e=>{const t=this.serviceRegistry.getServices(e.uri).references.ScopeComputation;e.precomputedScopes=await t.computeLocalScopes(e,a)}),await this.runCancelable(e,La.Linked,a,e=>this.serviceRegistry.getServices(e.uri).references.Linker.link(e,a)),await this.runCancelable(e,La.IndexedReferences,a,e=>this.indexManager.updateReferences(e,a));const r=e.filter(e=>this.shouldValidate(e));await this.runCancelable(r,La.Validated,a,e=>this.validate(e,a));for(const n of e){const e=this.buildState.get(n.uri.toString());e&&(e.completed=!0)}}prepareBuild(e,t){for(const a of e){const e=a.uri.toString(),r=this.buildState.get(e);r&&!r.completed||this.buildState.set(e,{completed:!1,options:t,result:null==r?void 0:r.result})}}async runCancelable(e,t,a,r){const n=e.filter(e=>e.statee.state===t);await this.notifyBuildPhase(i,t,a),this.currentState=t}onBuildPhase(e,t){return this.buildPhaseListeners.add(e,t),tr.create(()=>{this.buildPhaseListeners.delete(e,t)})}onDocumentPhase(e,t){return this.documentPhaseListeners.add(e,t),tr.create(()=>{this.documentPhaseListeners.delete(e,t)})}waitUntil(e,t,a){let r;if(t&&"path"in t?r=t:a=t,null!=a||(a=ca.XO.None),r){const t=this.langiumDocuments.getDocument(r);if(t&&t.state>e)return Promise.resolve(r)}return this.currentState>=e?Promise.resolve(void 0):a.isCancellationRequested?Promise.reject(la):new Promise((t,n)=>{const i=this.onBuildPhase(e,()=>{if(i.dispose(),o.dispose(),r){const e=this.langiumDocuments.getDocument(r);t(null==e?void 0:e.uri)}else t(void 0)}),o=a.onCancellationRequested(()=>{i.dispose(),o.dispose(),n(la)})})}async notifyDocumentPhase(e,t,a){const r=this.documentPhaseListeners.get(t).slice();for(const i of r)try{await i(e,a)}catch(n){if(!ua(n))throw n}}async notifyBuildPhase(e,t,a){if(0===e.length)return;const r=this.buildPhaseListeners.get(t).slice();for(const n of r)await pa(a),await n(e,a)}shouldValidate(e){return Boolean(this.getBuildOptions(e).validation)}async validate(e,t){var a,r;const n=this.serviceRegistry.getServices(e.uri).validation.DocumentValidator,i=this.getBuildOptions(e).validation,o="object"==typeof i?i:void 0,c=await n.validateDocument(e,o,t);e.diagnostics?e.diagnostics.push(...c):e.diagnostics=c;const s=this.buildState.get(e.uri.toString());if(s){null!==(a=s.result)&&void 0!==a||(s.result={});const e=null!==(r=null==o?void 0:o.categories)&&void 0!==r?r:Ua.all;s.result.validationChecks?s.result.validationChecks.push(...e):s.result.validationChecks=[...e]}}getBuildOptions(e){var t,a;return null!==(a=null===(t=this.buildState.get(e.uri.toString()))||void 0===t?void 0:t.options)&&void 0!==a?a:{}}}class ir{constructor(e){this.symbolIndex=new Map,this.symbolByTypeIndex=new Da,this.referenceIndex=new Map,this.documents=e.workspace.LangiumDocuments,this.serviceRegistry=e.ServiceRegistry,this.astReflection=e.AstReflection}findAllReferences(e,t){const a=(0,St.YE)(e).uri,r=[];return this.referenceIndex.forEach(e=>{e.forEach(e=>{Ta.equals(e.targetUri,a)&&e.targetPath===t&&r.push(e)})}),(0,Zt.Td)(r)}allElements(e,t){let a=(0,Zt.Td)(this.symbolIndex.keys());return t&&(a=a.filter(e=>!t||t.has(e))),a.map(t=>this.getFileDescriptions(t,e)).flat()}getFileDescriptions(e,t){var a;if(!t)return null!==(a=this.symbolIndex.get(e))&&void 0!==a?a:[];const r=this.symbolByTypeIndex.get(e,t,()=>{var a;return(null!==(a=this.symbolIndex.get(e))&&void 0!==a?a:[]).filter(e=>this.astReflection.isSubtype(e.type,t))});return r}remove(e){const t=e.toString();this.symbolIndex.delete(t),this.symbolByTypeIndex.clear(t),this.referenceIndex.delete(t)}async updateContent(e,t=ca.XO.None){const a=this.serviceRegistry.getServices(e.uri),r=await a.references.ScopeComputation.computeExports(e,t),n=e.uri.toString();this.symbolIndex.set(n,r),this.symbolByTypeIndex.clear(n)}async updateReferences(e,t=ca.XO.None){const a=this.serviceRegistry.getServices(e.uri),r=await a.workspace.ReferenceDescriptionProvider.createDescriptions(e,t);this.referenceIndex.set(e.uri.toString(),r)}isAffected(e,t){const a=this.referenceIndex.get(e.uri.toString());return!!a&&a.some(e=>!e.local&&t.has(e.targetUri.toString()))}}class or{constructor(e){this.initialBuildOptions={},this._ready=new ya,this.serviceRegistry=e.ServiceRegistry,this.langiumDocuments=e.workspace.LangiumDocuments,this.documentBuilder=e.workspace.DocumentBuilder,this.fileSystemProvider=e.workspace.FileSystemProvider,this.mutex=e.workspace.WorkspaceLock}get ready(){return this._ready.promise}get workspaceFolders(){return this.folders}initialize(e){var t;this.folders=null!==(t=e.workspaceFolders)&&void 0!==t?t:void 0}initialized(e){return this.mutex.write(e=>{var t;return this.initializeWorkspace(null!==(t=this.folders)&&void 0!==t?t:[],e)})}async initializeWorkspace(e,t=ca.XO.None){const a=await this.performStartup(e);await pa(t),await this.documentBuilder.build(a,this.initialBuildOptions,t)}async performStartup(e){const t=this.serviceRegistry.all.flatMap(e=>e.LanguageMetaData.fileExtensions),a=[],r=e=>{a.push(e),this.langiumDocuments.hasDocument(e.uri)||this.langiumDocuments.addDocument(e)};return await this.loadAdditionalDocuments(e,r),await Promise.all(e.map(e=>[e,this.getRootFolder(e)]).map(async e=>this.traverseFolder(...e,t,r))),this._ready.resolve(),a}loadAdditionalDocuments(e,t){return Promise.resolve()}getRootFolder(e){return wa.r.parse(e.uri)}async traverseFolder(e,t,a,r){const n=await this.fileSystemProvider.readDirectory(t);await Promise.all(n.map(async t=>{if(this.includeEntry(e,t,a))if(t.isDirectory)await this.traverseFolder(e,t.uri,a,r);else if(t.isFile){const e=await this.langiumDocuments.getOrCreateDocument(t.uri);r(e)}}))}includeEntry(e,t,a){const r=Ta.basename(t.uri);if(r.startsWith("."))return!1;if(t.isDirectory)return"node_modules"!==r&&"out"!==r;if(t.isFile){const e=Ta.extname(t.uri);return a.includes(e)}return!1}}class cr{buildUnexpectedCharactersMessage(e,t,a,r,n){return c.PW.buildUnexpectedCharactersMessage(e,t,a,r,n)}buildUnableToPopLexerModeMessage(e){return c.PW.buildUnableToPopLexerModeMessage(e)}}const sr={mode:"full"};class hr{constructor(e){this.errorMessageProvider=e.parser.LexerErrorMessageProvider,this.tokenBuilder=e.parser.TokenBuilder;const t=this.tokenBuilder.buildTokens(e.Grammar,{caseInsensitive:e.LanguageMetaData.caseInsensitive});this.tokenTypes=this.toTokenTypeDictionary(t);const a=lr(t)?Object.values(t):t,r="production"===e.LanguageMetaData.mode;this.chevrotainLexer=new c.JG(a,{positionTracking:"full",skipValidations:r,errorMessageProvider:this.errorMessageProvider})}get definition(){return this.tokenTypes}tokenize(e,t=sr){var a,r,n;const i=this.chevrotainLexer.tokenize(e);return{tokens:i.tokens,errors:i.errors,hidden:null!==(a=i.groups.hidden)&&void 0!==a?a:[],report:null===(n=(r=this.tokenBuilder).flushLexingReport)||void 0===n?void 0:n.call(r,e)}}toTokenTypeDictionary(e){if(lr(e))return e;const t=dr(e)?Object.values(e.modes).flat():e,a={};return t.forEach(e=>a[e.name]=e),a}}function dr(e){return e&&"modes"in e&&"defaultMode"in e}function lr(e){return!function(e){return Array.isArray(e)&&(0===e.length||"name"in e[0])}(e)&&!dr(e)}function ur(e,t,a){let r,n;"string"==typeof e?(n=t,r=a):(n=e.range.start,r=t),n||(n=se.create(0,0));const i=function(e){var t,a,r;const n=[];let i=e.position.line,o=e.position.character;for(let c=0;c=d.length){if(n.length>0){const e=se.create(i,o);n.push({type:"break",content:"",range:he.create(e,e)})}}else{yr.lastIndex=l;const e=yr.exec(d);if(e){const t=e[0],a=e[1],r=se.create(i,o+l),c=se.create(i,o+l+t.length);n.push({type:"tag",content:a,range:he.create(r,c)}),l+=t.length,l=Mr(d,l)}if(l0&&"break"===n[n.length-1].type)return n.slice(0,-1);return n}({lines:pr(e),position:n,options:Cr(r)});return function(e){var t,a,r,n;const i=se.create(e.position.line,e.position.character);if(0===e.tokens.length)return new Sr([],he.create(i,i));const o=[];for(;e.index0&&n.push({type:"text",content:t.substring(i,e),range:he.create(se.create(a,i+r),se.create(a,e+r))});let s=o.length+1;const h=c[1];if(n.push({type:"inline-tag",content:h,range:he.create(se.create(a,i+s+r),se.create(a,i+s+h.length+r))}),s+=h.length,4===c.length){s+=c[2].length;const e=c[3];n.push({type:"text",content:e,range:he.create(se.create(a,i+s+r),se.create(a,i+s+e.length+r))})}else n.push({type:"text",content:"",range:he.create(se.create(a,i+s+r),se.create(a,i+s+r))});i=e+c[0].length}const o=t.substring(i);o.length>0&&n.push({type:"text",content:o,range:he.create(se.create(a,i+r),se.create(a,i+r+o.length))})}return n}const mr=/\S/,gr=/\s*$/;function Mr(e,t){const a=e.substring(t).match(mr);return a?t+a.index:e.length}function vr(e){const t=e.match(gr);if(t&&"number"==typeof t.index)return t.index}function xr(e,t){const a=e.tokens[e.index];return"tag"===a.type?Ar(e,!1):"text"===a.type||"inline-tag"===a.type?Lr(e):(function(e,t){if(t){const a=new Pr("",e.range);"inlines"in t?t.inlines.push(a):t.content.inlines.push(a)}}(a,t),void e.index++)}function Lr(e){let t=e.tokens[e.index];const a=t;let r=t;const n=[];for(;t&&"break"!==t.type&&"tag"!==t.type;)n.push(wr(e)),r=t,t=e.tokens[e.index];return new Rr(n,he.create(a.range.start,r.range.end))}function wr(e){return"inline-tag"===e.tokens[e.index].type?Ar(e,!0):Ir(e)}function Ar(e,t){const a=e.tokens[e.index++],r=a.content.substring(1),n=e.tokens[e.index];if("text"===(null==n?void 0:n.type)){if(t){const n=Ir(e);return new Tr(r,new Rr([n],n.range),t,he.create(a.range.start,n.range.end))}{const n=Lr(e);return new Tr(r,n,t,he.create(a.range.start,n.range.end))}}{const e=a.range;return new Tr(r,new Rr([],e),t,e)}}function Ir(e){const t=e.tokens[e.index++];return new Pr(t.content,t.range)}function Cr(e){if(!e)return Cr({start:"/**",end:"*/",line:"*"});const{start:t,end:a,line:r}=e;return{start:br(t,!0),end:br(a,!1),line:br(r,!0)}}function br(e,t){if("string"==typeof e||"object"==typeof e){const a="string"==typeof e?(0,i.Nt)(e):e.source;return t?new RegExp(`^\\s*${a}`):new RegExp(`\\s*${a}\\s*$`)}return e}class Sr{constructor(e,t){this.elements=e,this.range=t}getTag(e){return this.getAllTags().find(t=>t.name===e)}getTags(e){return this.getAllTags().filter(t=>t.name===e)}getAllTags(){return this.elements.filter(e=>"name"in e)}toString(){let e="";for(const t of this.elements)if(0===e.length)e=t.toString();else{const a=t.toString();e+=qr(e)+a}return e.trim()}toMarkdown(e){let t="";for(const a of this.elements)if(0===t.length)t=a.toMarkdown(e);else{const r=a.toMarkdown(e);t+=qr(t)+r}return t.trim()}}class Tr{constructor(e,t,a,r){this.name=e,this.content=t,this.inline=a,this.range=r}toString(){let e=`@${this.name}`;const t=this.content.toString();return 1===this.content.inlines.length?e=`${e} ${t}`:this.content.inlines.length>1&&(e=`${e}\n${t}`),this.inline?`{${e}}`:e}toMarkdown(e){var t,a;return null!==(a=null===(t=null==e?void 0:e.renderTag)||void 0===t?void 0:t.call(e,this))&&void 0!==a?a:this.toMarkdownDefault(e)}toMarkdownDefault(e){const t=this.content.toMarkdown(e);if(this.inline){const a=function(e,t,a){var r,n;if("linkplain"===e||"linkcode"===e||"link"===e){const i=t.indexOf(" ");let o=t;if(i>0){const e=Mr(t,i);o=t.substring(e),t=t.substring(0,i)}("linkcode"===e||"link"===e&&"code"===a.link)&&(o=`\`${o}\``);const c=null!==(n=null===(r=a.renderLink)||void 0===r?void 0:r.call(a,t,o))&&void 0!==n?n:function(e,t){try{return wa.r.parse(e,!0),`[${t}](${e})`}catch(r){return e}}(t,o);return c}return}(this.name,t,null!=e?e:{});if("string"==typeof a)return a}let a="";"italic"===(null==e?void 0:e.tag)||void 0===(null==e?void 0:e.tag)?a="*":"bold"===(null==e?void 0:e.tag)?a="**":"bold-italic"===(null==e?void 0:e.tag)&&(a="***");let r=`${a}@${this.name}${a}`;return 1===this.content.inlines.length?r=`${r} \u2014 ${t}`:this.content.inlines.length>1&&(r=`${r}\n${t}`),this.inline?`{${r}}`:r}}class Rr{constructor(e,t){this.inlines=e,this.range=t}toString(){let e="";for(let t=0;ta.range.start.line&&(e+="\n")}return e}toMarkdown(e){let t="";for(let a=0;ar.range.start.line&&(t+="\n")}return t}}class Pr{constructor(e,t){this.text=e,this.range=t}toString(){return this.text}toMarkdown(){return this.text}}function qr(e){return e.endsWith("\n")?"\n":"\n\n"}class Er{constructor(e){this.indexManager=e.shared.workspace.IndexManager,this.commentProvider=e.documentation.CommentProvider}getDocumentation(e){const t=this.commentProvider.getComment(e);if(t&&function(e,t){const a=Cr(t),r=pr(e);if(0===r.length)return!1;const n=r[0],i=r[r.length-1],o=a.start,c=a.end;return Boolean(null==o?void 0:o.exec(n))&&Boolean(null==c?void 0:c.exec(i))}(t)){return ur(t).toMarkdown({renderLink:(t,a)=>this.documentationLinkRenderer(e,t,a),renderTag:t=>this.documentationTagRenderer(e,t)})}}documentationLinkRenderer(e,t,a){var r;const n=null!==(r=this.findNameInPrecomputedScopes(e,t))&&void 0!==r?r:this.findNameInGlobalScope(e,t);if(n&&n.nameSegment){const e=n.nameSegment.range.start.line+1,t=n.nameSegment.range.start.character+1;return`[${a}](${n.documentUri.with({fragment:`L${e},${t}`}).toString()})`}}documentationTagRenderer(e,t){}findNameInPrecomputedScopes(e,t){const a=(0,St.YE)(e).precomputedScopes;if(!a)return;let r=e;do{const e=a.get(r).find(e=>e.name===t);if(e)return e;r=r.$container}while(r)}findNameInGlobalScope(e,t){return this.indexManager.allElements().find(e=>e.name===t)}}class $r{constructor(e){this.grammarConfig=()=>e.parser.GrammarConfig}getComment(e){var t;return function(e){return"string"==typeof e.$comment}(e)?e.$comment:null===(t=(0,r.v)(e.$cstNode,this.grammarConfig().multilineCommentRules))||void 0===t?void 0:t.text}}class zr{constructor(e){this.syncParser=e.parser.LangiumParser}parse(e,t){return Promise.resolve(this.syncParser.parse(e))}}class Hr{constructor(){this.previousTokenSource=new ca.Qi,this.writeQueue=[],this.readQueue=[],this.done=!0}write(e){this.cancelWrite();const t=(ha=performance.now(),new ca.Qi);return this.previousTokenSource=t,this.enqueue(this.writeQueue,e,t.token)}read(e){return this.enqueue(this.readQueue,e)}enqueue(e,t,a=ca.XO.None){const r=new ya,n={action:t,deferred:r,cancellationToken:a};return e.push(n),this.performNextOperation(),r.promise}async performNextOperation(){if(!this.done)return;const e=[];if(this.writeQueue.length>0)e.push(this.writeQueue.shift());else{if(!(this.readQueue.length>0))return;e.push(...this.readQueue.splice(0,this.readQueue.length))}this.done=!1,await Promise.all(e.map(async({action:e,deferred:t,cancellationToken:a})=>{try{const r=await Promise.resolve().then(()=>e(a));t.resolve(r)}catch(r){ua(r)?t.resolve(void 0):t.reject(r)}})),this.done=!0,this.performNextOperation()}cancelWrite(){this.previousTokenSource.cancel()}}class Or{constructor(e){this.grammarElementIdMap=new qa,this.tokenTypeIdMap=new qa,this.grammar=e.Grammar,this.lexer=e.parser.Lexer,this.linker=e.references.Linker}dehydrate(e){return{lexerErrors:e.lexerErrors,lexerReport:e.lexerReport?this.dehydrateLexerReport(e.lexerReport):void 0,parserErrors:e.parserErrors.map(e=>Object.assign(Object.assign({},e),{message:e.message})),value:this.dehydrateAstNode(e.value,this.createDehyrationContext(e.value))}}dehydrateLexerReport(e){return e}createDehyrationContext(e){const t=new Map,a=new Map;for(const r of(0,St.jm)(e))t.set(r,{});if(e.$cstNode)for(const n of(0,r.NS)(e.$cstNode))a.set(n,{});return{astNodes:t,cstNodes:a}}dehydrateAstNode(e,t){const a=t.astNodes.get(e);a.$type=e.$type,a.$containerIndex=e.$containerIndex,a.$containerProperty=e.$containerProperty,void 0!==e.$cstNode&&(a.$cstNode=this.dehydrateCstNode(e.$cstNode,t));for(const[r,n]of Object.entries(e))if(!r.startsWith("$"))if(Array.isArray(n)){const e=[];a[r]=e;for(const a of 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processing`,()=>{if(this.modes.push(a),!1===this.config.skipValidations&&this.TRACE_INIT("validatePatterns",()=>{this.lexerDefinitionErrors=this.lexerDefinitionErrors.concat(it(e,d))}),(0,i.A)(this.lexerDefinitionErrors)){let r;St(e),this.TRACE_INIT("analyzeTokenTypes",()=>{r=nt(e,{lineTerminatorCharacters:this.config.lineTerminatorCharacters,positionTracking:t.positionTracking,ensureOptimizations:t.ensureOptimizations,safeMode:t.safeMode,tracer:this.TRACE_INIT})}),this.patternIdxToConfig[a]=r.patternIdxToConfig,this.charCodeToPatternIdxToConfig[a]=r.charCodeToPatternIdxToConfig,this.emptyGroups=x({},this.emptyGroups,r.emptyGroups),this.hasCustom=r.hasCustom||this.hasCustom,this.canModeBeOptimized[a]=r.canBeOptimized}})}),this.defaultMode=a.defaultMode,!(0,i.A)(this.lexerDefinitionErrors)&&!this.config.deferDefinitionErrorsHandling){const e=(0,o.A)(this.lexerDefinitionErrors,e=>e.message).join("-----------------------\n");throw new Error("Errors detected in definition of Lexer:\n"+e)}(0,r.A)(this.lexerDefinitionWarning,e=>{je(e.message)}),this.TRACE_INIT("Choosing sub-methods implementations",()=>{if(rt?(this.chopInput=vt.A,this.match=this.matchWithTest):(this.updateLastIndex=xt.A,this.match=this.matchWithExec),n&&(this.handleModes=xt.A),!1===this.trackStartLines&&(this.computeNewColumn=vt.A),!1===this.trackEndLines&&(this.updateTokenEndLineColumnLocation=xt.A),/full/i.test(this.config.positionTracking))this.createTokenInstance=this.createFullToken;else if(/onlyStart/i.test(this.config.positionTracking))this.createTokenInstance=this.createStartOnlyToken;else{if(!/onlyOffset/i.test(this.config.positionTracking))throw Error(`Invalid config option: "${this.config.positionTracking}"`);this.createTokenInstance=this.createOffsetOnlyToken}this.hasCustom?(this.addToken=this.addTokenUsingPush,this.handlePayload=this.handlePayloadWithCustom):(this.addToken=this.addTokenUsingMemberAccess,this.handlePayload=this.handlePayloadNoCustom)}),this.TRACE_INIT("Failed Optimization Warnings",()=>{const e=(0,Ce.A)(this.canModeBeOptimized,(e,t,a)=>(!1===t&&e.push(a),e),[]);if(t.ensureOptimizations&&!(0,i.A)(e))throw Error(`Lexer Modes: < ${e.join(", ")} > cannot be optimized.\n\t Disable the "ensureOptimizations" lexer config flag to silently ignore this and run the lexer in an un-optimized mode.\n\t Or inspect the console log for details on how to resolve these issues.`)}),this.TRACE_INIT("clearRegExpParserCache",()=>{Fe={}}),this.TRACE_INIT("toFastProperties",()=>{h(this)})})}tokenize(e,t=this.defaultMode){if(!(0,i.A)(this.lexerDefinitionErrors)){const e=(0,o.A)(this.lexerDefinitionErrors,e=>e.message).join("-----------------------\n");throw new Error("Unable to Tokenize because Errors detected in definition of Lexer:\n"+e)}return this.tokenizeInternal(e,t)}tokenizeInternal(e,t){let a,n,i,o,c,s,h,d,l,u,p,y,k,f,m;const g=e,v=g.length;let x=0,L=0;const w=this.hasCustom?0:Math.floor(e.length/10),A=new Array(w),I=[];let C=this.trackStartLines?1:void 0,b=this.trackStartLines?1:void 0;const S=function(e){const t={},a=(0,M.A)(e);return(0,r.A)(a,a=>{const r=e[a];if(!(0,Y.A)(r))throw Error("non exhaustive match");t[a]=[]}),t}(this.emptyGroups),T=this.trackStartLines,R=this.config.lineTerminatorsPattern;let P=0,q=[],E=[];const $=[],z=[];let H;function O(){return q}function D(e){const t=Mt(e),a=E[t];return void 0===a?z:a}Object.freeze(z);const N=e=>{if(1===$.length&&void 0===e.tokenType.PUSH_MODE){const t=this.config.errorMessageProvider.buildUnableToPopLexerModeMessage(e);I.push({offset:e.startOffset,line:e.startLine,column:e.startColumn,length:e.image.length,message:t})}else{$.pop();const e=(0,Lt.A)($);q=this.patternIdxToConfig[e],E=this.charCodeToPatternIdxToConfig[e],P=q.length;const t=this.canModeBeOptimized[e]&&!1===this.config.safeMode;H=E&&t?D:O}};function V(e){$.push(e),E=this.charCodeToPatternIdxToConfig[e],q=this.patternIdxToConfig[e],P=q.length,P=q.length;const t=this.canModeBeOptimized[e]&&!1===this.config.safeMode;H=E&&t?D:O}let j;V.call(this,t);const F=this.config.recoveryEnabled;for(;xs.length){s=o,h=d,j=t;break}}}break}}if(null!==s){if(l=s.length,u=j.group,void 0!==u&&(p=j.tokenTypeIdx,y=this.createTokenInstance(s,x,p,j.tokenType,C,b,l),this.handlePayload(y,h),!1===u?L=this.addToken(A,L,y):S[u].push(y)),e=this.chopInput(e,l),x+=l,b=this.computeNewColumn(b,l),!0===T&&!0===j.canLineTerminator){let e,t,a=0;R.lastIndex=0;do{e=R.test(s),!0===e&&(t=R.lastIndex-1,a++)}while(!0===e);0!==a&&(C+=a,b=l-t,this.updateTokenEndLineColumnLocation(y,u,t,a,C,b,l))}this.handleModes(j,N,V,y)}else{const t=x,a=C,r=b;let i=!1===F;for(;!1===i&&x`Expecting ${Dt(e)?`--\x3e ${Ot(e)} <--`:`token of type --\x3e ${e.name} <--`} but found --\x3e '${t.image}' <--`,buildNotAllInputParsedMessage:({firstRedundant:e,ruleName:t})=>"Redundant input, expecting EOF but found: "+e.image,buildNoViableAltMessage({expectedPathsPerAlt:e,actual:t,previous:a,customUserDescription:r,ruleName:n}){const i="Expecting: ",c="\nbut found: '"+De(t).image+"'";if(r)return i+r+c;{const t=(0,Ce.A)(e,(e,t)=>e.concat(t),[]),a=(0,o.A)(t,e=>`[${(0,o.A)(e,e=>Ot(e)).join(", ")}]`);return i+`one of these possible Token sequences:\n${(0,o.A)(a,(e,t)=>` ${t+1}. ${e}`).join("\n")}`+c}},buildEarlyExitMessage({expectedIterationPaths:e,actual:t,customUserDescription:a,ruleName:r}){const n="Expecting: ",i="\nbut found: '"+De(t).image+"'";if(a)return n+a+i;return n+`expecting at least one iteration which starts with one of these possible Token sequences::\n <${(0,o.A)(e,e=>`[${(0,o.A)(e,e=>Ot(e)).join(",")}]`).join(" ,")}>`+i}};Object.freeze(Qt);const Jt={buildRuleNotFoundError:(e,t)=>"Invalid grammar, reference to a rule which is not defined: ->"+t.nonTerminalName+"<-\ninside top level rule: ->"+e.name+"<-"},ea={buildDuplicateFoundError(e,t){const a=e.name,r=De(t),n=r.idx,i=ce(r),o=(c=r)instanceof U?c.terminalType.name:c instanceof H?c.nonTerminalName:"";var c;let s=`->${i}${n>0?n:""}<- ${o?`with argument: ->${o}<-`:""}\n appears more than once (${t.length} times) in the top level rule: ->${a}<-. \n For further details see: https://chevrotain.io/docs/FAQ.html#NUMERICAL_SUFFIXES \n `;return s=s.replace(/[ \t]+/g," "),s=s.replace(/\s\s+/g,"\n"),s},buildNamespaceConflictError:e=>`Namespace conflict found in grammar.\nThe grammar has both a Terminal(Token) and a Non-Terminal(Rule) named: <${e.name}>.\nTo resolve this make sure each Terminal and Non-Terminal names are unique\nThis is easy to accomplish by using the convention that Terminal names start with an uppercase letter\nand Non-Terminal names start with a lower case letter.`,buildAlternationPrefixAmbiguityError(e){const t=(0,o.A)(e.prefixPath,e=>Ot(e)).join(", "),a=0===e.alternation.idx?"":e.alternation.idx;return`Ambiguous alternatives: <${e.ambiguityIndices.join(" ,")}> due to common lookahead prefix\nin inside <${e.topLevelRule.name}> Rule,\n<${t}> may appears as a prefix path in all these alternatives.\nSee: https://chevrotain.io/docs/guide/resolving_grammar_errors.html#COMMON_PREFIX\nFor Further details.`},buildAlternationAmbiguityError(e){const t=(0,o.A)(e.prefixPath,e=>Ot(e)).join(", "),a=0===e.alternation.idx?"":e.alternation.idx;let r=`Ambiguous Alternatives Detected: <${e.ambiguityIndices.join(" ,")}> in inside <${e.topLevelRule.name}> Rule,\n<${t}> may appears as a prefix path in all these alternatives.\n`;return r+="See: https://chevrotain.io/docs/guide/resolving_grammar_errors.html#AMBIGUOUS_ALTERNATIVES\nFor Further details.",r},buildEmptyRepetitionError(e){let t=ce(e.repetition);0!==e.repetition.idx&&(t+=e.repetition.idx);return`The repetition <${t}> within Rule <${e.topLevelRule.name}> can never consume any tokens.\nThis could lead to an infinite loop.`},buildTokenNameError:e=>"deprecated",buildEmptyAlternationError:e=>`Ambiguous empty alternative: <${e.emptyChoiceIdx+1}> in inside <${e.topLevelRule.name}> Rule.\nOnly the last alternative may be an empty alternative.`,buildTooManyAlternativesError:e=>`An Alternation cannot have more than 256 alternatives:\n inside <${e.topLevelRule.name}> Rule.\n has ${e.alternation.definition.length+1} alternatives.`,buildLeftRecursionError(e){const t=e.topLevelRule.name;return`Left Recursion found in grammar.\nrule: <${t}> can be invoked from itself (directly or indirectly)\nwithout consuming any Tokens. The grammar path that causes this is: \n ${`${t} --\x3e ${(0,o.A)(e.leftRecursionPath,e=>e.name).concat([t]).join(" --\x3e ")}`}\n To fix this refactor your grammar to remove the left recursion.\nsee: https://en.wikipedia.org/wiki/LL_parser#Left_factoring.`},buildInvalidRuleNameError:e=>"deprecated",buildDuplicateRuleNameError(e){let t;t=e.topLevelRule instanceof O?e.topLevelRule.name:e.topLevelRule;return`Duplicate definition, rule: ->${t}<- is already defined in the grammar: ->${e.grammarName}<-`}};class ta extends W{constructor(e,t){super(),this.nameToTopRule=e,this.errMsgProvider=t,this.errors=[]}resolveRefs(){(0,r.A)((0,n.A)(this.nameToTopRule),e=>{this.currTopLevel=e,e.accept(this)})}visitNonTerminal(e){const t=this.nameToTopRule[e.nonTerminalName];if(t)e.referencedRule=t;else{const t=this.errMsgProvider.buildRuleNotFoundError(this.currTopLevel,e);this.errors.push({message:t,type:qr.UNRESOLVED_SUBRULE_REF,ruleName:this.currTopLevel.name,unresolvedRefName:e.nonTerminalName})}}}var aa=a(8139),ra=a(2528);const na=function(e,t,a,r){for(var n=-1,i=null==e?0:e.length;++n{!1===(0,i.A)(e.definition)&&(n=c(e.definition))}),n;if(!(t instanceof U))throw Error("non exhaustive match");a.push(t.terminalType)}}o++}return n.push({partialPath:a,suffixDef:u(e,o)}),n}function ga(e,t,a,r){const n="EXIT_NONE_TERMINAL",o=[n],c="EXIT_ALTERNATIVE";let h=!1;const d=t.length,l=d-r-1,p=[],y=[];for(y.push({idx:-1,def:e,ruleStack:[],occurrenceStack:[]});!(0,i.A)(y);){const e=y.pop();if(e===c){h&&(0,Lt.A)(y).idx<=l&&y.pop();continue}const r=e.def,k=e.idx,f=e.ruleStack,m=e.occurrenceStack;if((0,i.A)(r))continue;const g=r[0];if(g===n){const e={idx:k,def:u(r),ruleStack:ha(f),occurrenceStack:ha(m)};y.push(e)}else if(g instanceof U)if(k=0;t--){const e={idx:k,def:g.definition[t].definition.concat(u(r)),ruleStack:f,occurrenceStack:m};y.push(e),y.push(c)}else if(g instanceof D)y.push({idx:k,def:g.definition.concat(u(r)),ruleStack:f,occurrenceStack:m});else{if(!(g instanceof O))throw Error("non exhaustive match");y.push(Ma(g,k,f,m))}}return p}function Ma(e,t,a,r){const n=(0,s.A)(a);n.push(e.name);const i=(0,s.A)(r);return i.push(1),{idx:t,def:e.definition,ruleStack:n,occurrenceStack:i}}var va;function xa(e){if(e instanceof N||"Option"===e)return va.OPTION;if(e instanceof F||"Repetition"===e)return va.REPETITION;if(e instanceof V||"RepetitionMandatory"===e)return va.REPETITION_MANDATORY;if(e instanceof j||"RepetitionMandatoryWithSeparator"===e)return va.REPETITION_MANDATORY_WITH_SEPARATOR;if(e instanceof B||"RepetitionWithSeparator"===e)return va.REPETITION_WITH_SEPARATOR;if(e instanceof _||"Alternation"===e)return va.ALTERNATION;throw Error("non exhaustive match")}function La(e){const{occurrence:t,rule:a,prodType:r,maxLookahead:n}=e,i=xa(r);return i===va.ALTERNATION?Pa(t,a,n):qa(t,a,i,n)}function wa(e,t,a,n){const i=e.length,s=ie(e,e=>ie(e,e=>1===e.length));if(t)return function(t){const r=(0,o.A)(t,e=>e.GATE);for(let n=0;n(0,ue.A)(e)),a=(0,Ce.A)(t,(e,t,a)=>((0,r.A)(t,t=>{(0,c.A)(e,t.tokenTypeIdx)||(e[t.tokenTypeIdx]=a),(0,r.A)(t.categoryMatches,t=>{(0,c.A)(e,t)||(e[t]=a)})}),e),{});return function(){const e=this.LA(1);return a[e.tokenTypeIdx]}}return function(){for(let t=0;t1===e.length),o=e.length;if(n&&!a){const t=(0,ue.A)(e);if(1===t.length&&(0,i.A)(t[0].categoryMatches)){const e=t[0].tokenTypeIdx;return function(){return this.LA(1).tokenTypeIdx===e}}{const e=(0,Ce.A)(t,(e,t,a)=>(e[t.tokenTypeIdx]=!0,(0,r.A)(t.categoryMatches,t=>{e[t]=!0}),e),[]);return function(){const t=this.LA(1);return!0===e[t.tokenTypeIdx]}}}return function(){e:for(let a=0;ama([e],1)),n=ba(a.length),c=(0,o.A)(a,e=>{const t={};return(0,r.A)(e,e=>{const a=Sa(e.partialPath);(0,r.A)(a,e=>{t[e]=!0})}),t});let s=a;for(let o=1;o<=t;o++){const e=s;s=ba(e.length);for(let a=0;a{const t=Sa(e.partialPath);(0,r.A)(t,e=>{c[a][e]=!0})})}}}}return n}function Pa(e,t,a,r){const n=new Ca(e,va.ALTERNATION,r);return t.accept(n),Ra(n.result,a)}function qa(e,t,a,r){const n=new Ca(e,a);t.accept(n);const i=n.result,o=new Ia(t,e,a).startWalking();return Ra([new D({definition:i}),new D({definition:o})],r)}function Ea(e,t){e:for(let a=0;aie(e,e=>ie(e,e=>(0,i.A)(e.categoryMatches))))}function za(e,t,a,i){const c=(0,aa.A)(e,e=>function(e,t){const a=new Da;e.accept(a);const r=a.allProductions,i=sa(r,Ha),c=C(i,e=>e.length>1),s=(0,o.A)((0,n.A)(c),a=>{const r=De(a),n=t.buildDuplicateFoundError(e,a),i=ce(r),o={message:n,type:qr.DUPLICATE_PRODUCTIONS,ruleName:e.name,dslName:i,occurrence:r.idx},c=Oa(r);return c&&(o.parameter=c),o});return s}(e,a)),s=function(e,t,a){const n=[],i=(0,o.A)(t,e=>e.name);return(0,r.A)(e,e=>{const t=e.name;if(ae(i,t)){const r=a.buildNamespaceConflictError(e);n.push({message:r,type:qr.CONFLICT_TOKENS_RULES_NAMESPACE,ruleName:t})}}),n}(e,t,a),h=(0,aa.A)(e,e=>function(e,t){const a=new ja;e.accept(a);const r=a.alternations,n=(0,aa.A)(r,a=>a.definition.length>255?[{message:t.buildTooManyAlternativesError({topLevelRule:e,alternation:a}),type:qr.TOO_MANY_ALTS,ruleName:e.name,occurrence:a.idx}]:[]);return n}(e,a)),d=(0,aa.A)(e,t=>function(e,t,a,r){const n=[],i=(0,Ce.A)(t,(t,a)=>a.name===e.name?t+1:t,0);if(i>1){const t=r.buildDuplicateRuleNameError({topLevelRule:e,grammarName:a});n.push({message:t,type:qr.DUPLICATE_RULE_NAME,ruleName:e.name})}return n}(t,e,i,a));return c.concat(s,h,d)}function Ha(e){return`${ce(e)}_#_${e.idx}_#_${Oa(e)}`}function Oa(e){return e instanceof U?e.terminalType.name:e instanceof H?e.nonTerminalName:""}class Da extends W{constructor(){super(...arguments),this.allProductions=[]}visitNonTerminal(e){this.allProductions.push(e)}visitOption(e){this.allProductions.push(e)}visitRepetitionWithSeparator(e){this.allProductions.push(e)}visitRepetitionMandatory(e){this.allProductions.push(e)}visitRepetitionMandatoryWithSeparator(e){this.allProductions.push(e)}visitRepetition(e){this.allProductions.push(e)}visitAlternation(e){this.allProductions.push(e)}visitTerminal(e){this.allProductions.push(e)}}function Na(e,t,a,r=[]){const n=[],o=Va(t.definition);if((0,i.A)(o))return[];{const t=e.name;ae(o,e)&&n.push({message:a.buildLeftRecursionError({topLevelRule:e,leftRecursionPath:r}),type:qr.LEFT_RECURSION,ruleName:t});const i=He(o,r.concat([e])),c=(0,aa.A)(i,t=>{const n=(0,s.A)(r);return n.push(t),Na(e,t,a,n)});return n.concat(c)}}function Va(e){let t=[];if((0,i.A)(e))return t;const a=De(e);if(a instanceof H)t.push(a.referencedRule);else if(a instanceof D||a instanceof N||a instanceof V||a instanceof j||a instanceof B||a instanceof F)t=t.concat(Va(a.definition));else if(a instanceof _)t=(0,ue.A)((0,o.A)(a.definition,e=>Va(e.definition)));else if(!(a instanceof U))throw Error("non exhaustive match");const r=oe(a),n=e.length>1;if(r&&n){const a=u(e);return t.concat(Va(a))}return t}class ja extends W{constructor(){super(...arguments),this.alternations=[]}visitAlternation(e){this.alternations.push(e)}}function Fa(e,t,a){const n=new ja;e.accept(n);let i=n.alternations;i=Le(i,e=>!0===e.ignoreAmbiguities);const c=(0,aa.A)(i,n=>{const i=n.idx,c=n.maxLookahead||t,s=Pa(i,e,c,n),h=function(e,t,a,n){const i=[],c=(0,Ce.A)(e,(a,n,o)=>(!0===t.definition[o].ignoreAmbiguities||(0,r.A)(n,n=>{const c=[o];(0,r.A)(e,(e,a)=>{o!==a&&Ea(e,n)&&!0!==t.definition[a].ignoreAmbiguities&&c.push(a)}),c.length>1&&!Ea(i,n)&&(i.push(n),a.push({alts:c,path:n}))}),a),[]),s=(0,o.A)(c,e=>{const r=(0,o.A)(e.alts,e=>e+1);return{message:n.buildAlternationAmbiguityError({topLevelRule:a,alternation:t,ambiguityIndices:r,prefixPath:e.path}),type:qr.AMBIGUOUS_ALTS,ruleName:a.name,occurrence:t.idx,alternatives:e.alts}});return s}(s,n,e,a),d=function(e,t,a,r){const n=(0,Ce.A)(e,(e,t,a)=>{const r=(0,o.A)(t,e=>({idx:a,path:e}));return e.concat(r)},[]),i=Oe((0,aa.A)(n,e=>{if(!0===t.definition[e.idx].ignoreAmbiguities)return[];const i=e.idx,c=e.path,s=(0,be.A)(n,e=>{return!0!==t.definition[e.idx].ignoreAmbiguities&&e.idx{const a=r[t];return e===a||a.categoryMatchesMap[e.tokenTypeIdx]}));var a,r});return(0,o.A)(s,e=>{const n=[e.idx+1,i+1],o=0===t.idx?"":t.idx;return{message:r.buildAlternationPrefixAmbiguityError({topLevelRule:a,alternation:t,ambiguityIndices:n,prefixPath:e.path}),type:qr.AMBIGUOUS_PREFIX_ALTS,ruleName:a.name,occurrence:o,alternatives:n}})}));return i}(s,n,e,a);return h.concat(d)});return c}class Ba extends W{constructor(){super(...arguments),this.allProductions=[]}visitRepetitionWithSeparator(e){this.allProductions.push(e)}visitRepetitionMandatory(e){this.allProductions.push(e)}visitRepetitionMandatoryWithSeparator(e){this.allProductions.push(e)}visitRepetition(e){this.allProductions.push(e)}}function _a(e){const t=(0,ge.A)(e,{errMsgProvider:Jt}),a={};return(0,r.A)(e.rules,e=>{a[e.name]=e}),function(e,t){const a=new ta(e,t);return a.resolveRefs(),a.errors}(a,t.errMsgProvider)}const Ua="MismatchedTokenException",Ga="NoViableAltException",Wa="EarlyExitException",Ka="NotAllInputParsedException",Za=[Ua,Ga,Wa,Ka];function Xa(e){return ae(Za,e.name)}Object.freeze(Za);class Ya extends Error{constructor(e,t){super(e),this.token=t,this.resyncedTokens=[],Object.setPrototypeOf(this,new.target.prototype),Error.captureStackTrace&&Error.captureStackTrace(this,this.constructor)}}class Qa extends Ya{constructor(e,t,a){super(e,t),this.previousToken=a,this.name=Ua}}class Ja extends Ya{constructor(e,t,a){super(e,t),this.previousToken=a,this.name=Ga}}class er extends Ya{constructor(e,t){super(e,t),this.name=Ka}}class tr extends Ya{constructor(e,t,a){super(e,t),this.previousToken=a,this.name=Wa}}const ar={},rr="InRuleRecoveryException";class nr extends Error{constructor(e){super(e),this.name=rr}}function ir(e,t,a,r,n,i,o){const c=this.getKeyForAutomaticLookahead(r,n);let s=this.firstAfterRepMap[c];if(void 0===s){const e=this.getCurrRuleFullName();s=new i(this.getGAstProductions()[e],n).startWalking(),this.firstAfterRepMap[c]=s}let h=s.token,d=s.occurrence;const l=s.isEndOfRule;1===this.RULE_STACK.length&&l&&void 0===h&&(h=Zt,d=1),void 0!==h&&void 0!==d&&this.shouldInRepetitionRecoveryBeTried(h,d,o)&&this.tryInRepetitionRecovery(e,t,a,h)}const or=1024,cr=1280,sr=1536;function hr(e,t,a){return a|t|e}class dr{constructor(e){var t;this.maxLookahead=null!==(t=null==e?void 0:e.maxLookahead)&&void 0!==t?t:Rr.maxLookahead}validate(e){const t=this.validateNoLeftRecursion(e.rules);if((0,i.A)(t)){const a=this.validateEmptyOrAlternatives(e.rules),r=this.validateAmbiguousAlternationAlternatives(e.rules,this.maxLookahead),n=this.validateSomeNonEmptyLookaheadPath(e.rules,this.maxLookahead);return[...t,...a,...r,...n]}return t}validateNoLeftRecursion(e){return(0,aa.A)(e,e=>Na(e,e,ea))}validateEmptyOrAlternatives(e){return(0,aa.A)(e,e=>function(e,t){const a=new ja;e.accept(a);const r=a.alternations;return(0,aa.A)(r,a=>{const r=ha(a.definition);return(0,aa.A)(r,(r,n)=>{const o=ga([r],[],At,1);return(0,i.A)(o)?[{message:t.buildEmptyAlternationError({topLevelRule:e,alternation:a,emptyChoiceIdx:n}),type:qr.NONE_LAST_EMPTY_ALT,ruleName:e.name,occurrence:a.idx,alternative:n+1}]:[]})})}(e,ea))}validateAmbiguousAlternationAlternatives(e,t){return(0,aa.A)(e,e=>Fa(e,t,ea))}validateSomeNonEmptyLookaheadPath(e,t){return function(e,t,a){const n=[];return(0,r.A)(e,e=>{const o=new Ba;e.accept(o);const c=o.allProductions;(0,r.A)(c,r=>{const o=xa(r),c=r.maxLookahead||t,s=qa(r.idx,e,o,c)[0];if((0,i.A)((0,ue.A)(s))){const t=a.buildEmptyRepetitionError({topLevelRule:e,repetition:r});n.push({message:t,type:qr.NO_NON_EMPTY_LOOKAHEAD,ruleName:e.name})}})}),n}(e,t,ea)}buildLookaheadForAlternation(e){return function(e,t,a,r,n,i){const o=Pa(e,t,a);return i(o,r,$a(o)?It:At,n)}(e.prodOccurrence,e.rule,e.maxLookahead,e.hasPredicates,e.dynamicTokensEnabled,wa)}buildLookaheadForOptional(e){return function(e,t,a,r,n,i){const o=qa(e,t,n,a),c=$a(o)?It:At;return i(o[0],c,r)}(e.prodOccurrence,e.rule,e.maxLookahead,e.dynamicTokensEnabled,xa(e.prodType),Aa)}}const lr=new class extends W{constructor(){super(...arguments),this.dslMethods={option:[],alternation:[],repetition:[],repetitionWithSeparator:[],repetitionMandatory:[],repetitionMandatoryWithSeparator:[]}}reset(){this.dslMethods={option:[],alternation:[],repetition:[],repetitionWithSeparator:[],repetitionMandatory:[],repetitionMandatoryWithSeparator:[]}}visitOption(e){this.dslMethods.option.push(e)}visitRepetitionWithSeparator(e){this.dslMethods.repetitionWithSeparator.push(e)}visitRepetitionMandatory(e){this.dslMethods.repetitionMandatory.push(e)}visitRepetitionMandatoryWithSeparator(e){this.dslMethods.repetitionMandatoryWithSeparator.push(e)}visitRepetition(e){this.dslMethods.repetition.push(e)}visitAlternation(e){this.dslMethods.alternation.push(e)}};function ur(e,t){!0===isNaN(e.startOffset)?(e.startOffset=t.startOffset,e.endOffset=t.endOffset):e.endOffset!1===(0,we.A)(e[t])),r=(0,o.A)(a,t=>({msg:`Missing visitor method: <${t}> on ${e.constructor.name} CST Visitor.`,type:mr.MISSING_METHOD,methodName:t}));return Oe(r)}(e,t);return a}(this,t);if(!(0,i.A)(e)){const t=(0,o.A)(e,e=>e.msg);throw Error(`Errors Detected in CST Visitor <${this.constructor.name}>:\n\t${t.join("\n\n").replace(/\n/g,"\n\t")}`)}}};return(a.prototype=r).constructor=a,a._RULE_NAMES=t,a}var mr;!function(e){e[e.REDUNDANT_METHOD=0]="REDUNDANT_METHOD",e[e.MISSING_METHOD=1]="MISSING_METHOD"}(mr||(mr={}));var gr=a(3149);const Mr={description:"This Object indicates the Parser is during Recording Phase"};Object.freeze(Mr);const vr=!0,xr=Math.pow(2,8)-1,Lr=Kt({name:"RECORDING_PHASE_TOKEN",pattern:Ht.NA});St([Lr]);const wr=Xt(Lr,"This IToken indicates the Parser is in Recording Phase\n\tSee: https://chevrotain.io/docs/guide/internals.html#grammar-recording for details",-1,-1,-1,-1,-1,-1);Object.freeze(wr);const Ar={name:"This CSTNode indicates the Parser is in Recording Phase\n\tSee: https://chevrotain.io/docs/guide/internals.html#grammar-recording for details",children:{}};function Ir(e,t,a,r=!1){Sr(a);const n=(0,Lt.A)(this.recordingProdStack),i=(0,we.A)(t)?t:t.DEF,o=new e({definition:[],idx:a});return r&&(o.separator=t.SEP),(0,c.A)(t,"MAX_LOOKAHEAD")&&(o.maxLookahead=t.MAX_LOOKAHEAD),this.recordingProdStack.push(o),i.call(this),n.definition.push(o),this.recordingProdStack.pop(),Mr}function Cr(e,t){Sr(t);const a=(0,Lt.A)(this.recordingProdStack),n=!1===(0,Y.A)(e),i=!1===n?e:e.DEF,o=new _({definition:[],idx:t,ignoreAmbiguities:n&&!0===e.IGNORE_AMBIGUITIES});(0,c.A)(e,"MAX_LOOKAHEAD")&&(o.maxLookahead=e.MAX_LOOKAHEAD);const s=J(i,e=>(0,we.A)(e.GATE));return o.hasPredicates=s,a.definition.push(o),(0,r.A)(i,e=>{const t=new D({definition:[]});o.definition.push(t),(0,c.A)(e,"IGNORE_AMBIGUITIES")?t.ignoreAmbiguities=e.IGNORE_AMBIGUITIES:(0,c.A)(e,"GATE")&&(t.ignoreAmbiguities=!0),this.recordingProdStack.push(t),e.ALT.call(this),this.recordingProdStack.pop()}),Mr}function br(e){return 0===e?"":`${e}`}function Sr(e){if(e<0||e>xr){const t=new Error(`Invalid DSL Method idx value: <${e}>\n\tIdx value must be a none negative value smaller than ${xr+1}`);throw t.KNOWN_RECORDER_ERROR=!0,t}}const Tr=Xt(Zt,"",NaN,NaN,NaN,NaN,NaN,NaN);Object.freeze(Tr);const Rr=Object.freeze({recoveryEnabled:!1,maxLookahead:3,dynamicTokensEnabled:!1,outputCst:!0,errorMessageProvider:Qt,nodeLocationTracking:"none",traceInitPerf:!1,skipValidations:!1}),Pr=Object.freeze({recoveryValueFunc:()=>{},resyncEnabled:!0});var qr,Er;function $r(e=void 0){return function(){return e}}!function(e){e[e.INVALID_RULE_NAME=0]="INVALID_RULE_NAME",e[e.DUPLICATE_RULE_NAME=1]="DUPLICATE_RULE_NAME",e[e.INVALID_RULE_OVERRIDE=2]="INVALID_RULE_OVERRIDE",e[e.DUPLICATE_PRODUCTIONS=3]="DUPLICATE_PRODUCTIONS",e[e.UNRESOLVED_SUBRULE_REF=4]="UNRESOLVED_SUBRULE_REF",e[e.LEFT_RECURSION=5]="LEFT_RECURSION",e[e.NONE_LAST_EMPTY_ALT=6]="NONE_LAST_EMPTY_ALT",e[e.AMBIGUOUS_ALTS=7]="AMBIGUOUS_ALTS",e[e.CONFLICT_TOKENS_RULES_NAMESPACE=8]="CONFLICT_TOKENS_RULES_NAMESPACE",e[e.INVALID_TOKEN_NAME=9]="INVALID_TOKEN_NAME",e[e.NO_NON_EMPTY_LOOKAHEAD=10]="NO_NON_EMPTY_LOOKAHEAD",e[e.AMBIGUOUS_PREFIX_ALTS=11]="AMBIGUOUS_PREFIX_ALTS",e[e.TOO_MANY_ALTS=12]="TOO_MANY_ALTS",e[e.CUSTOM_LOOKAHEAD_VALIDATION=13]="CUSTOM_LOOKAHEAD_VALIDATION"}(qr||(qr={}));class zr{static performSelfAnalysis(e){throw Error("The **static** `performSelfAnalysis` method has been deprecated.\t\nUse the **instance** method with the same name instead.")}performSelfAnalysis(){this.TRACE_INIT("performSelfAnalysis",()=>{let e;this.selfAnalysisDone=!0;const t=this.className;this.TRACE_INIT("toFastProps",()=>{h(this)}),this.TRACE_INIT("Grammar Recording",()=>{try{this.enableRecording(),(0,r.A)(this.definedRulesNames,e=>{const t=this[e].originalGrammarAction;let a;this.TRACE_INIT(`${e} Rule`,()=>{a=this.topLevelRuleRecord(e,t)}),this.gastProductionsCache[e]=a})}finally{this.disableRecording()}});let a=[];if(this.TRACE_INIT("Grammar Resolving",()=>{a=_a({rules:(0,n.A)(this.gastProductionsCache)}),this.definitionErrors=this.definitionErrors.concat(a)}),this.TRACE_INIT("Grammar Validations",()=>{if((0,i.A)(a)&&!1===this.skipValidations){const a=(e={rules:(0,n.A)(this.gastProductionsCache),tokenTypes:(0,n.A)(this.tokensMap),errMsgProvider:ea,grammarName:t},za((e=(0,ge.A)(e,{errMsgProvider:ea})).rules,e.tokenTypes,e.errMsgProvider,e.grammarName)),r=function(e){const t=e.lookaheadStrategy.validate({rules:e.rules,tokenTypes:e.tokenTypes,grammarName:e.grammarName});return(0,o.A)(t,e=>Object.assign({type:qr.CUSTOM_LOOKAHEAD_VALIDATION},e))}({lookaheadStrategy:this.lookaheadStrategy,rules:(0,n.A)(this.gastProductionsCache),tokenTypes:(0,n.A)(this.tokensMap),grammarName:t});this.definitionErrors=this.definitionErrors.concat(a,r)}var e}),(0,i.A)(this.definitionErrors)&&(this.recoveryEnabled&&this.TRACE_INIT("computeAllProdsFollows",()=>{const e=function(e){const t={};return(0,r.A)(e,e=>{const a=new ke(e).startWalking();x(t,a)}),t}((0,n.A)(this.gastProductionsCache));this.resyncFollows=e}),this.TRACE_INIT("ComputeLookaheadFunctions",()=>{var e,t;null===(t=(e=this.lookaheadStrategy).initialize)||void 0===t||t.call(e,{rules:(0,n.A)(this.gastProductionsCache)}),this.preComputeLookaheadFunctions((0,n.A)(this.gastProductionsCache))})),!zr.DEFER_DEFINITION_ERRORS_HANDLING&&!(0,i.A)(this.definitionErrors))throw e=(0,o.A)(this.definitionErrors,e=>e.message),new Error(`Parser Definition Errors detected:\n ${e.join("\n-------------------------------\n")}`)})}constructor(e,t){this.definitionErrors=[],this.selfAnalysisDone=!1;const a=this;if(a.initErrorHandler(t),a.initLexerAdapter(),a.initLooksAhead(t),a.initRecognizerEngine(e,t),a.initRecoverable(t),a.initTreeBuilder(t),a.initContentAssist(),a.initGastRecorder(t),a.initPerformanceTracer(t),(0,c.A)(t,"ignoredIssues"))throw new Error("The IParserConfig property has been deprecated.\n\tPlease use the flag on the relevant DSL method instead.\n\tSee: https://chevrotain.io/docs/guide/resolving_grammar_errors.html#IGNORING_AMBIGUITIES\n\tFor further details.");this.skipValidations=(0,c.A)(t,"skipValidations")?t.skipValidations:Rr.skipValidations}}zr.DEFER_DEFINITION_ERRORS_HANDLING=!1,Er=zr,[class{initRecoverable(e){this.firstAfterRepMap={},this.resyncFollows={},this.recoveryEnabled=(0,c.A)(e,"recoveryEnabled")?e.recoveryEnabled:Rr.recoveryEnabled,this.recoveryEnabled&&(this.attemptInRepetitionRecovery=ir)}getTokenToInsert(e){const t=Xt(e,"",NaN,NaN,NaN,NaN,NaN,NaN);return t.isInsertedInRecovery=!0,t}canTokenTypeBeInsertedInRecovery(e){return!0}canTokenTypeBeDeletedInRecovery(e){return!0}tryInRepetitionRecovery(e,t,a,r){const n=this.findReSyncTokenType(),i=this.exportLexerState(),o=[];let c=!1;const s=this.LA(1);let h=this.LA(1);const d=()=>{const e=this.LA(0),t=this.errorMessageProvider.buildMismatchTokenMessage({expected:r,actual:s,previous:e,ruleName:this.getCurrRuleFullName()}),a=new Qa(t,s,this.LA(0));a.resyncedTokens=ha(o),this.SAVE_ERROR(a)};for(;!c;){if(this.tokenMatcher(h,r))return void d();if(a.call(this))return d(),void e.apply(this,t);this.tokenMatcher(h,n)?c=!0:(h=this.SKIP_TOKEN(),this.addToResyncTokens(h,o))}this.importLexerState(i)}shouldInRepetitionRecoveryBeTried(e,t,a){return!1!==a&&!this.tokenMatcher(this.LA(1),e)&&!this.isBackTracking()&&!this.canPerformInRuleRecovery(e,this.getFollowsForInRuleRecovery(e,t))}getFollowsForInRuleRecovery(e,t){const a=this.getCurrentGrammarPath(e,t);return this.getNextPossibleTokenTypes(a)}tryInRuleRecovery(e,t){if(this.canRecoverWithSingleTokenInsertion(e,t))return this.getTokenToInsert(e);if(this.canRecoverWithSingleTokenDeletion(e)){const e=this.SKIP_TOKEN();return this.consumeToken(),e}throw new nr("sad sad panda")}canPerformInRuleRecovery(e,t){return this.canRecoverWithSingleTokenInsertion(e,t)||this.canRecoverWithSingleTokenDeletion(e)}canRecoverWithSingleTokenInsertion(e,t){if(!this.canTokenTypeBeInsertedInRecovery(e))return!1;if((0,i.A)(t))return!1;const a=this.LA(1);return void 0!==(0,Ne.A)(t,e=>this.tokenMatcher(a,e))}canRecoverWithSingleTokenDeletion(e){return!!this.canTokenTypeBeDeletedInRecovery(e)&&this.tokenMatcher(this.LA(2),e)}isInCurrentRuleReSyncSet(e){const t=this.getCurrFollowKey(),a=this.getFollowSetFromFollowKey(t);return ae(a,e)}findReSyncTokenType(){const e=this.flattenFollowSet();let t=this.LA(1),a=2;for(;;){const r=(0,Ne.A)(e,e=>Yt(t,e));if(void 0!==r)return r;t=this.LA(a),a++}}getCurrFollowKey(){if(1===this.RULE_STACK.length)return ar;const e=this.getLastExplicitRuleShortName(),t=this.getLastExplicitRuleOccurrenceIndex(),a=this.getPreviousExplicitRuleShortName();return{ruleName:this.shortRuleNameToFullName(e),idxInCallingRule:t,inRule:this.shortRuleNameToFullName(a)}}buildFullFollowKeyStack(){const e=this.RULE_STACK,t=this.RULE_OCCURRENCE_STACK;return(0,o.A)(e,(a,r)=>0===r?ar:{ruleName:this.shortRuleNameToFullName(a),idxInCallingRule:t[r],inRule:this.shortRuleNameToFullName(e[r-1])})}flattenFollowSet(){const e=(0,o.A)(this.buildFullFollowKeyStack(),e=>this.getFollowSetFromFollowKey(e));return(0,ue.A)(e)}getFollowSetFromFollowKey(e){if(e===ar)return[Zt];const t=e.ruleName+e.idxInCallingRule+ye+e.inRule;return this.resyncFollows[t]}addToResyncTokens(e,t){return this.tokenMatcher(e,Zt)||t.push(e),t}reSyncTo(e){const t=[];let a=this.LA(1);for(;!1===this.tokenMatcher(a,e);)a=this.SKIP_TOKEN(),this.addToResyncTokens(a,t);return ha(t)}attemptInRepetitionRecovery(e,t,a,r,n,i,o){}getCurrentGrammarPath(e,t){return{ruleStack:this.getHumanReadableRuleStack(),occurrenceStack:(0,s.A)(this.RULE_OCCURRENCE_STACK),lastTok:e,lastTokOccurrence:t}}getHumanReadableRuleStack(){return(0,o.A)(this.RULE_STACK,e=>this.shortRuleNameToFullName(e))}},class{initLooksAhead(e){this.dynamicTokensEnabled=(0,c.A)(e,"dynamicTokensEnabled")?e.dynamicTokensEnabled:Rr.dynamicTokensEnabled,this.maxLookahead=(0,c.A)(e,"maxLookahead")?e.maxLookahead:Rr.maxLookahead,this.lookaheadStrategy=(0,c.A)(e,"lookaheadStrategy")?e.lookaheadStrategy:new dr({maxLookahead:this.maxLookahead}),this.lookAheadFuncsCache=new Map}preComputeLookaheadFunctions(e){(0,r.A)(e,e=>{this.TRACE_INIT(`${e.name} Rule Lookahead`,()=>{const{alternation:t,repetition:a,option:n,repetitionMandatory:i,repetitionMandatoryWithSeparator:o,repetitionWithSeparator:c}=function(e){lr.reset(),e.accept(lr);const t=lr.dslMethods;return lr.reset(),t}(e);(0,r.A)(t,t=>{const a=0===t.idx?"":t.idx;this.TRACE_INIT(`${ce(t)}${a}`,()=>{const a=this.lookaheadStrategy.buildLookaheadForAlternation({prodOccurrence:t.idx,rule:e,maxLookahead:t.maxLookahead||this.maxLookahead,hasPredicates:t.hasPredicates,dynamicTokensEnabled:this.dynamicTokensEnabled}),r=hr(this.fullRuleNameToShort[e.name],256,t.idx);this.setLaFuncCache(r,a)})}),(0,r.A)(a,t=>{this.computeLookaheadFunc(e,t.idx,768,"Repetition",t.maxLookahead,ce(t))}),(0,r.A)(n,t=>{this.computeLookaheadFunc(e,t.idx,512,"Option",t.maxLookahead,ce(t))}),(0,r.A)(i,t=>{this.computeLookaheadFunc(e,t.idx,or,"RepetitionMandatory",t.maxLookahead,ce(t))}),(0,r.A)(o,t=>{this.computeLookaheadFunc(e,t.idx,sr,"RepetitionMandatoryWithSeparator",t.maxLookahead,ce(t))}),(0,r.A)(c,t=>{this.computeLookaheadFunc(e,t.idx,cr,"RepetitionWithSeparator",t.maxLookahead,ce(t))})})})}computeLookaheadFunc(e,t,a,r,n,i){this.TRACE_INIT(`${i}${0===t?"":t}`,()=>{const i=this.lookaheadStrategy.buildLookaheadForOptional({prodOccurrence:t,rule:e,maxLookahead:n||this.maxLookahead,dynamicTokensEnabled:this.dynamicTokensEnabled,prodType:r}),o=hr(this.fullRuleNameToShort[e.name],a,t);this.setLaFuncCache(o,i)})}getKeyForAutomaticLookahead(e,t){return hr(this.getLastExplicitRuleShortName(),e,t)}getLaFuncFromCache(e){return this.lookAheadFuncsCache.get(e)}setLaFuncCache(e,t){this.lookAheadFuncsCache.set(e,t)}},class{initTreeBuilder(e){if(this.CST_STACK=[],this.outputCst=e.outputCst,this.nodeLocationTracking=(0,c.A)(e,"nodeLocationTracking")?e.nodeLocationTracking:Rr.nodeLocationTracking,this.outputCst)if(/full/i.test(this.nodeLocationTracking))this.recoveryEnabled?(this.setNodeLocationFromToken=pr,this.setNodeLocationFromNode=pr,this.cstPostRule=xt.A,this.setInitialNodeLocation=this.setInitialNodeLocationFullRecovery):(this.setNodeLocationFromToken=xt.A,this.setNodeLocationFromNode=xt.A,this.cstPostRule=this.cstPostRuleFull,this.setInitialNodeLocation=this.setInitialNodeLocationFullRegular);else if(/onlyOffset/i.test(this.nodeLocationTracking))this.recoveryEnabled?(this.setNodeLocationFromToken=ur,this.setNodeLocationFromNode=ur,this.cstPostRule=xt.A,this.setInitialNodeLocation=this.setInitialNodeLocationOnlyOffsetRecovery):(this.setNodeLocationFromToken=xt.A,this.setNodeLocationFromNode=xt.A,this.cstPostRule=this.cstPostRuleOnlyOffset,this.setInitialNodeLocation=this.setInitialNodeLocationOnlyOffsetRegular);else{if(!/none/i.test(this.nodeLocationTracking))throw Error(`Invalid config option: "${e.nodeLocationTracking}"`);this.setNodeLocationFromToken=xt.A,this.setNodeLocationFromNode=xt.A,this.cstPostRule=xt.A,this.setInitialNodeLocation=xt.A}else this.cstInvocationStateUpdate=xt.A,this.cstFinallyStateUpdate=xt.A,this.cstPostTerminal=xt.A,this.cstPostNonTerminal=xt.A,this.cstPostRule=xt.A}setInitialNodeLocationOnlyOffsetRecovery(e){e.location={startOffset:NaN,endOffset:NaN}}setInitialNodeLocationOnlyOffsetRegular(e){e.location={startOffset:this.LA(1).startOffset,endOffset:NaN}}setInitialNodeLocationFullRecovery(e){e.location={startOffset:NaN,startLine:NaN,startColumn:NaN,endOffset:NaN,endLine:NaN,endColumn:NaN}}setInitialNodeLocationFullRegular(e){const t=this.LA(1);e.location={startOffset:t.startOffset,startLine:t.startLine,startColumn:t.startColumn,endOffset:NaN,endLine:NaN,endColumn:NaN}}cstInvocationStateUpdate(e){const t={name:e,children:Object.create(null)};this.setInitialNodeLocation(t),this.CST_STACK.push(t)}cstFinallyStateUpdate(){this.CST_STACK.pop()}cstPostRuleFull(e){const t=this.LA(0),a=e.location;a.startOffset<=t.startOffset==1?(a.endOffset=t.endOffset,a.endLine=t.endLine,a.endColumn=t.endColumn):(a.startOffset=NaN,a.startLine=NaN,a.startColumn=NaN)}cstPostRuleOnlyOffset(e){const t=this.LA(0),a=e.location;a.startOffset<=t.startOffset==1?a.endOffset=t.endOffset:a.startOffset=NaN}cstPostTerminal(e,t){const a=this.CST_STACK[this.CST_STACK.length-1];var r,n,i;n=t,i=e,void 0===(r=a).children[i]?r.children[i]=[n]:r.children[i].push(n),this.setNodeLocationFromToken(a.location,t)}cstPostNonTerminal(e,t){const a=this.CST_STACK[this.CST_STACK.length-1];!function(e,t,a){void 0===e.children[t]?e.children[t]=[a]:e.children[t].push(a)}(a,t,e),this.setNodeLocationFromNode(a.location,e.location)}getBaseCstVisitorConstructor(){if((0,fe.A)(this.baseCstVisitorConstructor)){const e=fr(this.className,(0,M.A)(this.gastProductionsCache));return this.baseCstVisitorConstructor=e,e}return this.baseCstVisitorConstructor}getBaseCstVisitorConstructorWithDefaults(){if((0,fe.A)(this.baseCstVisitorWithDefaultsConstructor)){const e=function(e,t,a){const n=function(){};yr(n,e+"BaseSemanticsWithDefaults");const i=Object.create(a.prototype);return(0,r.A)(t,e=>{i[e]=kr}),(n.prototype=i).constructor=n,n}(this.className,(0,M.A)(this.gastProductionsCache),this.getBaseCstVisitorConstructor());return this.baseCstVisitorWithDefaultsConstructor=e,e}return this.baseCstVisitorWithDefaultsConstructor}getLastExplicitRuleShortName(){const e=this.RULE_STACK;return e[e.length-1]}getPreviousExplicitRuleShortName(){const e=this.RULE_STACK;return e[e.length-2]}getLastExplicitRuleOccurrenceIndex(){const e=this.RULE_OCCURRENCE_STACK;return e[e.length-1]}},class{initLexerAdapter(){this.tokVector=[],this.tokVectorLength=0,this.currIdx=-1}set input(e){if(!0!==this.selfAnalysisDone)throw Error("Missing invocation at the end of the Parser's constructor.");this.reset(),this.tokVector=e,this.tokVectorLength=e.length}get input(){return this.tokVector}SKIP_TOKEN(){return this.currIdx<=this.tokVector.length-2?(this.consumeToken(),this.LA(1)):Tr}LA(e){const t=this.currIdx+e;return t<0||this.tokVectorLength<=t?Tr:this.tokVector[t]}consumeToken(){this.currIdx++}exportLexerState(){return this.currIdx}importLexerState(e){this.currIdx=e}resetLexerState(){this.currIdx=-1}moveToTerminatedState(){this.currIdx=this.tokVector.length-1}getLexerPosition(){return this.exportLexerState()}},class{initRecognizerEngine(e,t){if(this.className=this.constructor.name,this.shortRuleNameToFull={},this.fullRuleNameToShort={},this.ruleShortNameIdx=256,this.tokenMatcher=It,this.subruleIdx=0,this.definedRulesNames=[],this.tokensMap={},this.isBackTrackingStack=[],this.RULE_STACK=[],this.RULE_OCCURRENCE_STACK=[],this.gastProductionsCache={},(0,c.A)(t,"serializedGrammar"))throw Error("The Parser's configuration can no longer contain a property.\n\tSee: https://chevrotain.io/docs/changes/BREAKING_CHANGES.html#_6-0-0\n\tFor Further details.");if((0,Y.A)(e)){if((0,i.A)(e))throw Error("A Token Vocabulary cannot be empty.\n\tNote that the first argument for the parser constructor\n\tis no longer a Token vector (since v4.0).");if("number"==typeof e[0].startOffset)throw Error("The Parser constructor no longer accepts a token vector as the first argument.\n\tSee: https://chevrotain.io/docs/changes/BREAKING_CHANGES.html#_4-0-0\n\tFor Further details.")}if((0,Y.A)(e))this.tokensMap=(0,Ce.A)(e,(e,t)=>(e[t.name]=t,e),{});else if((0,c.A)(e,"modes")&&ie((0,ue.A)((0,n.A)(e.modes)),qt)){const t=(0,ue.A)((0,n.A)(e.modes)),a=le(t);this.tokensMap=(0,Ce.A)(a,(e,t)=>(e[t.name]=t,e),{})}else{if(!(0,gr.A)(e))throw new Error(" argument must be An Array of Token constructors, A dictionary of Token constructors or an IMultiModeLexerDefinition");this.tokensMap=(0,s.A)(e)}this.tokensMap.EOF=Zt;const a=(0,c.A)(e,"modes")?(0,ue.A)((0,n.A)(e.modes)):(0,n.A)(e),r=ie(a,e=>(0,i.A)(e.categoryMatches));this.tokenMatcher=r?It:At,St((0,n.A)(this.tokensMap))}defineRule(e,t,a){if(this.selfAnalysisDone)throw Error(`Grammar rule <${e}> may not be defined after the 'performSelfAnalysis' method has been called'\nMake sure that all grammar rule definitions are done before 'performSelfAnalysis' is called.`);const r=(0,c.A)(a,"resyncEnabled")?a.resyncEnabled:Pr.resyncEnabled,n=(0,c.A)(a,"recoveryValueFunc")?a.recoveryValueFunc:Pr.recoveryValueFunc,i=this.ruleShortNameIdx<<12;let o;return this.ruleShortNameIdx++,this.shortRuleNameToFull[i]=e,this.fullRuleNameToShort[e]=i,o=!0===this.outputCst?function(...a){try{this.ruleInvocationStateUpdate(i,e,this.subruleIdx),t.apply(this,a);const r=this.CST_STACK[this.CST_STACK.length-1];return this.cstPostRule(r),r}catch(o){return this.invokeRuleCatch(o,r,n)}finally{this.ruleFinallyStateUpdate()}}:function(...a){try{return this.ruleInvocationStateUpdate(i,e,this.subruleIdx),t.apply(this,a)}catch(o){return this.invokeRuleCatch(o,r,n)}finally{this.ruleFinallyStateUpdate()}},Object.assign(o,{ruleName:e,originalGrammarAction:t})}invokeRuleCatch(e,t,a){const r=1===this.RULE_STACK.length,n=t&&!this.isBackTracking()&&this.recoveryEnabled;if(Xa(e)){const t=e;if(n){const r=this.findReSyncTokenType();if(this.isInCurrentRuleReSyncSet(r)){if(t.resyncedTokens=this.reSyncTo(r),this.outputCst){const e=this.CST_STACK[this.CST_STACK.length-1];return e.recoveredNode=!0,e}return a(e)}if(this.outputCst){const e=this.CST_STACK[this.CST_STACK.length-1];e.recoveredNode=!0,t.partialCstResult=e}throw t}if(r)return this.moveToTerminatedState(),a(e);throw t}throw e}optionInternal(e,t){const a=this.getKeyForAutomaticLookahead(512,t);return this.optionInternalLogic(e,t,a)}optionInternalLogic(e,t,a){let r,n=this.getLaFuncFromCache(a);if("function"!=typeof e){r=e.DEF;const t=e.GATE;if(void 0!==t){const e=n;n=()=>t.call(this)&&e.call(this)}}else r=e;if(!0===n.call(this))return r.call(this)}atLeastOneInternal(e,t){const a=this.getKeyForAutomaticLookahead(or,e);return this.atLeastOneInternalLogic(e,t,a)}atLeastOneInternalLogic(e,t,a){let r,n=this.getLaFuncFromCache(a);if("function"!=typeof t){r=t.DEF;const e=t.GATE;if(void 0!==e){const t=n;n=()=>e.call(this)&&t.call(this)}}else r=t;if(!0!==n.call(this))throw this.raiseEarlyExitException(e,va.REPETITION_MANDATORY,t.ERR_MSG);{let e=this.doSingleRepetition(r);for(;!0===n.call(this)&&!0===e;)e=this.doSingleRepetition(r)}this.attemptInRepetitionRecovery(this.atLeastOneInternal,[e,t],n,or,e,ka)}atLeastOneSepFirstInternal(e,t){const a=this.getKeyForAutomaticLookahead(sr,e);this.atLeastOneSepFirstInternalLogic(e,t,a)}atLeastOneSepFirstInternalLogic(e,t,a){const r=t.DEF,n=t.SEP;if(!0!==this.getLaFuncFromCache(a).call(this))throw this.raiseEarlyExitException(e,va.REPETITION_MANDATORY_WITH_SEPARATOR,t.ERR_MSG);{r.call(this);const t=()=>this.tokenMatcher(this.LA(1),n);for(;!0===this.tokenMatcher(this.LA(1),n);)this.CONSUME(n),r.call(this);this.attemptInRepetitionRecovery(this.repetitionSepSecondInternal,[e,n,t,r,fa],t,sr,e,fa)}}manyInternal(e,t){const a=this.getKeyForAutomaticLookahead(768,e);return this.manyInternalLogic(e,t,a)}manyInternalLogic(e,t,a){let r,n=this.getLaFuncFromCache(a);if("function"!=typeof t){r=t.DEF;const e=t.GATE;if(void 0!==e){const t=n;n=()=>e.call(this)&&t.call(this)}}else r=t;let i=!0;for(;!0===n.call(this)&&!0===i;)i=this.doSingleRepetition(r);this.attemptInRepetitionRecovery(this.manyInternal,[e,t],n,768,e,pa,i)}manySepFirstInternal(e,t){const a=this.getKeyForAutomaticLookahead(cr,e);this.manySepFirstInternalLogic(e,t,a)}manySepFirstInternalLogic(e,t,a){const r=t.DEF,n=t.SEP;if(!0===this.getLaFuncFromCache(a).call(this)){r.call(this);const t=()=>this.tokenMatcher(this.LA(1),n);for(;!0===this.tokenMatcher(this.LA(1),n);)this.CONSUME(n),r.call(this);this.attemptInRepetitionRecovery(this.repetitionSepSecondInternal,[e,n,t,r,ya],t,cr,e,ya)}}repetitionSepSecondInternal(e,t,a,r,n){for(;a();)this.CONSUME(t),r.call(this);this.attemptInRepetitionRecovery(this.repetitionSepSecondInternal,[e,t,a,r,n],a,sr,e,n)}doSingleRepetition(e){const t=this.getLexerPosition();return e.call(this),this.getLexerPosition()>t}orInternal(e,t){const a=this.getKeyForAutomaticLookahead(256,t),r=(0,Y.A)(e)?e:e.DEF,n=this.getLaFuncFromCache(a).call(this,r);if(void 0!==n)return r[n].ALT.call(this);this.raiseNoAltException(t,e.ERR_MSG)}ruleFinallyStateUpdate(){if(this.RULE_STACK.pop(),this.RULE_OCCURRENCE_STACK.pop(),this.cstFinallyStateUpdate(),0===this.RULE_STACK.length&&!1===this.isAtEndOfInput()){const e=this.LA(1),t=this.errorMessageProvider.buildNotAllInputParsedMessage({firstRedundant:e,ruleName:this.getCurrRuleFullName()});this.SAVE_ERROR(new er(t,e))}}subruleInternal(e,t,a){let r;try{const n=void 0!==a?a.ARGS:void 0;return this.subruleIdx=t,r=e.apply(this,n),this.cstPostNonTerminal(r,void 0!==a&&void 0!==a.LABEL?a.LABEL:e.ruleName),r}catch(n){throw this.subruleInternalError(n,a,e.ruleName)}}subruleInternalError(e,t,a){throw Xa(e)&&void 0!==e.partialCstResult&&(this.cstPostNonTerminal(e.partialCstResult,void 0!==t&&void 0!==t.LABEL?t.LABEL:a),delete e.partialCstResult),e}consumeInternal(e,t,a){let r;try{const t=this.LA(1);!0===this.tokenMatcher(t,e)?(this.consumeToken(),r=t):this.consumeInternalError(e,t,a)}catch(n){r=this.consumeInternalRecovery(e,t,n)}return this.cstPostTerminal(void 0!==a&&void 0!==a.LABEL?a.LABEL:e.name,r),r}consumeInternalError(e,t,a){let r;const n=this.LA(0);throw r=void 0!==a&&a.ERR_MSG?a.ERR_MSG:this.errorMessageProvider.buildMismatchTokenMessage({expected:e,actual:t,previous:n,ruleName:this.getCurrRuleFullName()}),this.SAVE_ERROR(new Qa(r,t,n))}consumeInternalRecovery(e,t,a){if(!this.recoveryEnabled||"MismatchedTokenException"!==a.name||this.isBackTracking())throw a;{const n=this.getFollowsForInRuleRecovery(e,t);try{return this.tryInRuleRecovery(e,n)}catch(r){throw r.name===rr?a:r}}}saveRecogState(){const e=this.errors,t=(0,s.A)(this.RULE_STACK);return{errors:e,lexerState:this.exportLexerState(),RULE_STACK:t,CST_STACK:this.CST_STACK}}reloadRecogState(e){this.errors=e.errors,this.importLexerState(e.lexerState),this.RULE_STACK=e.RULE_STACK}ruleInvocationStateUpdate(e,t,a){this.RULE_OCCURRENCE_STACK.push(a),this.RULE_STACK.push(e),this.cstInvocationStateUpdate(t)}isBackTracking(){return 0!==this.isBackTrackingStack.length}getCurrRuleFullName(){const e=this.getLastExplicitRuleShortName();return this.shortRuleNameToFull[e]}shortRuleNameToFullName(e){return this.shortRuleNameToFull[e]}isAtEndOfInput(){return this.tokenMatcher(this.LA(1),Zt)}reset(){this.resetLexerState(),this.subruleIdx=0,this.isBackTrackingStack=[],this.errors=[],this.RULE_STACK=[],this.CST_STACK=[],this.RULE_OCCURRENCE_STACK=[]}},class{ACTION(e){return e.call(this)}consume(e,t,a){return this.consumeInternal(t,e,a)}subrule(e,t,a){return this.subruleInternal(t,e,a)}option(e,t){return this.optionInternal(t,e)}or(e,t){return this.orInternal(t,e)}many(e,t){return this.manyInternal(e,t)}atLeastOne(e,t){return this.atLeastOneInternal(e,t)}CONSUME(e,t){return this.consumeInternal(e,0,t)}CONSUME1(e,t){return this.consumeInternal(e,1,t)}CONSUME2(e,t){return this.consumeInternal(e,2,t)}CONSUME3(e,t){return this.consumeInternal(e,3,t)}CONSUME4(e,t){return this.consumeInternal(e,4,t)}CONSUME5(e,t){return this.consumeInternal(e,5,t)}CONSUME6(e,t){return this.consumeInternal(e,6,t)}CONSUME7(e,t){return this.consumeInternal(e,7,t)}CONSUME8(e,t){return this.consumeInternal(e,8,t)}CONSUME9(e,t){return this.consumeInternal(e,9,t)}SUBRULE(e,t){return this.subruleInternal(e,0,t)}SUBRULE1(e,t){return this.subruleInternal(e,1,t)}SUBRULE2(e,t){return this.subruleInternal(e,2,t)}SUBRULE3(e,t){return this.subruleInternal(e,3,t)}SUBRULE4(e,t){return this.subruleInternal(e,4,t)}SUBRULE5(e,t){return this.subruleInternal(e,5,t)}SUBRULE6(e,t){return this.subruleInternal(e,6,t)}SUBRULE7(e,t){return this.subruleInternal(e,7,t)}SUBRULE8(e,t){return this.subruleInternal(e,8,t)}SUBRULE9(e,t){return this.subruleInternal(e,9,t)}OPTION(e){return this.optionInternal(e,0)}OPTION1(e){return this.optionInternal(e,1)}OPTION2(e){return this.optionInternal(e,2)}OPTION3(e){return this.optionInternal(e,3)}OPTION4(e){return this.optionInternal(e,4)}OPTION5(e){return this.optionInternal(e,5)}OPTION6(e){return this.optionInternal(e,6)}OPTION7(e){return this.optionInternal(e,7)}OPTION8(e){return this.optionInternal(e,8)}OPTION9(e){return this.optionInternal(e,9)}OR(e){return this.orInternal(e,0)}OR1(e){return this.orInternal(e,1)}OR2(e){return this.orInternal(e,2)}OR3(e){return this.orInternal(e,3)}OR4(e){return this.orInternal(e,4)}OR5(e){return this.orInternal(e,5)}OR6(e){return this.orInternal(e,6)}OR7(e){return this.orInternal(e,7)}OR8(e){return this.orInternal(e,8)}OR9(e){return this.orInternal(e,9)}MANY(e){this.manyInternal(0,e)}MANY1(e){this.manyInternal(1,e)}MANY2(e){this.manyInternal(2,e)}MANY3(e){this.manyInternal(3,e)}MANY4(e){this.manyInternal(4,e)}MANY5(e){this.manyInternal(5,e)}MANY6(e){this.manyInternal(6,e)}MANY7(e){this.manyInternal(7,e)}MANY8(e){this.manyInternal(8,e)}MANY9(e){this.manyInternal(9,e)}MANY_SEP(e){this.manySepFirstInternal(0,e)}MANY_SEP1(e){this.manySepFirstInternal(1,e)}MANY_SEP2(e){this.manySepFirstInternal(2,e)}MANY_SEP3(e){this.manySepFirstInternal(3,e)}MANY_SEP4(e){this.manySepFirstInternal(4,e)}MANY_SEP5(e){this.manySepFirstInternal(5,e)}MANY_SEP6(e){this.manySepFirstInternal(6,e)}MANY_SEP7(e){this.manySepFirstInternal(7,e)}MANY_SEP8(e){this.manySepFirstInternal(8,e)}MANY_SEP9(e){this.manySepFirstInternal(9,e)}AT_LEAST_ONE(e){this.atLeastOneInternal(0,e)}AT_LEAST_ONE1(e){return this.atLeastOneInternal(1,e)}AT_LEAST_ONE2(e){this.atLeastOneInternal(2,e)}AT_LEAST_ONE3(e){this.atLeastOneInternal(3,e)}AT_LEAST_ONE4(e){this.atLeastOneInternal(4,e)}AT_LEAST_ONE5(e){this.atLeastOneInternal(5,e)}AT_LEAST_ONE6(e){this.atLeastOneInternal(6,e)}AT_LEAST_ONE7(e){this.atLeastOneInternal(7,e)}AT_LEAST_ONE8(e){this.atLeastOneInternal(8,e)}AT_LEAST_ONE9(e){this.atLeastOneInternal(9,e)}AT_LEAST_ONE_SEP(e){this.atLeastOneSepFirstInternal(0,e)}AT_LEAST_ONE_SEP1(e){this.atLeastOneSepFirstInternal(1,e)}AT_LEAST_ONE_SEP2(e){this.atLeastOneSepFirstInternal(2,e)}AT_LEAST_ONE_SEP3(e){this.atLeastOneSepFirstInternal(3,e)}AT_LEAST_ONE_SEP4(e){this.atLeastOneSepFirstInternal(4,e)}AT_LEAST_ONE_SEP5(e){this.atLeastOneSepFirstInternal(5,e)}AT_LEAST_ONE_SEP6(e){this.atLeastOneSepFirstInternal(6,e)}AT_LEAST_ONE_SEP7(e){this.atLeastOneSepFirstInternal(7,e)}AT_LEAST_ONE_SEP8(e){this.atLeastOneSepFirstInternal(8,e)}AT_LEAST_ONE_SEP9(e){this.atLeastOneSepFirstInternal(9,e)}RULE(e,t,a=Pr){if(ae(this.definedRulesNames,e)){const t={message:ea.buildDuplicateRuleNameError({topLevelRule:e,grammarName:this.className}),type:qr.DUPLICATE_RULE_NAME,ruleName:e};this.definitionErrors.push(t)}this.definedRulesNames.push(e);const r=this.defineRule(e,t,a);return this[e]=r,r}OVERRIDE_RULE(e,t,a=Pr){const r=function(e,t,a){const r=[];let n;return ae(t,e)||(n=`Invalid rule override, rule: ->${e}<- cannot be overridden in the grammar: ->${a}<-as it is not defined in any of the super grammars `,r.push({message:n,type:qr.INVALID_RULE_OVERRIDE,ruleName:e})),r}(e,this.definedRulesNames,this.className);this.definitionErrors=this.definitionErrors.concat(r);const n=this.defineRule(e,t,a);return this[e]=n,n}BACKTRACK(e,t){return function(){this.isBackTrackingStack.push(1);const a=this.saveRecogState();try{return e.apply(this,t),!0}catch(r){if(Xa(r))return!1;throw r}finally{this.reloadRecogState(a),this.isBackTrackingStack.pop()}}}getGAstProductions(){return this.gastProductionsCache}getSerializedGastProductions(){return e=(0,n.A)(this.gastProductionsCache),(0,o.A)(e,G);var e}},class{initErrorHandler(e){this._errors=[],this.errorMessageProvider=(0,c.A)(e,"errorMessageProvider")?e.errorMessageProvider:Rr.errorMessageProvider}SAVE_ERROR(e){if(Xa(e))return e.context={ruleStack:this.getHumanReadableRuleStack(),ruleOccurrenceStack:(0,s.A)(this.RULE_OCCURRENCE_STACK)},this._errors.push(e),e;throw Error("Trying to save an Error which is not a RecognitionException")}get errors(){return(0,s.A)(this._errors)}set errors(e){this._errors=e}raiseEarlyExitException(e,t,a){const r=this.getCurrRuleFullName(),n=qa(e,this.getGAstProductions()[r],t,this.maxLookahead)[0],i=[];for(let c=1;c<=this.maxLookahead;c++)i.push(this.LA(c));const o=this.errorMessageProvider.buildEarlyExitMessage({expectedIterationPaths:n,actual:i,previous:this.LA(0),customUserDescription:a,ruleName:r});throw this.SAVE_ERROR(new tr(o,this.LA(1),this.LA(0)))}raiseNoAltException(e,t){const a=this.getCurrRuleFullName(),r=Pa(e,this.getGAstProductions()[a],this.maxLookahead),n=[];for(let c=1;c<=this.maxLookahead;c++)n.push(this.LA(c));const i=this.LA(0),o=this.errorMessageProvider.buildNoViableAltMessage({expectedPathsPerAlt:r,actual:n,previous:i,customUserDescription:t,ruleName:this.getCurrRuleFullName()});throw this.SAVE_ERROR(new Ja(o,this.LA(1),i))}},class{initContentAssist(){}computeContentAssist(e,t){const a=this.gastProductionsCache[e];if((0,fe.A)(a))throw Error(`Rule ->${e}<- does not exist in this grammar.`);return ga([a],t,this.tokenMatcher,this.maxLookahead)}getNextPossibleTokenTypes(e){const t=De(e.ruleStack),a=this.getGAstProductions()[t];return new la(a,e).startWalking()}},class{initGastRecorder(e){this.recordingProdStack=[],this.RECORDING_PHASE=!1}enableRecording(){this.RECORDING_PHASE=!0,this.TRACE_INIT("Enable Recording",()=>{for(let e=0;e<10;e++){const t=e>0?e:"";this[`CONSUME${t}`]=function(t,a){return this.consumeInternalRecord(t,e,a)},this[`SUBRULE${t}`]=function(t,a){return this.subruleInternalRecord(t,e,a)},this[`OPTION${t}`]=function(t){return this.optionInternalRecord(t,e)},this[`OR${t}`]=function(t){return this.orInternalRecord(t,e)},this[`MANY${t}`]=function(t){this.manyInternalRecord(e,t)},this[`MANY_SEP${t}`]=function(t){this.manySepFirstInternalRecord(e,t)},this[`AT_LEAST_ONE${t}`]=function(t){this.atLeastOneInternalRecord(e,t)},this[`AT_LEAST_ONE_SEP${t}`]=function(t){this.atLeastOneSepFirstInternalRecord(e,t)}}this.consume=function(e,t,a){return this.consumeInternalRecord(t,e,a)},this.subrule=function(e,t,a){return this.subruleInternalRecord(t,e,a)},this.option=function(e,t){return this.optionInternalRecord(t,e)},this.or=function(e,t){return this.orInternalRecord(t,e)},this.many=function(e,t){this.manyInternalRecord(e,t)},this.atLeastOne=function(e,t){this.atLeastOneInternalRecord(e,t)},this.ACTION=this.ACTION_RECORD,this.BACKTRACK=this.BACKTRACK_RECORD,this.LA=this.LA_RECORD})}disableRecording(){this.RECORDING_PHASE=!1,this.TRACE_INIT("Deleting Recording methods",()=>{const e=this;for(let t=0;t<10;t++){const a=t>0?t:"";delete e[`CONSUME${a}`],delete e[`SUBRULE${a}`],delete e[`OPTION${a}`],delete e[`OR${a}`],delete e[`MANY${a}`],delete e[`MANY_SEP${a}`],delete e[`AT_LEAST_ONE${a}`],delete e[`AT_LEAST_ONE_SEP${a}`]}delete e.consume,delete e.subrule,delete e.option,delete e.or,delete e.many,delete e.atLeastOne,delete e.ACTION,delete e.BACKTRACK,delete e.LA})}ACTION_RECORD(e){}BACKTRACK_RECORD(e,t){return()=>!0}LA_RECORD(e){return Tr}topLevelRuleRecord(e,t){try{const a=new O({definition:[],name:e});return a.name=e,this.recordingProdStack.push(a),t.call(this),this.recordingProdStack.pop(),a}catch(a){if(!0!==a.KNOWN_RECORDER_ERROR)try{a.message=a.message+'\n\t This error was thrown during the "grammar recording phase" For more info see:\n\thttps://chevrotain.io/docs/guide/internals.html#grammar-recording'}catch(r){throw a}throw a}}optionInternalRecord(e,t){return Ir.call(this,N,e,t)}atLeastOneInternalRecord(e,t){Ir.call(this,V,t,e)}atLeastOneSepFirstInternalRecord(e,t){Ir.call(this,j,t,e,vr)}manyInternalRecord(e,t){Ir.call(this,F,t,e)}manySepFirstInternalRecord(e,t){Ir.call(this,B,t,e,vr)}orInternalRecord(e,t){return Cr.call(this,e,t)}subruleInternalRecord(e,t,a){if(Sr(t),!e||!1===(0,c.A)(e,"ruleName")){const a=new Error(` argument is invalid expecting a Parser method reference but got: <${JSON.stringify(e)}>\n inside top level rule: <${this.recordingProdStack[0].name}>`);throw a.KNOWN_RECORDER_ERROR=!0,a}const r=(0,Lt.A)(this.recordingProdStack),n=e.ruleName,i=new 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To install Ollama, see the ",(0,r.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"}),"."]})}),(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["To connect to an Ollama server running on your local machine, enter your Ollama server's base URL address.\nThe default Ollama server address is ",(0,r.jsx)(n.code,{children:"http://localhost:11434"}),".\nOpenRAG connects to the Ollama server and populates the model lists with the server's available models."]}),"\n",(0,r.jsxs)(n.li,{children:["Select the ",(0,r.jsx)(n.strong,{children:"Embedding Model"})," and ",(0,r.jsx)(n.strong,{children:"Language Model"})," your Ollama server is running.","\n",(0,r.jsxs)(s,{closed:!0,children:[(0,r.jsx)("summary",{children:"Ollama model selection and external server configuration"}),(0,r.jsx)(d,{})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["Click ",(0,r.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,r.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,r.jsx)(n.strong,{children:"Add a Document"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Continue with the ",(0,r.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})]})]})]})}function p(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(h,{...e})}):h(e)}},3862:(e,n,s)=>{s.d(n,{Ay:()=>o,RM:()=>t});var r=s(4848),i=s(8453);const t=[];function l(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,i.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install",children:"Install WSL"})," with the Ubuntu distribution using WSL 2:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-powershell",children:"wsl --install -d Ubuntu\n"})}),"\n",(0,r.jsxs)(n.p,{children:["For new installations, the ",(0,r.jsx)(n.code,{children:"wsl --install"})," command uses WSL 2 and Ubuntu by default."]}),"\n",(0,r.jsxs)(n.p,{children:["For existing WSL installations, you can ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#change-the-default-linux-distribution-installed",children:"change the distribution"})," and ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2",children:"check the WSL version"}),"."]}),"\n",(0,r.jsx)(n.admonition,{title:"Known limitation",type:"warning",children:(0,r.jsx)(n.p,{children:"OpenRAG isn't compatible with nested virtualization, which can cause networking issues.\nDon't install OpenRAG on a WSL distribution that is installed inside a Windows VM.\nInstead, install OpenRAG on your base OS or a non-nested Linux VM."})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#ways-to-run-multiple-linux-distributions-with-wsl",children:"Start your WSL Ubuntu distribution"})," if it doesn't start automatically."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/setup/environment#set-up-your-linux-username-and-password",children:"Set up a username and password for your WSL distribution"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers",children:"Install Docker Desktop for Windows with WSL 2"}),". 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For more troubleshooting advice for networking issues, see ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/troubleshooting#common-issues",children:"Troubleshooting WSL common issues"}),"."]})]})}function o(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(l,{...e})}):l(e)}},4398:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>p,contentTitle:()=>h,default:()=>j,frontMatter:()=>c,metadata:()=>r,toc:()=>u});const r=JSON.parse('{"id":"get-started/install","title":"Install OpenRAG with TUI","description":"Install OpenRAG and then run the OpenRAG Terminal User Interface(TUI) to start your OpenRAG deployment with a guided setup process.","source":"@site/docs/get-started/install.mdx","sourceDirName":"get-started","slug":"/install","permalink":"/install","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/install.mdx","tags":[],"version":"current","frontMatter":{"title":"Install OpenRAG with TUI","slug":"/install"},"sidebar":"tutorialSidebar","previous":{"title":"Quickstart","permalink":"/quickstart"},"next":{"title":"Install OpenRAG containers","permalink":"/docker"}}');var i=s(4848),t=s(8453),l=s(1470),o=s(9365),a=s(3656),d=s(3862);const c={title:"Install OpenRAG with TUI",slug:"/install"},h=void 0,p={},u=[{value:"Prerequisites",id:"prerequisites",level:2},...d.RM,{value:"Install OpenRAG",id:"install",level:2},{value:"Set up OpenRAG with the TUI",id:"setup",level:2},...a.RM,{value:"Exit the OpenRAG TUI",id:"exit-the-openrag-tui",level:2},{value:"Manage OpenRAG containers with the TUI",id:"tui-container-management",level:2},{value:"Start all services",id:"start-all-services",level:3},{value:"Status",id:"status",level:3},{value:"Native services status",id:"native-services-status",level:3},{value:"Upgrade OpenRAG",id:"upgrade",level:2},{value:"Upgrade OpenRAG python package",id:"upgrade-openrag-python-package",level:3},{value:"Upgrade OpenRAG containers with the TUI",id:"upgrade-openrag-containers-with-the-tui",level:3},{value:"Diagnostics",id:"diagnostics",level:2},{value:"Reinstall OpenRAG",id:"reinstall",level:2}];function x(e){const n={a:"a",admonition:"admonition",code:"code",em:"em",h2:"h2",h3:"h3",img:"img",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,t.R)(),...e.components},{Details:r}=n;return r||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,i.jsxs)(i.Fragment,{children:[(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.a,{href:"#install",children:"Install OpenRAG"})," and then run the ",(0,i.jsx)(n.a,{href:"#setup",children:"OpenRAG Terminal User Interface(TUI)"})," to start your OpenRAG deployment with a guided setup process."]}),"\n",(0,i.jsx)(n.p,{children:"The OpenRAG Terminal User Interface (TUI) allows you to set up, configure, and monitor your OpenRAG deployment directly from the terminal."}),"\n",(0,i.jsx)(n.p,{children:(0,i.jsx)(n.img,{alt:"OpenRAG TUI Interface",src:s(5689).A+"",width:"1995",height:"1099"})}),"\n",(0,i.jsxs)(n.p,{children:["Instead of starting OpenRAG using Docker commands and manually editing values in the ",(0,i.jsx)(n.code,{children:".env"})," file, the TUI walks you through the setup. It prompts for variables where required, creates a ",(0,i.jsx)(n.code,{children:".env"})," file for you, and then starts OpenRAG."]}),"\n",(0,i.jsx)(n.p,{children:"Once OpenRAG is running, use the TUI to monitor your application, control your containers, and retrieve logs."}),"\n",(0,i.jsxs)(n.p,{children:["If you prefer running Podman or Docker containers and manually editing ",(0,i.jsx)(n.code,{children:".env"})," files, see ",(0,i.jsx)(n.a,{href:"/docker",children:"Install OpenRAG Containers"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["All OpenRAG installations require ",(0,i.jsx)(n.a,{href:"https://www.python.org/downloads/release/python-3100/",children:"Python"})," version 3.13 or later."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"If you aren't using the automatic installer script, install the following:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.a,{href:"https://docs.astral.sh/uv/getting-started/installation/",children:"uv"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.a,{href:"https://podman.io/docs/installation",children:"Podman"})," (recommended) or ",(0,i.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"Docker"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.a,{href:"https://docs.podman.io/en/latest/markdown/podman-compose.1.html",children:(0,i.jsx)(n.code,{children:"podman-compose"})})," or ",(0,i.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"Docker Compose"}),". To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Microsoft Windows only: To run OpenRAG on Windows, you must use the Windows Subsystem for Linux (WSL)."}),"\n",(0,i.jsxs)(r,{children:[(0,i.jsx)("summary",{children:"Install WSL for OpenRAG"}),(0,i.jsx)(d.Ay,{})]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Prepare model providers and credentials."}),"\n",(0,i.jsxs)(n.p,{children:["During ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),", you must select language model and embedding model providers.\nIf your chosen provider offers both types, you can use the same provider for both selections.\nIf your provider offers only one type, such as Anthropic, you must select two providers."]}),"\n",(0,i.jsx)(n.p,{children:"Gather the credentials and connection details for your chosen model providers before starting onboarding:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["OpenAI: Create an ",(0,i.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI API key"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:["Anthropic language models: Create an ",(0,i.jsx)(n.a,{href:"https://www.anthropic.com/docs/api/reference",children:"Anthropic API key"}),"."]}),"\n",(0,i.jsx)(n.li,{children:"IBM watsonx.ai: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment."}),"\n",(0,i.jsxs)(n.li,{children:["Ollama: Use the ",(0,i.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"})," to set up your Ollama instance locally, in the cloud, or on a remote server, and then get your Ollama server's base URL."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Optional: Install GPU support with an NVIDIA GPU, ",(0,i.jsx)(n.a,{href:"https://docs.nvidia.com/cuda/",children:"CUDA"})," support, and compatible NVIDIA drivers on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"install",children:"Install OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"Choose an installation method based on your needs:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:"For new users, the automatic installer script detects and installs prerequisites and then runs OpenRAG."}),"\n",(0,i.jsxs)(n.li,{children:["For a quick test, use ",(0,i.jsx)(n.code,{children:"uvx"})," to run OpenRAG without creating a project or modifying files."]}),"\n",(0,i.jsxs)(n.li,{children:["Use ",(0,i.jsx)(n.code,{children:"uv add"})," to install OpenRAG as a managed dependency in a new or existing Python project."]}),"\n",(0,i.jsxs)(n.li,{children:["Use ",(0,i.jsx)(n.code,{children:"uv pip install"})," to install OpenRAG into an existing virtual environment."]}),"\n"]}),"\n",(0,i.jsxs)(l.A,{groupId:"Installation method",children:[(0,i.jsxs)(o.A,{value:"installer",label:"Automatic installer",default:!0,children:[(0,i.jsxs)(n.p,{children:["The script detects and installs uv, Docker/Podman, and Docker Compose prerequisites, then runs OpenRAG with ",(0,i.jsx)(n.code,{children:"uvx"}),"."]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a directory to store the OpenRAG configuration files:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"mkdir openrag-workspace\ncd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Run the installer:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"curl -fsSL https://docs.openr.ag/files/run_openrag_with_prereqs.sh | bash\n"})}),"\n"]}),"\n"]}),(0,i.jsxs)(n.p,{children:["The TUI creates a ",(0,i.jsx)(n.code,{children:".env"})," file and docker-compose files in the current working directory."]})]}),(0,i.jsxs)(o.A,{value:"uvx",label:"Quick test with uvx",children:[(0,i.jsxs)(n.p,{children:["Use ",(0,i.jsx)(n.code,{children:"uvx"})," to quickly run OpenRAG without creating a project or modifying any files."]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a directory to store the OpenRAG configuration files:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"mkdir openrag-workspace\ncd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Run OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To run a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx --from openrag==0.1.30 openrag\n"})}),"\n"]}),"\n"]}),(0,i.jsxs)(n.p,{children:["The TUI creates a ",(0,i.jsx)(n.code,{children:".env"})," file and docker-compose files in the current working directory."]})]}),(0,i.jsxs)(o.A,{value:"uv-add",label:"Python project with uv add",children:[(0,i.jsxs)(n.p,{children:["Use ",(0,i.jsx)(n.code,{children:"uv add"})," to install OpenRAG as a dependency in your Python project. 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The OpenAI API key is optional and can be provided during onboarding.\n",(0,i.jsx)(n.strong,{children:"Basic Setup"})," does not set up OAuth connections for ingestion from cloud providers.\nFor OAuth setup, use ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),".\nFor information about the difference between basic (no auth) and OAuth in OpenRAG, see ",(0,i.jsx)(n.a,{href:"/knowledge#auth",children:"Authentication and document access"}),"."]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To install OpenRAG with ",(0,i.jsx)(n.strong,{children:"Basic Setup"}),", click ",(0,i.jsx)(n.strong,{children:"Basic Setup"})," or press ",(0,i.jsx)("kbd",{children:"1"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Generate Passwords"})," to generate passwords for OpenSearch and Langflow."]}),"\n",(0,i.jsxs)(n.p,{children:["The OpenSearch password is required. The Langflow admin password is optional.\nIf no Langflow admin password is generated, Langflow runs in ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Optional: Paste your OpenAI API key in the OpenAI API key field. You can also provide this during onboarding or choose a different model provider."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Save Configuration"}),".\nYour passwords are saved in the ",(0,i.jsx)(n.code,{children:".env"})," file used to start OpenRAG."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start OpenRAG, click ",(0,i.jsx)(n.strong,{children:"Start All Services"}),".\nStartup pulls container images and runs them, so it can take some time.\nWhen startup is complete, the TUI displays the following:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"Services started successfully\nCommand completed successfully\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start the Docling service, under ",(0,i.jsx)(n.strong,{children:"Native Services"}),", click ",(0,i.jsx)(n.strong,{children:"Start"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To open the OpenRAG application, navigate to the TUI main menu, and then click ",(0,i.jsx)(n.strong,{children:"Open App"}),".\nAlternatively, in your browser, navigate to ",(0,i.jsx)(n.code,{children:"localhost:3000"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n"]}),"\n"]})]}),(0,i.jsx)(o.A,{value:"Advanced setup",label:"Advanced setup",children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To install OpenRAG with ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),", click ",(0,i.jsx)(n.strong,{children:"Advanced Setup"})," or press ",(0,i.jsx)("kbd",{children:"2"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Generate Passwords"})," to generate passwords for OpenSearch and Langflow."]}),"\n",(0,i.jsxs)(n.p,{children:["The OpenSearch password is required. The Langflow admin password is optional.\nIf no Langflow admin password is generated, Langflow runs in ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Paste your OpenAI API key in the OpenAI API key field."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Add your client and secret values for Google or Microsoft OAuth.\nThese values can be found with your OAuth provider.\nFor more information, see the ",(0,i.jsx)(n.a,{href:"https://developers.google.com/identity/protocols/oauth2",children:"Google OAuth client"})," or ",(0,i.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth",children:"Microsoft Graph OAuth client"})," documentation."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"The OpenRAG TUI presents redirect URIs for your OAuth app.\nThese are the URLs your OAuth provider will redirect back to after user sign-in.\nRegister these redirect values with your OAuth provider as they are presented in the TUI."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start OpenRAG, click ",(0,i.jsx)(n.strong,{children:"Start All Services"}),".\nStartup pulls container images and runs them, so it can take some time.\nWhen startup is complete, the TUI displays the following:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"Services started successfully\nCommand completed successfully\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start the Docling service, under ",(0,i.jsx)(n.strong,{children:"Native Services"}),", click ",(0,i.jsx)(n.strong,{children:"Start"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To open the OpenRAG application, navigate to the TUI main menu, and then click ",(0,i.jsx)(n.strong,{children:"Open App"}),".\nAlternatively, in your browser, navigate to ",(0,i.jsx)(n.code,{children:"localhost:3000"}),".\nYou are presented with your provider's OAuth sign-in screen.\nAfter sign-in, you are redirected to the redirect URI."]}),"\n",(0,i.jsx)(n.p,{children:"Two additional variables are available for Advanced Setup:"}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.code,{children:"LANGFLOW_PUBLIC_URL"})," controls where the Langflow web interface can be accessed. This is where users interact with their flows in a browser."]}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.code,{children:"WEBHOOK_BASE_URL"})," controls where the endpoint for ",(0,i.jsx)(n.code,{children:"/connectors/CONNECTOR_TYPE/webhook"})," will be available.\nThis connection enables real-time document synchronization with external services.\nSupported webhook endpoints:"]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["Google Drive: ",(0,i.jsx)(n.code,{children:"/connectors/google_drive/webhook"})]}),"\n",(0,i.jsxs)(n.li,{children:["OneDrive: ",(0,i.jsx)(n.code,{children:"/connectors/onedrive/webhook"})]}),"\n",(0,i.jsxs)(n.li,{children:["SharePoint: ",(0,i.jsx)(n.code,{children:"/connectors/sharepoint/webhook"})]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n"]}),"\n"]})})]}),"\n",(0,i.jsx)(a.Ay,{}),"\n",(0,i.jsx)(n.h2,{id:"exit-the-openrag-tui",children:"Exit the OpenRAG TUI"}),"\n",(0,i.jsxs)(n.p,{children:["To exit the OpenRAG TUI, navigate to the main menu, and then press ",(0,i.jsx)("kbd",{children:"q"}),".\nThe OpenRAG containers continue to run until they are stopped.\nFor more information, see ",(0,i.jsx)(n.a,{href:"#tui-container-management",children:"Manage OpenRAG containers with the TUI "}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To relaunch the TUI, run ",(0,i.jsx)(n.code,{children:"uv run openrag"}),".\nIf you installed OpenRAG with ",(0,i.jsx)(n.code,{children:"uvx"}),", run ",(0,i.jsx)(n.code,{children:"uvx openrag"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"tui-container-management",children:"Manage OpenRAG containers with the TUI"}),"\n",(0,i.jsx)(n.p,{children:"After installation, the TUI can deploy, manage, and upgrade your OpenRAG containers."}),"\n",(0,i.jsx)(n.h3,{id:"start-all-services",children:"Start all services"}),"\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Start All Services"})," to start the OpenRAG containers.\nThe TUI automatically detects your container runtime, and then checks if your machine has compatible GPU support by checking for ",(0,i.jsx)(n.code,{children:"CUDA"}),", ",(0,i.jsx)(n.code,{children:"NVIDIA_SMI"}),", and Docker/Podman runtime support. This check determines which Docker Compose file OpenRAG uses.\nThe TUI then pulls the images and deploys the containers with the following command."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"docker compose up -d\n"})}),"\n",(0,i.jsxs)(n.p,{children:["If images are missing, the TUI runs ",(0,i.jsx)(n.code,{children:"docker compose pull"}),", then runs ",(0,i.jsx)(n.code,{children:"docker compose up -d"}),"."]}),"\n",(0,i.jsx)(n.h3,{id:"status",children:"Status"}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Status"})," menu displays information on your container deployment.\nHere you can check container health, find your service ports, view logs, and upgrade your containers."]}),"\n",(0,i.jsxs)(n.p,{children:["To view streaming logs, select the container you want to view, and press ",(0,i.jsx)("kbd",{children:"l"}),".\nTo copy your logs, click ",(0,i.jsx)(n.strong,{children:"Copy to Clipboard"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To ",(0,i.jsx)(n.strong,{children:"upgrade"})," your containers, click ",(0,i.jsx)(n.strong,{children:"Upgrade"}),".\n",(0,i.jsx)(n.strong,{children:"Upgrade"})," runs ",(0,i.jsx)(n.code,{children:"docker compose pull"})," and then ",(0,i.jsx)(n.code,{children:"docker compose up -d --force-recreate"}),".\nFor more information, see ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"Upgrade OpenRAG containers with the TUI"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To ",(0,i.jsx)(n.strong,{children:"reset"})," your containers, click ",(0,i.jsx)(n.strong,{children:"Reset"}),".\nReset gives you a completely fresh start.\nReset deletes all of your data, including OpenSearch data, uploaded documents, and authentication.\n",(0,i.jsx)(n.strong,{children:"Reset"})," runs two commands.\nIt first stops and removes all containers, volumes, and local images."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{children:"docker compose down --volumes --remove-orphans --rmi local\n"})}),"\n",(0,i.jsxs)(n.p,{children:["When the first command is complete, OpenRAG removes any additional Docker objects with ",(0,i.jsx)(n.code,{children:"prune"}),"."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{children:"docker system prune -f\n"})}),"\n",(0,i.jsx)(n.h3,{id:"native-services-status",children:"Native services status"}),"\n",(0,i.jsxs)(n.p,{children:["A ",(0,i.jsx)(n.em,{children:"native service"})," in OpenRAG refers to a service run locally on your machine, and not within a container.\nThe ",(0,i.jsx)(n.code,{children:"docling serve"})," process is a native service in OpenRAG, because it's a document processing service that is run on your local machine, and controlled separately from the containers."]}),"\n",(0,i.jsxs)(n.p,{children:["To start or stop ",(0,i.jsx)(n.code,{children:"docling serve"})," or any other native services, in the TUI Status menu, click ",(0,i.jsx)(n.strong,{children:"Stop"})," or ",(0,i.jsx)(n.strong,{children:"Restart"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To view the status, port, or PID of a native service, in the TUI main menu, click ",(0,i.jsx)(n.a,{href:"#status",children:"Status"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"upgrade",children:"Upgrade OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"To upgrade OpenRAG, upgrade the OpenRAG Python package, and then upgrade the OpenRAG containers using the OpenRAG TUI."}),"\n",(0,i.jsxs)(n.p,{children:["Upgrading the OpenRAG Python package updates the TUI and Python code, but container versions are controlled separately by environment variables in your ",(0,i.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,i.jsx)(n.h3,{id:"upgrade-openrag-python-package",children:"Upgrade OpenRAG python package"}),"\n",(0,i.jsxs)(n.p,{children:["Use the following steps to upgrade the OpenRAG Python package to the latest version from ",(0,i.jsx)(n.a,{href:"https://pypi.org/project/openrag/",children:"PyPI"}),".\nAfter upgrading the Python package, you should also ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your OpenRAG containers"}),"."]}),"\n",(0,i.jsxs)(l.A,{groupId:"Installation method",children:[(0,i.jsxs)(o.A,{value:"installer",label:"Automatic installer / uvx",default:!0,children:[(0,i.jsxs)(n.p,{children:["If you installed OpenRAG using the ",(0,i.jsx)(n.a,{href:"#install",children:"automatic installer"})," or ",(0,i.jsx)(n.a,{href:"#install",children:"uvx"}),", follow these steps to upgrade:"]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Navigate to your OpenRAG workspace directory:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"cd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Upgrade the OpenRAG package:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx --from openrag openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To upgrade to a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx --from openrag==0.1.33 openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["After upgrading the Python package, ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your containers"}),"."]}),"\n"]}),"\n"]})]}),(0,i.jsx)(o.A,{value:"uv-add",label:"Python project with uv add",children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Navigate to your project directory:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"cd YOUR_PROJECT_NAME\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Update OpenRAG to the latest version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add --upgrade openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To upgrade to a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add --upgrade openrag==0.1.33\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Start the OpenRAG TUI:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["After upgrading the Python package, ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your containers"}),"."]}),"\n"]}),"\n"]})}),(0,i.jsx)(o.A,{value:"uv-pip",label:"Existing virtual environment with uv pip install",children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Activate your virtual environment."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Upgrade OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv pip install --upgrade openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To upgrade to a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv pip install --upgrade openrag==0.1.33\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Start the OpenRAG TUI:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["After upgrading the Python package, ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your containers"}),"."]}),"\n"]}),"\n"]})})]}),"\n",(0,i.jsx)(n.h3,{id:"upgrade-openrag-containers-with-the-tui",children:"Upgrade OpenRAG containers with the TUI"}),"\n",(0,i.jsxs)(n.p,{children:["After upgrading the OpenRAG Python package, upgrade your containers to ensure they match the ",(0,i.jsx)(n.code,{children:"latest"})," version.\n",(0,i.jsx)(n.strong,{children:"Upgrade"})," runs ",(0,i.jsx)(n.code,{children:"docker compose pull"}),", which pulls container images based on versions specified in your ",(0,i.jsx)(n.code,{children:".env"})," file.\n",(0,i.jsx)(n.code,{children:"OPENRAG_VERSION"})," is set to ",(0,i.jsx)(n.code,{children:"latest"})," by default, so it pulls the ",(0,i.jsx)(n.code,{children:"latest"})," available container images."]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["In the OpenRAG TUI, click ",(0,i.jsx)(n.strong,{children:"Status"}),", and then click ",(0,i.jsx)(n.strong,{children:"Upgrade"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:["When the upgrade completes, close the ",(0,i.jsx)(n.strong,{children:"Status"})," window and continue using OpenRAG."]}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["If you encounter a ",(0,i.jsx)(n.code,{children:"langflow container already exists"})," error during upgrade, see ",(0,i.jsx)(n.a,{href:"/support/troubleshoot#langflow-container-already-exists-during-upgrade",children:"Langflow container already exists during upgrade"})," in the troubleshooting guide."]}),"\n",(0,i.jsxs)(n.p,{children:["To pin container versions to a specific release other than ",(0,i.jsx)(n.code,{children:"latest"}),", set the ",(0,i.jsx)(n.code,{children:"OPENRAG_VERSION"})," in your ",(0,i.jsx)(n.code,{children:".env"})," file:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"OPENRAG_VERSION=0.1.33\n"})}),"\n",(0,i.jsxs)(n.p,{children:["For more information, see ",(0,i.jsx)(n.a,{href:"/reference/configuration#system-settings",children:"System settings environment variables"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"diagnostics",children:"Diagnostics"}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Diagnostics"})," menu provides health monitoring for your container runtimes and monitoring of your OpenSearch security."]}),"\n",(0,i.jsx)(n.h2,{id:"reinstall",children:"Reinstall OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"To reinstall OpenRAG with a completely fresh setup:"}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Reset your containers using the ",(0,i.jsx)(n.strong,{children:"Reset"})," button in the ",(0,i.jsx)(n.a,{href:"#status",children:"TUI status"})," menu.\nThis removes all containers, volumes, and data."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Optional: Delete your project's ",(0,i.jsx)(n.code,{children:".env"})," file.\nThe Reset operation does not remove your project's ",(0,i.jsx)(n.code,{children:".env"})," file, so your passwords, API keys, and OAuth settings can be preserved.\nIf you delete the ",(0,i.jsx)(n.code,{children:".env"})," file, run the ",(0,i.jsx)(n.a,{href:"#setup",children:"Set up OpenRAG with the TUI"})," process again to create a new configuration."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["In the TUI Setup menu, follow these steps from ",(0,i.jsx)(n.a,{href:"#setup",children:"Basic Setup"}),":"]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["Click ",(0,i.jsx)(n.strong,{children:"Start All Services"})," to pull container images and start them."]}),"\n",(0,i.jsxs)(n.li,{children:["Under ",(0,i.jsx)(n.strong,{children:"Native Services"}),", click ",(0,i.jsx)(n.strong,{children:"Start"})," to start the Docling service."]}),"\n",(0,i.jsxs)(n.li,{children:["Click ",(0,i.jsx)(n.strong,{children:"Open App"})," to open the OpenRAG application."]}),"\n",(0,i.jsxs)(n.li,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n"]}),"\n"]}),"\n"]})]})}function j(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(x,{...e})}):x(e)}},5689:(e,n,s)=>{s.d(n,{A:()=>r});const r=s.p+"assets/images/OpenRAG_TUI_2025-09-10T13_04_11_757637-9441c53ba39162a88ac6c11cbeaed0e0.svg"}}]); \ No newline at end of file diff --git a/assets/js/d0314b07.788dda5b.js b/assets/js/d0314b07.788dda5b.js new file mode 100644 index 00000000..7d01dfde --- /dev/null +++ b/assets/js/d0314b07.788dda5b.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[5750],{3656:(e,n,s)=>{s.d(n,{Ay:()=>p,RM:()=>d});var r=s(4848),i=s(8453),t=s(1610),o=s(1470),l=s(9365);function a(e){const n={a:"a",code:"code",li:"li",ol:"ol",p:"p",strong:"strong",...(0,i.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.p,{children:"Using Ollama for your OpenRAG language model provider offers greater flexibility and configuration, but can also be overwhelming to start.\nThese recommendations are a reasonable starting point for users with at least one GPU and experience running LLMs locally."}),"\n",(0,r.jsxs)(n.p,{children:["For best performance, OpenRAG recommends OpenAI's ",(0,r.jsx)(n.code,{children:"gpt-oss:20b"})," language model. However, this model uses 16GB of RAM, so consider using Ollama Cloud or running Ollama on a remote machine."]}),"\n",(0,r.jsxs)(n.p,{children:["For generating embeddings, OpenRAG recommends the ",(0,r.jsx)(n.a,{href:"https://ollama.com/library/nomic-embed-text",children:(0,r.jsx)(n.code,{children:"nomic-embed-text"})})," embedding model, which provides high-quality embeddings optimized for retrieval tasks."]}),"\n",(0,r.jsxs)(n.p,{children:["To run models in ",(0,r.jsx)(n.a,{href:"https://docs.ollama.com/cloud",children:(0,r.jsx)(n.strong,{children:"Ollama Cloud"})}),", follow these steps:"]}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["Sign in to Ollama Cloud.\nIn a terminal, enter ",(0,r.jsx)(n.code,{children:"ollama signin"})," to connect your local environment with Ollama Cloud."]}),"\n",(0,r.jsxs)(n.li,{children:["To run the model, in Ollama, select the ",(0,r.jsx)(n.code,{children:"gpt-oss:20b-cloud"})," model, or run ",(0,r.jsx)(n.code,{children:"ollama run gpt-oss:20b-cloud"})," in a terminal.\nOllama Cloud models are run at the same URL as your local Ollama server at ",(0,r.jsx)(n.code,{children:"http://localhost:11434"}),", and automatically offloaded to Ollama's cloud service."]}),"\n",(0,r.jsxs)(n.li,{children:["Connect OpenRAG to the same local Ollama server as you would for local models in onboarding, using the default address of ",(0,r.jsx)(n.code,{children:"http://localhost:11434"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["In the ",(0,r.jsx)(n.strong,{children:"Language model"})," field, select the ",(0,r.jsx)(n.code,{children:"gpt-oss:20b-cloud"})," model."]}),"\n"]}),"\n",(0,r.jsx)("br",{}),"\n",(0,r.jsxs)(n.p,{children:["To run models on a ",(0,r.jsx)(n.strong,{children:"remote Ollama server"}),", follow these steps:"]}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsx)(n.li,{children:"Ensure your remote Ollama server is accessible from your OpenRAG instance."}),"\n",(0,r.jsxs)(n.li,{children:["In the ",(0,r.jsx)(n.strong,{children:"Ollama Base URL"})," field, enter your remote Ollama server's base URL, such as ",(0,r.jsx)(n.code,{children:"http://your-remote-server:11434"}),".\nOpenRAG connects to the remote Ollama server and populates the lists with the server's available models."]}),"\n",(0,r.jsxs)(n.li,{children:["Select your ",(0,r.jsx)(n.strong,{children:"Embedding model"})," and ",(0,r.jsx)(n.strong,{children:"Language model"})," from the available options."]}),"\n"]})]})}function c(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(a,{...e})}):a(e)}const d=[{value:"Application onboarding",id:"application-onboarding",level:2}];function h(e){const n={a:"a",admonition:"admonition",code:"code",h2:"h2",li:"li",ol:"ol",p:"p",strong:"strong",...(0,i.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.h2,{id:"application-onboarding",children:"Application onboarding"}),"\n",(0,r.jsx)(n.p,{children:"The first time you start OpenRAG, regardless of how you installed it, you must complete application onboarding."}),"\n",(0,r.jsxs)(n.p,{children:["Some of these variables, such as the embedding models, can be changed seamlessly after onboarding.\nOthers are immutable and require you to destroy and recreate the OpenRAG containers.\nFor more information, see ",(0,r.jsx)(n.a,{href:"/reference/configuration",children:"Environment variables"}),"."]}),"\n",(0,r.jsx)(n.p,{children:"You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embeddings model.\nAdditionally, you can set multiple embedding models."}),"\n",(0,r.jsx)(n.p,{children:"You only need to complete onboarding for your preferred providers."}),"\n",(0,r.jsxs)(o.A,{groupId:"Provider",children:[(0,r.jsxs)(l.A,{value:"Anthropic",label:"Anthropic",default:!0,children:[(0,r.jsx)(n.admonition,{type:"info",children:(0,r.jsx)(n.p,{children:"Anthropic doesn't provide embedding models. If you select Anthropic for your language model, you must select a different provider for embeddings."})}),(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["Enable ",(0,r.jsx)(n.strong,{children:"Use environment Anthropic API key"})," to automatically use your key from the ",(0,r.jsx)(n.code,{children:".env"})," file.\nAlternatively, paste an Anthropic API key into the field."]}),"\n",(0,r.jsxs)(n.li,{children:["Under ",(0,r.jsx)(n.strong,{children:"Advanced settings"}),", select your ",(0,r.jsx)(n.strong,{children:"Language Model"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Click ",(0,r.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["In the second onboarding panel, select a provider for embeddings and select your ",(0,r.jsx)(n.strong,{children:"Embedding Model"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,r.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,r.jsx)(n.strong,{children:"Add a Document"}),".\nAlternatively, click ",(0,r.jsx)(t.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Skip overview"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Continue with the ",(0,r.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})]}),(0,r.jsx)(l.A,{value:"OpenAI",label:"OpenAI",children:(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["Enable ",(0,r.jsx)(n.strong,{children:"Get API key from environment variable"})," to automatically enter your key from the TUI-generated ",(0,r.jsx)(n.code,{children:".env"})," file.\nAlternatively, paste an OpenAI API key into the field."]}),"\n",(0,r.jsxs)(n.li,{children:["Under ",(0,r.jsx)(n.strong,{children:"Advanced settings"}),", select your ",(0,r.jsx)(n.strong,{children:"Language Model"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Click ",(0,r.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["In the second onboarding panel, select a provider for embeddings and select your ",(0,r.jsx)(n.strong,{children:"Embedding Model"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,r.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,r.jsx)(n.strong,{children:"Add a Document"}),".\nAlternatively, click ",(0,r.jsx)(t.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Skip overview"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Continue with the ",(0,r.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})}),(0,r.jsx)(l.A,{value:"IBM watsonx.ai",label:"IBM watsonx.ai",children:(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["Complete the fields for ",(0,r.jsx)(n.strong,{children:"watsonx.ai API Endpoint"}),", ",(0,r.jsx)(n.strong,{children:"IBM Project ID"}),", and ",(0,r.jsx)(n.strong,{children:"IBM API key"}),".\nThese values are found in your IBM watsonx deployment."]}),"\n",(0,r.jsxs)(n.li,{children:["Under ",(0,r.jsx)(n.strong,{children:"Advanced settings"}),", select your ",(0,r.jsx)(n.strong,{children:"Language Model"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Click ",(0,r.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["In the second onboarding panel, select a provider for embeddings and select your ",(0,r.jsx)(n.strong,{children:"Embedding Model"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,r.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,r.jsx)(n.strong,{children:"Add a Document"}),".\nAlternatively, click ",(0,r.jsx)(t.A,{name:"ArrowRight","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Skip overview"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Continue with the ",(0,r.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})}),(0,r.jsxs)(l.A,{value:"Ollama",label:"Ollama",children:[(0,r.jsx)(n.admonition,{type:"info",children:(0,r.jsxs)(n.p,{children:["Ollama isn't installed with OpenRAG. To install Ollama, see the ",(0,r.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"}),"."]})}),(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["To connect to an Ollama server running on your local machine, enter your Ollama server's base URL address.\nThe default Ollama server address is ",(0,r.jsx)(n.code,{children:"http://localhost:11434"}),".\nOpenRAG connects to the Ollama server and populates the model lists with the server's available models."]}),"\n",(0,r.jsxs)(n.li,{children:["Select the ",(0,r.jsx)(n.strong,{children:"Embedding Model"})," and ",(0,r.jsx)(n.strong,{children:"Language Model"})," your Ollama server is running.","\n",(0,r.jsxs)(s,{closed:!0,children:[(0,r.jsx)("summary",{children:"Ollama model selection and external server configuration"}),(0,r.jsx)(c,{})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["Click ",(0,r.jsx)(n.strong,{children:"Complete"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To complete the onboarding tasks, click ",(0,r.jsx)(n.strong,{children:"What is OpenRAG"}),", and then click ",(0,r.jsx)(n.strong,{children:"Add a Document"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Continue with the ",(0,r.jsx)(n.a,{href:"/quickstart",children:"Quickstart"}),"."]}),"\n"]})]})]})]})}function p(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(h,{...e})}):h(e)}},3862:(e,n,s)=>{s.d(n,{Ay:()=>l,RM:()=>t});var r=s(4848),i=s(8453);const t=[];function o(e){const n={a:"a",admonition:"admonition",code:"code",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,i.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install",children:"Install WSL"})," with the Ubuntu distribution using WSL 2:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-powershell",children:"wsl --install -d Ubuntu\n"})}),"\n",(0,r.jsxs)(n.p,{children:["For new installations, the ",(0,r.jsx)(n.code,{children:"wsl --install"})," command uses WSL 2 and Ubuntu by default."]}),"\n",(0,r.jsxs)(n.p,{children:["For existing WSL installations, you can ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#change-the-default-linux-distribution-installed",children:"change the distribution"})," and ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#upgrade-version-from-wsl-1-to-wsl-2",children:"check the WSL version"}),"."]}),"\n",(0,r.jsx)(n.admonition,{title:"Known limitation",type:"warning",children:(0,r.jsx)(n.p,{children:"OpenRAG isn't compatible with nested virtualization, which can cause networking issues.\nDon't install OpenRAG on a WSL distribution that is installed inside a Windows VM.\nInstead, install OpenRAG on your base OS or a non-nested Linux VM."})}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/install#ways-to-run-multiple-linux-distributions-with-wsl",children:"Start your WSL Ubuntu distribution"})," if it doesn't start automatically."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/setup/environment#set-up-your-linux-username-and-password",children:"Set up a username and password for your WSL distribution"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/tutorials/wsl-containers",children:"Install Docker Desktop for Windows with WSL 2"}),". When you reach the Docker Desktop ",(0,r.jsx)(n.strong,{children:"WSL integration"})," settings, make sure your Ubuntu distribution is enabled, and then click ",(0,r.jsx)(n.strong,{children:"Apply & Restart"})," to enable Docker support in WSL."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Install and run OpenRAG from within your WSL Ubuntu distribution."}),"\n"]}),"\n"]}),"\n",(0,r.jsx)("br",{}),"\n",(0,r.jsxs)(n.p,{children:["If you encounter issues with port forwarding or the Windows Firewall, you might need to adjust the ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/security/operating-system-security/network-security/windows-firewall/hyper-v-firewall",children:"Hyper-V firewall settings"})," to allow communication between your WSL distribution and the Windows host. For more troubleshooting advice for networking issues, see ",(0,r.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/windows/wsl/troubleshooting#common-issues",children:"Troubleshooting WSL common issues"}),"."]})]})}function l(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(o,{...e})}):o(e)}},4398:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>p,contentTitle:()=>h,default:()=>j,frontMatter:()=>d,metadata:()=>r,toc:()=>u});const r=JSON.parse('{"id":"get-started/install","title":"Install OpenRAG with TUI","description":"Install OpenRAG and then run the OpenRAG Terminal User Interface(TUI) to start your OpenRAG deployment with a guided setup process.","source":"@site/docs/get-started/install.mdx","sourceDirName":"get-started","slug":"/install","permalink":"/install","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/install.mdx","tags":[],"version":"current","frontMatter":{"title":"Install OpenRAG with TUI","slug":"/install"},"sidebar":"tutorialSidebar","previous":{"title":"Quickstart","permalink":"/quickstart"},"next":{"title":"Install OpenRAG containers","permalink":"/docker"}}');var i=s(4848),t=s(8453),o=s(1470),l=s(9365),a=s(3656),c=s(3862);const d={title:"Install OpenRAG with TUI",slug:"/install"},h=void 0,p={},u=[{value:"Prerequisites",id:"prerequisites",level:2},...c.RM,{value:"Install OpenRAG",id:"install",level:2},{value:"Set up OpenRAG with the TUI",id:"setup",level:2},...a.RM,{value:"Exit the OpenRAG TUI",id:"exit-the-openrag-tui",level:2},{value:"Manage OpenRAG containers with the TUI",id:"tui-container-management",level:2},{value:"Start all services",id:"start-all-services",level:3},{value:"Status",id:"status",level:3},{value:"Native services status",id:"native-services-status",level:3},{value:"Upgrade OpenRAG",id:"upgrade",level:2},{value:"Upgrade OpenRAG python package",id:"upgrade-openrag-python-package",level:3},{value:"Upgrade OpenRAG containers with the TUI",id:"upgrade-openrag-containers-with-the-tui",level:3},{value:"Diagnostics",id:"diagnostics",level:2},{value:"Reinstall OpenRAG",id:"reinstall",level:2}];function x(e){const n={a:"a",admonition:"admonition",code:"code",em:"em",h2:"h2",h3:"h3",img:"img",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,t.R)(),...e.components},{Details:r}=n;return r||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,i.jsxs)(i.Fragment,{children:[(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.a,{href:"#install",children:"Install OpenRAG"})," and then run the ",(0,i.jsx)(n.a,{href:"#setup",children:"OpenRAG Terminal User Interface(TUI)"})," to start your OpenRAG deployment with a guided setup process."]}),"\n",(0,i.jsx)(n.p,{children:"The OpenRAG Terminal User Interface (TUI) allows you to set up, configure, and monitor your OpenRAG deployment directly from the terminal."}),"\n",(0,i.jsx)(n.p,{children:(0,i.jsx)(n.img,{alt:"OpenRAG TUI Interface",src:s(5689).A+"",width:"1995",height:"1099"})}),"\n",(0,i.jsxs)(n.p,{children:["Instead of starting OpenRAG using Docker commands and manually editing values in the ",(0,i.jsx)(n.code,{children:".env"})," file, the TUI walks you through the setup. It prompts for variables where required, creates a ",(0,i.jsx)(n.code,{children:".env"})," file for you, and then starts OpenRAG."]}),"\n",(0,i.jsx)(n.p,{children:"Once OpenRAG is running, use the TUI to monitor your application, control your containers, and retrieve logs."}),"\n",(0,i.jsxs)(n.p,{children:["If you prefer running Podman or Docker containers and manually editing ",(0,i.jsx)(n.code,{children:".env"})," files, see ",(0,i.jsx)(n.a,{href:"/docker",children:"Install OpenRAG Containers"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["All OpenRAG installations require ",(0,i.jsx)(n.a,{href:"https://www.python.org/downloads/release/python-3100/",children:"Python"})," version 3.13 or later."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"If you aren't using the automatic installer script, install the following:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.a,{href:"https://docs.astral.sh/uv/getting-started/installation/",children:"uv"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.a,{href:"https://podman.io/docs/installation",children:"Podman"})," (recommended) or ",(0,i.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"Docker"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.a,{href:"https://docs.podman.io/en/latest/markdown/podman-compose.1.html",children:(0,i.jsx)(n.code,{children:"podman-compose"})})," or ",(0,i.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"Docker Compose"}),". To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Microsoft Windows only: To run OpenRAG on Windows, you must use the Windows Subsystem for Linux (WSL)."}),"\n",(0,i.jsxs)(r,{children:[(0,i.jsx)("summary",{children:"Install WSL for OpenRAG"}),(0,i.jsx)(c.Ay,{})]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Prepare model providers and credentials."}),"\n",(0,i.jsxs)(n.p,{children:["During ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"application onboarding"}),", you must select language model and embedding model providers.\nIf your chosen provider offers both types, you can use the same provider for both selections.\nIf your provider offers only one type, such as Anthropic, you must select two providers."]}),"\n",(0,i.jsx)(n.p,{children:"Gather the credentials and connection details for your chosen model providers before starting onboarding:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["OpenAI: Create an ",(0,i.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI API key"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:["Anthropic language models: Create an ",(0,i.jsx)(n.a,{href:"https://www.anthropic.com/docs/api/reference",children:"Anthropic API key"}),"."]}),"\n",(0,i.jsx)(n.li,{children:"IBM watsonx.ai: Get your watsonx.ai API endpoint, IBM project ID, and IBM API key from your watsonx deployment."}),"\n",(0,i.jsxs)(n.li,{children:["Ollama: Use the ",(0,i.jsx)(n.a,{href:"https://docs.ollama.com/",children:"Ollama documentation"})," to set up your Ollama instance locally, in the cloud, or on a remote server, and then get your Ollama server's base URL."]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Optional: Install GPU support with an NVIDIA GPU, ",(0,i.jsx)(n.a,{href:"https://docs.nvidia.com/cuda/",children:"CUDA"})," support, and compatible NVIDIA drivers on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment."]}),"\n"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"install",children:"Install OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"Choose an installation method based on your needs:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:"For new users, the automatic installer script detects and installs prerequisites and then runs OpenRAG."}),"\n",(0,i.jsxs)(n.li,{children:["For a quick test, use ",(0,i.jsx)(n.code,{children:"uvx"})," to run OpenRAG without creating a project or modifying files."]}),"\n",(0,i.jsxs)(n.li,{children:["Use ",(0,i.jsx)(n.code,{children:"uv add"})," to install OpenRAG as a managed dependency in a new or existing Python project."]}),"\n",(0,i.jsxs)(n.li,{children:["Use ",(0,i.jsx)(n.code,{children:"uv pip install"})," to install OpenRAG into an existing virtual environment."]}),"\n"]}),"\n",(0,i.jsxs)(o.A,{groupId:"Installation method",children:[(0,i.jsxs)(l.A,{value:"installer",label:"Automatic installer",default:!0,children:[(0,i.jsxs)(n.p,{children:["The script detects and installs uv, Docker/Podman, and Docker Compose prerequisites, then runs OpenRAG with ",(0,i.jsx)(n.code,{children:"uvx"}),"."]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a directory to store the OpenRAG configuration files:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"mkdir openrag-workspace\ncd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Run the installer:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"curl -fsSL https://docs.openr.ag/files/run_openrag_with_prereqs.sh | bash\n"})}),"\n"]}),"\n"]}),(0,i.jsxs)(n.p,{children:["The TUI creates a ",(0,i.jsx)(n.code,{children:".env"})," file and docker-compose files in the current working directory."]})]}),(0,i.jsxs)(l.A,{value:"uvx",label:"Quick test with uvx",children:[(0,i.jsxs)(n.p,{children:["Use ",(0,i.jsx)(n.code,{children:"uvx"})," to quickly run OpenRAG without creating a project or modifying any files."]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a directory to store the OpenRAG configuration files:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"mkdir openrag-workspace\ncd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Run OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To run a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx --from openrag==0.1.30 openrag\n"})}),"\n"]}),"\n"]}),(0,i.jsxs)(n.p,{children:["The TUI creates a ",(0,i.jsx)(n.code,{children:".env"})," file and docker-compose files in the current working directory."]})]}),(0,i.jsxs)(l.A,{value:"uv-add",label:"Python project with uv add",children:[(0,i.jsxs)(n.p,{children:["Use ",(0,i.jsx)(n.code,{children:"uv add"})," to install OpenRAG as a dependency in your Python project. This adds OpenRAG to your ",(0,i.jsx)(n.code,{children:"pyproject.toml"})," and lockfile, making your installation reproducible and version-controlled."]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Create a new project with a virtual environment:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv init YOUR_PROJECT_NAME\ncd YOUR_PROJECT_NAME\n"})}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.code,{children:"(venv)"})," prompt doesn't change, but ",(0,i.jsx)(n.code,{children:"uv"})," commands will automatically use the project's virtual environment."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Add OpenRAG to your project:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To add a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add openrag==0.1.30\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Start the OpenRAG TUI:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n"]}),(0,i.jsxs)(r,{closed:!0,children:[(0,i.jsx)("summary",{children:"Install a local wheel"}),(0,i.jsx)(n.p,{children:"If you downloaded the OpenRAG wheel to your local machine, install it by specifying its path:"}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Add the wheel to your project:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add PATH/TO/openrag-VERSION-py3-none-any.whl\n"})}),"\n",(0,i.jsxs)(n.p,{children:["Replace ",(0,i.jsx)(n.code,{children:"PATH/TO/"})," and ",(0,i.jsx)(n.code,{children:"VERSION"})," with the path and version of your downloaded OpenRAG ",(0,i.jsx)(n.code,{children:".whl"})," file."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Run OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n"]})]})]}),(0,i.jsxs)(l.A,{value:"uv-pip",label:"Existing virtual environment with uv pip install",children:[(0,i.jsxs)(n.p,{children:["Use ",(0,i.jsx)(n.code,{children:"uv pip install"})," to install OpenRAG into an existing virtual environment that isn't managed by ",(0,i.jsx)(n.code,{children:"uv"}),"."]}),(0,i.jsx)(n.admonition,{type:"tip",children:(0,i.jsxs)(n.p,{children:["For new projects, ",(0,i.jsx)(n.code,{children:"uv add"})," is recommended as it manages dependencies in your project's lockfile."]})}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Activate your virtual environment."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Install OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv pip install openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Run OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n"]})]})]}),"\n",(0,i.jsxs)(n.p,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#setup",children:"Set up OpenRAG with the TUI"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["If you encounter errors during installation, see ",(0,i.jsx)(n.a,{href:"/support/troubleshoot",children:"Troubleshoot OpenRAG"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"setup",children:"Set up OpenRAG with the TUI"}),"\n",(0,i.jsxs)(n.p,{children:["The OpenRAG setup process creates a ",(0,i.jsx)(n.code,{children:".env"})," file at the root of your OpenRAG directory, and then starts OpenRAG.\nIf it detects a ",(0,i.jsx)(n.code,{children:".env"})," file in the OpenRAG root directory, it sources any variables from the ",(0,i.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,i.jsxs)(n.p,{children:["The TUI offers two setup methods to populate the required values. ",(0,i.jsx)(n.strong,{children:"Basic Setup"})," can generate all minimum required values for OpenRAG. However, ",(0,i.jsx)(n.strong,{children:"Basic Setup"})," doesn't enable ",(0,i.jsx)(n.a,{href:"/knowledge#auth",children:"OAuth connectors for cloud storage"}),". If you want to use OAuth connectors to upload documents from cloud storage, select ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),".\nIf OpenRAG detects OAuth credentials, it recommends ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),"\n",(0,i.jsxs)(o.A,{groupId:"Setup method",children:[(0,i.jsx)(l.A,{value:"Basic setup",label:"Basic setup",default:!0,children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To install OpenRAG with ",(0,i.jsx)(n.strong,{children:"Basic Setup"}),", click ",(0,i.jsx)(n.strong,{children:"Basic Setup"})," or press ",(0,i.jsx)("kbd",{children:"1"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Generate Passwords"})," to generate passwords for OpenSearch and Langflow."]}),"\n",(0,i.jsxs)(n.p,{children:["The OpenSearch password is required. The Langflow admin password is optional.\nIf no Langflow admin password is generated, Langflow runs in ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Optional: Paste your OpenAI API key in the OpenAI API key field. You can also provide this during onboarding or choose a different model provider."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Save Configuration"}),".\nYour passwords are saved in the ",(0,i.jsx)(n.code,{children:".env"})," file used to start OpenRAG."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start OpenRAG, click ",(0,i.jsx)(n.strong,{children:"Start All Services"}),".\nStartup pulls container images and runs them, so it can take some time.\nWhen startup is complete, the TUI displays the following:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"Services started successfully\nCommand completed successfully\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start the Docling service, under ",(0,i.jsx)(n.strong,{children:"Native Services"}),", click ",(0,i.jsx)(n.strong,{children:"Start"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To open the OpenRAG application, navigate to the TUI main menu, and then click ",(0,i.jsx)(n.strong,{children:"Open App"}),".\nAlternatively, in your browser, navigate to ",(0,i.jsx)(n.code,{children:"localhost:3000"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"application onboarding"}),"."]}),"\n"]}),"\n"]})}),(0,i.jsx)(l.A,{value:"Advanced setup",label:"Advanced setup",children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To install OpenRAG with ",(0,i.jsx)(n.strong,{children:"Advanced Setup"}),", click ",(0,i.jsx)(n.strong,{children:"Advanced Setup"})," or press ",(0,i.jsx)("kbd",{children:"2"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Generate Passwords"})," to generate passwords for OpenSearch and Langflow."]}),"\n",(0,i.jsxs)(n.p,{children:["The OpenSearch password is required. The Langflow admin password is optional.\nIf no Langflow admin password is generated, Langflow runs in ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication#langflow-auto-login",children:"autologin mode"})," with no password required."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Paste your OpenAI API key in the OpenAI API key field."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["If you want to upload documents from external storage, such as Google Drive, add the required OAuth credentials for the connectors that you want to use. These settings can be populated automatically if OpenRAG detects these credentials in a ",(0,i.jsx)(n.code,{children:".env"})," file in the OpenRAG installation directory."]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.strong,{children:"Amazon"}),": Provide your AWS Access Key ID and AWS Secret Access Key with access to your S3 instance. For more information, see the AWS documentation on ",(0,i.jsx)(n.a,{href:"https://docs.aws.amazon.com/singlesignon/latest/userguide/manage-your-applications.html",children:"Configuring access to AWS applications"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.strong,{children:"Google"}),": Provide your Google OAuth Client ID and Google OAuth Client Secret. You can generate these in the ",(0,i.jsx)(n.a,{href:"https://console.cloud.google.com/apis/credentials",children:"Google Cloud Console"}),". For more information, see the ",(0,i.jsx)(n.a,{href:"https://developers.google.com/identity/protocols/oauth2",children:"Google OAuth client documentation"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:[(0,i.jsx)(n.strong,{children:"Microsoft"}),": For the Microsoft OAuth Client ID and Microsoft OAuth Client Secret, provide ",(0,i.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/app-registration?view=odsp-graph-online",children:"Azure application registration credentials for SharePoint and OneDrive"}),". For more information, see the ",(0,i.jsx)(n.a,{href:"https://learn.microsoft.com/en-us/onedrive/developer/rest-api/getting-started/graph-oauth",children:"Microsoft Graph OAuth client documentation"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["You can ",(0,i.jsx)(n.a,{href:"/ingestion#oauth-ingestion",children:"manage OAuth credentials"})," later, but it is recommended to configure them during initial set up."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"The OpenRAG TUI presents redirect URIs for your OAuth app.\nThese are the URLs your OAuth provider will redirect back to after user sign-in.\nRegister these redirect values with your OAuth provider as they are presented in the TUI."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start OpenRAG, click ",(0,i.jsx)(n.strong,{children:"Start All Services"}),".\nStartup pulls container images and runs them, so it can take some time.\nWhen startup is complete, the TUI displays the following:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"Services started successfully\nCommand completed successfully\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To start the Docling service, under ",(0,i.jsx)(n.strong,{children:"Native Services"}),", click ",(0,i.jsx)(n.strong,{children:"Start"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["To open the OpenRAG application, navigate to the TUI main menu, and then click ",(0,i.jsx)(n.strong,{children:"Open App"}),".\nAlternatively, in your browser, navigate to ",(0,i.jsx)(n.code,{children:"localhost:3000"}),"."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"If you enabled OAuth connectors, you must sign in to your OAuth provider before being redirected to your OpenRAG instance."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Two additional variables are available for ",(0,i.jsx)(n.strong,{children:"Advanced Setup"})," at this point.\nOnly change these variables if you have a non-default network configuration for your deployment, such as using a reverse proxy or custom domain."]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.code,{children:"LANGFLOW_PUBLIC_URL"}),": Sets the base address to access the Langflow web interface. This is where users interact with flows in a browser."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:[(0,i.jsx)(n.code,{children:"WEBHOOK_BASE_URL"}),": Sets the base address of the OpenRAG OAuth connector endpoint.\nSupported webhook endpoints:"]}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:"Amazon S3: Not applicable."}),"\n",(0,i.jsxs)(n.li,{children:["Google Drive: ",(0,i.jsx)(n.code,{children:"/connectors/google_drive/webhook"})]}),"\n",(0,i.jsxs)(n.li,{children:["OneDrive: ",(0,i.jsx)(n.code,{children:"/connectors/onedrive/webhook"})]}),"\n",(0,i.jsxs)(n.li,{children:["SharePoint: ",(0,i.jsx)(n.code,{children:"/connectors/sharepoint/webhook"})]}),"\n"]}),"\n"]}),"\n"]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"application onboarding"}),"."]}),"\n"]}),"\n"]})})]}),"\n",(0,i.jsx)(a.Ay,{}),"\n",(0,i.jsx)(n.h2,{id:"exit-the-openrag-tui",children:"Exit the OpenRAG TUI"}),"\n",(0,i.jsxs)(n.p,{children:["To exit the OpenRAG TUI, navigate to the main menu, and then press ",(0,i.jsx)("kbd",{children:"q"}),".\nThe OpenRAG containers continue to run until they are stopped.\nFor more information, see ",(0,i.jsx)(n.a,{href:"#tui-container-management",children:"Manage OpenRAG containers with the TUI "}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To relaunch the TUI, run ",(0,i.jsx)(n.code,{children:"uv run openrag"}),".\nIf you installed OpenRAG with ",(0,i.jsx)(n.code,{children:"uvx"}),", run ",(0,i.jsx)(n.code,{children:"uvx openrag"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"tui-container-management",children:"Manage OpenRAG containers with the TUI"}),"\n",(0,i.jsx)(n.p,{children:"After installation, the TUI can deploy, manage, and upgrade your OpenRAG containers."}),"\n",(0,i.jsx)(n.h3,{id:"start-all-services",children:"Start all services"}),"\n",(0,i.jsxs)(n.p,{children:["Click ",(0,i.jsx)(n.strong,{children:"Start All Services"})," to start the OpenRAG containers.\nThe TUI automatically detects your container runtime, and then checks if your machine has compatible GPU support by checking for ",(0,i.jsx)(n.code,{children:"CUDA"}),", ",(0,i.jsx)(n.code,{children:"NVIDIA_SMI"}),", and Docker/Podman runtime support. This check determines which Docker Compose file OpenRAG uses.\nThe TUI then pulls the images and deploys the containers with the following command."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"docker compose up -d\n"})}),"\n",(0,i.jsxs)(n.p,{children:["If images are missing, the TUI runs ",(0,i.jsx)(n.code,{children:"docker compose pull"}),", then runs ",(0,i.jsx)(n.code,{children:"docker compose up -d"}),"."]}),"\n",(0,i.jsx)(n.h3,{id:"status",children:"Status"}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Status"})," menu displays information on your container deployment.\nHere you can check container health, find your service ports, view logs, and upgrade your containers."]}),"\n",(0,i.jsxs)(n.p,{children:["To view streaming logs, select the container you want to view, and press ",(0,i.jsx)("kbd",{children:"l"}),".\nTo copy your logs, click ",(0,i.jsx)(n.strong,{children:"Copy to Clipboard"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To ",(0,i.jsx)(n.strong,{children:"upgrade"})," your containers, click ",(0,i.jsx)(n.strong,{children:"Upgrade"}),".\n",(0,i.jsx)(n.strong,{children:"Upgrade"})," runs ",(0,i.jsx)(n.code,{children:"docker compose pull"})," and then ",(0,i.jsx)(n.code,{children:"docker compose up -d --force-recreate"}),".\nFor more information, see ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"Upgrade OpenRAG containers with the TUI"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To ",(0,i.jsx)(n.strong,{children:"reset"})," your containers, click ",(0,i.jsx)(n.strong,{children:"Reset"}),".\nReset gives you a completely fresh start.\nReset deletes all of your data, including OpenSearch data, uploaded documents, and authentication.\n",(0,i.jsx)(n.strong,{children:"Reset"})," runs two commands.\nIt first stops and removes all containers, volumes, and local images."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{children:"docker compose down --volumes --remove-orphans --rmi local\n"})}),"\n",(0,i.jsxs)(n.p,{children:["When the first command is complete, OpenRAG removes any additional Docker objects with ",(0,i.jsx)(n.code,{children:"prune"}),"."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{children:"docker system prune -f\n"})}),"\n",(0,i.jsx)(n.h3,{id:"native-services-status",children:"Native services status"}),"\n",(0,i.jsxs)(n.p,{children:["A ",(0,i.jsx)(n.em,{children:"native service"})," in OpenRAG refers to a service run locally on your machine, and not within a container.\nThe ",(0,i.jsx)(n.code,{children:"docling serve"})," process is a native service in OpenRAG, because it's a document processing service that is run on your local machine, and controlled separately from the containers."]}),"\n",(0,i.jsxs)(n.p,{children:["To start or stop ",(0,i.jsx)(n.code,{children:"docling serve"})," or any other native services, in the TUI Status menu, click ",(0,i.jsx)(n.strong,{children:"Stop"})," or ",(0,i.jsx)(n.strong,{children:"Restart"}),"."]}),"\n",(0,i.jsxs)(n.p,{children:["To view the status, port, or PID of a native service, in the TUI main menu, click ",(0,i.jsx)(n.a,{href:"#status",children:"Status"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"upgrade",children:"Upgrade OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"To upgrade OpenRAG, upgrade the OpenRAG Python package, and then upgrade the OpenRAG containers using the OpenRAG TUI."}),"\n",(0,i.jsxs)(n.p,{children:["Upgrading the OpenRAG Python package updates the TUI and Python code, but container versions are controlled separately by environment variables in your ",(0,i.jsx)(n.code,{children:".env"})," file."]}),"\n",(0,i.jsx)(n.h3,{id:"upgrade-openrag-python-package",children:"Upgrade OpenRAG python package"}),"\n",(0,i.jsxs)(n.p,{children:["Use the following steps to upgrade the OpenRAG Python package to the latest version from ",(0,i.jsx)(n.a,{href:"https://pypi.org/project/openrag/",children:"PyPI"}),".\nAfter upgrading the Python package, you should also ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your OpenRAG containers"}),"."]}),"\n",(0,i.jsxs)(o.A,{groupId:"Installation method",children:[(0,i.jsxs)(l.A,{value:"installer",label:"Automatic installer / uvx",default:!0,children:[(0,i.jsxs)(n.p,{children:["If you installed OpenRAG using the ",(0,i.jsx)(n.a,{href:"#install",children:"automatic installer"})," or ",(0,i.jsx)(n.a,{href:"#install",children:"uvx"}),", follow these steps to upgrade:"]}),(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Navigate to your OpenRAG workspace directory:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"cd openrag-workspace\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Upgrade the OpenRAG package:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx --from openrag openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To upgrade to a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uvx --from openrag==0.1.33 openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["After upgrading the Python package, ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your containers"}),"."]}),"\n"]}),"\n"]})]}),(0,i.jsx)(l.A,{value:"uv-add",label:"Python project with uv add",children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Navigate to your project directory:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"cd YOUR_PROJECT_NAME\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Update OpenRAG to the latest version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add --upgrade openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To upgrade to a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv add --upgrade openrag==0.1.33\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Start the OpenRAG TUI:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["After upgrading the Python package, ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your containers"}),"."]}),"\n"]}),"\n"]})}),(0,i.jsx)(l.A,{value:"uv-pip",label:"Existing virtual environment with uv pip install",children:(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Activate your virtual environment."}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Upgrade OpenRAG:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv pip install --upgrade openrag\n"})}),"\n",(0,i.jsx)(n.p,{children:"To upgrade to a specific version:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv pip install --upgrade openrag==0.1.33\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsx)(n.p,{children:"Start the OpenRAG TUI:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["After upgrading the Python package, ",(0,i.jsx)(n.a,{href:"#upgrade-openrag-containers-with-the-tui",children:"upgrade your containers"}),"."]}),"\n"]}),"\n"]})})]}),"\n",(0,i.jsx)(n.h3,{id:"upgrade-openrag-containers-with-the-tui",children:"Upgrade OpenRAG containers with the TUI"}),"\n",(0,i.jsxs)(n.p,{children:["After upgrading the OpenRAG Python package, upgrade your containers to ensure they match the ",(0,i.jsx)(n.code,{children:"latest"})," version.\n",(0,i.jsx)(n.strong,{children:"Upgrade"})," runs ",(0,i.jsx)(n.code,{children:"docker compose pull"}),", which pulls container images based on versions specified in your ",(0,i.jsx)(n.code,{children:".env"})," file.\n",(0,i.jsx)(n.code,{children:"OPENRAG_VERSION"})," is set to ",(0,i.jsx)(n.code,{children:"latest"})," by default, so it pulls the ",(0,i.jsx)(n.code,{children:"latest"})," available container images."]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["In the OpenRAG TUI, click ",(0,i.jsx)(n.strong,{children:"Status"}),", and then click ",(0,i.jsx)(n.strong,{children:"Upgrade"}),"."]}),"\n",(0,i.jsxs)(n.li,{children:["When the upgrade completes, close the ",(0,i.jsx)(n.strong,{children:"Status"})," window and continue using OpenRAG."]}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["If you encounter a ",(0,i.jsx)(n.code,{children:"langflow container already exists"})," error during upgrade, see ",(0,i.jsx)(n.a,{href:"/support/troubleshoot#langflow-container-already-exists-during-upgrade",children:"Langflow container already exists during upgrade"})," in the troubleshooting guide."]}),"\n",(0,i.jsxs)(n.p,{children:["To pin container versions to a specific release other than ",(0,i.jsx)(n.code,{children:"latest"}),", set the ",(0,i.jsx)(n.code,{children:"OPENRAG_VERSION"})," in your ",(0,i.jsx)(n.code,{children:".env"})," file:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"OPENRAG_VERSION=0.1.33\n"})}),"\n",(0,i.jsxs)(n.p,{children:["For more information, see ",(0,i.jsx)(n.a,{href:"/reference/configuration#system-settings",children:"System settings environment variables"}),"."]}),"\n",(0,i.jsx)(n.h2,{id:"diagnostics",children:"Diagnostics"}),"\n",(0,i.jsxs)(n.p,{children:["The ",(0,i.jsx)(n.strong,{children:"Diagnostics"})," menu provides health monitoring for your container runtimes and monitoring of your OpenSearch security."]}),"\n",(0,i.jsx)(n.h2,{id:"reinstall",children:"Reinstall OpenRAG"}),"\n",(0,i.jsx)(n.p,{children:"To reinstall OpenRAG with a completely fresh setup:"}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Reset your containers using the ",(0,i.jsx)(n.strong,{children:"Reset"})," button in the ",(0,i.jsx)(n.a,{href:"#status",children:"TUI status"})," menu.\nThis removes all containers, volumes, and data."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["Optional: Delete your project's ",(0,i.jsx)(n.code,{children:".env"})," file.\nThe Reset operation doesn't remove your project's ",(0,i.jsx)(n.code,{children:".env"})," file, so your passwords, API keys, and OAuth settings can be preserved.\nIf you delete the ",(0,i.jsx)(n.code,{children:".env"})," file, run the ",(0,i.jsx)(n.a,{href:"#setup",children:"Set up OpenRAG with the TUI"})," process again to create a new configuration."]}),"\n"]}),"\n",(0,i.jsxs)(n.li,{children:["\n",(0,i.jsxs)(n.p,{children:["In the TUI Setup menu, follow these steps from ",(0,i.jsx)(n.a,{href:"#setup",children:"Basic Setup"}),":"]}),"\n",(0,i.jsxs)(n.ol,{children:["\n",(0,i.jsxs)(n.li,{children:["Click ",(0,i.jsx)(n.strong,{children:"Start All Services"})," to pull container images and start them."]}),"\n",(0,i.jsxs)(n.li,{children:["Under ",(0,i.jsx)(n.strong,{children:"Native Services"}),", click ",(0,i.jsx)(n.strong,{children:"Start"})," to start the Docling service."]}),"\n",(0,i.jsxs)(n.li,{children:["Click ",(0,i.jsx)(n.strong,{children:"Open App"})," to open the OpenRAG application."]}),"\n",(0,i.jsxs)(n.li,{children:["Continue with ",(0,i.jsx)(n.a,{href:"#application-onboarding",children:"application onboarding"}),"."]}),"\n"]}),"\n"]}),"\n"]})]})}function j(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(x,{...e})}):x(e)}},5689:(e,n,s)=>{s.d(n,{A:()=>r});const r=s.p+"assets/images/OpenRAG_TUI_2025-09-10T13_04_11_757637-9441c53ba39162a88ac6c11cbeaed0e0.svg"}}]); \ No newline at end of file diff --git a/assets/js/e633a5ea.6a095ec9.js b/assets/js/e633a5ea.6a095ec9.js new file mode 100644 index 00000000..2d986f1d --- /dev/null +++ b/assets/js/e633a5ea.6a095ec9.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[9172],{9359:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>i,default:()=>h,frontMatter:()=>o,metadata:()=>s,toc:()=>l});const s=JSON.parse('{"id":"get-started/what-is-openrag","title":"What is OpenRAG?","description":"OpenRAG is an open-source package for building agentic RAG systems that integrates with a wide range of orchestration tools, vector databases, and LLM providers.","source":"@site/docs/get-started/what-is-openrag.mdx","sourceDirName":"get-started","slug":"/","permalink":"/","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/what-is-openrag.mdx","tags":[],"version":"current","frontMatter":{"title":"What is OpenRAG?","slug":"/","hide_table_of_contents":true},"sidebar":"tutorialSidebar","next":{"title":"Quickstart","permalink":"/quickstart"}}');var r=t(4848),a=t(8453);const o={title:"What is OpenRAG?",slug:"/",hide_table_of_contents:!0},i=void 0,c={},l=[{value:"OpenRAG architecture",id:"openrag-architecture",level:2}];function d(e){const n={a:"a",admonition:"admonition",h2:"h2",li:"li",mermaid:"mermaid",p:"p",strong:"strong",ul:"ul",...(0,a.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.p,{children:"OpenRAG is an open-source package for building agentic RAG systems that integrates with a wide range of orchestration tools, vector databases, and LLM providers."}),"\n",(0,r.jsx)(n.p,{children:"OpenRAG connects and amplifies three popular, proven open-source projects into one powerful platform:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://docs.langflow.org",children:"Langflow"}),": Langflow is a versatile tool for building and deploying AI agents and MCP servers. It supports all major LLMs, vector databases, and a growing library of AI tools."]}),"\n",(0,r.jsx)(n.p,{children:"OpenRAG uses several built-in flows, and it provides full access to all Langflow features through the embedded Langflow visual editor."}),"\n",(0,r.jsx)(n.p,{children:"By customizing the built-in flows or creating your own flows, every part of the OpenRAG stack interchangeable. You can modify any aspect of the flows from basic settings, like changing the language model, to replacing entire components. You can also write your own custom Langflow components, integrate MCP servers, call APIs, and leverage any other functionality provided by Langflow."}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"}),": OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data.\nIt provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support."]}),"\n",(0,r.jsx)(n.p,{children:"OpenRAG uses OpenSearch as the underlying vector database for storing and retrieving your documents and associated vector data (embeddings). You can ingest documents from a variety of sources, including your local filesystem and OAuth authenticated connectors to popular cloud storage services."}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.a,{href:"https://docling-project.github.io/docling/",children:"Docling"}),": Docling simplifies document processing, supports many file formats and advanced PDF parsing, and provides seamless integrations with the generative AI ecosystem."]}),"\n",(0,r.jsx)(n.p,{children:"OpenRAG uses Docling to parse and chunk documents that are stored in your OpenSearch knowledge base."}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.admonition,{type:"tip",children:(0,r.jsxs)(n.p,{children:["Ready to get started? Try the ",(0,r.jsx)(n.a,{href:"/quickstart",children:"quickstart"})," to install OpenRAG and start exploring in minutes."]})}),"\n",(0,r.jsx)(n.h2,{id:"openrag-architecture",children:"OpenRAG architecture"}),"\n",(0,r.jsxs)(n.p,{children:["OpenRAG deploys and orchestrates a lightweight, container-based architecture that combines ",(0,r.jsx)(n.strong,{children:"Langflow"}),", ",(0,r.jsx)(n.strong,{children:"OpenSearch"}),", and ",(0,r.jsx)(n.strong,{children:"Docling"})," into a cohesive RAG platform."]}),"\n",(0,r.jsx)(n.mermaid,{value:"---\nconfig:\n theme: 'base'\n themeVariables:\n lineColor: '#2e8555'\n---\nflowchart TD\n subgraph Containers\n backend[OpenRAG backend] --\x3e langflow[Langflow]\n langflow <--\x3e opensearch[OpenSearch]\n backend <--\x3e frontend[OpenRAG frontend]\n end\n subgraph local [Local services]\n docling[Docling Serve]\n end\n subgraph ext [External connectors]\n drive1[Google Drive]\n drive2[OneDrive]\n drive3[SharePoint]\n drive4[Others]\n end\n local --\x3e backend\n ext --\x3e backend"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.strong,{children:"OpenRAG backend"}),": The central orchestration service that coordinates all other components."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:[(0,r.jsx)(n.strong,{children:"Langflow"}),": This container runs a Langflow instance. 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It supports all major LLMs, vector databases, and a growing library of AI tools."]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"}),": OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data."]}),"\n"]}),"\n",(0,s.jsxs)(n.li,{children:["\n",(0,s.jsxs)(n.p,{children:[(0,s.jsx)(n.a,{href:"https://docling-project.github.io/docling/",children:"Docling"}),": Docling simplifies document processing, parsing diverse formats \u2014 including advanced PDF understanding \u2014 and providing seamless integrations with the gen AI ecosystem."]}),"\n"]}),"\n"]}),"\n",(0,s.jsx)(n.p,{children:"OpenRAG builds on Langflow's familiar interface while adding OpenSearch for vector storage and Docling for simplified document parsing. It uses opinionated flows that serve as ready-to-use recipes for ingestion, retrieval, and generation from familiar sources like Google Drive, OneDrive, and SharePoint."}),"\n",(0,s.jsx)(n.p,{children:"What's more, every part of the stack is interchangeable: You can write your own custom components in Python, try different language models, and customize your flows to build a personalized agentic RAG system."}),"\n",(0,s.jsx)(n.admonition,{type:"tip",children:(0,s.jsxs)(n.p,{children:["Ready to get started? 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OpenRAG","description":"This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG.","source":"@site/docs/support/troubleshoot.mdx","sourceDirName":"support","slug":"/support/troubleshoot","permalink":"/support/troubleshoot","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/support/troubleshoot.mdx","tags":[],"version":"current","frontMatter":{"title":"Troubleshoot OpenRAG","slug":"/support/troubleshoot"},"sidebar":"tutorialSidebar","previous":{"title":"Environment variables","permalink":"/reference/configuration"}}');var o=s(4848),a=s(8453),i=s(1470),l=s(9365);const t={title:"Troubleshoot OpenRAG",slug:"/support/troubleshoot"},c=void 0,d={},h=[{value:"OpenSearch fails to start",id:"opensearch-fails-to-start",level:2},{value:"OpenRAG fails to start from the TUI with operation not supported",id:"openrag-fails-to-start-from-the-tui-with-operation-not-supported",level:2},{value:"OpenRAG installation fails with unable to get local issuer certificate",id:"openrag-installation-fails-with-unable-to-get-local-issuer-certificate",level:2},{value:"Langflow connection issues",id:"langflow-connection-issues",level:2},{value:"Container out of memory errors",id:"container-out-of-memory-errors",level:2},{value:"Memory issue with Podman on macOS",id:"memory-issue-with-podman-on-macos",level:2},{value:"Port conflicts",id:"port-conflicts",level:2},{value:"OCR ingestion fails (easyocr not installed)",id:"ocr-ingestion-fails-easyocr-not-installed",level:2},{value:"Upgrade fails due to Langflow container already exists",id:"langflow-container-already-exists-during-upgrade",level:2}];function p(e){const n={a:"a",admonition:"admonition",code:"code",h2:"h2",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,a.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsx)(n.p,{children:"This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG."}),"\n",(0,o.jsx)(n.h2,{id:"opensearch-fails-to-start",children:"OpenSearch fails to start"}),"\n",(0,o.jsxs)(n.p,{children:["Check that ",(0,o.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})," set in ",(0,o.jsx)(n.a,{href:"/reference/configuration",children:"Environment variables"})," meets requirements.\nThe password must contain at least 8 characters, and must contain at least one uppercase letter, one lowercase letter, one digit, and one special character that is strong."]}),"\n",(0,o.jsx)(n.h2,{id:"openrag-fails-to-start-from-the-tui-with-operation-not-supported",children:"OpenRAG fails to start from the TUI with operation not 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OpenRAG."]}),"\n",(0,o.jsx)(n.h2,{id:"memory-issue-with-podman-on-macos",children:"Memory issue with Podman on macOS"}),"\n",(0,o.jsx)(n.p,{children:"If you're using Podman on macOS, you might need to increase VM memory on your Podman machine.\nThis example increases the machine size to 8 GB of RAM, which should be sufficient to run OpenRAG."}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:"podman machine stop\npodman machine rm\npodman machine init --memory 8192 # 8 GB example\npodman machine start\n"})}),"\n",(0,o.jsx)(n.h2,{id:"port-conflicts",children:"Port conflicts"}),"\n",(0,o.jsx)(n.p,{children:"Ensure ports 3000, 7860, 8000, 9200, 5601 are available."}),"\n",(0,o.jsx)(n.h2,{id:"ocr-ingestion-fails-easyocr-not-installed",children:"OCR ingestion fails (easyocr not installed)"}),"\n",(0,o.jsxs)(n.p,{children:["If Docling ingestion fails with an OCR-related error and mentions ",(0,o.jsx)(n.code,{children:"easyocr"})," is missing, this is likely due to a stale ",(0,o.jsx)(n.code,{children:"uv"})," cache."]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.code,{children:"easyocr"})," is already included as a dependency in OpenRAG's ",(0,o.jsx)(n.code,{children:"pyproject.toml"}),". Project-managed installations using ",(0,o.jsx)(n.code,{children:"uv sync"})," and ",(0,o.jsx)(n.code,{children:"uv run"})," always sync dependencies directly from your ",(0,o.jsx)(n.code,{children:"pyproject.toml"}),", so they should have ",(0,o.jsx)(n.code,{children:"easyocr"})," installed."]}),"\n",(0,o.jsxs)(n.p,{children:["If you're running OpenRAG with ",(0,o.jsx)(n.code,{children:"uvx openrag"}),", ",(0,o.jsx)(n.code,{children:"uvx"})," creates a cached, ephemeral environment that doesn't modify your project. This cache can become stale."]}),"\n",(0,o.jsxs)(n.p,{children:["On macOS, this cache directory is typically a user cache directory such as ",(0,o.jsx)(n.code,{children:"/Users/USER_NAME/.cache/uv"}),"."]}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"To clear the uv cache, run:"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:"uv cache clean\n"})}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Start OpenRAG:"}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:"uvx openrag\n"})}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(n.p,{children:["If you do not need OCR, you can disable OCR-based processing in your ingestion settings to avoid requiring ",(0,o.jsx)(n.code,{children:"easyocr"}),"."]}),"\n",(0,o.jsx)(n.h2,{id:"langflow-container-already-exists-during-upgrade",children:"Upgrade fails due to Langflow container already 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the upgrade."}),"\n",(0,o.jsx)(n.admonition,{type:"warning",children:(0,o.jsxs)(n.p,{children:["This is a destructive operation that completely resets your OpenRAG containers and removes all OpenRAG data, including OpenSearch data, uploaded documents, and authentication details.\nYour ",(0,o.jsx)(n.code,{children:".env"})," file is preserved, so your configuration settings remain intact, but all other data is lost."]})}),"\n",(0,o.jsxs)(n.p,{children:["To reset your installation, stop your containers, and then completely remove them.\nAfter removing the containers, retry the upgrade in the OpenRAG TUI by clicking ",(0,o.jsx)(n.strong,{children:"Status"})," and then ",(0,o.jsx)(n.strong,{children:"Upgrade"}),"."]}),"\n",(0,o.jsxs)(i.A,{groupId:"Container software",children:[(0,o.jsx)(l.A,{value:"Podman",label:"Podman",children:(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Stop all running 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+

Chat in OpenRAG

After you upload documents to your knowledge base, you can use the OpenRAG Chat feature to interact with your knowledge through natural language queries.

+
tip

Try chatting, uploading documents, and modifying chat settings in the quickstart.

+

OpenRAG OpenSearch Agent flow​

+

When you use the OpenRAG Chat, the OpenRAG OpenSearch Agent flow runs in the background to retrieve relevant information from your knowledge base and generate a response.

+

If you inspect the flow in Langflow, you'll see that it is comprised of eight components that work together to ingest chat messages, retrieve relevant information from your knowledge base, and then generate responses.

+

OpenRAG Open Search Agent Flow

+
    +
  • +

    Chat Input component: This component starts the flow when it receives a chat message. It is connected to the Agent component's Input port. +When you use the OpenRAG Chat, your chat messages are passed to the Chat Input component, which then sends them to the Agent component for processing.

    +
    • +
  • +

    Agent component: This component orchestrates the entire flow by processing chat messages, searching the knowledge base, and organizing the retrieved information into a cohesive response. +The agent's general behavior is defined by the prompt in the Agent Instructions field and the model connected to the Language Model port. +One or more specialized tools can be attached to the Tools port to extend the agent's capabilities. In this case, there are two tools: MCP Tools and OpenSearch.

    +

    The Agent component is the star of this flow because it powers decision making, tool calling, and an LLM-driven conversational experience.

    +
    How do agents work?

    Agents extend Large Language Models (LLMs) by integrating tools, which are functions that provide additional context and enable autonomous task execution. These integrations make agents more specialized and powerful than standalone LLMs.

    Whereas an LLM might generate acceptable, inert responses to general queries and tasks, an agent can leverage the integrated context and tools to provide more relevant responses and even take action. For example, you might create an agent that can access your company's documentation, repositories, and other resources to help your team with tasks that require knowledge of your specific products, customers, and code.

    Agents use LLMs as a reasoning engine to process input, determine which actions to take to address the query, and then generate a response. The response could be a typical text-based LLM response, or it could involve an action, like editing a file, running a script, or calling an external API.

    In an agentic context, tools are functions that the agent can run to perform tasks or access external resources. A function is wrapped as a Tool object with a common interface that the agent understands. Agents become aware of tools through tool registration, which is when the agent is provided a list of available tools typically at agent initialization. The Tool object's description tells the agent what the tool can do so that it can decide whether the tool is appropriate for a given request.

    +
    • +
  • +

    Language Model component: Connected to the Agent component's Language Model port, this component provides the base language model driver for the agent. The agent cannot function without a model because the model is used for general knowledge, reasoning, and generating responses.

    +

    Different models can change the style and content of the agent's responses, and some models might be better suited for certain tasks than others. If the agent doesn't seem to be handling requests well, try changing the model to see how the responses change. For example, fast models might be good for simple queries, but they might not have the depth of reasoning for complex, multi-faceted queries.

    +
    • +
  • +

    MCP Tools component: Connected to the Agent component's Tools port, this component can be used to access any Model Context Protocol (MCP) server and the MCP tools provided by that server. In this case, your OpenRAG Langflow instance's Starter Project is the MCP server, and the OpenSearch URL Ingestion flow is the MCP tool. +This flow fetches content from URLs, and then stores the content in your OpenRAG OpenSearch knowledge base. By serving this flow as an MCP tool, the agent can selectively call this tool if a URL is detected in the chat input.

    +
    • +
  • +

    OpenSearch component: Connected to the Agent component's Tools port, this component lets the agent search your OpenRAG OpenSearch knowledge base. The agent might not use this database for every request; the agent uses this connection only if it decides that documents in your knowledge base are relevant to your query.

    +
    • +
  • +

    Embedding Model component: Connected to the OpenSearch component's Embedding port, this component generates embeddings from chat input that are used in similarity search to find content in your knowledge base that is relevant to the chat input. The agent uses this information to generate context-aware responses that are specialized for your data.

    +

    It is critical that the embedding model used here matches the embedding model used when you upload documents to your knowledge base. Mismatched models and dimensions can degrade the quality of similarity search results causing the agent to retrieve irrelevant documents from your knowledge base.

    +
    • +
  • +

    Text Input component: Connected to the OpenSearch component's Search Filters port, this component is populated with a Langflow global variable named OPENRAG-QUERY-FILTER. If a global or chat-level knowledge filter is set, then the variable contains the filter expression, which limits the documents that the agent can access in the knowledge base. +If no knowledge filter is set, then the OPENRAG-QUERY-FILTER variable is empty, and the agent can access all documents in the knowledge base.

    +
    • +
  • +

    Chat Output component: Connected to the Agent component's Output port, this component returns the agent's generated response as a chat message.

    +
    • +
+

Nudges​

+

When you use the OpenRAG Chat, the OpenRAG OpenSearch Nudges flow runs in the background to pull additional context from your knowledge base and chat history.

+

Nudges appear as prompts in the chat. +Click a nudge to accept it and provide the nudge's context to the OpenRAG Chat agent (the OpenRAG OpenSearch Agent flow).

+

Like OpenRAG's other built-in flows, you can inspect the flow in Langflow, and you can customize it if you want to change the nudge behavior.

+

Upload documents to the chat​

+

When using the OpenRAG Chat, click in the chat input field to upload a file to the current chat session. +Files added this way are processed and made available to the agent for the current conversation only. +These files aren't stored in the knowledge base permanently.

+

Inspect tool calls and knowledge​

+

During the chat, you'll see information about the agent's process. For more detail, you can inspect individual tool calls. This is helpful for troubleshooting because it shows you how the agent used particular tools. For example, click Function Call: search_documents (tool_call) to view the log of tool calls made by the agent to the OpenSearch component.

+

If documents in your knowledge base seem to be missing or interpreted incorrectly, see Troubleshoot ingestion.

+

If tool calls and knowledge appear normal, but the agent's responses seem off-topic or incorrect, consider changing the agent's language model or prompt, as explained in Inspect and modify flows.

+

Integrate OpenRAG chat into an application​

+

You can integrate OpenRAG flows into your applications using the Langflow API. +To simplify this integration, you can get pre-configured code snippets directly from the embedded Langflow visual editor.

+

The following example demonstrates how to generate and use code snippets for the OpenRAG OpenSearch Agent flow:

+
    +
  1. +

    Open the OpenRAG OpenSearch Agent flow in the Langflow visual editor: From the Chat window, click Settings, click Edit in Langflow, and then click Proceed.

    +
    2. +
  2. +

    Create a Langflow API key, which is a user-specific token required to send requests to the Langflow server. +This key doesn't grant access to OpenRAG.

    +
      +
    1. In the Langflow visual editor, click your user icon in the header, and then select Settings.
      2. +
    2. Click Langflow API Keys, and then click Add New.
      3. +
    3. Name your key, and then click Create API Key.
      4. +
    4. Copy the API key and store it securely.
      5. +
    5. Exit the Langflow Settings page to return to the visual editor.
      6. +
    +
    3. +
  3. +

    Click Share, and then select API access to get pregenerated code snippets that call the Langflow API and run the flow.

    +

    These code snippets construct API requests with your Langflow server URL (LANGFLOW_SERVER_ADDRESS), the flow to run (FLOW_ID), required headers (LANGFLOW_API_KEY, Content-Type), and a payload containing the required inputs to run the flow, including a default chat input message.

    +

    In production, you would modify the inputs to suit your application logic. For example, you could replace the default chat input message with dynamic user input.

    +
    import requests
    import os
    import uuid

    api_key = 'LANGFLOW_API_KEY'
    url = "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID"  # The complete API endpoint URL for this flow

    # Request payload configuration
    payload = {
        "output_type": "chat",
        "input_type": "chat",
        "input_value": "hello world!"
    }
    payload["session_id"] = str(uuid.uuid4())

    headers = {"x-api-key": api_key}

    try:
        # Send API request
        response = requests.request("POST", url, json=payload, headers=headers)
        response.raise_for_status()  # Raise exception for bad status codes

        # Print response
        print(response.text)

    except requests.exceptions.RequestException as e:
        print(f"Error making API request: {e}")
    except ValueError as e:
        print(f"Error parsing response: {e}")
    +
    4. +
  4. +

    Copy your preferred snippet, and then run it:

    +
      +
    • Python: Paste the snippet into a .py file, save it, and then run it with python filename.py.
      • +
    • TypeScript: Paste the snippet into a .ts file, save it, and then run it with ts-node filename.ts.
      • +
    • curl: Paste and run snippet directly in your terminal.
      • +
    +
    5. +
+

If the request is successful, the response includes many details about the flow run, including the session ID, inputs, outputs, components, durations, and more.

+

In production, you won't pass the raw response to the user in its entirety. +Instead, you extract and reformat relevant fields for different use cases, as demonstrated in the Langflow quickstart. +For example, you could pass the chat output text to a front-end user-facing application, and store specific fields in logs and backend data stores for monitoring, chat history, or analytics. +You could also pass the output from one flow as input to another flow.

  • + © 2025 OpenRAG +
+ + \ No newline at end of file diff --git a/docker/index.html b/docker/index.html index b1856d42..0ff4700d 100644 --- a/docker/index.html +++ b/docker/index.html @@ -4,14 +4,14 @@ Install OpenRAG containers | OpenRAG - - + + -

Install OpenRAG containers

OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments:

+

Install OpenRAG containers

OpenRAG has two Docker Compose files. Both files deploy the same applications and containers locally, but they are for different environments:

  • docker-compose.yml is an OpenRAG deployment with GPU support for accelerated AI processing. This Docker Compose file requires an NVIDIA GPU with CUDA support.

    @@ -61,7 +61,7 @@ Instead, install OpenRAG on your base OS or a non-nested Linux VM.

  • Prepare model providers and credentials.

    -

    During Application Onboarding, you must select language model and embedding model providers. +

    During application onboarding, you must select language model and embedding model providers. If your chosen provider offers both types, you can use the same provider for both selections. If your provider offers only one type, such as Anthropic, you must select two providers.

    Gather the credentials and connection details for your chosen model providers before starting onboarding:

    @@ -100,7 +100,7 @@ The OPENSEARCH_PASSWORD value must be set. OPENSEARCH_PASSWORD can be automatically generated when using the TUI, but for a Docker Compose installation, you can set it manually instead. To generate an OpenSearch admin password, see the OpenSearch documentation.

    The following values are optional:

    OPENAI_API_KEY=your_openai_api_key
    LANGFLOW_SECRET_KEY=your_secret_key
    -

    OPENAI_API_KEY is optional. You can provide it during Application Onboarding or choose a different model provider. If you want to set it in your .env file, you can find your OpenAI API key in your OpenAI account.

    +

    OPENAI_API_KEY is optional. You can provide it during application onboarding or choose a different model provider. If you want to set it in your .env file, you can find your OpenAI API key in your OpenAI account.

    LANGFLOW_SECRET_KEY is optional. Langflow will auto-generate it if not set. For more information, see the Langflow documentation.

    The following Langflow configuration values are optional but important to consider:

    LANGFLOW_SUPERUSER=admin
    LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
    @@ -136,17 +136,20 @@ This enables -

    Continue with Application Onboarding.

    +

    Continue with application onboarding.

    • To stop docling serve when you're done with your OpenRAG deployment, run:

    uv run python scripts/docling_ctl.py stop

    Application onboarding​

    -

    The first time you start OpenRAG, whether using the TUI or a .env file, you must complete application onboarding.

    -
    warning

    Most values from onboarding can be changed later in the OpenRAG Settings page, but there are important restrictions.

    The language model provider and embeddings model provider can only be selected at onboarding. -To change your provider selection later, you must reinstall OpenRAG.

    You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embeddings model.

    -

    Choose one LLM provider and complete these steps:

    -
    info

    Anthropic does not provide embedding models. If you select Anthropic for your language model, you must then select a different provider for embeddings.

      +

      The first time you start OpenRAG, regardless of how you installed it, you must complete application onboarding.

      +

      Some of these variables, such as the embedding models, can be changed seamlessly after onboarding. +Others are immutable and require you to destroy and recreate the OpenRAG containers. +For more information, see Environment variables.

      +

      You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embeddings model. +Additionally, you can set multiple embedding models.

      +

      You only need to complete onboarding for your preferred providers.

      +
      info

      Anthropic doesn't provide embedding models. If you select Anthropic for your language model, you must select a different provider for embeddings.

      1. Enable Use environment Anthropic API key to automatically use your key from the .env file. Alternatively, paste an Anthropic API key into the field.
      2. Under Advanced settings, select your Language Model.
        3. @@ -173,7 +176,7 @@ These values are found in your IBM watsonx deployment.
      3. To complete the onboarding tasks, click What is OpenRAG, and then click Add a Document. Alternatively, click Skip overview.
      4. Continue with the Quickstart.
        5. -
    • +
      docker compose down --volumes --remove-orphans --rmi local
      docker system prune -f
    • © 2025 OpenRAG
    diff --git a/index.html b/index.html index e7c4f95b..8fb7d627 100644 --- a/index.html +++ b/index.html @@ -4,47 +4,50 @@ What is OpenRAG? | OpenRAG - - + + -

    What is OpenRAG?

    OpenRAG is an open-source package for building agentic RAG systems that integrates with a wide range of orchestration tools, vector databases, and LLM providers.

    +

    What is OpenRAG?

    OpenRAG is an open-source package for building agentic RAG systems that integrates with a wide range of orchestration tools, vector databases, and LLM providers.

    OpenRAG connects and amplifies three popular, proven open-source projects into one powerful platform:

    • Langflow: Langflow is a versatile tool for building and deploying AI agents and MCP servers. It supports all major LLMs, vector databases, and a growing library of AI tools.

      +

      OpenRAG uses several built-in flows, and it provides full access to all Langflow features through the embedded Langflow visual editor.

      +

      By customizing the built-in flows or creating your own flows, every part of the OpenRAG stack interchangeable. You can modify any aspect of the flows from basic settings, like changing the language model, to replacing entire components. You can also write your own custom Langflow components, integrate MCP servers, call APIs, and leverage any other functionality provided by Langflow.

    • -

      OpenSearch: OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data.

      +

      OpenSearch: OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data. +It provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support.

      +

      OpenRAG uses OpenSearch as the underlying vector database for storing and retrieving your documents and associated vector data (embeddings). You can ingest documents from a variety of sources, including your local filesystem and OAuth authenticated connectors to popular cloud storage services.

    • -

      Docling: Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem.

      +

      Docling: Docling simplifies document processing, supports many file formats and advanced PDF parsing, and provides seamless integrations with the generative AI ecosystem.

      +

      OpenRAG uses Docling to parse and chunk documents that are stored in your OpenSearch knowledge base.

    -

    OpenRAG builds on Langflow's familiar interface while adding OpenSearch for vector storage and Docling for simplified document parsing. It uses opinionated flows that serve as ready-to-use recipes for ingestion, retrieval, and generation from familiar sources like Google Drive, OneDrive, and SharePoint.

    -

    What's more, every part of the stack is interchangeable: You can write your own custom components in Python, try different language models, and customize your flows to build a personalized agentic RAG system.

    tip

    Ready to get started? Try the quickstart to install OpenRAG and start exploring in minutes.

    OpenRAG architecture​

    OpenRAG deploys and orchestrates a lightweight, container-based architecture that combines Langflow, OpenSearch, and Docling into a cohesive RAG platform.

    • -

      The OpenRAG Backend is the central orchestration service that coordinates all other components.

      +

      OpenRAG backend: The central orchestration service that coordinates all other components.

    • -

      Langflow provides a visual workflow engine for building AI agents, and connects to OpenSearch for vector storage and retrieval.

      +

      Langflow: This container runs a Langflow instance. It provides the embedded Langflow visual editor for editing and creating flow, and it connects to the OpenSearch container for vector storage and retrieval.

    • -

      Docling Serve is a local document processing service managed by the OpenRAG Backend.

      +

      Docling Serve: This is a local document processing service managed by the OpenRAG backend.

    • -

      External connectors integrate third-party cloud storage services through OAuth authenticated connections to the OpenRAG Backend, allowing synchronization of external storage with your OpenSearch knowledge base.

      +

      External connectors: Integrate third-party cloud storage services with OAuth authenticated connectors to the OpenRAG backend, allowing you to load documents from external storage to your OpenSearch knowledge base.

    • -

      The OpenRAG Frontend provides the user interface for interacting with the platform.

      +

      OpenRAG frontend: Provides the user interface for interacting with the OpenRAG platform.

    • © 2025 OpenRAG diff --git a/ingestion/index.html b/ingestion/index.html index 1cb1f973..c4da25a5 100644 --- a/ingestion/index.html +++ b/ingestion/index.html @@ -3,91 +3,287 @@ -Docling in OpenRAG | OpenRAG - - +Ingest knowledge | OpenRAG + + -

      Docling in OpenRAG

      OpenRAG uses Docling for document ingestion. -More specifically, OpenRAG uses Docling Serve, which starts a docling serve process on your local machine and runs Docling ingestion through an API service.

      -

      Docling ingests documents from your local machine or OAuth connectors, splits them into chunks, and stores them as separate, structured documents in the OpenSearch documents index.

      -

      OpenRAG chose Docling for its support for a wide variety of file formats, high performance, and advanced understanding of tables and images.

      -

      To modify OpenRAG's ingestion settings, including the Docling settings and ingestion flows, click 2" aria-hidden="true"/> Settings.

      -

      Knowledge ingestion settings​

      -

      These settings configure the Docling ingestion parameters.

      -

      OpenRAG will warn you if docling serve is not running. -To start or stop docling serve or any other native services, in the TUI main menu, click Start Native Services or Stop Native Services.

      -

      Embedding model determines which AI model is used to create vector embeddings. The default is the OpenAI text-embedding-3-small model.

      -

      Chunk size determines how large each text chunk is in number of characters. -Larger chunks yield more context per chunk, but can include irrelevant information. Smaller chunks yield more precise semantic search, but can lack context. -The default value of 1000 characters provides a good starting point that balances these considerations.

      -

      Chunk overlap controls the number of characters that overlap over chunk boundaries. -Use larger overlap values for documents where context is most important, and use smaller overlap values for simpler documents, or when optimization is most important. -The default value of 200 characters of overlap with a chunk size of 1000 (20% overlap) is suitable for general use cases. Decrease the overlap to 10% for a more efficient pipeline, or increase to 40% for more complex documents.

      -

      Table Structure enables Docling's DocumentConverter tool for parsing tables. Instead of treating tables as plain text, tables are output as structured table data with preserved relationships and metadata. Table Structure is enabled by default.

      -

      OCR enables or disabled OCR processing when extracting text from images and scanned documents. -OCR is disabled by default. This setting is best suited for processing text-based documents as quickly as possible with Docling's DocumentConverter. Images are ignored and not processed.

      -

      Enable OCR when you are processing documents containing images with text that requires extraction, or for scanned documents. Enabling OCR can slow ingestion performance.

      -

      If OpenRAG detects that the local machine is running on macOS, OpenRAG uses the ocrmac OCR engine. Other platforms use easyocr.

      -

      Picture descriptions adds image descriptions generated by the SmolVLM-256M-Instruct model to OCR processing. Enabling picture descriptions can slow ingestion performance.

      -

      Knowledge ingestion flows​

      -

      Flows in Langflow are functional representations of application workflows, with multiple component nodes connected as single steps in a workflow.

      -

      The OpenSearch Ingestion flow is the default knowledge ingestion flow in OpenRAG: when you Add Knowledge in OpenRAG, you run the OpenSearch Ingestion flow in the background. The flow ingests documents using Docling Serve to import and process documents.

      -

      This flow contains ten components connected together to process and store documents in your knowledge base.

      +

      Ingest knowledge

      Upload documents to your OpenRAG OpenSearch instance to populate your knowledge base with unique content, such as your own company documents, research papers, or websites. +Documents are processed through OpenRAG's knowledge ingestion flows with Docling.

      +

      OpenRAG can ingest knowledge from direct file uploads, URLs, and OAuth authenticated connectors.

      +

      Knowledge ingestion is powered by OpenRAG's built-in knowledge ingestion flows that use Docling to process documents before storing the documents in your OpenSearch database. +During ingestion, documents are broken into smaller chunks of content that are then embedded using your selected embedding model. +Then, the chunks, embeddings, and associated metadata (which connects chunks of the same document) are stored in your OpenSearch database.

      +

      To modify chunking behavior and other ingestion settings, see Knowledge ingestion settings and Inspect and modify flows.

      +

      Ingest local files and folders​

      +

      You can upload files and folders from your local machine to your knowledge base:

      +
        +
      1. +

        Click Knowledge to view your OpenSearch knowledge base.

        +
        2. +
      2. +

        Click Add Knowledge to add your own documents to your OpenRAG knowledge base.

        +
        3. +
      3. +

        To upload one file, click File. To upload all documents in a folder, click Folder.

        +

        The default path is the ./documents subdirectory in your OpenRAG installation directory. +To change this path, see Set the local documents path.

        +
        4. +
      +

      The selected files are processed in the background through the OpenSearch Ingestion flow.

      +
      About the OpenSearch Ingestion flow

      When you upload documents locally or with OAuth connectors, the OpenSearch Ingestion flow runs in the background. +By default, this flow uses Docling Serve to import and process documents.

      Like all OpenRAG flows, you can inspect the flow in Langflow, and you can customize it if you want to change the knowledge ingestion settings.

      The OpenSearch Ingestion flow is comprised of several components that work together to process and store documents in your knowledge base:

        +
      • +

        Docling Serve component: Ingests files and processes them by connecting to OpenRAG's local Docling Serve service. The output is DoclingDocument data that contains the extracted text and metadata from the documents.

        +
        • +
      • +

        Export DoclingDocument component: Exports processed DoclingDocument data to Markdown format with image placeholders. This conversion standardizes the document data in preparation for further processing.

        +
        • +
      • +

        DataFrame Operations component: Three of these components run sequentially to add metadata to the document data: filename, file_size, and mimetype.

        +
        • +
      • +

        Split Text component: Splits the processed text into chunks, based on the configured chunk size and overlap settings.

        +
        • +
      • +

        Secret Input component: If needed, four of these components securely fetch the OAuth authentication configuration variables: CONNECTOR_TYPE, OWNER, OWNER_EMAIL, and OWNER_NAME.

        +
        • +
      • +

        Create Data component: Combines the authentication credentials from the Secret Input components into a structured data object that is associated with the document embeddings.

        +
        • +
      • +

        Embedding Model component: Generates vector embeddings using your selected embedding model.

        +
        • +
      • +

        OpenSearch component: Stores the processed documents and their embeddings in a documents index of your OpenRAG OpenSearch knowledge base.

        +

        The default address for the OpenSearch instance is https://opensearch:9200. To change this address, edit the OPENSEARCH_PORT environment variable.

        +

        The default authentication method is JSON Web Token (JWT) authentication. If you edit the flow, you can select basic auth mode, which uses the OPENSEARCH_USERNAME and OPENSEARCH_PASSWORD environment variables for authentication instead of JWT.

        +
        • +
      +

      You can monitor ingestion to see the progress of the uploads and check for failed uploads.

      +

      Ingest local files temporarily​

      +

      When using the OpenRAG Chat, click in the chat input field to upload a file to the current chat session. +Files added this way are processed and made available to the agent for the current conversation only. +These files aren't stored in the knowledge base permanently.

      +

      Ingest files with OAuth connectors​

      +

      OpenRAG can use OAuth authenticated connectors to ingest documents from the following external services:

        -
      • The Docling Serve component processes input documents by connecting to your instance of Docling Serve.
        • -
      • The Export DoclingDocument component exports the processed DoclingDocument to markdown format with image export mode set to placeholder. This conversion makes the structured document data into a standardized format for further processing.
        • -
      • Three DataFrame Operations components sequentially add metadata columns to the document data of filename, file_size, and mimetype.
        • -
      • The Split Text component splits the processed text into chunks with a chunk size of 1000 characters and an overlap of 200 characters.
        • -
      • Four Secret Input components provide secure access to configuration variables: CONNECTOR_TYPE, OWNER, OWNER_EMAIL, and OWNER_NAME. These are runtime variables populated from OAuth login.
        • -
      • The Create Data component combines the secret inputs into a structured data object that will be associated with the document embeddings.
        • -
      • The Embedding Model component generates vector embeddings using OpenAI's text-embedding-3-small model. The embedding model is selected at [Application onboarding] and cannot be changed.
        • -
      • The OpenSearch component stores the processed documents and their embeddings in the documents index at https://opensearch:9200. By default, the component is authenticated with a JWT token, but you can also select basic auth mode, and enter your OpenSearch admin username and password.
        • +
      • AWS S3
        • +
      • Google Drive
        • +
      • Microsoft OneDrive
        • +
      • Microsoft Sharepoint
      -

      All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic. -To modify a flow, click Settings, and click Edit in Langflow. -OpenRAG's visual editor is based on the Langflow visual editor, so you can edit your flows to match your specific use case.

      -

      OpenSearch URL Ingestion flow​

      -

      An additional knowledge ingestion flow is included in OpenRAG, where it is used as an MCP tool by the Open Search Agent flow. -The agent calls this component to fetch web content, and the results are ingested into OpenSearch.

      -

      For more on using MCP clients in Langflow, see MCP clients.
      -To connect additional MCP servers to the MCP client, see Connect to MCP servers from your application.

      -

      Use OpenRAG default ingestion instead of Docling serve​

      -

      If you want to use OpenRAG's built-in pipeline instead of Docling serve, set DISABLE_INGEST_WITH_LANGFLOW=true in Environment variables.

      -

      The built-in pipeline still uses the Docling processor, but uses it directly without the Docling Serve API.

      -

      For more information, see processors.py in the OpenRAG repository.

      -

      Performance expectations​

      +

      These connectors enable seamless ingestion of files from cloud storage to your OpenRAG knowledge base.

      +

      Individual users can connect their personal cloud storage accounts to OpenRAG. Each user must separately authorize OpenRAG to access their own cloud storage. When a user connects a cloud storage service, they are redirected to authenticate with that service provider and grant OpenRAG permission to sync documents from their personal cloud storage.

      +

      Enable OAuth connectors​

      +

      Before users can connect their own cloud storage accounts, you must configure the provider's OAuth credentials in OpenRAG. Typically, this requires that you register OpenRAG as an OAuth application in your cloud provider, and then obtain the app's OAuth credentials, such as a client ID and secret key. +To enable multiple connectors, you must register an app and generate credentials for each provider.

      +

      If you use the TUI to manage your OpenRAG containers, provide OAuth credentials in the Advanced Setup.

      You can do this during installation, or you can add the credentials afterwards:

        +
      1. +

        If OpenRAG is running, stop it: Go to Status, and then click Stop Services.

        +
        2. +
      2. +

        Click Advanced Setup, and then add the OAuth credentials for the cloud storage providers that you want to use:

        + +
        3. +
      3. +

        The OpenRAG TUI presents redirect URIs for your OAuth app that you must register with your OAuth provider. +These are the URLs your OAuth provider will redirect back to after users authenticate and grant access to their cloud storage.

        +
        4. +
      4. +

        Click Save Configuration.

        +

        OpenRAG regenerates the .env file with the given credentials.

        +
        5. +
      5. +

        Click Start Container Services.

        +
        6. +
      +

      Authenticate and ingest files from cloud storage​

      +

      After you start OpenRAG with OAuth connectors enabled, each user is prompted to authenticate with the OAuth provider upon accessing your OpenRAG instance. +Individual authentication is required to access a user's cloud storage from your OpenRAG instance. +For example, if a user navigates to the default OpenRAG URL at http://localhost:3000, they are redirected to the OAuth provider's sign-in page. +After authenticating and granting the required permissions for OpenRAG, the user is redirected back to OpenRAG.

      +

      To ingest knowledge with an OAuth connector, do the following:

      +
        +
      1. +

        Click Knowledge to view your OpenSearch knowledge base.

        +
        2. +
      2. +

        Click Add Knowledge, and then select a storage provider.

        +
        3. +
      3. +

        On the Add Cloud Knowledge page, click Add Files, and then select the files and folders to ingest from the connected storage.

        +
        4. +
      4. +

        Click Ingest Files.

        +
        5. +
      +

      The selected files are processed in the background through the OpenSearch Ingestion flow.

      +
      About the OpenSearch Ingestion flow

      When you upload documents locally or with OAuth connectors, the OpenSearch Ingestion flow runs in the background. +By default, this flow uses Docling Serve to import and process documents.

      Like all OpenRAG flows, you can inspect the flow in Langflow, and you can customize it if you want to change the knowledge ingestion settings.

      The OpenSearch Ingestion flow is comprised of several components that work together to process and store documents in your knowledge base:

        +
      • +

        Docling Serve component: Ingests files and processes them by connecting to OpenRAG's local Docling Serve service. The output is DoclingDocument data that contains the extracted text and metadata from the documents.

        +
        • +
      • +

        Export DoclingDocument component: Exports processed DoclingDocument data to Markdown format with image placeholders. This conversion standardizes the document data in preparation for further processing.

        +
        • +
      • +

        DataFrame Operations component: Three of these components run sequentially to add metadata to the document data: filename, file_size, and mimetype.

        +
        • +
      • +

        Split Text component: Splits the processed text into chunks, based on the configured chunk size and overlap settings.

        +
        • +
      • +

        Secret Input component: If needed, four of these components securely fetch the OAuth authentication configuration variables: CONNECTOR_TYPE, OWNER, OWNER_EMAIL, and OWNER_NAME.

        +
        • +
      • +

        Create Data component: Combines the authentication credentials from the Secret Input components into a structured data object that is associated with the document embeddings.

        +
        • +
      • +

        Embedding Model component: Generates vector embeddings using your selected embedding model.

        +
        • +
      • +

        OpenSearch component: Stores the processed documents and their embeddings in a documents index of your OpenRAG OpenSearch knowledge base.

        +

        The default address for the OpenSearch instance is https://opensearch:9200. To change this address, edit the OPENSEARCH_PORT environment variable.

        +

        The default authentication method is JSON Web Token (JWT) authentication. If you edit the flow, you can select basic auth mode, which uses the OPENSEARCH_USERNAME and OPENSEARCH_PASSWORD environment variables for authentication instead of JWT.

        +
        • +
      +

      You can monitor ingestion to see the progress of the uploads and check for failed uploads.

      +

      Ingest knowledge from URLs​

      +

      The OpenSearch URL Ingestion flow is used to ingest web content from URLs. +This flow isn't directly accessible from the OpenRAG user interface. +Instead, this flow is called by the OpenRAG OpenSearch Agent flow as a Model Context Protocol (MCP) tool. +The agent can call this component to fetch web content from a given URL, and then ingest that content into your OpenSearch knowledge base.

      +

      Like all OpenRAG flows, you can inspect the flow in Langflow, and you can customize it.

      +

      For more information about MCP in Langflow, see the Langflow documentation on MCP clients and MCP servers.

      +

      Monitor ingestion​

      +

      Document ingestion tasks run in the background.

      +

      In the OpenRAG user interface, a badge is shown on Tasks when OpenRAG tasks are active. +Click Tasks to inspect and cancel tasks:

      +
        +
      • +

        Active Tasks: All tasks that are Pending, Running, or Processing. +For each active task, depending on its state, you can find the task ID, start time, duration, number of files processed, and the total files enqueued for processing.

        +
        • +
      • +

        Pending: The task is queued and waiting to start.

        +
        • +
      • +

        Running: The task is actively processing files.

        +
        • +
      • +

        Processing: The task is performing ingestion operations.

        +
        • +
      • +

        Failed: Something went wrong during ingestion, or the task was manually canceled. +For troubleshooting advice, see Troubleshoot ingestion.

        +
        • +
      +

      To stop an active task, click Cancel. Canceling a task stops processing immediately and marks the task as Failed.

      +

      Ingestion performance expectations​

      +

      The following performance test was conducted with Docling Serve.

      On a local VM with 7 vCPUs and 8 GiB RAM, OpenRAG ingested approximately 5.03 GB across 1,083 files in about 42 minutes. This equates to approximately 2.4 documents per second.

      -

      You can generally expect equal or better performance on developer laptops and significantly faster on servers. -Throughput scales with CPU cores, memory, storage speed, and configuration choices such as embedding model, chunk size and overlap, and concurrency.

      -

      This test returned 12 errors (approximately 1.1%). +

      You can generally expect equal or better performance on developer laptops, and significantly faster performance on servers. +Throughput scales with CPU cores, memory, storage speed, and configuration choices, such as the embedding model, chunk size, overlap, and concurrency.

      +

      This test returned 12 error, approximately 1.1 percent of the total files ingested. All errors were file-specific, and they didn't stop the pipeline.

      +
      Ingestion performance test details
        +

      • Ingestion dataset:

        • Total files: 1,083 items mounted
        • Total size on disk: 5,026,474,862 bytes (approximately 5.03 GB)
        +
        • +

      • Hardware specifications:

        • Machine: Apple M4 Pro
        • Podman VM:
            -
          • Name: podman-machine-default
            • -
          • Type: applehv
            • +
          • Name: podman-machine-default
            • +
          • Type: applehv
          • vCPUs: 7
          • Memory: 8 GiB
          • Disk size: 100 GiB
        +
        • +

      • Test results:

        2025-09-24T22:40:45.542190Z /app/src/main.py:231 Ingesting default documents when ready disable_langflow_ingest=False
        2025-09-24T22:40:45.546385Z /app/src/main.py:270 Using Langflow ingestion pipeline for default documents file_count=1082
        ...
        2025-09-24T23:19:44.866365Z /app/src/main.py:351 Langflow ingestion completed success_count=1070 error_count=12 total_files=1082
        -

        Elapsed time: ~42 minutes 15 seconds (2,535 seconds)

        -

        Throughput: ~2.4 documents/second

      • +
        • +
      • +

        Elapsed time: Approximately 42 minutes 15 seconds (2,535 seconds)

        +
        • +
      • +

        Throughput: Approximately 2.4 documents per second

        +
        • +
      +

      Troubleshoot ingestion​

      +

      If an ingestion task fails, do the following:

      +
        +
      • Make sure you are uploading supported file types.
        • +
      • Split excessively large files into smaller files before uploading.
        • +
      • Remove unusual embedded content, such as videos or animations, before uploading. Although Docling can replace some non-text content with placeholders during ingestion, some embedded content might cause errors.
        • +
      +

      If the OpenRAG Chat doesn't seem to use your documents correctly, browse your knowledge base to confirm that the documents are uploaded in full, and the chunks are correct.

      +

      If the documents are present and well-formed, check your knowledge filters. +If a global filter is applied, make sure the expected documents are included in the global filter. +If the global filter excludes any documents, the agent cannot access those documents unless you apply a chat-level filter or change the global filter.

      +

      If text is missing or incorrectly processed, you need to reupload the documents after modifying the ingestion parameters or the documents themselves. +For example:

      +
        +
      • Break combined documents into separate files for better metadata context.
        • +
      • Make sure scanned documents are legible enough for extraction, and enable the OCR option. Poorly scanned documents might require additional preparation or rescanning before ingestion.
        • +
      • Adjust the Chunk Size and Chunk Overlap settings to better suit your documents. Larger chunks provide more context but can include irrelevant information, while smaller chunks yield more precise semantic search but can lack context.
        • +
      +

      For more information about modifying ingestion parameters and flows, see Knowledge ingestion settings.

      +

      See also​

      +
      • © 2025 OpenRAG
      diff --git a/install/index.html b/install/index.html index 8bf5e3d2..2dcac678 100644 --- a/install/index.html +++ b/install/index.html @@ -4,14 +4,14 @@ Install OpenRAG with TUI | OpenRAG - - + + -

      Install OpenRAG with TUI

      Install OpenRAG and then run the OpenRAG Terminal User Interface(TUI) to start your OpenRAG deployment with a guided setup process.

      +

      Install OpenRAG with TUI

      Install OpenRAG and then run the OpenRAG Terminal User Interface(TUI) to start your OpenRAG deployment with a guided setup process.

      The OpenRAG Terminal User Interface (TUI) allows you to set up, configure, and monitor your OpenRAG deployment directly from the terminal.

      OpenRAG TUI Interface

      Instead of starting OpenRAG using Docker commands and manually editing values in the .env file, the TUI walks you through the setup. It prompts for variables where required, creates a .env file for you, and then starts OpenRAG.

      @@ -60,7 +60,7 @@ Instead, install OpenRAG on your base OS or a non-nested Linux VM.

    • Prepare model providers and credentials.

      -

      During Application Onboarding, you must select language model and embedding model providers. +

      During application onboarding, you must select language model and embedding model providers. If your chosen provider offers both types, you can use the same provider for both selections. If your provider offers only one type, such as Anthropic, you must select two providers.

      Gather the credentials and connection details for your chosen model providers before starting onboarding:

      @@ -145,13 +145,11 @@ If your provider offers only one type, such as Anthropic, you must select two pr

      Continue with Set up OpenRAG with the TUI.

      If you encounter errors during installation, see Troubleshoot OpenRAG.

      Set up OpenRAG with the TUI​

      -

      The TUI creates a .env file in your OpenRAG directory root and starts OpenRAG. -If the TUI detects a .env file in the OpenRAG root directory, it sources any variables from the .env file. -If the TUI detects OAuth credentials, it enforces the Advanced Setup path.

      -

      Basic Setup can generate all of the required values for OpenRAG. The OpenAI API key is optional and can be provided during onboarding. -Basic Setup does not set up OAuth connections for ingestion from cloud providers. -For OAuth setup, use Advanced Setup. -For information about the difference between basic (no auth) and OAuth in OpenRAG, see Authentication and document access.

        +

        The OpenRAG setup process creates a .env file at the root of your OpenRAG directory, and then starts OpenRAG. +If it detects a .env file in the OpenRAG root directory, it sources any variables from the .env file.

        +

        The TUI offers two setup methods to populate the required values. Basic Setup can generate all minimum required values for OpenRAG. However, Basic Setup doesn't enable OAuth connectors for cloud storage. If you want to use OAuth connectors to upload documents from cloud storage, select Advanced Setup. +If OpenRAG detects OAuth credentials, it recommends Advanced Setup.

        +

        1. To install OpenRAG with Basic Setup, click Basic Setup or press 1.

          2. @@ -181,7 +179,7 @@ When startup is complete, the TUI displays the following:

          Alternatively, in your browser, navigate to localhost:3000.

        2. -

          Continue with Application Onboarding.

          +

          Continue with application onboarding.

        Application onboarding​

        -

        The first time you start OpenRAG, whether using the TUI or a .env file, you must complete application onboarding.

        -
        warning

        Most values from onboarding can be changed later in the OpenRAG Settings page, but there are important restrictions.

        The language model provider and embeddings model provider can only be selected at onboarding. -To change your provider selection later, you must reinstall OpenRAG.

        You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embeddings model.

        -

        Choose one LLM provider and complete these steps:

        -
        info

        Anthropic does not provide embedding models. If you select Anthropic for your language model, you must then select a different provider for embeddings.

          +

          The first time you start OpenRAG, regardless of how you installed it, you must complete application onboarding.

          +

          Some of these variables, such as the embedding models, can be changed seamlessly after onboarding. +Others are immutable and require you to destroy and recreate the OpenRAG containers. +For more information, see Environment variables.

          +

          You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embeddings model. +Additionally, you can set multiple embedding models.

          +

          You only need to complete onboarding for your preferred providers.

          +
          info

          Anthropic doesn't provide embedding models. If you select Anthropic for your language model, you must select a different provider for embeddings.

          1. Enable Use environment Anthropic API key to automatically use your key from the .env file. Alternatively, paste an Anthropic API key into the field.
          2. Under Advanced settings, select your Language Model.
            3. @@ -269,7 +284,7 @@ These values are found in your IBM watsonx deployment.
          3. To complete the onboarding tasks, click What is OpenRAG, and then click Add a Document. Alternatively, click Skip overview.
          4. Continue with the Quickstart.
            5. -
      • diff --git a/knowledge-filters/index.html b/knowledge-filters/index.html new file mode 100644 index 00000000..8f0146c6 --- /dev/null +++ b/knowledge-filters/index.html @@ -0,0 +1,70 @@ + + + + + +Filter knowledge | OpenRAG + + + + + + + +

        Filter knowledge

        OpenRAG's knowledge filters help you organize and manage your knowledge base by creating pre-defined views of your documents.

        +

        Each knowledge filter captures a specific subset of documents based on given a search query and filters.

        +

        Knowledge filters can be used with different OpenRAG functionality. +For example, knowledge filters can help agents access large knowledge bases efficiently by narrowing the scope of documents that you want the agent to use.

        +

        Create a filter​

        +

        To create a knowledge filter, do the following:

        +
          +
        1. +

          Click Knowledge, and then click Knowledge Filters.

          +
          2. +
        2. +

          Enter a Name and Description, and then click Create Filter.

          +

          By default, new filters match all documents in your knowledge base. +Modify the filter to customize it.

          +
          3. +
        3. +

          To modify the filter, click Knowledge, and then click your new filter. You can edit the following settings:

          +
            +
          • Search Query: Enter text for semantic search, such as financial reports from Q4.
            • +
          • Data Sources: Select specific data sources or folders to include.
            • +
          • Document Types: Filter by file type.
            • +
          • Owners: Filter by the user that uploaded the documents.
            • +
          • Connectors: Filter by upload source, such as the local file system or a Google Drive OAuth connector.
            • +
          • Response Limit: Set the maximum number of results to return from the knowledge base. The default is 10.
            • +
          • Score Threshold: Set the minimum relevance score for similarity search. The default score is 0.
            • +
          +
          4. +
        4. +

          To save your changes, click Update Filter.

          +
          5. +
        +

        Apply a filter​

        +
          +
        • +

          Apply a global filter: Click Knowledge, and then enable the toggle next to your preferred filter. Only one filter can be the global filter. The global filter applies to all chat sessions.

          +
          • +
        • +

          Apply a chat filter: In the Chat window, click Filter, and then select the filter to apply. +Chat filters apply to one chat session only.

          +
          • +
        +

        Delete a filter​

        +
          +
        1. +

          Click Knowledge.

          +
          2. +
        2. +

          Click the filter that you want to delete.

          +
          3. +
        3. +

          Click Delete Filter.

          +
          4. +
        • + © 2025 OpenRAG +
        + + \ No newline at end of file diff --git a/knowledge/index.html b/knowledge/index.html index 36b3c47e..b5ff6a2a 100644 --- a/knowledge/index.html +++ b/knowledge/index.html @@ -3,126 +3,123 @@ -OpenSearch in OpenRAG | OpenRAG - - +Configure knowledge | OpenRAG + + -

        OpenSearch in OpenRAG

        OpenRAG uses OpenSearch for its vector-backed knowledge store. -This is a specialized database for storing and retrieving embeddings, which helps your Agent efficiently find relevant information. -OpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support.

        -

        Authentication and document access​

        -

        OpenRAG supports two authentication modes based on how you install OpenRAG, and which mode you choose affects document access.

        -

        No-auth mode (Basic Setup): This mode uses a single anonymous JWT token for OpenSearch authentication, so documents uploaded to the documents index by one user are visible to all other users on the OpenRAG server.

        -

        OAuth mode (Advanced Setup): Each OpenRAG user is granted a JWT token, and each document is tagged with user ownership. Documents are filtered by user ownership, ensuring users only see documents they uploaded or have access to.

        -

        Ingest knowledge​

        -

        OpenRAG supports knowledge ingestion through direct file uploads and OAuth connectors. -To configure the knowledge ingestion pipeline parameters, see Docling Ingestion.

        -

        Direct file ingestion​

        -

        The Knowledge Ingest flow uses Langflow's File component to split and embed files loaded from your local machine into the OpenSearch database.

        -

        The default path to your local folder is mounted from the ./openrag-documents folder in your OpenRAG project directory to the /app/openrag-documents/ directory inside the Docker container. Files added to the host or the container will be visible in both locations. To configure this location, modify the Documents Paths variable in either the TUI's Advanced Setup menu or in the .env used by Docker Compose.

        -

        To load and process a single file from the mapped location, click Add Knowledge, and then click File. -The file is loaded into your OpenSearch database, and appears in the Knowledge page.

        -

        To load and process a directory from the mapped location, click Add Knowledge, and then click Folder. -The files are loaded into your OpenSearch database, and appear in the Knowledge page.

        -

        To add files directly to a chat session, click in the chat input and select the files you want to include. Files added this way are processed and made available to the agent for the current conversation, and are not permanently added to the knowledge base.

        -

        Ingest files through OAuth connectors​

        -

        OpenRAG supports Google Drive, OneDrive, and Sharepoint as OAuth connectors for seamless document synchronization.

        -

        OAuth integration allows individual users to connect their personal cloud storage accounts to OpenRAG. Each user must separately authorize OpenRAG to access their own cloud storage files. When a user connects a cloud service, they are redirected to authenticate with that service provider and grant OpenRAG permission to sync documents from their personal cloud storage.

        -

        Before users can connect their cloud storage accounts, you must configure OAuth credentials in OpenRAG. This requires registering OpenRAG as an OAuth application with a cloud provider and obtaining client ID and secret keys for each service you want to support.

        -

        To add an OAuth connector to OpenRAG, do the following. -This example uses Google OAuth. -If you wish to use another provider, add the secrets to another provider.

        -
          -
        1. If OpenRAG is running, stop it with Status > Stop Services.
          2. -
        2. Click Advanced Setup.
          3. -
        3. Add the OAuth provider's client and secret key in the Advanced Setup menu.
          4. -
        4. Click Save Configuration. -The TUI generates a new .env file with your OAuth values.
          5. -
        5. Click Start Container Services.
          6. -
        -

        The OpenRAG frontend at http://localhost:3000 now redirects to an OAuth callback login page for your OAuth provider. -A successful authentication opens OpenRAG with the required scopes for your connected storage.

        -

        To add knowledge from an OAuth-connected storage provider, do the following:

        -
          -
        1. Click Add Knowledge, and then select the storage provider, for example, Google Drive. -The Add Cloud Knowledge page opens.
          2. -
        2. To add files or folders from the connected storage, click Add Files. -Select the files or folders you want and click Select. -You can select multiple files.
          3. -
        3. When your files are selected, click Ingest Files. -The ingestion process can take some time depending on the size of your documents.
          4. -
        4. When ingestion is complete, your documents are available in the Knowledge screen.
          5. -
        -

        If ingestion fails, click Status to view the logged error.

        -

        Monitor ingestion tasks​

        -

        When you upload files, process folders, or sync documents, OpenRAG processes them as background tasks. -A badge appears on the Tasks icon when there are active tasks running. -To open the Tasks menu, click Tasks.

        -

        Active Tasks shows tasks that are currently processing. -A Pending task is queued and waiting to start, a Running task is actively processing files, and a Processing task is performing ingestion operations. For each active task, you can find the task ID, start time, duration, the number of files processed so far, and the total files.

        -

        You can cancel active tasks by clicking Cancel. Canceling a task stops processing immediately and marks the task as failed.

        -

        Explore knowledge​

        -

        The Knowledge page lists the documents OpenRAG has ingested into the OpenSearch vector database's documents index.

        -

        To explore your current knowledge, click Knowledge. -Click on a document to display the chunks derived from splitting the default documents into the vector database.

        -

        Documents are processed with the default Knowledge Ingest flow, so if you want to split your documents differently, edit the Knowledge Ingest flow.

        -

        All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic. -To modify a flow, click Settings, and click Edit in Langflow. -OpenRAG's visual editor is based on the Langflow visual editor, so you can edit your flows to match your specific use case.

        -

        Create knowledge filters​

        -

        OpenRAG includes a knowledge filter system for organizing and managing document collections. -Knowledge filters are saved search configurations that allow you to create custom views of your document collection. They store search queries, filter criteria, and display settings that can be reused across different parts of OpenRAG.

        -

        Knowledge filters help agents work more efficiently with large document collections by focusing their context within relevant documents sets.

        -

        To create a knowledge filter, do the following:

        -
          -
        1. -

          Click Knowledge, and then click Knowledge Filters. -The Knowledge Filter pane appears.

          -
          2. -
        2. -

          Enter a Name and Description, and then click Create Filter. -A new filter is created with default settings that match all documents.

          -
          3. -
        3. -

          To modify the filter, click Knowledge, and then click your new filter to edit it in the Knowledge Filter pane.

          -

          The following filter options are configurable.

          +

          Configure knowledge

          OpenRAG includes a built-in OpenSearch instance that serves as the underlying datastore for your knowledge (documents). +This specialized database is used to store and retrieve your documents and the associated vector data (embeddings).

          +

          The documents in your OpenSearch knowledge base provide specialized context in addition to the general knowledge available to the language model that you select when you install OpenRAG or edit a flow.

          +

          You can upload documents from a variety of sources to populate your knowledge base with unique content, such as your own company documents, research papers, or websites. +Documents are processed through OpenRAG's knowledge ingestion flows with Docling.

          +

          Then, the OpenRAG Chat can run similarity searches against your OpenSearch database to retrieve relevant information and generate context-aware responses.

          +

          You can configure how documents are ingested and how the Chat interacts with your knowledge base.

          +

          Browse knowledge​

          +

          The Knowledge page lists the documents OpenRAG has ingested into your OpenSearch database, specifically in an OpenSearch index named documents.

          +

          To explore the raw contents of your knowledge base, click Knowledge to get a list of all ingested documents. +Click a document to view the chunks produced from splitting the document during ingestion.

          +

          OpenRAG includes some initial documents about OpenRAG. You can use these documents to ask OpenRAG about itself, and to test the Chat feature before uploading your own documents. +If you delete these documents, you won't be able to ask OpenRAG about itself and it's own functionality. +It is recommended that you keep these documents, and use filters to separate them from your other knowledge.

          +

          OpenSearch authentication and document access​

          +

          When you install OpenRAG, you can choose between two setup modes: Basic Setup and Advanced Setup. +The mode you choose determines how OpenRAG authenticates with OpenSearch and controls access to documents:

            -
          • Search Query: Enter text for semantic search, such as "financial reports from Q4".
            • -
          • Data Sources: Select specific data sources or folders to include.
            • -
          • Document Types: Filter by file type.
            • -
          • Owners: Filter by who uploaded the documents.
            • -
          • Connectors: Filter by connector types, such as local upload or Google Drive.
            • -
          • Response Limit: Set maximum number of results. The default is 10.
            • -
          • Score Threshold: Set minimum relevance score. The default score is 0.
            • +
          • +

            Basic Setup (no-auth mode): If you choose Basic Setup, then OpenRAG is installed in no-auth mode. +This mode uses one, anonymous JWT token for OpenSearch authentication. +There is no differentiation between users. +All users that access your OpenRAG instance can access all documents uploaded to your OpenSearch knowledge base.

            +
            • +
          • +

            Advanced Setup (OAuth mode): If you choose Advanced Setup, then OpenRAG is installed in OAuth mode. +This mode uses a unique JWT token for each OpenRAG user, and each document is tagged with user ownership. Documents are filtered by user owner. +This means users see only the documents that they uploaded or have access to.

            +
          +

          You can enable OAuth mode after installation. +For more information, see Ingest files with OAuth connectors.

          +

          OpenSearch indexes​

          +

          An OpenSearch index is a collection of documents in an OpenSearch database.

          +

          By default, all documents you upload to your OpenRAG knowledge base are stored in an index named documents.

          +

          It is possible to change the index name by editing the ingestion flow. +However, this can impact dependent processes, such as the filters and Chat flow, that reference the documents index by default. +Make sure you edit other flows as needed to ensure all processes use the same index name.

          +

          If you encounter errors or unexpected behavior after changing the index name, you can revert the flows to their original configuration, or delete knowledge to clear the existing documents from your knowledge base.

          +

          Knowledge ingestion settings​

          +
          warning

          Knowledge ingestion settings apply to documents you upload after making the changes. +Documents uploaded before changing these settings aren't reprocessed.

          +

          After changing knowledge ingestion settings, you must determine if you need to reupload any documents to be consistent with the new settings.

          +

          It isn't always necessary to reupload documents after changing knowledge ingestion settings. +For example, it is typical to upload some documents with OCR enabled and others without OCR enabled.

          +

          If needed, you can use filters to separate documents that you uploaded with different settings, such as different embedding models.

          +

          Set the embedding model and dimensions​

          +

          When you install OpenRAG, you select at least one embedding model during application onboarding. +OpenRAG automatically detects and configures the appropriate vector dimensions for your selected embedding model, ensuring optimal search performance and compatibility.

          +

          In the OpenRAG repository, you can find the complete list of supported models in models_service.py and the corresponding vector dimensions in settings.py.

          +

          During application onboarding, you can select from the supported models. +The default embedding dimension is 1536, and the default model is the OpenAI text-embedding-3-small.

          +

          If you want to use an unsupported model, you must manually set the model in your OpenRAG configuration. +If you use an unsupported embedding model that doesn't have defined dimensions in settings.py, then OpenRAG falls back to the default dimensions (1536) and logs a warning. OpenRAG's OpenSearch instance and flows continue to work, but similarity search quality can be affected if the actual model dimensions aren't 1536.

          +

          To change the embedding model after onboarding, it is recommended that you modify the embedding model setting in the OpenRAG Settings page or in your OpenRAG configuration. +This will automatically update all relevant OpenRAG flows to use the new embedding model configuration.

          +

          Set Docling parameters​

          +

          OpenRAG uses Docling for document ingestion because it supports many file formats, processes tables and images well, and performs efficiently.

          +

          When you upload documents, Docling processes the files, splits them into chunks, and stores them as separate, structured documents in your OpenSearch knowledge base.

          +

          You can use either Docling Serve or OpenRAG's built-in Docling ingestion pipeline to process documents.

          +

          By default, OpenRAG uses Docling Serve. +This means that OpenRAG starts a docling serve process on your local machine and runs Docling ingestion through an API service.

          +

          To modify the Docling ingestion and embedding parameters, click Settings in the OpenRAG user interface.

          +
          tip

          OpenRAG warns you if docling serve isn't running. +You can start and stop OpenRAG services from the TUI main menu with Start Native Services or Stop Native Services.

          +
            +
          • +

            Embedding model: Select the model to use to generate vector embeddings for your documents.

            +

            This is initially set during installation. +The recommended way to change this setting is in the OpenRAG Settings or your OpenRAG configuration. +This will automatically update all relevant OpenRAG flows to use the new embedding model configuration.

            +

            If you uploaded documents prior to changing the embedding model, you can create filters to separate documents embedded with different models, or you can reupload all documents to regenerate embeddings with the new model. +If you want to use multiple embeddings models, similarity search (in the Chat) can take longer as it searching each model's embeddings separately.

          • -

            When you're done editing the filter, click Update Filter.

            +

            Chunk size: Set the number of characters for each text chunk when breaking down a file. +Larger chunks yield more context per chunk, but can include irrelevant information. Smaller chunks yield more precise semantic search, but can lack context. +The default value is 1000 characters, which is usually a good balance between context and precision.

          • -

            To apply the filter to OpenRAG globally, click Knowledge, and then select the filter to apply. One filter can be enabled at a time.

            -

            To apply the filter to a single chat session, in the Chat window, click , and then select the filter to apply.

            -

            To delete the filter, in the Knowledge Filter pane, click Delete Filter.

            +

            Chunk overlap: Set the number of characters to overlap over chunk boundaries. +Use larger overlap values for documents where context is most important. Use smaller overlap values for simpler documents or when optimization is most important. +The default value is 200 characters, which represents an overlap of 20 percent if the Chunk size is 1000. This is suitable for general use. For faster processing, decrease the overlap to approximately 10 percent. For more complex documents where you need to preserve context across chunks, increase it to approximately 40 percent.

            • -
        -

        OpenRAG default configuration​

        -

        OpenRAG automatically detects and configures the correct vector dimensions for embedding models, ensuring optimal search performance and compatibility.

        -

        The complete list of supported models is available at models_service.py in the OpenRAG repository.

        -

        You can use custom embedding models by specifying them in your configuration.

        -

        If you use an unknown embedding model, OpenRAG automatically falls back to 1536 dimensions and logs a warning. The system continues to work, but search quality can be affected if the actual model dimensions differ from 1536.

        -

        The default embedding dimension is 1536 and the default model is text-embedding-3-small.

        -

        For models with known vector dimensions, see settings.py in the OpenRAG repository.

        • +
        • +

          Table Structure: Enables Docling's DocumentConverter tool for parsing tables. Instead of treating tables as plain text, tables are output as structured table data with preserved relationships and metadata. This option is enabled by default.

          +
          • +
        • +

          OCR: Enables Optical Character Recognition (OCR) processing when extracting text from images and ingesting scanned documents. This setting is best suited for processing text-based documents faster with Docling's DocumentConverter. Images are ignored and not processed.

          +

          This option is disabled by default. Enabling OCR can slow ingestion performance.

          +

          If OpenRAG detects that the local machine is running on macOS, OpenRAG uses the ocrmac OCR engine. Other platforms use easyocr.

          +
          • +
        • +

          Picture descriptions: Only applicable if OCR is enabled. Adds image descriptions generated by the SmolVLM-256M-Instruct model. Enabling picture descriptions can slow ingestion performance.

          +
          • +
        +

        Set the local documents path​

        +

        The default path for local uploads is the ./openrag-documents subdirectory in your OpenRAG installation directory. This is mounted to the /app/openrag-documents/ directory inside the OpenRAG container. Files added to the host or container directory are visible in both locations.

        +

        To change this location, modify the Documents Paths variable in either the Advanced Setup menu or in the .env used by Docker Compose.

        +

        Delete knowledge​

        +

        To clear your entire knowledge base, delete the contents of the ./opensearch-data folder in your OpenRAG installation directory. +This is a destructive operation that cannot be undone.

        +

        See also​

        +
      • © 2025 OpenRAG
      diff --git a/quickstart/index.html b/quickstart/index.html index fe7a1885..220b28ad 100644 --- a/quickstart/index.html +++ b/quickstart/index.html @@ -4,14 +4,14 @@ Quickstart | OpenRAG - - + + -

      Quickstart

      Use this quickstart to install OpenRAG, and then try some of OpenRAG's core features.

      +

      Quickstart

      Use this quickstart to install OpenRAG, and then try some of OpenRAG's core features.

      Prerequisites​

      This quickstart requires the following:

        @@ -97,7 +97,7 @@ You can complete this quickstart without going through the overview.

        Load and chat with documents​

        -

        OpenRAG's knowledge base chat is powered by the OpenRAG OpenSearch Agent. +

        Use the OpenRAG Chat to explore the documents in your OpenRAG database using natural language queries. Some documents are included by default to get you started, and you can load your own documents.

        1. @@ -117,7 +117,7 @@ You can click a document to view the chunks of the document as they are stored i

          For this quickstart, use either the File or Folder upload options to load documents from your local machine. Folder uploads an entire directory. The default directory is the /openrag-documents subdirectory in your OpenRAG installation directory.

          -

          For information about the cloud storage provider options, see Ingest files through OAuth connectors.

          +

          For information about the cloud storage provider options, see Ingest files with OAuth connectors.

        2. Return to the Chat window, and then ask a question related to the documents that you just uploaded.

          @@ -134,7 +134,7 @@ If a document was chunked improperly, you might need to tweak the ingestion or m

          Click Settings to modify the knowledge ingestion settings.

      -

      For more information about knowledge bases and knowledge ingestion, see OpenSearch in OpenRAG.

      +

      For more information, see Configure knowledge and Ingest knowledge.

      • Change the language model and chat settings​

      @@ -146,13 +146,13 @@ If a document was chunked improperly, you might need to tweak the ingestion or m

    • For greater insight into the underlying Langflow flow that drives the OpenRAG chat, click Edit in Langflow and then click Proceed to launch the Langflow visual editor in a new browser window.

      If Langflow requests login information, enter the LANGFLOW_SUPERUSER and LANGFLOW_SUPERUSER_PASSWORD from the .env file in your OpenRAG installation directory.

      -

      The OpenRAG OpenSearch Agent flow opens in a new browser window.

      +

      The OpenRAG OpenSearch Agent flow opens in a new browser window.

      OpenRAG OpenSearch Agent flow

    • For this quickstart, try changing the model. Click the Language Model component, and then change the Model Name to a different OpenAI model.

      -

      When editing built-in flows, you can click Restore flow to revert the flow to its initial state.

      +

      After you edit a built-in flow, you can click Restore flow on the Settings page to revert the flow to its original state when you first installed OpenRAG.

    • Press Command+S (Ctrl+S) to save your changes.

      @@ -172,7 +172,7 @@ You can use these flows as-is or modify them to better suit your needs, as demon

      You can send and receive requests with the Langflow API using Python, TypeScript, or curl.

      1. -

        Open the OpenRAG OpenSearch Agent flow in the Langflow visual editor: From the Chat window, click Settings, click Edit in Langflow, and then click Proceed.

        +

        Open the OpenRAG OpenSearch Agent flow in the Langflow visual editor: From the Chat window, click Settings, click Edit in Langflow, and then click Proceed.

      2. Create a Langflow API key, which is a user-specific token required to send requests to the Langflow server. diff --git a/reference/configuration/index.html b/reference/configuration/index.html index 14d9c244..cad4ce0f 100644 --- a/reference/configuration/index.html +++ b/reference/configuration/index.html @@ -4,14 +4,14 @@ Environment variables | OpenRAG - - + + -

        Environment variables

        OpenRAG recognizes environment variables from the following sources:

        +

        Environment variables

        OpenRAG recognizes environment variables from the following sources:

        • Environment variables: Values set in the .env file.
        • Langflow runtime overrides: Langflow components can set environment variables at runtime.
          • @@ -23,39 +23,55 @@

          The Docker Compose files are populated with values from your .env, so you don't need to edit the Docker Compose files manually.

          Environment variables always take precedence over other variables.

          Set environment variables​

          -

          To set environment variables, do the following.

          +

          After you start OpenRAG, you must stop and restart OpenRAG containers to apply any changes you make to the .env file.

          +

          To set mutable environment variables, do the following:

            -
          1. Stop OpenRAG.
            2. -
          2. Set the values in the .env file: +
          3. +

            Stop OpenRAG with the TUI or Docker Compose.

            +
            4. +
          4. +

            Set the values in the .env file:

            LOG_LEVEL=DEBUG
            LOG_FORMAT=json
            SERVICE_NAME=openrag-dev
            5. -
          5. Start OpenRAG.
            6. +
          6. +

            Start OpenRAG with the TUI or Docker Compose.

            +
          -

          Updating provider API keys or provider endpoints in the .env file will not take effect after Application onboarding. To change these values, you must:

          +

          Certain environment variables that you set during application onboarding, such as provider API keys and provider endpoints, require resetting the containers after modifying the .env file.

          +

          To change immutable variables with TUI-managed containers, you must reinstall OpenRAG and either delete or modify the .env file before you repeat the setup and onboarding process in the TUI.

          +

          To change immutable variables with self-managed containers, do the following:

            -
          1. Stop OpenRAG.
            2. -
          2. Remove the containers: -
            docker-compose down
            +
          3. +

            Stop OpenRAG with Docker Compose.

            4. -
          4. Update the values in your .env file.
            5. -
          5. Start OpenRAG containers. -
            docker-compose up -d
            +
          6. +

            Remove the containers:

            +
            docker-compose down
            +
            7. +
          7. +

            Update the values in your .env file.

            +
            8. +
          8. +

            Start OpenRAG with Docker Compose:

            +
            docker-compose up -d
            +
            9. +
          9. +

            Repeat application onboarding. The values in your .env file are automatically populated.

            10. -
          10. Complete Application onboarding again.

          Supported environment variables​

          All OpenRAG configuration can be controlled through environment variables.

          AI provider settings​

          -

          Configure which AI models and providers OpenRAG uses for language processing and embeddings. -For more information, see Application onboarding.

          -
          VariableDefaultDescription
          EMBEDDING_MODELtext-embedding-3-smallEmbedding model for vector search.
          LLM_MODELgpt-4o-miniLanguage model for the chat agent.
          MODEL_PROVIDERopenaiModel provider, such as OpenAI or IBM watsonx.ai.
          OPENAI_API_KEY-Your OpenAI API key. Optional. Can be provided during application onboarding when installing OpenRAG.
          PROVIDER_API_KEY-API key for the model provider.
          PROVIDER_ENDPOINT-Custom provider endpoint. Only used for IBM or Ollama providers.
          PROVIDER_PROJECT_ID-Project ID for providers. Only required for the IBM watsonx.ai provider.
          +

          Configure which models and providers OpenRAG uses to generate text and embeddings. +These are initially set during application onboarding. +Some values are immutable and can only be changed by recreating the OpenRAG containers, as explained in Set environment variables.

          +
          VariableDefaultDescription
          EMBEDDING_MODELtext-embedding-3-smallEmbedding model for generating vector embeddings for documents in the knowledge base and similarity search queries. Can be changed after application onboarding. Accepts one or more models.
          LLM_MODELgpt-4o-miniLanguage model for language processing and text generation in the Chat feature.
          MODEL_PROVIDERopenaiModel provider, such as OpenAI or IBM watsonx.ai.
          OPENAI_API_KEYNot setOptional OpenAI API key for the default model. For other providers, use PROVIDER_API_KEY.
          PROVIDER_API_KEYNot setAPI key for the model provider.
          PROVIDER_ENDPOINTNot setCustom provider endpoint for the IBM and Ollama model providers. Leave unset for other model providers.
          PROVIDER_PROJECT_IDNot setProject ID for the IBM watsonx.ai model provider only. Leave unset for other model providers.

          Document processing​

          -

          Control how OpenRAG processes and ingests documents into your knowledge base. -For more information, see Ingestion.

          -
          VariableDefaultDescription
          CHUNK_OVERLAP200Overlap between chunks.
          CHUNK_SIZE1000Text chunk size for document processing.
          DISABLE_INGEST_WITH_LANGFLOWfalseDisable Langflow ingestion pipeline.
          DOCLING_OCR_ENGINE-OCR engine for document processing.
          OCR_ENABLEDfalseEnable OCR for image processing.
          OPENRAG_DOCUMENTS_PATHS./openrag-documentsDocument paths for ingestion.
          PICTURE_DESCRIPTIONS_ENABLEDfalseEnable picture descriptions.
          +

          Control how OpenRAG processes and ingests documents into your knowledge base.

          +
          VariableDefaultDescription
          CHUNK_OVERLAP200Overlap between chunks.
          CHUNK_SIZE1000Text chunk size for document processing.
          DISABLE_INGEST_WITH_LANGFLOWfalseDisable Langflow ingestion pipeline.
          DOCLING_OCR_ENGINESet by OSOCR engine for document processing. For macOS, ocrmac. For any other OS, easyocr.
          OCR_ENABLEDfalseEnable OCR for image processing.
          OPENRAG_DOCUMENTS_PATHS./openrag-documentsDocument paths for ingestion.
          PICTURE_DESCRIPTIONS_ENABLEDfalseEnable picture descriptions.

          Langflow settings​

          Configure Langflow authentication.

          -
          VariableDefaultDescription
          LANGFLOW_AUTO_LOGINFalseEnable auto-login for Langflow.
          LANGFLOW_CHAT_FLOW_IDpre-filledThis value is pre-filled. The default value is found in .env.example.
          LANGFLOW_ENABLE_SUPERUSER_CLIFalseEnable superuser CLI.
          LANGFLOW_INGEST_FLOW_IDpre-filledThis value is pre-filled. The default value is found in .env.example.
          LANGFLOW_KEYauto-generatedExplicit Langflow API key.
          LANGFLOW_NEW_USER_IS_ACTIVEFalseNew users are active by default.
          LANGFLOW_PUBLIC_URLhttp://localhost:7860Public URL for Langflow.
          LANGFLOW_SECRET_KEY-Secret key for Langflow internal operations.
          LANGFLOW_SUPERUSER-Langflow admin username. Required.
          LANGFLOW_SUPERUSER_PASSWORD-Langflow admin password. Required.
          LANGFLOW_URLhttp://localhost:7860Langflow URL.
          NUDGES_FLOW_IDpre-filledThis value is pre-filled. The default value is found in .env.example.
          SYSTEM_PROMPT"You are a helpful AI assistant with access to a knowledge base. Answer questions based on the provided context."System prompt for the Langflow agent.
          +
          VariableDefaultDescription
          LANGFLOW_AUTO_LOGINFalseEnable auto-login for Langflow.
          LANGFLOW_CHAT_FLOW_IDBuilt-in flow IDThis value is automatically set to the ID of the chat flow. The default value is found in .env.example. Only change this value if you explicitly don't want to use this built-in flow.
          LANGFLOW_ENABLE_SUPERUSER_CLIFalseEnable superuser privileges for Langflow CLI commands.
          LANGFLOW_INGEST_FLOW_IDBuilt-in flow IDThis value is automatically set to the ID of the ingestion flow. The default value is found in .env.example. Only change this value if you explicitly don't want to use this built-in flow.
          LANGFLOW_KEYAutomatically generatedExplicit Langflow API key.
          LANGFLOW_NEW_USER_IS_ACTIVEFalseWhether new Langflow users are active by default.
          LANGFLOW_PUBLIC_URLhttp://localhost:7860Public URL for the Langflow instance.
          LANGFLOW_SECRET_KEYNot setSecret key for Langflow internal operations.
          LANGFLOW_SUPERUSERNone, must be explicitly setLangflow admin username. Required.
          LANGFLOW_SUPERUSER_PASSWORDNone, must be explicitly setLangflow admin password. Required.
          LANGFLOW_URLhttp://localhost:7860URL for the Langflow instance.
          NUDGES_FLOW_IDBuilt-in flow IDThis value is automatically set to the ID of the nudges flow. The default value is found in .env.example. Only change this value if you explicitly don't want to use this built-in flow.
          SYSTEM_PROMPTYou are a helpful AI assistant with access to a knowledge base. Answer questions based on the provided context.System prompt instructions for the agent driving the Chat flow.

          OAuth provider settings​

          Configure OAuth providers and external service integrations.

          VariableDefaultDescription
          AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY-AWS integrations.
          GOOGLE_OAUTH_CLIENT_ID / GOOGLE_OAUTH_CLIENT_SECRET-Google OAuth authentication.
          MICROSOFT_GRAPH_OAUTH_CLIENT_ID / MICROSOFT_GRAPH_OAUTH_CLIENT_SECRET-Microsoft OAuth.
          WEBHOOK_BASE_URL-Base URL for webhook endpoints.
          @@ -64,18 +80,25 @@ For more information, see Ingestion.

          VariableDefaultDescription
          OPENSEARCH_HOSTlocalhostOpenSearch host.
          OPENSEARCH_PASSWORD-Password for OpenSearch admin user. Required.
          OPENSEARCH_PORT9200OpenSearch port.
          OPENSEARCH_USERNAMEadminOpenSearch username.

          System settings​

          Configure general system components, session management, and logging.

          -
          VariableDefaultDescription
          LANGFLOW_KEY_RETRIES15Number of retries for Langflow key generation.
          LANGFLOW_KEY_RETRY_DELAY2.0Delay between retries in seconds.
          LANGFLOW_VERSIONlatestLangflow Docker image version.
          LOG_FORMAT-Log format (set to "json" for JSON output).
          LOG_LEVELINFOLogging level (DEBUG, INFO, WARNING, ERROR).
          MAX_WORKERS-Maximum number of workers for document processing.
          OPENRAG_VERSIONlatestOpenRAG Docker image version.
          SERVICE_NAMEopenragService name for logging.
          SESSION_SECRETauto-generatedSession management.
          +
          VariableDefaultDescription
          LANGFLOW_KEY_RETRIES15Number of retries for Langflow key generation.
          LANGFLOW_KEY_RETRY_DELAY2.0Delay between retries in seconds.
          LANGFLOW_VERSIONlatestLangflow Docker image version.
          LOG_FORMATDisabledSet to json to enabled JSON-formatted log output.
          LOG_LEVELINFOLogging level (DEBUG, INFO, WARNING, ERROR).
          MAX_WORKERS1Maximum number of workers for document processing.
          OPENRAG_VERSIONlatestOpenRAG Docker image version.
          SERVICE_NAMEopenragService name for logging.
          SESSION_SECRETAutomatically generatedSession management.

          Langflow runtime overrides​

          -

          Langflow runtime overrides allow you to modify component settings at runtime without changing the base configuration.

          -

          Runtime overrides are implemented through tweaks - parameter modifications that are passed to specific Langflow components during flow execution.

          -

          For more information on tweaks, see Input schema (tweaks).

          +

          You can modify flow settings at runtime without permanently changing the flow's configuration.

          +

          Runtime overrides are implemented through tweaks, which are one-time parameter modifications that are passed to specific Langflow components during flow execution.

          +

          For more information on tweaks, see the Langflow documentation on Input schema (tweaks).

          Default values and fallbacks​

          -

          When no environment variables or configuration file values are provided, OpenRAG uses default values. -These values can be found in the code base at the following locations.

          -

          OpenRAG configuration defaults​

          -

          These values are defined in config_manager.py in the OpenRAG repository.

          -

          System configuration defaults​

          -

          These fallback values are defined in settings.py in the OpenRAG repository.

        • +

          If a variable isn't set by environment variables or a configuration file, OpenRAG can use a default value if one is defined in the codebase. +Default values can be found in the OpenRAG repository:

          +
        • © 2025 OpenRAG
        diff --git a/support/troubleshoot/index.html b/support/troubleshoot/index.html index 8c72f73a..9b64c46b 100644 --- a/support/troubleshoot/index.html +++ b/support/troubleshoot/index.html @@ -4,14 +4,14 @@ Troubleshoot OpenRAG | OpenRAG - - + + -

        Troubleshoot OpenRAG

        This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG.

        +

        Troubleshoot OpenRAG

        This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG.

        OpenSearch fails to start​

        Check that OPENSEARCH_PASSWORD set in Environment variables meets requirements. The password must contain at least 8 characters, and must contain at least one uppercase letter, one lowercase letter, one digit, and one special character that is strong.

        @@ -48,7 +48,7 @@ This example increases the machine size to 8 GB of RAM, which should be sufficie 
        uvx openrag
      -

      If you do not need OCR, you can disable OCR-based processing in your ingestion settings to avoid requiring easyocr.

      +

      If you don't need OCR, you can disable OCR-based processing in your ingestion settings to avoid requiring easyocr.

      Upgrade fails due to Langflow container already exists​

      If you encounter a langflow container already exists error when upgrading OpenRAG, this typically means you upgraded OpenRAG with uv, but you didn't remove or upgrade containers from a previous installation.

      To resolve this issue, do the following:

      @@ -128,7 +128,9 @@ After removing the containers, retry the upgrade in the OpenRAG TUI by clicking

      Clean up any leftover data:

      docker system prune --all --force --volumes
      • -