diff --git a/404.html b/404.html index 07d403b6..0843ed1d 100644 --- a/404.html +++ b/404.html @@ -3,14 +3,14 @@ -OpenRAG - - +OpenRAG + + -
Skip to main content

Page Not Found

We could not find what you were looking for.

Please contact the owner of the site that linked you to the original URL and let them know their link is broken.

+
Skip to main content

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We could not find what you were looking for.

Please contact the owner of the site that linked you to the original URL and let them know their link is broken.

\ No newline at end of file diff --git a/CNAME b/CNAME new file mode 100644 index 00000000..5208db85 --- /dev/null +++ b/CNAME @@ -0,0 +1 @@ +docs.openr.ag \ No newline at end of file diff --git a/agents/index.html b/agents/index.html index f87c2c61..6bfc4240 100644 --- a/agents/index.html +++ b/agents/index.html @@ -3,15 +3,15 @@ -Agents powered by Langflow | OpenRAG - - +Agents powered by Langflow | OpenRAG + + -
Skip to main content

Agents powered by Langflow

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

+

Agents powered by Langflow

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

This flow intelligently chats with your knowledge by embedding your query, comparing it the vector database embeddings, and generating a response with the LLM.

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.

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.

@@ -33,8 +33,8 @@ This filter is the Knowledge filter, and filters which knowledge sources to sear

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. Flows are edited in the same way as in the Langflow visual editor.

-

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

+

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

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.

+OpenRAG warns you that this discards all custom settings. Click Restore to restore the flow.

\ No newline at end of file diff --git a/assets/js/0ba6a408.3c6461ab.js b/assets/js/0ba6a408.3c6461ab.js deleted file mode 100644 index 2df023a6..00000000 --- a/assets/js/0ba6a408.3c6461ab.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:()=>g,contentTitle:()=>h,default:()=>x,frontMatter:()=>a,metadata:()=>i,toc:()=>u});const i=JSON.parse('{"id":"core-components/knowledge","title":"OpenSearch Knowledge","description":"OpenRAG uses OpenSearch for its vector-backed knowledge store.","source":"@site/docs/core-components/knowledge.mdx","sourceDirName":"core-components","slug":"/knowledge","permalink":"/openrag/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 Knowledge","slug":"/knowledge"},"sidebar":"tutorialSidebar","previous":{"title":"Langflow Agents","permalink":"/openrag/agents"},"next":{"title":"Docling Ingestion","permalink":"/openrag/ingestion"}}');var o=s(4848),t=s(8453),r=s(9179),l=s(1470),c=s(9365),d=s(3782);const a={title:"OpenSearch Knowledge",slug:"/knowledge"},h=void 0,g={},u=[{value:"Explore knowledge",id:"explore-knowledge",level:2},...d.RM,{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:"Sync cloud connectors",id:"sync-cloud-connectors",level:3},{value:"Knowledge ingestion settings",id:"knowledge-ingestion-settings",level:3},{value:"Create knowledge filters",id:"create-knowledge-filters",level:2},{value:"OpenRAG default configuration",id:"openrag-default-configuration",level:2}];function p(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,t.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.p,{children:["OpenRAG uses ",(0,o.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"})," for its vector-backed knowledge store.\nOpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support."]}),"\n",(0,o.jsx)(n.h2,{id:"explore-knowledge",children:"Explore knowledge"}),"\n",(0,o.jsxs)(n.p,{children:["The Knowledge page lists the documents OpenRAG has ingested into the OpenSearch vector database's ",(0,o.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,o.jsxs)(n.p,{children:["To explore your current knowledge, click ",(0,o.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,o.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,o.jsxs)(n.p,{children:["Documents are processed with the default ",(0,o.jsx)(n.strong,{children:"Knowledge Ingest"})," flow, so if you want to split your documents differently, edit the ",(0,o.jsx)(n.strong,{children:"Knowledge Ingest"})," flow."]}),"\n",(0,o.jsx)(d.Ay,{}),"\n",(0,o.jsx)(n.h2,{id:"ingest-knowledge",children:"Ingest knowledge"}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG supports knowledge ingestion through direct file uploads and OAuth connectors."}),"\n",(0,o.jsx)(n.h3,{id:"direct-file-ingestion",children:"Direct file ingestion"}),"\n",(0,o.jsxs)(n.p,{children:["The ",(0,o.jsx)(n.strong,{children:"Knowledge Ingest"})," flow uses Langflow's ",(0,o.jsxs)(n.a,{href:"https://docs.langflow.org/components-data#file",children:[(0,o.jsx)(n.strong,{children:"File"})," component"]})," to split and embed files loaded from your local machine into the OpenSearch database."]}),"\n",(0,o.jsxs)(n.p,{children:["The default path to your local folder is mounted from the ",(0,o.jsx)(n.code,{children:"./documents"})," folder in your OpenRAG project directory to the ",(0,o.jsx)(n.code,{children:"/app/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,o.jsx)(n.strong,{children:"Documents Paths"})," variable in either the TUI's ",(0,o.jsx)(n.a,{href:"/install#advanced-setup",children:"Advanced Setup"})," or in the ",(0,o.jsx)(n.code,{children:".env"})," used by Docker Compose."]}),"\n",(0,o.jsxs)(n.p,{children:["To load and process a single file from the mapped location, click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add File"}),".\nThe file is loaded into your OpenSearch database, and appears in the Knowledge page."]}),"\n",(0,o.jsxs)(n.p,{children:["To load and process a directory from the mapped location, click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,o.jsx)(n.strong,{children:"Process Folder"}),".\nThe files are loaded into your OpenSearch database, and appear in the Knowledge page."]}),"\n",(0,o.jsx)(n.h3,{id:"oauth-ingestion",children:"Ingest files through OAuth connectors"}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG supports Google Drive, OneDrive, and AWS S3 as OAuth connectors for seamless document synchronization."}),"\n",(0,o.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,o.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,o.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,o.jsxs)(l.A,{groupId:"Installation type",children:[(0,o.jsx)(c.A,{value:"TUI",label:"TUI",default:!0,children:(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["If OpenRAG is running, stop it with ",(0,o.jsx)(n.strong,{children:"Status"})," > ",(0,o.jsx)(n.strong,{children:"Stop Services"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,o.jsx)(n.a,{href:"/install#advanced-setup",children:"Advanced Setup"})," menu."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Save Configuration"}),".\nThe TUI generates a new ",(0,o.jsx)(n.code,{children:".env"})," file with your OAuth values."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Start Container Services"}),"."]}),"\n"]})}),(0,o.jsxs)(c.A,{value:".env",label:".env",children:[(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsx)(n.li,{children:"Stop the Docker deployment."}),"\n",(0,o.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,o.jsx)(n.code,{children:".env"})," file for Docker Compose."]}),"\n"]}),(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:"GOOGLE_OAUTH_CLIENT_ID='YOUR_OAUTH_CLIENT_ID'\nGOOGLE_OAUTH_CLIENT_SECRET='YOUR_OAUTH_CLIENT_SECRET'\n"})}),(0,o.jsxs)(n.ol,{start:"3",children:["\n",(0,o.jsxs)(n.li,{children:["Save your ",(0,o.jsx)(n.code,{children:".env"}),". file."]}),"\n",(0,o.jsx)(n.li,{children:"Start the Docker deployment."}),"\n"]})]})]}),"\n",(0,o.jsxs)(n.p,{children:["The OpenRAG frontend at ",(0,o.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,o.jsx)(n.p,{children:"To add knowledge from an OAuth-connected storage provider, do the following:"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),", and then select the storage provider, for example, ",(0,o.jsx)(n.strong,{children:"Google Drive"}),".\nThe ",(0,o.jsx)(n.strong,{children:"Add Cloud Knowledge"})," page opens."]}),"\n",(0,o.jsxs)(n.li,{children:["To add files or folders from the connected storage, click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Files"}),".\nSelect the files or folders you want and click ",(0,o.jsx)(n.strong,{children:"Select"}),".\nYou can select multiples."]}),"\n",(0,o.jsxs)(n.li,{children:["When your files are selected, click ",(0,o.jsx)(n.strong,{children:"Ingest Files"}),".\nThe ingestion process may take some time, depending on the size of your documents."]}),"\n",(0,o.jsx)(n.li,{children:"When ingestion is complete, your documents are available in the Knowledge screen."}),"\n"]}),"\n",(0,o.jsx)(n.h3,{id:"sync-cloud-connectors",children:"Sync cloud connectors"}),"\n",(0,o.jsxs)(n.p,{children:["Your connected data sources are found in the ",(0,o.jsx)(r.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"})," page."]}),"\n",(0,o.jsxs)(n.p,{children:["When you click ",(0,o.jsx)(n.strong,{children:"Sync Now"})," for a connected cloud service like Google Drive, OpenRAG scans your connected Google Drive account to find files that match your sync criteria. Sync criteria are controlled in ",(0,o.jsx)(n.strong,{children:"Sync Settings"})," on the same page. You can sync all files, or select a maximum number of files to sync."]}),"\n",(0,o.jsx)(n.p,{children:"For each file found, OpenRAG downloads, converts, and embeds the processed content into OpenSearch."}),"\n",(0,o.jsxs)(n.p,{children:["You can monitor the sync progress in the ",(0,o.jsx)(r.A,{name:"Bell","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Tasks"})," sidebar."]}),"\n",(0,o.jsx)(n.p,{children:"Once processing is complete, the synced documents become available in your knowledge base and can be searched through the chat interface or Knowledge page."}),"\n",(0,o.jsx)(n.h3,{id:"knowledge-ingestion-settings",children:"Knowledge ingestion settings"}),"\n",(0,o.jsxs)(n.p,{children:["To configure the knowledge ingestion pipeline parameters, see ",(0,o.jsx)(n.a,{href:"/ingestion",children:"Docling Ingestion"}),"."]}),"\n",(0,o.jsx)(n.h2,{id:"create-knowledge-filters",children:"Create knowledge filters"}),"\n",(0,o.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,o.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,o.jsx)(n.p,{children:"To create a knowledge filter, do the following:"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Click ",(0,o.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"All Knowledge"}),", and then click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Create New Filter"}),".\nThe ",(0,o.jsx)(n.strong,{children:"Create New Knowledge Filter"})," pane appears."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Enter a ",(0,o.jsx)(n.strong,{children:"Name"})," and ",(0,o.jsx)(n.strong,{children:"Description"}),", and then click ",(0,o.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Create Filter"}),".\nA new filter is created with default settings that match everything."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To modify the default filter, click ",(0,o.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"All Knowledge"}),", and then click your new filter to edit it in the ",(0,o.jsx)(n.strong,{children:"Knowledge Filter"})," pane."]}),"\n",(0,o.jsx)(n.p,{children:"The following filter options are configurable."}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Search Query"}),': Enter text for semantic search, such as "financial reports from Q4".']}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Data Sources"}),": Select specific data sources or folders to include."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Document Types"}),": Filter by file type."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Owners"}),": Filter by who uploaded the documents."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Sources"}),": Filter by connector types, such as local upload or Google Drive."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Result Limit"}),": Set maximum number of results. The default is ",(0,o.jsx)(n.code,{children:"10"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Score Threshold"}),": Set minimum relevance score. The default score is ",(0,o.jsx)(n.code,{children:"0"}),"."]}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["When you're done editing the filter, click ",(0,o.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To apply the filter to OpenRAG globally, click ",(0,o.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"All Knowledge"}),", and then select the filter to apply."]}),"\n",(0,o.jsxs)(n.p,{children:["To apply the filter to a single chat session, in the ",(0,o.jsx)(r.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Chat"})," window, click ",(0,o.jsx)(n.strong,{children:"@"}),", and then select the filter to apply."]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"openrag-default-configuration",children:"OpenRAG default configuration"}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG automatically detects and configures the correct vector dimensions for embedding models, ensuring optimal search performance and compatibility."}),"\n",(0,o.jsxs)(n.p,{children:["The complete list of supported models is available at ",(0,o.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/services/models_service.py",children:"/src/services/models_service.py"}),"."]}),"\n",(0,o.jsx)(n.p,{children:"You can use custom embedding models by specifying them in your configuration."}),"\n",(0,o.jsxs)(n.p,{children:["If you use an unknown embedding model, OpenRAG will automatically fall back to ",(0,o.jsx)(n.code,{children:"1536"})," dimensions and log a warning. The system will continue to work, but search quality may be affected if the actual model dimensions differ from ",(0,o.jsx)(n.code,{children:"1536"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["The default embedding dimension is ",(0,o.jsx)(n.code,{children:"1536"})," and the default model is ",(0,o.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["For models with known vector dimensions, see ",(0,o.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/config/settings.py",children:"/src/config/settings.py"}),"."]})]})}function x(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(p,{...e})}):p(e)}},3782:(e,n,s)=>{s.d(n,{Ay:()=>c,RM:()=>r});var i=s(4848),o=s(8453),t=s(9179);const r=[];function l(e){const n={a:"a",p:"p",strong:"strong",...(0,o.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)(t.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nFlows are edited in the same way as in the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),"."]})}function c(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(l,{...e})}):l(e)}},9179:(e,n,s)=>{s.d(n,{A:()=>t});s(6540);var i=s(4827),o=s(4848);function t({name:e,...n}){const s=i[e];return s?(0,o.jsx)(s,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/0ba6a408.4d0ae6a2.js b/assets/js/0ba6a408.4d0ae6a2.js new file mode 100644 index 00000000..933139e2 --- /dev/null +++ b/assets/js/0ba6a408.4d0ae6a2.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:()=>u,contentTitle:()=>h,default:()=>x,frontMatter:()=>a,metadata:()=>i,toc:()=>g});const i=JSON.parse('{"id":"core-components/knowledge","title":"OpenSearch Knowledge","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 Knowledge","slug":"/knowledge"},"sidebar":"tutorialSidebar","previous":{"title":"Langflow Agents","permalink":"/agents"},"next":{"title":"Docling Ingestion","permalink":"/ingestion"}}');var o=s(4848),t=s(8453),r=s(9179),l=s(1470),c=s(9365),d=s(3782);const a={title:"OpenSearch Knowledge",slug:"/knowledge"},h=void 0,u={},g=[{value:"Explore knowledge",id:"explore-knowledge",level:2},...d.RM,{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:"Sync cloud connectors",id:"sync-cloud-connectors",level:3},{value:"Knowledge ingestion settings",id:"knowledge-ingestion-settings",level:3},{value:"Create knowledge filters",id:"create-knowledge-filters",level:2},{value:"OpenRAG default configuration",id:"openrag-default-configuration",level:2}];function p(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,t.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.p,{children:["OpenRAG uses ",(0,o.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"})," for its vector-backed knowledge store.\nOpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support."]}),"\n",(0,o.jsx)(n.h2,{id:"explore-knowledge",children:"Explore knowledge"}),"\n",(0,o.jsxs)(n.p,{children:["The Knowledge page lists the documents OpenRAG has ingested into the OpenSearch vector database's ",(0,o.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,o.jsxs)(n.p,{children:["To explore your current knowledge, click ",(0,o.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,o.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,o.jsxs)(n.p,{children:["Documents are processed with the default ",(0,o.jsx)(n.strong,{children:"Knowledge Ingest"})," flow, so if you want to split your documents differently, edit the ",(0,o.jsx)(n.strong,{children:"Knowledge Ingest"})," flow."]}),"\n",(0,o.jsx)(d.Ay,{}),"\n",(0,o.jsx)(n.h2,{id:"ingest-knowledge",children:"Ingest knowledge"}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG supports knowledge ingestion through direct file uploads and OAuth connectors."}),"\n",(0,o.jsx)(n.h3,{id:"direct-file-ingestion",children:"Direct file ingestion"}),"\n",(0,o.jsxs)(n.p,{children:["The ",(0,o.jsx)(n.strong,{children:"Knowledge Ingest"})," flow uses Langflow's ",(0,o.jsxs)(n.a,{href:"https://docs.langflow.org/components-data#file",children:[(0,o.jsx)(n.strong,{children:"File"})," component"]})," to split and embed files loaded from your local machine into the OpenSearch database."]}),"\n",(0,o.jsxs)(n.p,{children:["The default path to your local folder is mounted from the ",(0,o.jsx)(n.code,{children:"./documents"})," folder in your OpenRAG project directory to the ",(0,o.jsx)(n.code,{children:"/app/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,o.jsx)(n.strong,{children:"Documents Paths"})," variable in either the TUI's ",(0,o.jsx)(n.a,{href:"/install#advanced-setup",children:"Advanced Setup"})," or in the ",(0,o.jsx)(n.code,{children:".env"})," used by Docker Compose."]}),"\n",(0,o.jsxs)(n.p,{children:["To load and process a single file from the mapped location, click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,o.jsx)(n.strong,{children:"Add File"}),".\nThe file is loaded into your OpenSearch database, and appears in the Knowledge page."]}),"\n",(0,o.jsxs)(n.p,{children:["To load and process a directory from the mapped location, click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,o.jsx)(n.strong,{children:"Process Folder"}),".\nThe files are loaded into your OpenSearch database, and appear in the Knowledge page."]}),"\n",(0,o.jsx)(n.h3,{id:"oauth-ingestion",children:"Ingest files through OAuth connectors"}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG supports Google Drive, OneDrive, and AWS S3 as OAuth connectors for seamless document synchronization."}),"\n",(0,o.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,o.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,o.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,o.jsxs)(l.A,{groupId:"Installation type",children:[(0,o.jsx)(c.A,{value:"TUI",label:"TUI",default:!0,children:(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["If OpenRAG is running, stop it with ",(0,o.jsx)(n.strong,{children:"Status"})," > ",(0,o.jsx)(n.strong,{children:"Stop Services"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,o.jsx)(n.a,{href:"/install#advanced-setup",children:"Advanced Setup"})," menu."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Save Configuration"}),".\nThe TUI generates a new ",(0,o.jsx)(n.code,{children:".env"})," file with your OAuth values."]}),"\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(n.strong,{children:"Start Container Services"}),"."]}),"\n"]})}),(0,o.jsxs)(c.A,{value:".env",label:".env",children:[(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsx)(n.li,{children:"Stop the Docker deployment."}),"\n",(0,o.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,o.jsx)(n.code,{children:".env"})," file for Docker Compose."]}),"\n"]}),(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:"GOOGLE_OAUTH_CLIENT_ID='YOUR_OAUTH_CLIENT_ID'\nGOOGLE_OAUTH_CLIENT_SECRET='YOUR_OAUTH_CLIENT_SECRET'\n"})}),(0,o.jsxs)(n.ol,{start:"3",children:["\n",(0,o.jsxs)(n.li,{children:["Save your ",(0,o.jsx)(n.code,{children:".env"}),". file."]}),"\n",(0,o.jsx)(n.li,{children:"Start the Docker deployment."}),"\n"]})]})]}),"\n",(0,o.jsxs)(n.p,{children:["The OpenRAG frontend at ",(0,o.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,o.jsx)(n.p,{children:"To add knowledge from an OAuth-connected storage provider, do the following:"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["Click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),", and then select the storage provider, for example, ",(0,o.jsx)(n.strong,{children:"Google Drive"}),".\nThe ",(0,o.jsx)(n.strong,{children:"Add Cloud Knowledge"})," page opens."]}),"\n",(0,o.jsxs)(n.li,{children:["To add files or folders from the connected storage, click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Files"}),".\nSelect the files or folders you want and click ",(0,o.jsx)(n.strong,{children:"Select"}),".\nYou can select multiples."]}),"\n",(0,o.jsxs)(n.li,{children:["When your files are selected, click ",(0,o.jsx)(n.strong,{children:"Ingest Files"}),".\nThe ingestion process may take some time, depending on the size of your documents."]}),"\n",(0,o.jsx)(n.li,{children:"When ingestion is complete, your documents are available in the Knowledge screen."}),"\n"]}),"\n",(0,o.jsx)(n.h3,{id:"sync-cloud-connectors",children:"Sync cloud connectors"}),"\n",(0,o.jsxs)(n.p,{children:["Your connected data sources are found in the ",(0,o.jsx)(r.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"})," page."]}),"\n",(0,o.jsxs)(n.p,{children:["When you click ",(0,o.jsx)(n.strong,{children:"Sync Now"})," for a connected cloud service like Google Drive, OpenRAG scans your connected Google Drive account to find files that match your sync criteria. Sync criteria are controlled in ",(0,o.jsx)(n.strong,{children:"Sync Settings"})," on the same page. You can sync all files, or select a maximum number of files to sync."]}),"\n",(0,o.jsx)(n.p,{children:"For each file found, OpenRAG downloads, converts, and embeds the processed content into OpenSearch."}),"\n",(0,o.jsxs)(n.p,{children:["You can monitor the sync progress in the ",(0,o.jsx)(r.A,{name:"Bell","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Tasks"})," sidebar."]}),"\n",(0,o.jsx)(n.p,{children:"Once processing is complete, the synced documents become available in your knowledge base and can be searched through the chat interface or Knowledge page."}),"\n",(0,o.jsx)(n.h3,{id:"knowledge-ingestion-settings",children:"Knowledge ingestion settings"}),"\n",(0,o.jsxs)(n.p,{children:["To configure the knowledge ingestion pipeline parameters, see ",(0,o.jsx)(n.a,{href:"/ingestion",children:"Docling Ingestion"}),"."]}),"\n",(0,o.jsx)(n.h2,{id:"create-knowledge-filters",children:"Create knowledge filters"}),"\n",(0,o.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,o.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,o.jsx)(n.p,{children:"To create a knowledge filter, do the following:"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Click ",(0,o.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"All Knowledge"}),", and then click ",(0,o.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Create New Filter"}),".\nThe ",(0,o.jsx)(n.strong,{children:"Create New Knowledge Filter"})," pane appears."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Enter a ",(0,o.jsx)(n.strong,{children:"Name"})," and ",(0,o.jsx)(n.strong,{children:"Description"}),", and then click ",(0,o.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Create Filter"}),".\nA new filter is created with default settings that match everything."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To modify the default filter, click ",(0,o.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"All Knowledge"}),", and then click your new filter to edit it in the ",(0,o.jsx)(n.strong,{children:"Knowledge Filter"})," pane."]}),"\n",(0,o.jsx)(n.p,{children:"The following filter options are configurable."}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Search Query"}),': Enter text for semantic search, such as "financial reports from Q4".']}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Data Sources"}),": Select specific data sources or folders to include."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Document Types"}),": Filter by file type."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Owners"}),": Filter by who uploaded the documents."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Sources"}),": Filter by connector types, such as local upload or Google Drive."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Result Limit"}),": Set maximum number of results. The default is ",(0,o.jsx)(n.code,{children:"10"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:[(0,o.jsx)(n.strong,{children:"Score Threshold"}),": Set minimum relevance score. The default score is ",(0,o.jsx)(n.code,{children:"0"}),"."]}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["When you're done editing the filter, click ",(0,o.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To apply the filter to OpenRAG globally, click ",(0,o.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"All Knowledge"}),", and then select the filter to apply."]}),"\n",(0,o.jsxs)(n.p,{children:["To apply the filter to a single chat session, in the ",(0,o.jsx)(r.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Chat"})," window, click ",(0,o.jsx)(n.strong,{children:"@"}),", and then select the filter to apply."]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"openrag-default-configuration",children:"OpenRAG default configuration"}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG automatically detects and configures the correct vector dimensions for embedding models, ensuring optimal search performance and compatibility."}),"\n",(0,o.jsxs)(n.p,{children:["The complete list of supported models is available at ",(0,o.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/services/models_service.py",children:"/src/services/models_service.py"}),"."]}),"\n",(0,o.jsx)(n.p,{children:"You can use custom embedding models by specifying them in your configuration."}),"\n",(0,o.jsxs)(n.p,{children:["If you use an unknown embedding model, OpenRAG will automatically fall back to ",(0,o.jsx)(n.code,{children:"1536"})," dimensions and log a warning. The system will continue to work, but search quality may be affected if the actual model dimensions differ from ",(0,o.jsx)(n.code,{children:"1536"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["The default embedding dimension is ",(0,o.jsx)(n.code,{children:"1536"})," and the default model is ",(0,o.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["For models with known vector dimensions, see ",(0,o.jsx)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/config/settings.py",children:"/src/config/settings.py"}),"."]})]})}function x(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(p,{...e})}):p(e)}},3782:(e,n,s)=>{s.d(n,{Ay:()=>c,RM:()=>r});var i=s(4848),o=s(8453),t=s(9179);const r=[];function l(e){const n={a:"a",p:"p",strong:"strong",...(0,o.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)(t.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nFlows are edited in the same way as in the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),"."]})}function c(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(l,{...e})}):l(e)}},9179:(e,n,s)=>{s.d(n,{A:()=>t});s(6540);var i=s(4827),o=s(4848);function t({name:e,...n}){const s=i[e];return s?(0,o.jsx)(s,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/21afe7ac.215fefff.js b/assets/js/21afe7ac.215fefff.js deleted file mode 100644 index 9c289868..00000000 --- a/assets/js/21afe7ac.215fefff.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[961],{5689:(e,n,t)=>{t.d(n,{A:()=>s});const s=t.p+"assets/images/OpenRAG_TUI_2025-09-10T13_04_11_757637-9441c53ba39162a88ac6c11cbeaed0e0.svg"},6239:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>c,contentTitle:()=>a,default:()=>h,frontMatter:()=>o,metadata:()=>s,toc:()=>d});const s=JSON.parse('{"id":"get-started/tui","title":"Terminal User Interface (TUI) commands","description":"The OpenRAG Terminal User Interface (TUI) provides a streamlined way to set up, configure, and monitor your OpenRAG deployment directly from the terminal, on any operating system.","source":"@site/docs/get-started/tui.mdx","sourceDirName":"get-started","slug":"/get-started/tui","permalink":"/openrag/get-started/tui","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/tui.mdx","tags":[],"version":"current","frontMatter":{"title":"Terminal User Interface (TUI) commands","slug":"/get-started/tui"},"sidebar":"tutorialSidebar","previous":{"title":"Docker Deployment","permalink":"/openrag/get-started/docker"},"next":{"title":"Langflow Agents","permalink":"/openrag/agents"}}');var r=t(4848),i=t(8453);const o={title:"Terminal User Interface (TUI) commands",slug:"/get-started/tui"},a="OpenRAG TUI Guide",c={},d=[{value:"Start the TUI",id:"start-the-tui",level:2},{value:"Navigation",id:"navigation",level:2},{value:"Container management",id:"container-management",level:2},{value:"Start container services",id:"start-container-services",level:3},{value:"Start native services",id:"start-native-services",level:3},{value:"Status",id:"status",level:3},{value:"Diagnostics",id:"diagnostics",level:2}];function l(e){const n={a:"a",code:"code",h1:"h1",h2:"h2",h3:"h3",header:"header",img:"img",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,i.R)(),...e.components};return(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.header,{children:(0,r.jsx)(n.h1,{id:"openrag-tui-guide",children:"OpenRAG TUI Guide"})}),"\n",(0,r.jsx)(n.p,{children:"The OpenRAG Terminal User Interface (TUI) provides a streamlined way to set up, configure, and monitor your OpenRAG deployment directly from the terminal, on any operating system."}),"\n",(0,r.jsx)(n.p,{children:(0,r.jsx)(n.img,{alt:"OpenRAG TUI Interface",src:t(5689).A+"",width:"1995",height:"1099"})}),"\n",(0,r.jsxs)(n.p,{children:["The TUI offers an easier way to use OpenRAG without sacrificing control.\nInstead of starting OpenRAG using Docker commands and manually editing values in the ",(0,r.jsx)(n.code,{children:".env"})," file, the TUI walks you through the setup. It prompts for variables where required, creates a ",(0,r.jsx)(n.code,{children:".env"})," file for you, and then starts OpenRAG."]}),"\n",(0,r.jsx)(n.p,{children:"Once OpenRAG is running, use the TUI to monitor your application, control your containers, and retrieve logs."}),"\n",(0,r.jsx)(n.h2,{id:"start-the-tui",children:"Start the TUI"}),"\n",(0,r.jsxs)(n.p,{children:["To start the TUI, run the following commands from the directory where you installed OpenRAG.\nFor more information, see ",(0,r.jsx)(n.a,{href:"/install",children:"Install OpenRAG"}),"."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"uv sync\nuv run openrag\n"})}),"\n",(0,r.jsxs)(n.p,{children:["The TUI Welcome Screen offers basic and advanced setup options.\nFor more information on setup values during installation, see ",(0,r.jsx)(n.a,{href:"/install",children:"Install OpenRAG"}),"."]}),"\n",(0,r.jsx)(n.h2,{id:"navigation",children:"Navigation"}),"\n",(0,r.jsx)(n.p,{children:"The TUI accepts mouse input or keyboard commands."}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Arrow keys"}),": move between options"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Tab"}),"/",(0,r.jsx)("kbd",{children:"Shift+Tab"}),": switch fields and buttons"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Enter"}),": select/confirm"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Escape"}),": back"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Q"}),": quit"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Number keys (1-4)"}),": quick access to main screens"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"container-management",children:"Container management"}),"\n",(0,r.jsx)(n.p,{children:"The TUI can deploy, manage, and upgrade your OpenRAG containers."}),"\n",(0,r.jsx)(n.h3,{id:"start-container-services",children:"Start container services"}),"\n",(0,r.jsxs)(n.p,{children:["Click ",(0,r.jsx)(n.strong,{children:"Start Container 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,r.jsx)(n.code,{children:"CUDA"}),", ",(0,r.jsx)(n.code,{children:"NVIDIA_SMI"}),", and Docker/Podman runtime support. 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It prompts for variables where required, creates a ",(0,r.jsx)(n.code,{children:".env"})," file for you, and then starts OpenRAG."]}),"\n",(0,r.jsx)(n.p,{children:"Once OpenRAG is running, use the TUI to monitor your application, control your containers, and retrieve logs."}),"\n",(0,r.jsx)(n.h2,{id:"start-the-tui",children:"Start the TUI"}),"\n",(0,r.jsxs)(n.p,{children:["To start the TUI, run the following commands from the directory where you installed OpenRAG.\nFor more information, see ",(0,r.jsx)(n.a,{href:"/install",children:"Install OpenRAG"}),"."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"uv sync\nuv run openrag\n"})}),"\n",(0,r.jsxs)(n.p,{children:["The TUI Welcome Screen offers basic and advanced setup options.\nFor more information on setup values during installation, see ",(0,r.jsx)(n.a,{href:"/install",children:"Install OpenRAG"}),"."]}),"\n",(0,r.jsx)(n.h2,{id:"navigation",children:"Navigation"}),"\n",(0,r.jsx)(n.p,{children:"The TUI accepts mouse input or keyboard commands."}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Arrow keys"}),": move between options"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Tab"}),"/",(0,r.jsx)("kbd",{children:"Shift+Tab"}),": switch fields and buttons"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Enter"}),": select/confirm"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Escape"}),": back"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Q"}),": quit"]}),"\n",(0,r.jsxs)(n.li,{children:[(0,r.jsx)("kbd",{children:"Number keys (1-4)"}),": quick access to main screens"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"container-management",children:"Container management"}),"\n",(0,r.jsx)(n.p,{children:"The TUI can deploy, manage, and upgrade your OpenRAG containers."}),"\n",(0,r.jsx)(n.h3,{id:"start-container-services",children:"Start container services"}),"\n",(0,r.jsxs)(n.p,{children:["Click ",(0,r.jsx)(n.strong,{children:"Start Container 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,r.jsx)(n.code,{children:"CUDA"}),", ",(0,r.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,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{className:"language-bash",children:"docker compose up -d\n"})}),"\n",(0,r.jsxs)(n.p,{children:["If images are missing, the TUI runs ",(0,r.jsx)(n.code,{children:"docker compose pull"}),", then runs ",(0,r.jsx)(n.code,{children:"docker compose up -d"}),"."]}),"\n",(0,r.jsx)(n.h3,{id:"start-native-services",children:"Start native services"}),"\n",(0,r.jsxs)(n.p,{children:['A "native" service in OpenRAG refers to a service run natively on your machine, and not within a container.\nThe ',(0,r.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,r.jsxs)(n.p,{children:["To start or stop ",(0,r.jsx)(n.code,{children:"docling-serve"})," or any other native services, in the TUI main menu, click ",(0,r.jsx)(n.strong,{children:"Start Native Services"})," or ",(0,r.jsx)(n.strong,{children:"Stop Native Services"}),"."]}),"\n",(0,r.jsxs)(n.p,{children:["To view the status, port, or PID of a native service, in the TUI main menu, click ",(0,r.jsx)(n.a,{href:"#status",children:"Status"}),"."]}),"\n",(0,r.jsx)(n.h3,{id:"status",children:"Status"}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.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,r.jsxs)(n.p,{children:["To view streaming logs, select the container you want to view, and press ",(0,r.jsx)("kbd",{children:"l"}),".\nTo copy your logs, click ",(0,r.jsx)(n.strong,{children:"Copy to Clipboard"}),"."]}),"\n",(0,r.jsxs)(n.p,{children:["To ",(0,r.jsx)(n.strong,{children:"upgrade"})," your containers, click ",(0,r.jsx)(n.strong,{children:"Upgrade"}),".\n",(0,r.jsx)(n.strong,{children:"Upgrade"})," runs ",(0,r.jsx)(n.code,{children:"docker compose pull"})," and then ",(0,r.jsx)(n.code,{children:"docker compose up -d --force-recreate"}),".\nThe first command pulls the latest images of OpenRAG.\nThe second command recreates the containers with your data persisted."]}),"\n",(0,r.jsxs)(n.p,{children:["To ",(0,r.jsx)(n.strong,{children:"reset"})," your containers, click ",(0,r.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,r.jsx)(n.strong,{children:"Reset"})," runs two commands.\nIt first stops and removes all containers, volumes, and local images."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{children:"docker compose down --volumes --remove-orphans --rmi local\n"})}),"\n",(0,r.jsxs)(n.p,{children:["When the first command is complete, OpenRAG removes any additional Docker objects with ",(0,r.jsx)(n.code,{children:"prune"}),"."]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.jsx)(n.code,{children:"docker system prune -f\n"})}),"\n",(0,r.jsx)(n.h2,{id:"diagnostics",children:"Diagnostics"}),"\n",(0,r.jsxs)(n.p,{children:["The ",(0,r.jsx)(n.strong,{children:"Diagnostics"})," menu provides health monitoring for your container runtimes and monitoring of your OpenSearch security."]})]})}function h(e={}){const{wrapper:n}={...(0,i.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(l,{...e})}):l(e)}},8453:(e,n,t)=>{t.d(n,{R:()=>o,x:()=>a});var s=t(6540);const r={},i=s.createContext(r);function o(e){const n=s.useContext(i);return s.useMemo(function(){return"function"==typeof e?e(n):{...n,...e}},[n,e])}function a(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(r):e.components||r:o(e.components),s.createElement(i.Provider,{value:n},e.children)}}}]); 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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. 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operations"})]})]})]}),"\n",(0,s.jsx)(n.h2,{id:"openrag-configuration-variables",children:"OpenRAG Configuration Variables"}),"\n",(0,s.jsxs)(n.p,{children:["These environment variables override settings in ",(0,s.jsx)(n.code,{children:"config.yaml"}),":"]}),"\n",(0,s.jsx)(n.h3,{id:"provider-settings",children:"Provider Settings"}),"\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:"Description"}),(0,s.jsx)(n.th,{children:"Default"})]})}),(0,s.jsxs)(n.tbody,{children:[(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:"Model provider (openai, anthropic, etc.)"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"openai"})})]}),(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:"API key for the model provider"}),(0,s.jsx)(n.td,{})]}),(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:"OpenAI API key (backward compatibility)"}),(0,s.jsx)(n.td,{})]})]})]}),"\n",(0,s.jsx)(n.h3,{id:"knowledge-settings",children:"Knowledge Settings"}),"\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:"Description"}),(0,s.jsx)(n.th,{children:"Default"})]})}),(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:"Embedding model for vector search"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"text-embedding-3-small"})})]}),(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:"Text chunk size for document processing"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"1000"})})]}),(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:"Overlap between chunks"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"200"})})]}),(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:"Enable OCR for image processing"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"true"})})]}),(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:"Enable picture descriptions"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"false"})})]})]})]}),"\n",(0,s.jsx)(n.h3,{id:"agent-settings",children:"Agent Settings"}),"\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:"Description"}),(0,s.jsx)(n.th,{children:"Default"})]})}),(0,s.jsxs)(n.tbody,{children:[(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:"Language model for the chat agent"}),(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"gpt-4o-mini"})})]}),(0,s.jsxs)(n.tr,{children:[(0,s.jsx)(n.td,{children:(0,s.jsx)(n.code,{children:"SYSTEM_PROMPT"})}),(0,s.jsx)(n.td,{children:"System prompt for the agent"}),(0,s.jsx)(n.td,{children:"Default assistant prompt"})]})]})]}),"\n",(0,s.jsxs)(n.p,{children:["See ",(0,s.jsx)(n.code,{children:".env.example"})," for a complete list with descriptions, and ",(0,s.jsx)(n.code,{children:"docker-compose*.yml"})," for runtime usage."]})]})}function a(e={}){const{wrapper:n}={...(0,d.R)(),...e.components};return n?(0,s.jsx)(n,{...e,children:(0,s.jsx)(h,{...e})}):h(e)}},8453:(e,n,i)=>{i.d(n,{R:()=>t,x:()=>l});var r=i(6540);const s={},d=r.createContext(s);function t(e){const n=r.useContext(d);return r.useMemo(function(){return"function"==typeof e?e(n):{...n,...e}},[n,e])}function l(e){let n;return n=e.disableParentContext?"function"==typeof e.components?e.components(s):e.components||s:t(e.components),r.createElement(d.Provider,{value:n},e.children)}}}]); \ No newline at end of file diff --git a/assets/js/af920ffe.1ef126f6.js b/assets/js/af920ffe.1ef126f6.js new file mode 100644 index 00000000..d29a6b42 --- /dev/null +++ b/assets/js/af920ffe.1ef126f6.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[717],{1260:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>h,contentTitle:()=>c,default:()=>g,frontMatter:()=>d,metadata:()=>s,toc:()=>u});const s=JSON.parse('{"id":"get-started/quickstart","title":"Quickstart","description":"Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API.","source":"@site/docs/get-started/quickstart.mdx","sourceDirName":"get-started","slug":"/quickstart","permalink":"/quickstart","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/quickstart.mdx","tags":[],"version":"current","frontMatter":{"title":"Quickstart","slug":"/quickstart"},"sidebar":"tutorialSidebar","previous":{"title":"Installation","permalink":"/install"},"next":{"title":"Docker Deployment","permalink":"/get-started/docker"}}');var o=t(4848),r=t(8453),a=t(9179),i=t(1470),l=t(9365);const d={title:"Quickstart",slug:"/quickstart"},c=void 0,h={},u=[{value:"Prerequisites",id:"prerequisites",level:2},{value:"Find your way around",id:"find-your-way-around",level:2},{value:"Add your own knowledge",id:"add-your-own-knowledge",level:2},{value:"Swap out the language model to modify agent behavior",id:"change-components",level:2},{value:"Integrate OpenRAG into your application",id:"integrate-openrag-into-your-application",level:2}];function p(e){const n={a:"a",code:"code",h2:"h2",img:"img",li:"li",ol:"ol",p:"p",pre:"pre",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.jsx)(n.p,{children:"Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API."}),"\n",(0,o.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:(0,o.jsx)(n.a,{href:"/install",children:"Install and start OpenRAG"})}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Create a ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"})]}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Create a Langflow API key"}),(0,o.jsxs)(n.p,{children:["A Langflow API key is a user-specific token you can use with Langflow.\nIt is ",(0,o.jsx)(n.strong,{children:"only"})," used for sending requests to the Langflow server.\nIt does ",(0,o.jsx)(n.strong,{children:"not"})," access to OpenRAG."]}),(0,o.jsx)(n.p,{children:"To create a Langflow API key, do the following:"}),(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["In Langflow, click your user icon, and then select ",(0,o.jsx)(n.strong,{children:"Settings"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Click ",(0,o.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,o.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add New"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Name your key, and then click ",(0,o.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Copy the API key and store it securely."}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To use your Langflow API key in a request, set a ",(0,o.jsx)(n.code,{children:"LANGFLOW_API_KEY"})," environment variable in your terminal, and then include an ",(0,o.jsx)(n.code,{children:"x-api-key"})," header or query parameter with your request.\nFor example:"]}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:'# Set variable\nexport LANGFLOW_API_KEY="sk..."\n\n# Send request\ncurl --request POST \\\n--url "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" \\\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"\n}\'\n'})}),"\n"]}),"\n"]})]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"find-your-way-around",children:"Find your way around"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["In OpenRAG, click ",(0,o.jsx)(a.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Chat"}),".\nThe chat is powered by the OpenRAG OpenSearch Agent.\nFor more information, see ",(0,o.jsx)(n.a,{href:"/agents",children:"Langflow Agents"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Ask ",(0,o.jsx)(n.code,{children:"What documents are available to you?"}),"\nThe agent responds with a message summarizing the documents that OpenRAG loads by default, which are PDFs about evaluating data quality when using LLMs in health care.\nKnowledge is stored in OpenSearch.\nFor more information, see ",(0,o.jsx)(n.a,{href:"/knowledge",children:"Knowledge"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To confirm the agent is correct, click ",(0,o.jsx)(a.A,{name:"Library","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Knowledge"}),".\nThe ",(0,o.jsx)(n.strong,{children:"Knowledge"})," page lists the documents OpenRAG has ingested into the OpenSearch vector database.\nClick on a document to display the chunks derived from splitting the default documents into the vector database."]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"add-your-own-knowledge",children:"Add your own knowledge"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["To add documents to your knowledge base, click ",(0,o.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),".","\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["Select ",(0,o.jsx)(n.strong,{children:"Add File"})," to add a single file from your local machine (mapped with the Docker volume mount)."]}),"\n",(0,o.jsxs)(n.li,{children:["Select ",(0,o.jsx)(n.strong,{children:"Process Folder"})," to process an entire folder of documents from your local machine (mapped with the Docker volume mount)."]}),"\n",(0,o.jsxs)(n.li,{children:["Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see ",(0,o.jsx)(n.a,{href:"/knowledge#oauth-ingestion",children:"OAuth ingestion"}),"."]}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["Return to the Chat window and ask a question about your loaded data.\nFor example, with a manual about a PC tablet loaded, ask ",(0,o.jsx)(n.code,{children:"How do I connect this device to WiFI?"}),"\nThe agent responds with a message indicating it now has your knowledge as context for answering questions."]}),"\n",(0,o.jsxs)(n.li,{children:["Click the ",(0,o.jsx)(a.A,{name:"Gear","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Function Call: search_documents (tool_call)"})," that is printed in the Playground.\nThese events log the agent's request to the tool and the tool's response, so you have direct visibility into your agent's functionality.\nIf you aren't getting the results you need, you can further tune the knowledge ingestion and agent behavior in the next section."]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"change-components",children:"Swap out the language model to modify agent behavior"}),"\n",(0,o.jsxs)(n.p,{children:["To modify the knowledge ingestion or Agent behavior, click ",(0,o.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["In this example, you'll try a different LLM to demonstrate how the Agent's response changes.\nYou can only change the ",(0,o.jsx)(n.strong,{children:"Language model"}),", and not the ",(0,o.jsx)(n.strong,{children:"Model provider"})," that you started with in OpenRAG.\nIf you're using Ollama, you can use any installed model."]}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To edit the Agent's behavior, click ",(0,o.jsx)(n.strong,{children:"Edit in Langflow"}),".\nYou can more quickly access the ",(0,o.jsx)(n.strong,{children:"Language Model"})," and ",(0,o.jsx)(n.strong,{children:"Agent Instructions"})," fields in this page, but for illustration purposes, navigate to the Langflow visual builder."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["OpenRAG warns you that you're entering Langflow. Click ",(0,o.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["The OpenRAG OpenSearch Agent flow appears.\n",(0,o.jsx)(n.img,{alt:"OpenRAG Open Search Agent Flow",src:t(3982).A+"",width:"4108",height:"2250"})]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["In the ",(0,o.jsx)(n.strong,{children:"Language Model"})," component, under ",(0,o.jsx)(n.strong,{children:"Model"}),", select a different OpenAI model."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Save your flow with ",(0,o.jsx)("kbd",{children:"Command+S"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["In OpenRAG, start a new conversation by clicking the ",(0,o.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," in the ",(0,o.jsx)(n.strong,{children:"Conversations"})," tab."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Ask the same question as before to demonstrate how a different language model changes the results."}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"integrate-openrag-into-your-application",children:"Integrate OpenRAG into your application"}),"\n",(0,o.jsxs)(n.p,{children:["To integrate OpenRAG into your application, use the ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Langflow API"}),".\nMake requests with Python, TypeScript, or any HTTP client to run one of OpenRAG's default flows and get a response, and then modify the flow further to improve results."]}),"\n",(0,o.jsx)(n.p,{children:"Langflow provides code snippets to help you get started with the Langflow API."}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To navigate to the OpenRAG OpenSearch Agent flow, click ",(0,o.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"}),", and then click ",(0,o.jsx)(n.strong,{children:"Edit in Langflow"})," in the OpenRAG OpenSearch Agent flow."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Click ",(0,o.jsx)(n.strong,{children:"Share"}),", and then click ",(0,o.jsx)(n.strong,{children:"API access"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["The default code in the API access pane constructs a request with the Langflow server ",(0,o.jsx)(n.code,{children:"url"}),", ",(0,o.jsx)(n.code,{children:"headers"}),", and a ",(0,o.jsx)(n.code,{children:"payload"})," of request data. The code snippets automatically include the ",(0,o.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"})," and ",(0,o.jsx)(n.code,{children:"FLOW_ID"})," values for the flow. Replace these values if you're using the code for a different server or flow. The default Langflow server address is ",(0,o.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"}),"."]}),"\n",(0,o.jsxs)(i.A,{children:[(0,o.jsx)(l.A,{value:"python",label:"Python",children:(0,o.jsx)(n.pre,{children:(0,o.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,o.jsx)(l.A,{value:"typescript",label:"TypeScript",children:(0,o.jsx)(n.pre,{children:(0,o.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,o.jsx)(l.A,{value:"curl",label:"curl",children:(0,o.jsx)(n.pre,{children:(0,o.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\t\t "output_type": "chat",\n\t\t "input_type": "chat",\n\t\t "input_value": "hello world!",\n\t\t }\'\n'})})})]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Copy the snippet, paste it in a script file, and then run the script to send the request. If you are using the curl snippet, you can run the command directly in your terminal."}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(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.\nThe following is an example of a response from running the ",(0,o.jsx)(n.strong,{children:"Simple Agent"})," template flow:"]}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Result"}),(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-json",children:'{\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "outputs": [\n {\n "inputs": {\n "input_value": "hello world!"\n },\n "outputs": [\n {\n "results": {\n "message": {\n "text_key": "text",\n "data": {\n "timestamp": "2025-06-16 19:58:23 UTC",\n "sender": "Machine",\n "sender_name": "AI",\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "text": "Hello world! \ud83c\udf0d How can I assist you today?",\n "files": [],\n "error": false,\n "edit": false,\n "properties": {\n "text_color": "",\n "background_color": "",\n "edited": false,\n "source": {\n "id": "Agent-ZOknz",\n "display_name": "Agent",\n "source": "gpt-4o-mini"\n },\n "icon": "bot",\n "allow_markdown": false,\n "positive_feedback": null,\n "state": "complete",\n "targets": []\n },\n "category": "message",\n "content_blocks": [\n {\n "title": "Agent Steps",\n "contents": [\n {\n "type": "text",\n "duration": 2,\n "header": {\n "title": "Input",\n "icon": "MessageSquare"\n },\n "text": "**Input**: hello world!"\n },\n {\n "type": "text",\n "duration": 226,\n "header": {\n "title": "Output",\n "icon": "MessageSquare"\n },\n "text": "Hello world! \ud83c\udf0d How can I assist you today?"\n }\n ],\n "allow_markdown": true,\n "media_url": null\n }\n ],\n "id": "f3d85d9a-261c-4325-b004-95a1bf5de7ca",\n "flow_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "duration": null\n },\n "default_value": "",\n "text": "Hello world! \ud83c\udf0d How can I assist you today?",\n "sender": "Machine",\n "sender_name": "AI",\n "files": [],\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "timestamp": "2025-06-16T19:58:23+00:00",\n "flow_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "error": false,\n "edit": false,\n "properties": {\n "text_color": "",\n "background_color": "",\n "edited": false,\n "source": {\n "id": "Agent-ZOknz",\n "display_name": "Agent",\n "source": "gpt-4o-mini"\n },\n "icon": "bot",\n "allow_markdown": false,\n "positive_feedback": null,\n "state": "complete",\n "targets": []\n },\n "category": "message",\n "content_blocks": [\n {\n "title": "Agent Steps",\n "contents": [\n {\n "type": "text",\n "duration": 2,\n "header": {\n "title": "Input",\n "icon": "MessageSquare"\n },\n "text": "**Input**: hello world!"\n },\n {\n "type": "text",\n "duration": 226,\n "header": {\n "title": "Output",\n "icon": "MessageSquare"\n },\n "text": "Hello world! \ud83c\udf0d How can I assist you today?"\n }\n ],\n "allow_markdown": true,\n "media_url": null\n }\n ],\n "duration": null\n }\n },\n "artifacts": {\n "message": "Hello world! \ud83c\udf0d How can I assist you today?",\n "sender": "Machine",\n "sender_name": "AI",\n "files": [],\n "type": "object"\n },\n "outputs": {\n "message": {\n "message": "Hello world! \ud83c\udf0d How can I assist you today?",\n "type": "text"\n }\n },\n "logs": {\n "message": []\n },\n "messages": [\n {\n "message": "Hello world! \ud83c\udf0d How can I assist you today?",\n "sender": "Machine",\n "sender_name": "AI",\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "stream_url": null,\n "component_id": "ChatOutput-aF5lw",\n "files": [],\n "type": "text"\n }\n ],\n "timedelta": null,\n "duration": null,\n "component_display_name": "Chat Output",\n "component_id": "ChatOutput-aF5lw",\n "used_frozen_result": false\n }\n ]\n }\n ]\n}\n'})})]}),"\n",(0,o.jsx)(n.p,{children:"To further explore the API, see:"}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["The Langflow ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/quickstart#extract-data-from-the-response",children:"Quickstart"})," extends this example with extracting fields from the response."]}),"\n",(0,o.jsx)(n.li,{children:(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Get started with the Langflow API"})}),"\n"]})]})}function g(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(p,{...e})}):p(e)}},3982:(e,n,t)=>{t.d(n,{A:()=>s});const s=t.p+"assets/images/opensearch-agent-flow-a3c183a9f2d5ec513819aba1f1b49c39.png"},9179:(e,n,t)=>{t.d(n,{A:()=>r});t(6540);var s=t(4827),o=t(4848);function r({name:e,...n}){const t=s[e];return t?(0,o.jsx)(t,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/af920ffe.646b8dda.js b/assets/js/af920ffe.646b8dda.js deleted file mode 100644 index c49f74da..00000000 --- a/assets/js/af920ffe.646b8dda.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[717],{1260:(e,n,t)=>{t.r(n),t.d(n,{assets:()=>h,contentTitle:()=>c,default:()=>g,frontMatter:()=>d,metadata:()=>s,toc:()=>u});const s=JSON.parse('{"id":"get-started/quickstart","title":"Quickstart","description":"Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API.","source":"@site/docs/get-started/quickstart.mdx","sourceDirName":"get-started","slug":"/quickstart","permalink":"/openrag/quickstart","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/get-started/quickstart.mdx","tags":[],"version":"current","frontMatter":{"title":"Quickstart","slug":"/quickstart"},"sidebar":"tutorialSidebar","previous":{"title":"Installation","permalink":"/openrag/install"},"next":{"title":"Docker Deployment","permalink":"/openrag/get-started/docker"}}');var o=t(4848),r=t(8453),a=t(9179),i=t(1470),l=t(9365);const d={title:"Quickstart",slug:"/quickstart"},c=void 0,h={},u=[{value:"Prerequisites",id:"prerequisites",level:2},{value:"Find your way around",id:"find-your-way-around",level:2},{value:"Add your own knowledge",id:"add-your-own-knowledge",level:2},{value:"Swap out the language model to modify agent behavior",id:"change-components",level:2},{value:"Integrate OpenRAG into your application",id:"integrate-openrag-into-your-application",level:2}];function p(e){const n={a:"a",code:"code",h2:"h2",img:"img",li:"li",ol:"ol",p:"p",pre:"pre",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.jsx)(n.p,{children:"Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API."}),"\n",(0,o.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:(0,o.jsx)(n.a,{href:"/install",children:"Install and start OpenRAG"})}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Create a ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"})]}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Create a Langflow API key"}),(0,o.jsxs)(n.p,{children:["A Langflow API key is a user-specific token you can use with Langflow.\nIt is ",(0,o.jsx)(n.strong,{children:"only"})," used for sending requests to the Langflow server.\nIt does ",(0,o.jsx)(n.strong,{children:"not"})," access to OpenRAG."]}),(0,o.jsx)(n.p,{children:"To create a Langflow API key, do the following:"}),(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["In Langflow, click your user icon, and then select ",(0,o.jsx)(n.strong,{children:"Settings"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Click ",(0,o.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,o.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add New"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Name your key, and then click ",(0,o.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Copy the API key and store it securely."}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To use your Langflow API key in a request, set a ",(0,o.jsx)(n.code,{children:"LANGFLOW_API_KEY"})," environment variable in your terminal, and then include an ",(0,o.jsx)(n.code,{children:"x-api-key"})," header or query parameter with your request.\nFor example:"]}),"\n",(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-bash",children:'# Set variable\nexport LANGFLOW_API_KEY="sk..."\n\n# Send request\ncurl --request POST \\\n--url "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" \\\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"\n}\'\n'})}),"\n"]}),"\n"]})]}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"find-your-way-around",children:"Find your way around"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["In OpenRAG, click ",(0,o.jsx)(a.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Chat"}),".\nThe chat is powered by the OpenRAG OpenSearch Agent.\nFor more information, see ",(0,o.jsx)(n.a,{href:"/agents",children:"Langflow Agents"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["Ask ",(0,o.jsx)(n.code,{children:"What documents are available to you?"}),"\nThe agent responds with a message summarizing the documents that OpenRAG loads by default, which are PDFs about evaluating data quality when using LLMs in health care.\nKnowledge is stored in OpenSearch.\nFor more information, see ",(0,o.jsx)(n.a,{href:"/knowledge",children:"Knowledge"}),"."]}),"\n",(0,o.jsxs)(n.li,{children:["To confirm the agent is correct, click ",(0,o.jsx)(a.A,{name:"Library","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Knowledge"}),".\nThe ",(0,o.jsx)(n.strong,{children:"Knowledge"})," page lists the documents OpenRAG has ingested into the OpenSearch vector database.\nClick on a document to display the chunks derived from splitting the default documents into the vector database."]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"add-your-own-knowledge",children:"Add your own knowledge"}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["To add documents to your knowledge base, click ",(0,o.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Add Knowledge"}),".","\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["Select ",(0,o.jsx)(n.strong,{children:"Add File"})," to add a single file from your local machine (mapped with the Docker volume mount)."]}),"\n",(0,o.jsxs)(n.li,{children:["Select ",(0,o.jsx)(n.strong,{children:"Process Folder"})," to process an entire folder of documents from your local machine (mapped with the Docker volume mount)."]}),"\n",(0,o.jsxs)(n.li,{children:["Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see ",(0,o.jsx)(n.a,{href:"/knowledge#oauth-ingestion",children:"OAuth ingestion"}),"."]}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["Return to the Chat window and ask a question about your loaded data.\nFor example, with a manual about a PC tablet loaded, ask ",(0,o.jsx)(n.code,{children:"How do I connect this device to WiFI?"}),"\nThe agent responds with a message indicating it now has your knowledge as context for answering questions."]}),"\n",(0,o.jsxs)(n.li,{children:["Click the ",(0,o.jsx)(a.A,{name:"Gear","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Function Call: search_documents (tool_call)"})," that is printed in the Playground.\nThese events log the agent's request to the tool and the tool's response, so you have direct visibility into your agent's functionality.\nIf you aren't getting the results you need, you can further tune the knowledge ingestion and agent behavior in the next section."]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"change-components",children:"Swap out the language model to modify agent behavior"}),"\n",(0,o.jsxs)(n.p,{children:["To modify the knowledge ingestion or Agent behavior, click ",(0,o.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["In this example, you'll try a different LLM to demonstrate how the Agent's response changes.\nYou can only change the ",(0,o.jsx)(n.strong,{children:"Language model"}),", and not the ",(0,o.jsx)(n.strong,{children:"Model provider"})," that you started with in OpenRAG.\nIf you're using Ollama, you can use any installed model."]}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To edit the Agent's behavior, click ",(0,o.jsx)(n.strong,{children:"Edit in Langflow"}),".\nYou can more quickly access the ",(0,o.jsx)(n.strong,{children:"Language Model"})," and ",(0,o.jsx)(n.strong,{children:"Agent Instructions"})," fields in this page, but for illustration purposes, navigate to the Langflow visual builder."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["OpenRAG warns you that you're entering Langflow. Click ",(0,o.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["The OpenRAG OpenSearch Agent flow appears.\n",(0,o.jsx)(n.img,{alt:"OpenRAG Open Search Agent Flow",src:t(3982).A+"",width:"4108",height:"2250"})]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["In the ",(0,o.jsx)(n.strong,{children:"Language Model"})," component, under ",(0,o.jsx)(n.strong,{children:"Model"}),", select a different OpenAI model."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Save your flow with ",(0,o.jsx)("kbd",{children:"Command+S"}),"."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["In OpenRAG, start a new conversation by clicking the ",(0,o.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," in the ",(0,o.jsx)(n.strong,{children:"Conversations"})," tab."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Ask the same question as before to demonstrate how a different language model changes the results."}),"\n"]}),"\n"]}),"\n",(0,o.jsx)(n.h2,{id:"integrate-openrag-into-your-application",children:"Integrate OpenRAG into your application"}),"\n",(0,o.jsxs)(n.p,{children:["To integrate OpenRAG into your application, use the ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Langflow API"}),".\nMake requests with Python, TypeScript, or any HTTP client to run one of OpenRAG's default flows and get a response, and then modify the flow further to improve results."]}),"\n",(0,o.jsx)(n.p,{children:"Langflow provides code snippets to help you get started with the Langflow API."}),"\n",(0,o.jsxs)(n.ol,{children:["\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["To navigate to the OpenRAG OpenSearch Agent flow, click ",(0,o.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,o.jsx)(n.strong,{children:"Settings"}),", and then click ",(0,o.jsx)(n.strong,{children:"Edit in Langflow"})," in the OpenRAG OpenSearch Agent flow."]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsxs)(n.p,{children:["Click ",(0,o.jsx)(n.strong,{children:"Share"}),", and then click ",(0,o.jsx)(n.strong,{children:"API access"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:["The default code in the API access pane constructs a request with the Langflow server ",(0,o.jsx)(n.code,{children:"url"}),", ",(0,o.jsx)(n.code,{children:"headers"}),", and a ",(0,o.jsx)(n.code,{children:"payload"})," of request data. The code snippets automatically include the ",(0,o.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"})," and ",(0,o.jsx)(n.code,{children:"FLOW_ID"})," values for the flow. Replace these values if you're using the code for a different server or flow. The default Langflow server address is ",(0,o.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"}),"."]}),"\n",(0,o.jsxs)(i.A,{children:[(0,o.jsx)(l.A,{value:"python",label:"Python",children:(0,o.jsx)(n.pre,{children:(0,o.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,o.jsx)(l.A,{value:"typescript",label:"TypeScript",children:(0,o.jsx)(n.pre,{children:(0,o.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,o.jsx)(l.A,{value:"curl",label:"curl",children:(0,o.jsx)(n.pre,{children:(0,o.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\t\t "output_type": "chat",\n\t\t "input_type": "chat",\n\t\t "input_value": "hello world!",\n\t\t }\'\n'})})})]}),"\n"]}),"\n",(0,o.jsxs)(n.li,{children:["\n",(0,o.jsx)(n.p,{children:"Copy the snippet, paste it in a script file, and then run the script to send the request. If you are using the curl snippet, you can run the command directly in your terminal."}),"\n"]}),"\n"]}),"\n",(0,o.jsxs)(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.\nThe following is an example of a response from running the ",(0,o.jsx)(n.strong,{children:"Simple Agent"})," template flow:"]}),"\n",(0,o.jsxs)(s,{children:[(0,o.jsx)("summary",{children:"Result"}),(0,o.jsx)(n.pre,{children:(0,o.jsx)(n.code,{className:"language-json",children:'{\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "outputs": [\n {\n "inputs": {\n "input_value": "hello world!"\n },\n "outputs": [\n {\n "results": {\n "message": {\n "text_key": "text",\n "data": {\n "timestamp": "2025-06-16 19:58:23 UTC",\n "sender": "Machine",\n "sender_name": "AI",\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "text": "Hello world! \ud83c\udf0d How can I assist you today?",\n "files": [],\n "error": false,\n "edit": false,\n "properties": {\n "text_color": "",\n "background_color": "",\n "edited": false,\n "source": {\n "id": "Agent-ZOknz",\n "display_name": "Agent",\n "source": "gpt-4o-mini"\n },\n "icon": "bot",\n "allow_markdown": false,\n "positive_feedback": null,\n "state": "complete",\n "targets": []\n },\n "category": "message",\n "content_blocks": [\n {\n "title": "Agent Steps",\n "contents": [\n {\n "type": "text",\n "duration": 2,\n "header": {\n "title": "Input",\n "icon": "MessageSquare"\n },\n "text": "**Input**: hello world!"\n },\n {\n "type": "text",\n "duration": 226,\n "header": {\n "title": "Output",\n "icon": "MessageSquare"\n },\n "text": "Hello world! \ud83c\udf0d How can I assist you today?"\n }\n ],\n "allow_markdown": true,\n "media_url": null\n }\n ],\n "id": "f3d85d9a-261c-4325-b004-95a1bf5de7ca",\n "flow_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "duration": null\n },\n "default_value": "",\n "text": "Hello world! \ud83c\udf0d How can I assist you today?",\n "sender": "Machine",\n "sender_name": "AI",\n "files": [],\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "timestamp": "2025-06-16T19:58:23+00:00",\n "flow_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "error": false,\n "edit": false,\n "properties": {\n "text_color": "",\n "background_color": "",\n "edited": false,\n "source": {\n "id": "Agent-ZOknz",\n "display_name": "Agent",\n "source": "gpt-4o-mini"\n },\n "icon": "bot",\n "allow_markdown": false,\n "positive_feedback": null,\n "state": "complete",\n "targets": []\n },\n "category": "message",\n "content_blocks": [\n {\n "title": "Agent Steps",\n "contents": [\n {\n "type": "text",\n "duration": 2,\n "header": {\n "title": "Input",\n "icon": "MessageSquare"\n },\n "text": "**Input**: hello world!"\n },\n {\n "type": "text",\n "duration": 226,\n "header": {\n "title": "Output",\n "icon": "MessageSquare"\n },\n "text": "Hello world! \ud83c\udf0d How can I assist you today?"\n }\n ],\n "allow_markdown": true,\n "media_url": null\n }\n ],\n "duration": null\n }\n },\n "artifacts": {\n "message": "Hello world! \ud83c\udf0d How can I assist you today?",\n "sender": "Machine",\n "sender_name": "AI",\n "files": [],\n "type": "object"\n },\n "outputs": {\n "message": {\n "message": "Hello world! \ud83c\udf0d How can I assist you today?",\n "type": "text"\n }\n },\n "logs": {\n "message": []\n },\n "messages": [\n {\n "message": "Hello world! \ud83c\udf0d How can I assist you today?",\n "sender": "Machine",\n "sender_name": "AI",\n "session_id": "29deb764-af3f-4d7d-94a0-47491ed241d6",\n "stream_url": null,\n "component_id": "ChatOutput-aF5lw",\n "files": [],\n "type": "text"\n }\n ],\n "timedelta": null,\n "duration": null,\n "component_display_name": "Chat Output",\n "component_id": "ChatOutput-aF5lw",\n "used_frozen_result": false\n }\n ]\n }\n ]\n}\n'})})]}),"\n",(0,o.jsx)(n.p,{children:"To further explore the API, see:"}),"\n",(0,o.jsxs)(n.ul,{children:["\n",(0,o.jsxs)(n.li,{children:["The Langflow ",(0,o.jsx)(n.a,{href:"https://docs.langflow.org/quickstart#extract-data-from-the-response",children:"Quickstart"})," extends this example with extracting fields from the response."]}),"\n",(0,o.jsx)(n.li,{children:(0,o.jsx)(n.a,{href:"https://docs.langflow.org/api-reference-api-examples",children:"Get started with the Langflow API"})}),"\n"]})]})}function g(e={}){const{wrapper:n}={...(0,r.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(p,{...e})}):p(e)}},3982:(e,n,t)=>{t.d(n,{A:()=>s});const s=t.p+"assets/images/opensearch-agent-flow-a3c183a9f2d5ec513819aba1f1b49c39.png"},9179:(e,n,t)=>{t.d(n,{A:()=>r});t(6540);var s=t(4827),o=t(4848);function r({name:e,...n}){const t=s[e];return t?(0,o.jsx)(t,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/ca2c3c0c.40e07761.js b/assets/js/ca2c3c0c.40e07761.js deleted file mode 100644 index 46baa793..00000000 --- a/assets/js/ca2c3c0c.40e07761.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[919],{3782:(e,n,s)=>{s.d(n,{Ay:()=>a,RM:()=>r});var i=s(4848),o=s(8453),t=s(9179);const r=[];function c(e){const n={a:"a",p:"p",strong:"strong",...(0,o.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)(t.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nFlows are edited in the same way as in the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),"."]})}function a(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(c,{...e})}):c(e)}},7125:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>a,contentTitle:()=>c,default:()=>g,frontMatter:()=>r,metadata:()=>i,toc:()=>l});const i=JSON.parse('{"id":"core-components/ingestion","title":"Docling Ingestion","description":"OpenRAG uses Docling for its document ingestion pipeline.","source":"@site/docs/core-components/ingestion.mdx","sourceDirName":"core-components","slug":"/ingestion","permalink":"/openrag/ingestion","draft":false,"unlisted":false,"editUrl":"https://github.com/openrag/openrag/tree/main/docs/docs/core-components/ingestion.mdx","tags":[],"version":"current","frontMatter":{"title":"Docling Ingestion","slug":"/ingestion"},"sidebar":"tutorialSidebar","previous":{"title":"OpenSearch Knowledge","permalink":"/openrag/knowledge"},"next":{"title":"Environment Variables","permalink":"/openrag/configure/configuration"}}');var o=s(4848),t=s(8453);s(9179),s(1470),s(9365),s(3782);const r={title:"Docling Ingestion",slug:"/ingestion"},c=void 0,a={},l=[{value:"Docling ingestion settings",id:"docling-ingestion-settings",level:2},{value:"Use OpenRAG default ingestion instead of Docling serve",id:"use-openrag-default-ingestion-instead-of-docling-serve",level:2}];function d(e){const n={a:"a",code:"code",h2:"h2",p:"p",strong:"strong",...(0,t.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.p,{children:["OpenRAG uses ",(0,o.jsx)(n.a,{href:"https://docling-project.github.io/docling/",children:"Docling"})," for its document ingestion pipeline.\nMore specifically, OpenRAG uses ",(0,o.jsx)(n.a,{href:"https://github.com/docling-project/docling-serve",children:"Docling Serve"}),", which starts a ",(0,o.jsx)(n.code,{children:"docling-serve"})," process on your local machine and runs Docling ingestion through an API service."]}),"\n",(0,o.jsxs)(n.p,{children:["Docling ingests documents from your local machine or OAuth connectors, splits them into chunks, and stores them as separate, structured documents in the OpenSearch ",(0,o.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG chose Docling for its support for a wide variety of file formats, high performance, and advanced understanding of tables and images."}),"\n",(0,o.jsx)(n.h2,{id:"docling-ingestion-settings",children:"Docling ingestion settings"}),"\n",(0,o.jsx)(n.p,{children:"These settings configure the Docling ingestion parameters."}),"\n",(0,o.jsxs)(n.p,{children:["OpenRAG will warn you if ",(0,o.jsx)(n.code,{children:"docling-serve"})," is not running.\nTo start or stop ",(0,o.jsx)(n.code,{children:"docling-serve"})," or any other native services, in the TUI main menu, click ",(0,o.jsx)(n.strong,{children:"Start Native Services"})," or ",(0,o.jsx)(n.strong,{children:"Stop Native Services"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Embedding model"})," determines which AI model is used to create vector embeddings. 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Enabling picture descriptions can slow ingestion performance."]}),"\n",(0,o.jsx)(n.h2,{id:"use-openrag-default-ingestion-instead-of-docling-serve",children:"Use OpenRAG default ingestion instead of Docling serve"}),"\n",(0,o.jsxs)(n.p,{children:["If you want to use OpenRAG's built-in pipeline instead of Docling serve, set ",(0,o.jsx)(n.code,{children:"DISABLE_INGEST_WITH_LANGFLOW=true"})," in ",(0,o.jsx)(n.a,{href:"/configure/configuration#ingestion-configuration",children:"Environment variables"}),"."]}),"\n",(0,o.jsx)(n.p,{children:"The built-in pipeline still uses the Docling processor, but uses it directly without the Docling Serve API."}),"\n",(0,o.jsxs)(n.p,{children:["For more information, see ",(0,o.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/models/processors.py#L58",children:[(0,o.jsx)(n.code,{children:"processors.py"})," in the OpenRAG repository"]}),"."]})]})}function g(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,o.jsx)(n,{...e,children:(0,o.jsx)(d,{...e})}):d(e)}},9179:(e,n,s)=>{s.d(n,{A:()=>t});s(6540);var i=s(4827),o=s(4848);function t({name:e,...n}){const s=i[e];return s?(0,o.jsx)(s,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/ca2c3c0c.6fd3d15e.js b/assets/js/ca2c3c0c.6fd3d15e.js new file mode 100644 index 00000000..65b46dcc --- /dev/null +++ b/assets/js/ca2c3c0c.6fd3d15e.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkopenrag_docs=self.webpackChunkopenrag_docs||[]).push([[919],{3782:(e,n,s)=>{s.d(n,{Ay:()=>a,RM:()=>r});var i=s(4848),o=s(8453),t=s(9179);const r=[];function c(e){const n={a:"a",p:"p",strong:"strong",...(0,o.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)(t.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nFlows are edited in the same way as in the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),"."]})}function a(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(c,{...e})}):c(e)}},7125:(e,n,s)=>{s.r(n),s.d(n,{assets:()=>a,contentTitle:()=>c,default:()=>h,frontMatter:()=>r,metadata:()=>i,toc:()=>l});const i=JSON.parse('{"id":"core-components/ingestion","title":"Docling Ingestion","description":"OpenRAG uses Docling for its document ingestion pipeline.","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":"Docling Ingestion","slug":"/ingestion"},"sidebar":"tutorialSidebar","previous":{"title":"OpenSearch Knowledge","permalink":"/knowledge"},"next":{"title":"Environment Variables","permalink":"/configure/configuration"}}');var o=s(4848),t=s(8453);s(9179),s(1470),s(9365),s(3782);const r={title:"Docling Ingestion",slug:"/ingestion"},c=void 0,a={},l=[{value:"Docling ingestion settings",id:"docling-ingestion-settings",level:2},{value:"Use OpenRAG default ingestion instead of Docling serve",id:"use-openrag-default-ingestion-instead-of-docling-serve",level:2}];function d(e){const n={a:"a",code:"code",h2:"h2",p:"p",strong:"strong",...(0,t.R)(),...e.components};return(0,o.jsxs)(o.Fragment,{children:[(0,o.jsxs)(n.p,{children:["OpenRAG uses ",(0,o.jsx)(n.a,{href:"https://docling-project.github.io/docling/",children:"Docling"})," for its document ingestion pipeline.\nMore specifically, OpenRAG uses ",(0,o.jsx)(n.a,{href:"https://github.com/docling-project/docling-serve",children:"Docling Serve"}),", which starts a ",(0,o.jsx)(n.code,{children:"docling-serve"})," process on your local machine and runs Docling ingestion through an API service."]}),"\n",(0,o.jsxs)(n.p,{children:["Docling ingests documents from your local machine or OAuth connectors, splits them into chunks, and stores them as separate, structured documents in the OpenSearch ",(0,o.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,o.jsx)(n.p,{children:"OpenRAG chose Docling for its support for a wide variety of file formats, high performance, and advanced understanding of tables and images."}),"\n",(0,o.jsx)(n.h2,{id:"docling-ingestion-settings",children:"Docling ingestion settings"}),"\n",(0,o.jsx)(n.p,{children:"These settings configure the Docling ingestion parameters."}),"\n",(0,o.jsxs)(n.p,{children:["OpenRAG will warn you if ",(0,o.jsx)(n.code,{children:"docling-serve"})," is not running.\nTo start or stop ",(0,o.jsx)(n.code,{children:"docling-serve"})," or any other native services, in the TUI main menu, click ",(0,o.jsx)(n.strong,{children:"Start Native Services"})," or ",(0,o.jsx)(n.strong,{children:"Stop Native Services"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Embedding model"})," determines which AI model is used to create vector embeddings. The default is ",(0,o.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Chunk size"})," determines how large each text chunk is in number of characters.\nLarger chunks yield more context per chunk, but may include irrelevant information. Smaller chunks yield more precise semantic search, but may lack context.\nThe default value of ",(0,o.jsx)(n.code,{children:"1000"})," characters provides a good starting point that balances these considerations."]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Chunk overlap"})," controls the number of characters that overlap over chunk boundaries.\nUse larger overlap values for documents where context is most important, and use smaller overlap values for simpler documents, or when optimization is most important.\nThe default value of 200 characters of overlap with a chunk size of 1000 (20% overlap) is suitable for general use cases. 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Enabling OCR can slow ingestion performance."}),"\n",(0,o.jsxs)(n.p,{children:["If OpenRAG detects that the local machine is running on macOS, OpenRAG uses the ",(0,o.jsx)(n.a,{href:"https://www.piwheels.org/project/ocrmac/",children:"ocrmac"})," OCR engine. Other platforms use ",(0,o.jsx)(n.a,{href:"https://www.jaided.ai/easyocr/",children:"easyocr"}),"."]}),"\n",(0,o.jsxs)(n.p,{children:[(0,o.jsx)(n.strong,{children:"Picture descriptions"})," adds image descriptions generated by the ",(0,o.jsx)(n.a,{href:"https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct",children:"SmolVLM-256M-Instruct"})," model to OCR processing. 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commands."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.a,{href:"get-started/docker",children:(0,t.jsx)(n.strong,{children:"Docker Compose"})}),": Clone the OpenRAG repository and deploy OpenRAG with Docker Compose, including all services and dependencies."]}),"\n"]}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://www.python.org/downloads/release/python-3100/",children:"Python Version 3.10 to 3.13"})}),"\n",(0,t.jsx)(n.li,{children:(0,t.jsx)(n.a,{href:"https://docs.astral.sh/uv/getting-started/installation/",children:"uv"})}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.a,{href:"https://docs.docker.com/get-docker/",children:"Docker"})," or ",(0,t.jsx)(n.a,{href:"https://podman.io/docs/installation",children:"Podman"})," installed"]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.a,{href:"https://docs.docker.com/compose/install/",children:"Docker Compose"})," installed. If using Podman, use ",(0,t.jsx)(n.a,{href:"https://docs.podman.io/en/latest/markdown/podman-compose.1.html",children:"podman-compose"})," or alias Docker compose commands to Podman commands."]}),"\n",(0,t.jsx)(n.li,{children:"For GPU support: (TBD)"}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"install-python-wheel",children:"Python wheel"}),"\n",(0,t.jsxs)(n.p,{children:["The Python wheel is currently available internally, but will be available on PyPI at launch.\nThe wheel installs the OpenRAG wheel, which includes the TUI for installing, running, and managing OpenRAG.\nFor more information on virtual environments, see ",(0,t.jsx)(n.a,{href:"https://docs.astral.sh/uv/pip/environments",children:"uv"}),"."]}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Create a new project with a virtual environment using ",(0,t.jsx)(n.a,{href:"https://docs.astral.sh/uv/pip/environments",children:"uv"}),"."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv init YOUR_PROJECT_NAME\ncd YOUR_PROJECT_NAME\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Add the OpenRAG wheel to your project and install it in the virtual environment.\nReplace ",(0,t.jsx)(n.code,{children:"PATH/TO/"})," and ",(0,t.jsx)(n.code,{children:"VERSION"})," with your OpenRAG wheel location and version."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv add PATH/TO/openrag-VERSION-py3-none-any.whl\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Ensure all dependencies are installed and updated in your virtual environment."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv sync\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Start the OpenRAG TUI."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv run openrag\n"})}),"\n",(0,t.jsx)(n.p,{children:"The OpenRAG TUI opens."}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To install OpenRAG with Basic Setup, click ",(0,t.jsx)(n.strong,{children:"Basic Setup"})," or press ",(0,t.jsx)("kbd",{children:"1"}),". Basic Setup does not set up OAuth connections for ingestion from Google Drive, OneDrive, or AWS. For OAuth setup, see ",(0,t.jsx)(n.a,{href:"#advanced-setup",children:"Advanced Setup"}),".\nThe TUI prompts you for the required startup values.\nClick ",(0,t.jsx)(n.strong,{children:"Generate Passwords"})," to autocomplete fields that contain ",(0,t.jsx)(n.strong,{children:"Auto-generated Secure Password"}),", or bring your own passwords."]}),"\n",(0,t.jsxs)(r,{closed:!0,children:[(0,t.jsx)("summary",{children:"Where do I find the required startup values?"}),(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Variable"}),(0,t.jsx)(n.th,{children:"Where to Find"}),(0,t.jsx)(n.th,{children:"Description"})]})}),(0,t.jsxs)(n.tbody,{children:[(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:(0,t.jsx)(n.code,{children:"OPENSEARCH_PASSWORD"})}),(0,t.jsx)(n.td,{children:"Auto-generated secure password"}),(0,t.jsx)(n.td,{children:"The password for OpenSearch database access. 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Tl(e,t,t.pendingProps,n),t.child;case 8:case 12:return Tl(e,t,t.pendingProps.children,n),t.child;case 10:return r=t.pendingProps,wo(0,t.type,r.value),Tl(e,t,r.children,n),t.child;case 9:return o=t.type._context,r=t.pendingProps.children,Ao(t),r=r(o=_o(o)),t.flags|=1,Tl(e,t,r,n),t.child;case 14:return Pl(e,t,t.type,t.pendingProps,n);case 15:return Nl(e,t,t.type,t.pendingProps,n);case 19:return Ql(e,t,n);case 31:return r=t.pendingProps,n=t.mode,r={mode:r.mode,children:r.children},null===e?((n=Hl(r,n)).ref=t.ref,t.child=n,n.return=t,t=n):((n=Ir(e.child,r)).ref=t.ref,t.child=n,n.return=t,t=n),t;case 22:return Ll(e,t,n);case 24:return Ao(t),r=_o(Oo),null===e?(null===(o=qo())&&(o=ru,a=Ro(),o.pooledCache=a,a.refCount++,null!==a&&(o.pooledCacheLanes|=n),o=a),t.memoizedState={parent:r,cache:o},ra(t),wo(0,Oo,o)):(0!==(e.lanes&n)&&(oa(e,t),da(t,null,null,n),ca()),o=e.memoizedState,a=t.memoizedState,o.parent!==r?(o={parent:r,cache:r},t.memoizedState=o,0===t.lanes&&(t.memoizedState=t.updateQueue.baseState=o),wo(0,Oo,r)):(r=a.cache,wo(0,Oo,r),r!==o.cache&&xo(t,[Oo],n,!0))),Tl(e,t,t.pendingProps.children,n),t.child;case 29:throw t.pendingProps}throw Error(i(156,t.tag))}function Zl(e){e.flags|=4}function Jl(e,t){if("stylesheet"!==t.type||4&t.state.loading)e.flags&=-16777217;else if(e.flags|=16777216,!$d(t)){if(null!==(t=ol.current)&&((4194048&au)===au?null!==al:(62914560&au)!==au&&!(536870912&au)||t!==al))throw Jo=Ko,Wo;e.flags|=8192}}function es(e,t){null!==t&&(e.flags|=4),16384&e.flags&&(t=22!==e.tag?xe():536870912,e.lanes|=t,yu|=t)}function ts(e,t){if(!ao)switch(e.tailMode){case"hidden":t=e.tail;for(var n=null;null!==t;)null!==t.alternate&&(n=t),t=t.sibling;null===n?e.tail=null:n.sibling=null;break;case"collapsed":n=e.tail;for(var r=null;null!==n;)null!==n.alternate&&(r=n),n=n.sibling;null===r?t||null===e.tail?e.tail=null:e.tail.sibling=null:r.sibling=null}}function ns(e){var t=null!==e.alternate&&e.alternate.child===e.child,n=0,r=0;if(t)for(var o=e.child;null!==o;)n|=o.lanes|o.childLanes,r|=65011712&o.subtreeFlags,r|=65011712&o.flags,o.return=e,o=o.sibling;else for(o=e.child;null!==o;)n|=o.lanes|o.childLanes,r|=o.subtreeFlags,r|=o.flags,o.return=e,o=o.sibling;return e.subtreeFlags|=r,e.childLanes=n,t}function rs(e,t,n){var r=t.pendingProps;switch(no(t),t.tag){case 31:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:case 1:return ns(t),null;case 3:return n=t.stateNode,r=null,null!==e&&(r=e.memoizedState.cache),t.memoizedState.cache!==r&&(t.flags|=2048),ko(Oo),W(),n.pendingContext&&(n.context=n.pendingContext,n.pendingContext=null),null!==e&&null!==e.child||(po(t)?Zl(t):null===e||e.memoizedState.isDehydrated&&!(256&t.flags)||(t.flags|=1024,ho())),ns(t),null;case 26:return n=t.memoizedState,null===e?(Zl(t),null!==n?(ns(t),Jl(t,n)):(ns(t),t.flags&=-16777217)):n?n!==e.memoizedState?(Zl(t),ns(t),Jl(t,n)):(ns(t),t.flags&=-16777217):(e.memoizedProps!==r&&Zl(t),ns(t),t.flags&=-16777217),null;case 27:K(t),n=H.current;var o=t.type;if(null!==e&&null!=t.stateNode)e.memoizedProps!==r&&Zl(t);else{if(!r){if(null===t.stateNode)throw Error(i(166));return ns(t),null}e=U.current,po(t)?co(t):(e=wd(o,r,n),t.stateNode=e,Zl(t))}return ns(t),null;case 5:if(K(t),n=t.type,null!==e&&null!=t.stateNode)e.memoizedProps!==r&&Zl(t);else{if(!r){if(null===t.stateNode)throw Error(i(166));return ns(t),null}if(e=U.current,po(t))co(t);else{switch(o=rd(H.current),e){case 1:e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case 2:e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;default:switch(n){case"svg":e=o.createElementNS("http://www.w3.org/2000/svg",n);break;case"math":e=o.createElementNS("http://www.w3.org/1998/Math/MathML",n);break;case"script":(e=o.createElement("div")).innerHTML=" - - +Configuration | OpenRAG + + -

Configuration

+

Configuration

OpenRAG supports multiple configuration methods with the following priority:

  1. Environment Variables (highest priority)
    2. @@ -43,6 +43,6 @@
    VariableDescriptionDefault
    EMBEDDING_MODELEmbedding model for vector searchtext-embedding-3-small
    CHUNK_SIZEText chunk size for document processing1000
    CHUNK_OVERLAPOverlap between chunks200
    OCR_ENABLEDEnable OCR for image processingtrue
    PICTURE_DESCRIPTIONS_ENABLEDEnable picture descriptionsfalse

    Agent Settings​

    VariableDescriptionDefault
    LLM_MODELLanguage model for the chat agentgpt-4o-mini
    SYSTEM_PROMPTSystem prompt for the agentDefault assistant prompt
    -

    See .env.example for a complete list with descriptions, and docker-compose*.yml for runtime usage.

+

See .env.example for a complete list with descriptions, and docker-compose*.yml for runtime usage.

\ No newline at end of file diff --git a/get-started/docker/index.html b/get-started/docker/index.html index 5adfbc00..d9055cac 100644 --- a/get-started/docker/index.html +++ b/get-started/docker/index.html @@ -3,15 +3,15 @@ -Docker deployment | OpenRAG - - +Docker deployment | OpenRAG + + -

Docker deployment

There are two different Docker Compose files. +

Docker deployment

There are two different Docker Compose files. They deploy the same applications and containers, but to different environments.

  • @@ -37,8 +37,8 @@ The example file includes all environment variables with comments to guide you i

  • Set environment variables. The Docker Compose files are populated with values from your .env, so the following values are required to be set:

    OPENSEARCH_PASSWORD=your_secure_password
    OPENAI_API_KEY=your_openai_api_key

    LANGFLOW_SUPERUSER=admin
    LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
    LANGFLOW_SECRET_KEY=your_secret_key
    -

    For more information on configuring OpenRAG with environment variables, see Environment variables. -For additional configuration values, including config.yaml, see Configuration.

    +

    For more information on configuring OpenRAG with environment variables, see Environment variables. +For additional configuration values, including config.yaml, see Configuration.

  • Deploy OpenRAG with Docker Compose based on your deployment type.

    @@ -60,11 +60,11 @@ For additional configuration values, including config.yaml, see
    • -

    Continue with the Quickstart.

    +

    Continue with the Quickstart.

    Rebuild all Docker containers​

    If you need to reset state and rebuild all of your containers, run the following command. Your OpenSearch and Langflow databases will be lost. Documents stored in the ./documents directory will persist, since the directory is mounted as a volume in the OpenRAG backend container.

    -
    docker compose up --build --force-recreate --remove-orphans
+
docker compose up --build --force-recreate --remove-orphans
\ No newline at end of file diff --git a/get-started/tui/index.html b/get-started/tui/index.html index 4bdc6e4d..3ccae2c2 100644 --- a/get-started/tui/index.html +++ b/get-started/tui/index.html @@ -3,26 +3,26 @@ -Terminal User Interface (TUI) commands | OpenRAG - - +Terminal User Interface (TUI) commands | OpenRAG + + -

OpenRAG TUI Guide

+

OpenRAG TUI Guide

The OpenRAG Terminal User Interface (TUI) provides a streamlined way to set up, configure, and monitor your OpenRAG deployment directly from the terminal, on any operating system.

-

OpenRAG TUI Interface

+

OpenRAG TUI Interface

The TUI offers an easier way to use OpenRAG without sacrificing control. 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.

Once OpenRAG is running, use the TUI to monitor your application, control your containers, and retrieve logs.

Start the TUI​

To start the TUI, run the following commands from the directory where you installed OpenRAG. -For more information, see Install OpenRAG.

+For more information, see Install OpenRAG.

uv sync
uv run openrag

The TUI Welcome Screen offers basic and advanced setup options. -For more information on setup values during installation, see Install OpenRAG.

+For more information on setup values during installation, see Install OpenRAG.

The TUI accepts mouse input or keyboard commands.

    @@ -64,6 +64,6 @@ It first stops and removes all containers, volumes, and local images.

    When the first command is complete, OpenRAG removes any additional Docker objects with prune.

    docker system prune -f

    Diagnostics​

    -

    The Diagnostics menu provides health monitoring for your container runtimes and monitoring of your OpenSearch security.

+

The Diagnostics menu provides health monitoring for your container runtimes and monitoring of your OpenSearch security.

\ No newline at end of file diff --git a/index.html b/index.html index 0a2c3bc7..9e3facc8 100644 --- a/index.html +++ b/index.html @@ -3,15 +3,15 @@ -What is OpenRAG? | OpenRAG - - +What is OpenRAG? | OpenRAG + + -

What is OpenRAG?

OpenRAG is an open-source package for building agentic RAG systems. +

What is OpenRAG?

OpenRAG is an open-source package for building agentic RAG systems. It supports integration 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:

    @@ -26,6 +26,6 @@ It supports integration with a wide range of orchestration tools, vector databas

OpenRAG builds on Langflow's familiar interface while adding OpenSearch for vector storage and Docling for simplified document parsing, with opinionated flows that serve as ready-to-use recipes for ingestion, retrieval, and generation from popular sources like OneDrive, Google Drive, and AWS. And don't fear: every part of the stack is swappable. Write your own custom components in Python, try different language models, and customize your flows to build an agentic RAG system that solves problems.

-

Ready to get started? Install OpenRAG and then run the Quickstart to create a powerful RAG pipeline.

+

Ready to get started? Install OpenRAG and then run the Quickstart to create a powerful RAG pipeline.

\ No newline at end of file diff --git a/ingestion/index.html b/ingestion/index.html index c6850de4..347791b4 100644 --- a/ingestion/index.html +++ b/ingestion/index.html @@ -3,15 +3,15 @@ -Docling Ingestion | OpenRAG - - +Docling Ingestion | OpenRAG + + -

Docling Ingestion

OpenRAG uses Docling for its document ingestion pipeline. +

Docling Ingestion

OpenRAG uses Docling for its document ingestion pipeline. 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.

@@ -32,8 +32,8 @@ OCR is disabled by default. This setting is best suited for processing text-base

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.

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.

+

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.

+

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

\ No newline at end of file diff --git a/install/index.html b/install/index.html index cbb52d10..fa8d2917 100644 --- a/install/index.html +++ b/install/index.html @@ -3,21 +3,21 @@ -Install OpenRAG | OpenRAG - - +Install OpenRAG | OpenRAG + + -

Install OpenRAG

OpenRAG can be installed in multiple ways:

+

Install OpenRAG

OpenRAG can be installed in multiple ways:

Prerequisites​

@@ -100,7 +100,7 @@ This is recommended, but not required.
  • Click Complete.
      • -
    1. Continue with the Quickstart.
      2. +
    2. Continue with the Quickstart.

    Advanced Setup​

    Advanced Setup includes the required values from Basic Setup, with additional settings for OAuth credentials. @@ -118,6 +118,6 @@ You will be presented with your provider's OAuth sign-in screen, and be red

    The LANGFLOW_PUBLIC_URL controls where the Langflow web interface can be accessed. This is where users interact with their flows in a browser.

    The WEBHOOK_BASE_URL controls where the endpoint for /connectors/CONNECTOR_TYPE/webhook will be available. This connection enables real-time document synchronization with external services. -For example, for Google Drive file synchronization the webhook URL is /connectors/google_drive/webhook.

    +For example, for Google Drive file synchronization the webhook URL is /connectors/google_drive/webhook.

    \ No newline at end of file diff --git a/knowledge/index.html b/knowledge/index.html index f3384322..b1e312d9 100644 --- a/knowledge/index.html +++ b/knowledge/index.html @@ -3,15 +3,15 @@ -OpenSearch Knowledge | OpenRAG - - +OpenSearch Knowledge | OpenRAG + + -

    OpenSearch Knowledge

    OpenRAG uses OpenSearch for its vector-backed knowledge store. +

    OpenSearch Knowledge

    OpenRAG uses OpenSearch for its vector-backed knowledge store. OpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support.

    Explore knowledge​

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

    @@ -25,7 +25,7 @@ Flows are edited in the same way as in the 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 ./documents folder in your OpenRAG project directory to the /app/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 or in the .env used by Docker Compose.

    +

    The default path to your local folder is mounted from the ./documents folder in your OpenRAG project directory to the /app/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 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 Add 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 Process Folder. @@ -40,7 +40,7 @@ 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. Click Advanced Setup.
      3. -
    3. Add the OAuth provider's client and secret key in the Advanced Setup menu.
      4. +
    4. Add the OAuth provider's client and secret key in the Advanced Setup menu.
    5. Click Save Configuration. The TUI generates a new .env file with your OAuth values.
    6. Click Start Container Services.
      7. @@ -71,7 +71,7 @@ The ingestion process may take some time, depending on the size of your document

      You can monitor the sync progress in the Tasks sidebar.

      Once processing is complete, the synced documents become available in your knowledge base and can be searched through the chat interface or Knowledge page.

      Knowledge ingestion settings​

      -

      To configure the knowledge ingestion pipeline parameters, see Docling Ingestion.

      +

      To configure the knowledge ingestion pipeline parameters, see Docling Ingestion.

      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.

      @@ -113,6 +113,6 @@ A new filter is created with default settings that match everything.

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

      If you use an unknown embedding model, OpenRAG will automatically fall back to 1536 dimensions and log a warning. The system will continue to work, but search quality may 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 /src/config/settings.py.

    +

    For models with known vector dimensions, see /src/config/settings.py.

    \ No newline at end of file diff --git a/quickstart/index.html b/quickstart/index.html index 6049f72d..6e582c0f 100644 --- a/quickstart/index.html +++ b/quickstart/index.html @@ -3,19 +3,19 @@ -Quickstart | OpenRAG - - +Quickstart | OpenRAG + + -

    Quickstart

    Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API.

    +

    Quickstart

    Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API.

    Prerequisites​

    • -

      Install and start OpenRAG

      +

      Install and start OpenRAG

    • Create a Langflow API key

      @@ -46,11 +46,11 @@ For example:

      1. In OpenRAG, click Chat. The chat is powered by the OpenRAG OpenSearch Agent. -For more information, see Langflow Agents.
        2. +For more information, see Langflow Agents.
      2. Ask What documents are available to you? The agent responds with a message summarizing the documents that OpenRAG loads by default, which are PDFs about evaluating data quality when using LLMs in health care. Knowledge is stored in OpenSearch. -For more information, see Knowledge.
        3. +For more information, see Knowledge.
      3. To confirm the agent is correct, click Knowledge. The Knowledge page lists the documents OpenRAG has ingested into the OpenSearch vector database. Click on a document to display the chunks derived from splitting the default documents into the vector database.
        4. @@ -61,7 +61,7 @@ Click on a document to display the chunks derived from splitting the default doc
        • Select Add File to add a single file from your local machine (mapped with the Docker volume mount).
        • Select Process Folder to process an entire folder of documents from your local machine (mapped with the Docker volume mount).
          • -
        • Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see OAuth ingestion.
          • +
        • Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see OAuth ingestion.
      4. Return to the Chat window and ask a question about your loaded data. @@ -86,7 +86,7 @@ You can more quickly access the Language Model and Agen

      5. The OpenRAG OpenSearch Agent flow appears. -OpenRAG Open Search Agent Flow

        +OpenRAG Open Search Agent Flow

      6. In the Language Model component, under Model, select a different OpenAI model.

        @@ -125,6 +125,6 @@ The following is an example of a response from running the Simple Agent<
    +
    \ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml index 40650423..79a83962 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1 +1 @@ -https://langflow-ai.github.io/openrag/agentsweekly0.5https://langflow-ai.github.io/openrag/configure/configurationweekly0.5https://langflow-ai.github.io/openrag/get-started/dockerweekly0.5https://langflow-ai.github.io/openrag/get-started/tuiweekly0.5https://langflow-ai.github.io/openrag/ingestionweekly0.5https://langflow-ai.github.io/openrag/installweekly0.5https://langflow-ai.github.io/openrag/knowledgeweekly0.5https://langflow-ai.github.io/openrag/quickstartweekly0.5https://langflow-ai.github.io/openrag/support/troubleshootweekly0.5https://langflow-ai.github.io/openrag/weekly0.5 \ No newline at end of file +https://docs.openr.ag/agentsweekly0.5https://docs.openr.ag/configure/configurationweekly0.5https://docs.openr.ag/get-started/dockerweekly0.5https://docs.openr.ag/get-started/tuiweekly0.5https://docs.openr.ag/ingestionweekly0.5https://docs.openr.ag/installweekly0.5https://docs.openr.ag/knowledgeweekly0.5https://docs.openr.ag/quickstartweekly0.5https://docs.openr.ag/support/troubleshootweekly0.5https://docs.openr.ag/weekly0.5 \ No newline at end of file diff --git a/support/troubleshoot/index.html b/support/troubleshoot/index.html index 1cbd74f1..1166a84e 100644 --- a/support/troubleshoot/index.html +++ b/support/troubleshoot/index.html @@ -3,15 +3,15 @@ -Troubleshoot | OpenRAG - - +Troubleshoot | OpenRAG + + -

    Troubleshoot

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

    +

    Troubleshoot

    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 is set and 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.

    @@ -44,6 +44,6 @@ This example increases the machine size to 8 GB of RAM, which should be sufficie When the Close button is active, the upgrade is complete. Close the window and open the OpenRAG appplication.

    -
    +
    \ No newline at end of file