From 8f4373a7ae22ea6965720216e46ebb4db44449e6 Mon Sep 17 00:00:00 2001 From: zznate Date: Thu, 23 Oct 2025 16:15:31 +0000 Subject: [PATCH] deploy: d36623e434558dcb1241974c5d7e7ce3c5839f75 --- 404.html | 2 +- agents/index.html | 2 +- assets/js/0ba6a408.21d91e2f.js | 1 - assets/js/0ba6a408.eb57b569.js | 1 + assets/js/22dd74f7.4cc55718.js | 1 + assets/js/22dd74f7.5a552cfa.js | 1 - assets/js/749371cc.c67142db.js | 1 - assets/js/749371cc.c90a8e18.js | 1 + assets/js/af920ffe.36fc9a9a.js | 1 - assets/js/af920ffe.87292094.js | 1 + assets/js/d0314b07.636e9726.js | 1 + assets/js/d0314b07.81b2f228.js | 1 - ...n.c8893f6b.js => runtime~main.80b1444b.js} | 2 +- get-started/docker/index.html | 22 +++++++------- get-started/tui/index.html | 4 +-- index.html | 4 +-- ingestion/index.html | 2 +- install/index.html | 30 +++++++++++-------- knowledge/index.html | 4 +-- quickstart/index.html | 10 +++---- reference/configuration/index.html | 2 +- support/troubleshoot/index.html | 2 +- 22 files changed, 48 insertions(+), 48 deletions(-) delete mode 100644 assets/js/0ba6a408.21d91e2f.js create mode 100644 assets/js/0ba6a408.eb57b569.js create mode 100644 assets/js/22dd74f7.4cc55718.js delete mode 100644 assets/js/22dd74f7.5a552cfa.js delete mode 100644 assets/js/749371cc.c67142db.js create mode 100644 assets/js/749371cc.c90a8e18.js delete mode 100644 assets/js/af920ffe.36fc9a9a.js create mode 100644 assets/js/af920ffe.87292094.js create mode 100644 assets/js/d0314b07.636e9726.js delete mode 100644 assets/js/d0314b07.81b2f228.js rename assets/js/{runtime~main.c8893f6b.js => runtime~main.80b1444b.js} (89%) diff --git a/404.html b/404.html index 3caed445..2b40f763 100644 --- a/404.html +++ b/404.html @@ -4,7 +4,7 @@ OpenRAG - + diff --git a/agents/index.html b/agents/index.html index 598996de..c8cc83c4 100644 --- a/agents/index.html +++ b/agents/index.html @@ -4,7 +4,7 @@ Langflow Agents | OpenRAG - + diff --git a/assets/js/0ba6a408.21d91e2f.js b/assets/js/0ba6a408.21d91e2f.js deleted file mode 100644 index 01f9e411..00000000 --- a/assets/js/0ba6a408.21d91e2f.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:()=>u,contentTitle:()=>h,default:()=>x,frontMatter:()=>a,metadata:()=>i,toc:()=>p});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 t=s(4848),o=s(8453),r=s(9179),l=s(1470),d=s(9365),c=s(3782);const a={title:"OpenSearch Knowledge",slug:"/knowledge"},h=void 0,u={},p=[{value:"Authentication and document access",id:"auth",level:2},{value:"Ingest knowledge",id:"ingest-knowledge",level:2},{value:"Direct file ingestion",id:"direct-file-ingestion",level:3},{value:"Ingest files through OAuth connectors",id:"oauth-ingestion",level:3},{value:"Explore knowledge",id:"explore-knowledge",level:2},...c.RM,{value:"Create knowledge filters",id:"create-knowledge-filters",level:2},{value:"OpenRAG default configuration",id:"openrag-default-configuration",level:2}];function g(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(n.p,{children:["OpenRAG uses ",(0,t.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"})," for its vector-backed knowledge store.\nThis is a specialized database for storing and retrieving embeddings, which helps your Agent efficiently find relevant information.\nOpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support."]}),"\n",(0,t.jsx)(n.h2,{id:"auth",children:"Authentication and document access"}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG supports two authentication modes based on how you ",(0,t.jsx)(n.a,{href:"/install",children:"install OpenRAG"}),", and which mode you choose affects document access."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"No-auth mode (Basic Setup)"}),": This mode uses a single anonymous JWT token for OpenSearch authentication, so documents uploaded to the ",(0,t.jsx)(n.code,{children:"documents"})," index by one user are visible to all other users on the OpenRAG server."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"OAuth mode (Advanced Setup)"}),": Each OpenRAG user is granted a JWT token, and each document is tagged with user ownership. Documents are filtered by user ownership, ensuring users only see documents they uploaded or have access to."]}),"\n",(0,t.jsx)(n.h2,{id:"ingest-knowledge",children:"Ingest knowledge"}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG supports knowledge ingestion through direct file uploads and OAuth connectors.\nTo configure the knowledge ingestion pipeline parameters, see ",(0,t.jsx)(n.a,{href:"/ingestion",children:"Docling Ingestion"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"direct-file-ingestion",children:"Direct file ingestion"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow uses Langflow's ",(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/components-data#file",children:[(0,t.jsx)(n.strong,{children:"File"})," component"]})," to split and embed files loaded from your local machine into the OpenSearch database."]}),"\n",(0,t.jsxs)(n.p,{children:["The default path to your local folder is mounted from the ",(0,t.jsx)(n.code,{children:"./documents"})," folder in your OpenRAG project directory to the ",(0,t.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,t.jsx)(n.strong,{children:"Documents Paths"})," variable in either the TUI's ",(0,t.jsx)(n.a,{href:"/install#setup",children:"Advanced Setup"})," menu or in the ",(0,t.jsx)(n.code,{children:".env"})," used by Docker Compose."]}),"\n",(0,t.jsxs)(n.p,{children:["To load and process a single file from the mapped location, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,t.jsx)(n.strong,{children:"Add File"}),".\nThe file is loaded into your OpenSearch database, and appears in the Knowledge page."]}),"\n",(0,t.jsxs)(n.p,{children:["To load and process a directory from the mapped location, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,t.jsx)(n.strong,{children:"Process Folder"}),".\nThe files are loaded into your OpenSearch database, and appear in the Knowledge page."]}),"\n",(0,t.jsx)(n.h3,{id:"oauth-ingestion",children:"Ingest files through OAuth connectors"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG supports Google Drive, OneDrive, and AWS S3 as OAuth connectors for seamless document synchronization."}),"\n",(0,t.jsx)(n.p,{children:"OAuth integration allows individual users to connect their personal cloud storage accounts to OpenRAG. Each user must separately authorize OpenRAG to access their own cloud storage files. When a user connects a cloud service, they are redirected to authenticate with that service provider and grant OpenRAG permission to sync documents from their personal cloud storage."}),"\n",(0,t.jsx)(n.p,{children:"Before users can connect their cloud storage accounts, you must configure OAuth credentials in OpenRAG. This requires registering OpenRAG as an OAuth application with a cloud provider and obtaining client ID and secret keys for each service you want to support."}),"\n",(0,t.jsx)(n.p,{children:"To add an OAuth connector to OpenRAG, do the following.\nThis example uses Google OAuth.\nIf you wish to use another provider, add the secrets to another provider."}),"\n",(0,t.jsxs)(l.A,{groupId:"Installation type",children:[(0,t.jsx)(d.A,{value:"TUI",label:"TUI",default:!0,children:(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["If OpenRAG is running, stop it with ",(0,t.jsx)(n.strong,{children:"Status"})," > ",(0,t.jsx)(n.strong,{children:"Stop Services"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,t.jsx)(n.a,{href:"/install#setup",children:"Advanced Setup"})," menu."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Save Configuration"}),".\nThe TUI generates a new ",(0,t.jsx)(n.code,{children:".env"})," file with your OAuth values."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Start Container Services"}),"."]}),"\n"]})}),(0,t.jsxs)(d.A,{value:".env",label:".env",children:[(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsx)(n.li,{children:"Stop the Docker deployment."}),"\n",(0,t.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,t.jsx)(n.code,{children:".env"})," file for Docker Compose."]}),"\n"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"GOOGLE_OAUTH_CLIENT_ID='YOUR_OAUTH_CLIENT_ID'\nGOOGLE_OAUTH_CLIENT_SECRET='YOUR_OAUTH_CLIENT_SECRET'\n"})}),(0,t.jsxs)(n.ol,{start:"3",children:["\n",(0,t.jsxs)(n.li,{children:["Save your ",(0,t.jsx)(n.code,{children:".env"}),". file."]}),"\n",(0,t.jsx)(n.li,{children:"Start the Docker deployment."}),"\n"]})]})]}),"\n",(0,t.jsxs)(n.p,{children:["The OpenRAG frontend at ",(0,t.jsx)(n.code,{children:"http://localhost:3000"})," now redirects to an OAuth callback login page for your OAuth provider.\nA successful authentication opens OpenRAG with the required scopes for your connected storage."]}),"\n",(0,t.jsx)(n.p,{children:"To add knowledge from an OAuth-connected storage provider, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then select the storage provider, for example, ",(0,t.jsx)(n.strong,{children:"Google Drive"}),".\nThe ",(0,t.jsx)(n.strong,{children:"Add Cloud Knowledge"})," page opens."]}),"\n",(0,t.jsxs)(n.li,{children:["To add files or folders from the connected storage, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Files"}),".\nSelect the files or folders you want and click ",(0,t.jsx)(n.strong,{children:"Select"}),".\nYou can select multiples."]}),"\n",(0,t.jsxs)(n.li,{children:["When your files are selected, click ",(0,t.jsx)(n.strong,{children:"Ingest Files"}),".\nThe ingestion process may take some time, depending on the size of your documents."]}),"\n",(0,t.jsx)(n.li,{children:"When ingestion is complete, your documents are available in the Knowledge screen."}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"explore-knowledge",children:"Explore knowledge"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"Knowledge"})," page lists the documents OpenRAG has ingested into the OpenSearch vector database's ",(0,t.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,t.jsxs)(n.p,{children:["To explore your current knowledge, click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"}),".\nClick on a document to display the chunks derived from splitting the default documents into the vector database."]}),"\n",(0,t.jsxs)(n.p,{children:["Documents are processed with the default ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow, so if you want to split your documents differently, edit the ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow."]}),"\n",(0,t.jsx)(c.Ay,{}),"\n",(0,t.jsx)(n.h2,{id:"create-knowledge-filters",children:"Create knowledge filters"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG includes a knowledge filter system for organizing and managing document collections.\nKnowledge filters are saved search configurations that allow you to create custom views of your document collection. They store search queries, filter criteria, and display settings that can be reused across different parts of OpenRAG."}),"\n",(0,t.jsx)(n.p,{children:"Knowledge filters help agents work more efficiently with large document collections by focusing their context within relevant documents sets."}),"\n",(0,t.jsx)(n.p,{children:"To create a knowledge filter, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"All Knowledge"}),", and then click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Create New Filter"}),".\nThe ",(0,t.jsx)(n.strong,{children:"Create New Knowledge Filter"})," pane appears."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Enter a ",(0,t.jsx)(n.strong,{children:"Name"})," and ",(0,t.jsx)(n.strong,{children:"Description"}),", and then click ",(0,t.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Create Filter"}),".\nA new filter is created with default settings that match everything."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To modify the default filter, click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"All Knowledge"}),", and then click your new filter to edit it in the ",(0,t.jsx)(n.strong,{children:"Knowledge Filter"})," pane."]}),"\n",(0,t.jsx)(n.p,{children:"The following filter options are configurable."}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Search Query"}),': Enter text for semantic search, such as "financial reports from Q4".']}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Sources"}),": Select specific data sources or folders to include."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Document Types"}),": Filter by file type."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Owners"}),": Filter by who uploaded the documents."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Sources"}),": Filter by connector types, such as local upload or Google Drive."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Result Limit"}),": Set maximum number of results. The default is ",(0,t.jsx)(n.code,{children:"10"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Score Threshold"}),": Set minimum relevance score. The default score is ",(0,t.jsx)(n.code,{children:"0"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["When you're done editing the filter, click ",(0,t.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To apply the filter to OpenRAG globally, click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"All Knowledge"}),", and then select the filter to apply."]}),"\n",(0,t.jsxs)(n.p,{children:["To apply the filter to a single chat session, in the ",(0,t.jsx)(r.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Chat"})," window, click ",(0,t.jsx)(n.strong,{children:"@"}),", and then select the filter to apply."]}),"\n"]}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"openrag-default-configuration",children:"OpenRAG default configuration"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG automatically detects and configures the correct vector dimensions for embedding models, ensuring optimal search performance and compatibility."}),"\n",(0,t.jsxs)(n.p,{children:["The complete list of supported models is available at ",(0,t.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/services/models_service.py",children:[(0,t.jsx)(n.code,{children:"models_service.py"})," in the OpenRAG repository"]}),"."]}),"\n",(0,t.jsx)(n.p,{children:"You can use custom embedding models by specifying them in your configuration."}),"\n",(0,t.jsxs)(n.p,{children:["If you use an unknown embedding model, OpenRAG will automatically fall back to ",(0,t.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,t.jsx)(n.code,{children:"1536"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["The default embedding dimension is ",(0,t.jsx)(n.code,{children:"1536"})," and the default model is ",(0,t.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["For models with known vector dimensions, see ",(0,t.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/config/settings.py",children:[(0,t.jsx)(n.code,{children:"settings.py"})," in the OpenRAG repository"]}),"."]})]})}function x(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(g,{...e})}):g(e)}},3782:(e,n,s)=>{s.d(n,{Ay:()=>d,RM:()=>r});var i=s(4848),t=s(8453),o=s(9179);const r=[];function l(e){const n={a:"a",p:"p",strong:"strong",...(0,t.R)(),...e.components};return(0,i.jsxs)(n.p,{children:["All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic.\nTo modify a flow, click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nOpenRAG's visual editor is based on the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),", so you can edit your flows to match your specific use case."]})}function d(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(l,{...e})}):l(e)}},9179:(e,n,s)=>{s.d(n,{A:()=>o});s(6540);var i=s(4827),t=s(4848);function o({name:e,...n}){const s=i[e];return s?(0,t.jsx)(s,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/0ba6a408.eb57b569.js b/assets/js/0ba6a408.eb57b569.js new file mode 100644 index 00000000..acf74e9f --- /dev/null +++ b/assets/js/0ba6a408.eb57b569.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:()=>p});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 t=s(4848),o=s(8453),r=s(9179),l=s(1470),d=s(9365),c=s(3782);const a={title:"OpenSearch Knowledge",slug:"/knowledge"},h=void 0,u={},p=[{value:"Authentication and document access",id:"auth",level:2},{value:"Ingest knowledge",id:"ingest-knowledge",level:2},{value:"Direct file ingestion",id:"direct-file-ingestion",level:3},{value:"Ingest files through OAuth connectors",id:"oauth-ingestion",level:3},{value:"Explore knowledge",id:"explore-knowledge",level:2},...c.RM,{value:"Create knowledge filters",id:"create-knowledge-filters",level:2},{value:"OpenRAG default configuration",id:"openrag-default-configuration",level:2}];function g(e){const n={a:"a",code:"code",h2:"h2",h3:"h3",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,o.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsxs)(n.p,{children:["OpenRAG uses ",(0,t.jsx)(n.a,{href:"https://docs.opensearch.org/latest/",children:"OpenSearch"})," for its vector-backed knowledge store.\nThis is a specialized database for storing and retrieving embeddings, which helps your Agent efficiently find relevant information.\nOpenSearch provides powerful hybrid search capabilities with enterprise-grade security and multi-tenancy support."]}),"\n",(0,t.jsx)(n.h2,{id:"auth",children:"Authentication and document access"}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG supports two authentication modes based on how you ",(0,t.jsx)(n.a,{href:"/install",children:"install OpenRAG"}),", and which mode you choose affects document access."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"No-auth mode (Basic Setup)"}),": This mode uses a single anonymous JWT token for OpenSearch authentication, so documents uploaded to the ",(0,t.jsx)(n.code,{children:"documents"})," index by one user are visible to all other users on the OpenRAG server."]}),"\n",(0,t.jsxs)(n.p,{children:[(0,t.jsx)(n.strong,{children:"OAuth mode (Advanced Setup)"}),": Each OpenRAG user is granted a JWT token, and each document is tagged with user ownership. Documents are filtered by user ownership, ensuring users only see documents they uploaded or have access to."]}),"\n",(0,t.jsx)(n.h2,{id:"ingest-knowledge",children:"Ingest knowledge"}),"\n",(0,t.jsxs)(n.p,{children:["OpenRAG supports knowledge ingestion through direct file uploads and OAuth connectors.\nTo configure the knowledge ingestion pipeline parameters, see ",(0,t.jsx)(n.a,{href:"/ingestion",children:"Docling Ingestion"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"direct-file-ingestion",children:"Direct file ingestion"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow uses Langflow's ",(0,t.jsxs)(n.a,{href:"https://docs.langflow.org/components-data#file",children:[(0,t.jsx)(n.strong,{children:"File"})," component"]})," to split and embed files loaded from your local machine into the OpenSearch database."]}),"\n",(0,t.jsxs)(n.p,{children:["The default path to your local folder is mounted from the ",(0,t.jsx)(n.code,{children:"./documents"})," folder in your OpenRAG project directory to the ",(0,t.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,t.jsx)(n.strong,{children:"Documents Paths"})," variable in either the TUI's ",(0,t.jsx)(n.a,{href:"/install#setup",children:"Advanced Setup"})," menu or in the ",(0,t.jsx)(n.code,{children:".env"})," used by Docker Compose."]}),"\n",(0,t.jsxs)(n.p,{children:["To load and process a single file from the mapped location, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,t.jsx)(n.strong,{children:"Add File"}),".\nThe file is loaded into your OpenSearch database, and appears in the Knowledge page."]}),"\n",(0,t.jsxs)(n.p,{children:["To load and process a directory from the mapped location, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then click ",(0,t.jsx)(n.strong,{children:"Process Folder"}),".\nThe files are loaded into your OpenSearch database, and appear in the Knowledge page."]}),"\n",(0,t.jsx)(n.h3,{id:"oauth-ingestion",children:"Ingest files through OAuth connectors"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG supports Google Drive, OneDrive, and Sharepoint as OAuth connectors for seamless document synchronization."}),"\n",(0,t.jsx)(n.p,{children:"OAuth integration allows individual users to connect their personal cloud storage accounts to OpenRAG. Each user must separately authorize OpenRAG to access their own cloud storage files. When a user connects a cloud service, they are redirected to authenticate with that service provider and grant OpenRAG permission to sync documents from their personal cloud storage."}),"\n",(0,t.jsx)(n.p,{children:"Before users can connect their cloud storage accounts, you must configure OAuth credentials in OpenRAG. This requires registering OpenRAG as an OAuth application with a cloud provider and obtaining client ID and secret keys for each service you want to support."}),"\n",(0,t.jsx)(n.p,{children:"To add an OAuth connector to OpenRAG, do the following.\nThis example uses Google OAuth.\nIf you wish to use another provider, add the secrets to another provider."}),"\n",(0,t.jsxs)(l.A,{groupId:"Installation type",children:[(0,t.jsx)(d.A,{value:"TUI",label:"TUI",default:!0,children:(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["If OpenRAG is running, stop it with ",(0,t.jsx)(n.strong,{children:"Status"})," > ",(0,t.jsx)(n.strong,{children:"Stop Services"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Advanced Setup"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,t.jsx)(n.a,{href:"/install#setup",children:"Advanced Setup"})," menu."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Save Configuration"}),".\nThe TUI generates a new ",(0,t.jsx)(n.code,{children:".env"})," file with your OAuth values."]}),"\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(n.strong,{children:"Start Container Services"}),"."]}),"\n"]})}),(0,t.jsxs)(d.A,{value:".env",label:".env",children:[(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsx)(n.li,{children:"Stop the Docker deployment."}),"\n",(0,t.jsxs)(n.li,{children:["Add the OAuth provider's client and secret key in the ",(0,t.jsx)(n.code,{children:".env"})," file for Docker Compose."]}),"\n"]}),(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"GOOGLE_OAUTH_CLIENT_ID='YOUR_OAUTH_CLIENT_ID'\nGOOGLE_OAUTH_CLIENT_SECRET='YOUR_OAUTH_CLIENT_SECRET'\n"})}),(0,t.jsxs)(n.ol,{start:"3",children:["\n",(0,t.jsxs)(n.li,{children:["Save your ",(0,t.jsx)(n.code,{children:".env"}),". file."]}),"\n",(0,t.jsx)(n.li,{children:"Start the Docker deployment."}),"\n"]})]})]}),"\n",(0,t.jsxs)(n.p,{children:["The OpenRAG frontend at ",(0,t.jsx)(n.code,{children:"http://localhost:3000"})," now redirects to an OAuth callback login page for your OAuth provider.\nA successful authentication opens OpenRAG with the required scopes for your connected storage."]}),"\n",(0,t.jsx)(n.p,{children:"To add knowledge from an OAuth-connected storage provider, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["Click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Knowledge"}),", and then select the storage provider, for example, ",(0,t.jsx)(n.strong,{children:"Google Drive"}),".\nThe ",(0,t.jsx)(n.strong,{children:"Add Cloud Knowledge"})," page opens."]}),"\n",(0,t.jsxs)(n.li,{children:["To add files or folders from the connected storage, click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Add Files"}),".\nSelect the files or folders you want and click ",(0,t.jsx)(n.strong,{children:"Select"}),".\nYou can select multiples."]}),"\n",(0,t.jsxs)(n.li,{children:["When your files are selected, click ",(0,t.jsx)(n.strong,{children:"Ingest Files"}),".\nThe ingestion process may take some time, depending on the size of your documents."]}),"\n",(0,t.jsx)(n.li,{children:"When ingestion is complete, your documents are available in the Knowledge screen."}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"explore-knowledge",children:"Explore knowledge"}),"\n",(0,t.jsxs)(n.p,{children:["The ",(0,t.jsx)(n.strong,{children:"Knowledge"})," page lists the documents OpenRAG has ingested into the OpenSearch vector database's ",(0,t.jsx)(n.code,{children:"documents"})," index."]}),"\n",(0,t.jsxs)(n.p,{children:["To explore your current knowledge, click ",(0,t.jsx)(r.A,{name:"Library","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Knowledge"}),".\nClick on a document to display the chunks derived from splitting the default documents into the vector database."]}),"\n",(0,t.jsxs)(n.p,{children:["Documents are processed with the default ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow, so if you want to split your documents differently, edit the ",(0,t.jsx)(n.strong,{children:"Knowledge Ingest"})," flow."]}),"\n",(0,t.jsx)(c.Ay,{}),"\n",(0,t.jsx)(n.h2,{id:"create-knowledge-filters",children:"Create knowledge filters"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG includes a knowledge filter system for organizing and managing document collections.\nKnowledge filters are saved search configurations that allow you to create custom views of your document collection. They store search queries, filter criteria, and display settings that can be reused across different parts of OpenRAG."}),"\n",(0,t.jsx)(n.p,{children:"Knowledge filters help agents work more efficiently with large document collections by focusing their context within relevant documents sets."}),"\n",(0,t.jsx)(n.p,{children:"To create a knowledge filter, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"All Knowledge"}),", and then click ",(0,t.jsx)(r.A,{name:"Plus","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Create New Filter"}),".\nThe ",(0,t.jsx)(n.strong,{children:"Create New Knowledge Filter"})," pane appears."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Enter a ",(0,t.jsx)(n.strong,{children:"Name"})," and ",(0,t.jsx)(n.strong,{children:"Description"}),", and then click ",(0,t.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Create Filter"}),".\nA new filter is created with default settings that match everything."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To modify the default filter, click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"All Knowledge"}),", and then click your new filter to edit it in the ",(0,t.jsx)(n.strong,{children:"Knowledge Filter"})," pane."]}),"\n",(0,t.jsx)(n.p,{children:"The following filter options are configurable."}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Search Query"}),': Enter text for semantic search, such as "financial reports from Q4".']}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Data Sources"}),": Select specific data sources or folders to include."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Document Types"}),": Filter by file type."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Owners"}),": Filter by who uploaded the documents."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Sources"}),": Filter by connector types, such as local upload or Google Drive."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Result Limit"}),": Set maximum number of results. The default is ",(0,t.jsx)(n.code,{children:"10"}),"."]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Score Threshold"}),": Set minimum relevance score. The default score is ",(0,t.jsx)(n.code,{children:"0"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["When you're done editing the filter, click ",(0,t.jsx)(r.A,{name:"Save","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Save Configuration"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["To apply the filter to OpenRAG globally, click ",(0,t.jsx)(r.A,{name:"Funnel","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"All Knowledge"}),", and then select the filter to apply."]}),"\n",(0,t.jsxs)(n.p,{children:["To apply the filter to a single chat session, in the ",(0,t.jsx)(r.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,t.jsx)(n.strong,{children:"Chat"})," window, click ",(0,t.jsx)(n.strong,{children:"@"}),", and then select the filter to apply."]}),"\n"]}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"openrag-default-configuration",children:"OpenRAG default configuration"}),"\n",(0,t.jsx)(n.p,{children:"OpenRAG automatically detects and configures the correct vector dimensions for embedding models, ensuring optimal search performance and compatibility."}),"\n",(0,t.jsxs)(n.p,{children:["The complete list of supported models is available at ",(0,t.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/services/models_service.py",children:[(0,t.jsx)(n.code,{children:"models_service.py"})," in the OpenRAG repository"]}),"."]}),"\n",(0,t.jsx)(n.p,{children:"You can use custom embedding models by specifying them in your configuration."}),"\n",(0,t.jsxs)(n.p,{children:["If you use an unknown embedding model, OpenRAG will automatically fall back to ",(0,t.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,t.jsx)(n.code,{children:"1536"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["The default embedding dimension is ",(0,t.jsx)(n.code,{children:"1536"})," and the default model is ",(0,t.jsx)(n.code,{children:"text-embedding-3-small"}),"."]}),"\n",(0,t.jsxs)(n.p,{children:["For models with known vector dimensions, see ",(0,t.jsxs)(n.a,{href:"https://github.com/langflow-ai/openrag/blob/main/src/config/settings.py",children:[(0,t.jsx)(n.code,{children:"settings.py"})," in the OpenRAG repository"]}),"."]})]})}function x(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(g,{...e})}):g(e)}},3782:(e,n,s)=>{s.d(n,{Ay:()=>d,RM:()=>r});var i=s(4848),t=s(8453),o=s(9179);const r=[];function l(e){const n={a:"a",p:"p",strong:"strong",...(0,t.R)(),...e.components};return(0,i.jsxs)(n.p,{children:["All flows included with OpenRAG are designed to be modular, performant, and provider-agnostic.\nTo modify a flow, click ",(0,i.jsx)(o.A,{name:"Settings2","aria-hidden":"true"})," ",(0,i.jsx)(n.strong,{children:"Settings"}),", and click ",(0,i.jsx)(n.strong,{children:"Edit in Langflow"}),".\nOpenRAG's visual editor is based on the ",(0,i.jsx)(n.a,{href:"https://docs.langflow.org/concepts-overview",children:"Langflow visual editor"}),", so you can edit your flows to match your specific use case."]})}function d(e={}){const{wrapper:n}={...(0,t.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(l,{...e})}):l(e)}},9179:(e,n,s)=>{s.d(n,{A:()=>o});s(6540);var i=s(4827),t=s(4848);function o({name:e,...n}){const s=i[e];return s?(0,t.jsx)(s,{...n}):null}}}]); 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If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment."}),"\n"]}),"\n",(0,t.jsx)(n.h2,{id:"deploy-openrag-with-docker-compose",children:"Deploy OpenRAG with Docker Compose"}),"\n",(0,t.jsx)(n.p,{children:"To install OpenRAG with Docker Compose, do the following:"}),"\n",(0,t.jsxs)(n.ol,{children:["\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Clone the OpenRAG repository."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"git clone https://github.com/langflow-ai/openrag.git\ncd openrag\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Install dependencies."}),"\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.jsxs)(n.p,{children:["Copy the example ",(0,t.jsx)(n.code,{children:".env"})," file included in the repository root.\nThe example file includes all environment variables with comments to guide you in finding and setting their values."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"cp .env.example .env\n"})}),"\n",(0,t.jsxs)(n.p,{children:["Alternatively, create a new ",(0,t.jsx)(n.code,{children:".env"})," file in the repository root."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{children:"touch .env\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Set environment variables. The Docker Compose files will be populated with values from your ",(0,t.jsx)(n.code,{children:".env"}),".\nThe following values are ",(0,t.jsx)(n.strong,{children:"required"})," to be set:"]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"OPENSEARCH_PASSWORD=your_secure_password\nOPENAI_API_KEY=your_openai_api_key\nLANGFLOW_SUPERUSER=admin\nLANGFLOW_SUPERUSER_PASSWORD=your_langflow_password\nLANGFLOW_SECRET_KEY=your_secret_key\n"})}),"\n",(0,t.jsxs)(n.p,{children:["For more information on configuring OpenRAG with environment variables, see ",(0,t.jsx)(n.a,{href:"/reference/configuration",children:"Environment variables"}),"."]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Start ",(0,t.jsx)(n.code,{children:"docling serve"})," on the host machine.\nBoth Docker deployments depend on ",(0,t.jsx)(n.code,{children:"docling serve"})," to be running on port ",(0,t.jsx)(n.code,{children:"5001"})," on the host machine. This enables ",(0,t.jsx)(n.a,{href:"https://opensource.apple.com/projects/mlx/",children:"Mac MLX"})," support for document processing."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv run python scripts/docling_ctl.py start --port 5001\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Confirm ",(0,t.jsx)(n.code,{children:"docling serve"})," is running."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{children:"uv run python scripts/docling_ctl.py status\n"})}),"\n",(0,t.jsx)(n.p,{children:"Successful result:"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"Status: running\nEndpoint: http://127.0.0.1:5001\nDocs: http://127.0.0.1:5001/docs\nPID: 27746\n"})}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Deploy OpenRAG with Docker Compose based on your deployment type."}),"\n",(0,t.jsx)(n.p,{children:"For GPU-enabled systems, run the following commands:"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose build\ndocker compose up -d\n"})}),"\n",(0,t.jsx)(n.p,{children:"For environments without GPU support, run:"}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose -f docker-compose-cpu.yml up -d\n"})}),"\n",(0,t.jsx)(n.p,{children:"The OpenRAG Docker Compose file starts five containers:"}),"\n",(0,t.jsxs)(n.table,{children:[(0,t.jsx)(n.thead,{children:(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.th,{children:"Container Name"}),(0,t.jsx)(n.th,{children:"Default Address"}),(0,t.jsx)(n.th,{children:"Purpose"})]})}),(0,t.jsxs)(n.tbody,{children:[(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"OpenRAG Backend"}),(0,t.jsx)(n.td,{children:(0,t.jsx)(n.a,{href:"http://localhost:8000",children:"http://localhost:8000"})}),(0,t.jsx)(n.td,{children:"FastAPI server and core functionality."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"OpenRAG Frontend"}),(0,t.jsx)(n.td,{children:(0,t.jsx)(n.a,{href:"http://localhost:3000",children:"http://localhost:3000"})}),(0,t.jsx)(n.td,{children:"React web interface for users."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"Langflow"}),(0,t.jsx)(n.td,{children:(0,t.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"})}),(0,t.jsx)(n.td,{children:"AI workflow engine and flow management."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"OpenSearch"}),(0,t.jsx)(n.td,{children:(0,t.jsx)(n.a,{href:"http://localhost:9200",children:"http://localhost:9200"})}),(0,t.jsx)(n.td,{children:"Vector database for document storage."})]}),(0,t.jsxs)(n.tr,{children:[(0,t.jsx)(n.td,{children:"OpenSearch Dashboards"}),(0,t.jsx)(n.td,{children:(0,t.jsx)(n.a,{href:"http://localhost:5601",children:"http://localhost:5601"})}),(0,t.jsx)(n.td,{children:"Database administration interface."})]})]})]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Verify installation by confirming all services are running."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose ps\n"})}),"\n",(0,t.jsx)(n.p,{children:"You can now access the application at:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Frontend"}),": ",(0,t.jsx)(n.a,{href:"http://localhost:3000",children:"http://localhost:3000"})]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Backend API"}),": ",(0,t.jsx)(n.a,{href:"http://localhost:8000",children:"http://localhost:8000"})]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Langflow"}),": ",(0,t.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"})]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Continue with ",(0,t.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["To stop ",(0,t.jsx)(n.code,{children:"docling serve"})," when you're done with your OpenRAG deployment, run:"]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv run python scripts/docling_ctl.py stop\n"})}),"\n",(0,t.jsx)(l.Ay,{}),"\n",(0,t.jsx)(n.h2,{id:"container-management-commands",children:"Container management commands"}),"\n",(0,t.jsxs)(n.p,{children:["Manage your OpenRAG containers with the following commands.\nThese commands are also available in the TUI's ",(0,t.jsx)(n.a,{href:"/get-started/tui#status",children:"Status menu"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"upgrade-containers",children:"Upgrade containers"}),"\n",(0,t.jsx)(n.p,{children:"Upgrade your containers to the latest version while preserving your data."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose pull\ndocker compose up -d --force-recreate\n"})}),"\n",(0,t.jsx)(n.h3,{id:"rebuild-containers-destructive",children:"Rebuild containers (destructive)"}),"\n",(0,t.jsxs)(n.p,{children:["Reset state by rebuilding all of your containers.\nYour OpenSearch and Langflow databases will be lost.\nDocuments stored in the ",(0,t.jsx)(n.code,{children:"./documents"})," directory will persist, since the directory is mounted as a volume in the OpenRAG backend container."]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose up --build --force-recreate --remove-orphans\n"})}),"\n",(0,t.jsx)(n.h3,{id:"remove-all-containers-and-data-destructive",children:"Remove all containers and data (destructive)"}),"\n",(0,t.jsx)(n.p,{children:"Completely remove your OpenRAG installation and delete all data.\nThis deletes all of your data, including OpenSearch data, uploaded documents, and authentication."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose down --volumes --remove-orphans --rmi local\ndocker system prune -f\n"})})]})}function u(e={}){const{wrapper:n}={...(0,o.R)(),...e.components};return n?(0,t.jsx)(n,{...e,children:(0,t.jsx)(h,{...e})}):h(e)}},8453:(e,n,r)=>{r.d(n,{R:()=>l,x:()=>a});var s=r(6540);const t={},o=s.createContext(t);function l(e){const n=s.useContext(o);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(t):e.components||t:l(e.components),s.createElement(o.Provider,{value:n},e.children)}},9365:(e,n,r)=>{r.d(n,{A:()=>l});r(6540);var s=r(4164);const t={tabItem:"tabItem_Ymn6"};var o=r(4848);function l({children:e,hidden:n,className:r}){return(0,o.jsx)("div",{role:"tabpanel",className:(0,s.A)(t.tabItem,r),hidden:n,children:e})}}}]); 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Use this Docker compose file for environments where GPU drivers aren't available."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["Both Docker deployments depend on ",(0,t.jsx)(n.code,{children:"docling serve"})," to be running on port ",(0,t.jsx)(n.code,{children:"5001"})," on the host machine. This enables ",(0,t.jsx)(n.a,{href:"https://opensource.apple.com/projects/mlx/",children:"Mac MLX"})," support for document processing. 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If you're 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.jsxs)(n.li,{children:["Create an ",(0,t.jsx)(n.a,{href:"https://platform.openai.com/api-keys",children:"OpenAI API key"}),". This key is ",(0,t.jsx)(n.strong,{children:"required"})," to start OpenRAG, but you can choose a different model provider during ",(0,t.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n",(0,t.jsx)(n.li,{children:"Optional: GPU support requires an NVIDIA GPU with CUDA support and compatible NVIDIA drivers installed on the OpenRAG host machine. 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interface."})]})]})]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsx)(n.p,{children:"Verify installation by confirming all services are running."}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"docker compose ps\n"})}),"\n",(0,t.jsx)(n.p,{children:"You can now access the application at:"}),"\n",(0,t.jsxs)(n.ul,{children:["\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Frontend"}),": ",(0,t.jsx)(n.a,{href:"http://localhost:3000",children:"http://localhost:3000"})]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Backend API"}),": ",(0,t.jsx)(n.a,{href:"http://localhost:8000",children:"http://localhost:8000"})]}),"\n",(0,t.jsxs)(n.li,{children:[(0,t.jsx)(n.strong,{children:"Langflow"}),": ",(0,t.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"})]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.li,{children:["\n",(0,t.jsxs)(n.p,{children:["Continue with ",(0,t.jsx)(n.a,{href:"#application-onboarding",children:"Application Onboarding"}),"."]}),"\n"]}),"\n"]}),"\n",(0,t.jsxs)(n.p,{children:["To stop ",(0,t.jsx)(n.code,{children:"docling serve"})," when you're done with your OpenRAG deployment, run:"]}),"\n",(0,t.jsx)(n.pre,{children:(0,t.jsx)(n.code,{className:"language-bash",children:"uv run python scripts/docling_ctl.py stop\n"})}),"\n",(0,t.jsx)(l.Ay,{}),"\n",(0,t.jsx)(n.h2,{id:"container-management-commands",children:"Container management commands"}),"\n",(0,t.jsxs)(n.p,{children:["Manage your OpenRAG containers with the following commands.\nThese commands are also available in the TUI's ",(0,t.jsx)(n.a,{href:"/get-started/tui#status",children:"Status menu"}),"."]}),"\n",(0,t.jsx)(n.h3,{id:"upgrade-containers",children:"Upgrade containers"}),"\n",(0,t.jsx)(n.p,{children:"Upgrade your containers to the latest version while preserving your 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",(0,r.jsx)(a.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Chat"}),".\nThe chat is powered by the OpenRAG OpenSearch Agent.\nFor more information, see ",(0,r.jsx)(n.a,{href:"/agents",children:"Langflow Agents"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Ask ",(0,r.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,r.jsx)(n.a,{href:"/knowledge",children:"Knowledge"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To confirm the agent is correct, click ",(0,r.jsx)(a.A,{name:"Library","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Knowledge"}),".\nThe ",(0,r.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,r.jsx)(n.h2,{id:"add-your-own-knowledge",children:"Add your own knowledge"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["To add documents to your knowledge base, click ",(0,r.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Add Knowledge"}),".","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["Select ",(0,r.jsx)(n.strong,{children:"Add File"})," to add a single file from your local machine (mapped with the Docker volume mount)."]}),"\n",(0,r.jsxs)(n.li,{children:["Select ",(0,r.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,r.jsxs)(n.li,{children:["Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see ",(0,r.jsx)(n.a,{href:"/knowledge#oauth-ingestion",children:"OAuth ingestion"}),"."]}),"\n"]}),"\n"]}),"\n",(0,r.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,r.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,r.jsxs)(n.li,{children:["Click the ",(0,r.jsx)(a.A,{name:"Gear","aria-hidden":"true"})," ",(0,r.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,r.jsx)(n.h2,{id:"change-components",children:"Swap out the language model to modify agent behavior"}),"\n",(0,r.jsxs)(n.p,{children:["To modify the knowledge ingestion or Agent behavior, click ",(0,r.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,r.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,r.jsx)(n.strong,{children:"Language model"}),", and not the ",(0,r.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,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["To edit the Agent's behavior, click ",(0,r.jsx)(n.strong,{children:"Edit in Langflow"}),".\nYou can more quickly access the ",(0,r.jsx)(n.strong,{children:"Language Model"})," and ",(0,r.jsx)(n.strong,{children:"Agent Instructions"})," fields in this page, but for illustration purposes, navigate to the Langflow visual builder."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["OpenRAG warns you that you're entering Langflow. Click ",(0,r.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["The OpenRAG OpenSearch Agent flow appears.\n",(0,r.jsx)(n.img,{alt:"OpenRAG Open Search Agent Flow",src:t(3982).A+"",width:"4086",height:"2240"})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["In the ",(0,r.jsx)(n.strong,{children:"Language Model"})," component, under ",(0,r.jsx)(n.strong,{children:"Model"}),", select a different OpenAI model."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Save your flow with ",(0,r.jsx)("kbd",{children:"Command+S"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["In OpenRAG, start a new conversation by clicking the ",(0,r.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," in the ",(0,r.jsx)(n.strong,{children:"Conversations"})," tab."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Ask the same question as before to demonstrate how a different language model changes the results."}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"integrate-openrag-into-your-application",children:"Integrate OpenRAG into your application"}),"\n",(0,r.jsxs)(n.p,{children:["To integrate OpenRAG into your application, use the ",(0,r.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. Langflow provides code snippets to help you get started."]}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Create a ",(0,r.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Create a Langflow API key"}),(0,r.jsxs)(n.p,{children:["A Langflow API key is a user-specific token you can use with Langflow.\nIt is ",(0,r.jsx)(n.strong,{children:"only"})," used for sending requests to the Langflow server.\nIt does ",(0,r.jsx)(n.strong,{children:"not"})," access to OpenRAG."]}),(0,r.jsx)(n.p,{children:"To create a Langflow API key, do the following:"}),(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["In Langflow, click your user icon, and then select ",(0,r.jsx)(n.strong,{children:"Settings"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Click ",(0,r.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,r.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Add New"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Name your key, and then click ",(0,r.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Copy the API key and store it securely."}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["To use your Langflow API key in a request, set a ",(0,r.jsx)(n.code,{children:"LANGFLOW_API_KEY"})," environment variable in your terminal, and then include an ",(0,r.jsx)(n.code,{children:"x-api-key"})," header or query parameter with your request.\nFor example:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.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",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["To navigate to the OpenRAG OpenSearch Agent flow, click ",(0,r.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Settings"}),", and then click ",(0,r.jsx)(n.strong,{children:"Edit in Langflow"})," in the OpenRAG OpenSearch Agent flow."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Click ",(0,r.jsx)(n.strong,{children:"Share"}),", and then click ",(0,r.jsx)(n.strong,{children:"API access"}),"."]}),"\n",(0,r.jsxs)(n.p,{children:["The default code in the API access pane constructs a request with the Langflow server ",(0,r.jsx)(n.code,{children:"url"}),", ",(0,r.jsx)(n.code,{children:"headers"}),", and a ",(0,r.jsx)(n.code,{children:"payload"})," of request data. The code snippets automatically include the ",(0,r.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"})," and ",(0,r.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,r.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"}),"."]}),"\n",(0,r.jsxs)(i.A,{children:[(0,r.jsx)(l.A,{value:"python",label:"Python",children:(0,r.jsx)(n.pre,{children:(0,r.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,r.jsx)(l.A,{value:"typescript",label:"TypeScript",children:(0,r.jsx)(n.pre,{children:(0,r.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,r.jsx)(l.A,{value:"curl",label:"curl",children:(0,r.jsx)(n.pre,{children:(0,r.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,r.jsxs)(n.li,{children:["\n",(0,r.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,r.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,r.jsx)(n.strong,{children:"Simple Agent"})," template flow:"]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Result"}),(0,r.jsx)(n.pre,{children:(0,r.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,r.jsx)(n.p,{children:"To further explore the API, see:"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["The Langflow ",(0,r.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,r.jsx)(n.li,{children:(0,r.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,o.R)(),...e.components};return n?(0,r.jsx)(n,{...e,children:(0,r.jsx)(p,{...e})}):p(e)}},3982:(e,n,t)=>{t.d(n,{A:()=>s});const s=t.p+"assets/images/opensearch-agent-flow-a759d00657f2fdb62e64c84c643e8896.png"},9179:(e,n,t)=>{t.d(n,{A:()=>o});t(6540);var s=t(4827),r=t(4848);function o({name:e,...n}){const t=s[e];return t?(0,r.jsx)(t,{...n}):null}}}]); \ No newline at end of file diff --git a/assets/js/af920ffe.87292094.js b/assets/js/af920ffe.87292094.js new file mode 100644 index 00000000..30537f7a --- /dev/null +++ b/assets/js/af920ffe.87292094.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":"Install with Docker","permalink":"/get-started/docker"},"next":{"title":"Terminal User Interface (TUI)","permalink":"/get-started/tui"}}');var r=t(4848),o=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,o.R)(),...e.components},{Details:s}=n;return s||function(e,n){throw new Error("Expected "+(n?"component":"object")+" `"+e+"` to be defined: you likely forgot to import, pass, or provide it.")}("Details",!0),(0,r.jsxs)(r.Fragment,{children:[(0,r.jsx)(n.p,{children:"Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API."}),"\n",(0,r.jsx)(n.h2,{id:"prerequisites",children:"Prerequisites"}),"\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsx)(n.li,{children:(0,r.jsx)(n.a,{href:"/install",children:"Install and start OpenRAG"})}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"find-your-way-around",children:"Find your way around"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["In OpenRAG, click ",(0,r.jsx)(a.A,{name:"MessageSquare","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Chat"}),".\nThe chat is powered by the OpenRAG OpenSearch Agent.\nFor more information, see ",(0,r.jsx)(n.a,{href:"/agents",children:"Langflow Agents"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["Ask ",(0,r.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,r.jsx)(n.a,{href:"/knowledge",children:"Knowledge"}),"."]}),"\n",(0,r.jsxs)(n.li,{children:["To confirm the agent is correct, click ",(0,r.jsx)(a.A,{name:"Library","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Knowledge"}),".\nThe ",(0,r.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,r.jsx)(n.h2,{id:"add-your-own-knowledge",children:"Add your own knowledge"}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["To add documents to your knowledge base, click ",(0,r.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Add Knowledge"}),".","\n",(0,r.jsxs)(n.ul,{children:["\n",(0,r.jsxs)(n.li,{children:["Select ",(0,r.jsx)(n.strong,{children:"Add File"})," to add a single file from your local machine (mapped with the Docker volume mount)."]}),"\n",(0,r.jsxs)(n.li,{children:["Select ",(0,r.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,r.jsxs)(n.li,{children:["Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see ",(0,r.jsx)(n.a,{href:"/knowledge#oauth-ingestion",children:"OAuth ingestion"}),"."]}),"\n"]}),"\n"]}),"\n",(0,r.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,r.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,r.jsxs)(n.li,{children:["Click the ",(0,r.jsx)(a.A,{name:"Gear","aria-hidden":"true"})," ",(0,r.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,r.jsx)(n.h2,{id:"change-components",children:"Swap out the language model to modify agent behavior"}),"\n",(0,r.jsxs)(n.p,{children:["To modify the knowledge ingestion or Agent behavior, click ",(0,r.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Settings"}),"."]}),"\n",(0,r.jsx)(n.p,{children:"In this example, you'll try a different LLM to demonstrate how the Agent's response changes."}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["To edit the Agent's behavior, click ",(0,r.jsx)(n.strong,{children:"Edit in Langflow"}),".\nYou can more quickly access the ",(0,r.jsx)(n.strong,{children:"Language Model"})," and ",(0,r.jsx)(n.strong,{children:"Agent Instructions"})," fields in this page, but for illustration purposes, navigate to the Langflow visual builder."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["OpenRAG warns you that you're entering Langflow. Click ",(0,r.jsx)(n.strong,{children:"Proceed"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["The OpenRAG OpenSearch Agent flow appears.\n",(0,r.jsx)(n.img,{alt:"OpenRAG Open Search Agent Flow",src:t(3982).A+"",width:"4086",height:"2240"})]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["In the ",(0,r.jsx)(n.strong,{children:"Language Model"})," component, under ",(0,r.jsx)(n.strong,{children:"Model"}),", select a different OpenAI model."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Save your flow with ",(0,r.jsx)("kbd",{children:"Command+S"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["In OpenRAG, start a new conversation by clicking the ",(0,r.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," in the ",(0,r.jsx)(n.strong,{children:"Conversations"})," tab."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Ask the same question as before to demonstrate how a different language model changes the results."}),"\n"]}),"\n"]}),"\n",(0,r.jsx)(n.h2,{id:"integrate-openrag-into-your-application",children:"Integrate OpenRAG into your application"}),"\n",(0,r.jsxs)(n.p,{children:["To integrate OpenRAG into your application, use the ",(0,r.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. Langflow provides code snippets to help you get started."]}),"\n",(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Create a ",(0,r.jsx)(n.a,{href:"https://docs.langflow.org/api-keys-and-authentication",children:"Langflow API key"}),"."]}),"\n",(0,r.jsxs)(s,{children:[(0,r.jsx)("summary",{children:"Create a Langflow API key"}),(0,r.jsxs)(n.p,{children:["A Langflow API key is a user-specific token you can use with Langflow.\nIt is ",(0,r.jsx)(n.strong,{children:"only"})," used for sending requests to the Langflow server.\nIt does ",(0,r.jsx)(n.strong,{children:"not"})," access to OpenRAG."]}),(0,r.jsx)(n.p,{children:"To create a Langflow API key, do the following:"}),(0,r.jsxs)(n.ol,{children:["\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["In Langflow, click your user icon, and then select ",(0,r.jsx)(n.strong,{children:"Settings"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Click ",(0,r.jsx)(n.strong,{children:"Langflow API Keys"}),", and then click ",(0,r.jsx)(a.A,{name:"Plus","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Add New"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Name your key, and then click ",(0,r.jsx)(n.strong,{children:"Create API Key"}),"."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Copy the API key and store it securely."}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["To use your Langflow API key in a request, set a ",(0,r.jsx)(n.code,{children:"LANGFLOW_API_KEY"})," environment variable in your terminal, and then include an ",(0,r.jsx)(n.code,{children:"x-api-key"})," header or query parameter with your request.\nFor example:"]}),"\n",(0,r.jsx)(n.pre,{children:(0,r.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",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["To navigate to the OpenRAG OpenSearch Agent flow, click ",(0,r.jsx)(a.A,{name:"Settings2","aria-hidden":"true"})," ",(0,r.jsx)(n.strong,{children:"Settings"}),", and then click ",(0,r.jsx)(n.strong,{children:"Edit in Langflow"})," in the OpenRAG OpenSearch Agent flow."]}),"\n"]}),"\n",(0,r.jsxs)(n.li,{children:["\n",(0,r.jsxs)(n.p,{children:["Click ",(0,r.jsx)(n.strong,{children:"Share"}),", and then click ",(0,r.jsx)(n.strong,{children:"API access"}),"."]}),"\n",(0,r.jsxs)(n.p,{children:["The default code in the API access pane constructs a request with the Langflow server ",(0,r.jsx)(n.code,{children:"url"}),", ",(0,r.jsx)(n.code,{children:"headers"}),", and a ",(0,r.jsx)(n.code,{children:"payload"})," of request data. The code snippets automatically include the ",(0,r.jsx)(n.code,{children:"LANGFLOW_SERVER_ADDRESS"})," and ",(0,r.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,r.jsx)(n.a,{href:"http://localhost:7860",children:"http://localhost:7860"}),"."]}),"\n",(0,r.jsxs)(i.A,{children:[(0,r.jsx)(l.A,{value:"python",label:"Python",children:(0,r.jsx)(n.pre,{children:(0,r.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,r.jsx)(l.A,{value:"typescript",label:"TypeScript",children:(0,r.jsx)(n.pre,{children:(0,r.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,r.jsx)(l.A,{value:"curl",label:"curl",children:(0,r.jsx)(n.pre,{children:(0,r.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,r.jsxs)(n.li,{children:["\n",(0,r.jsx)(n.p,{children:"Copy the snippet, paste it in a script file, and then run the script to send the request. 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e={354:0,869:0};c.f.j=(t,r)=>{var a=c.o(e,t)?e[t]:void 0;if(0!==a)if(a)r.push(a[2]);else if(/^(354|869)$/.test(t))e[t]=0;else{var o=new Promise((r,o)=>a=e[t]=[r,o]);r.push(a[2]=o);var n=c.p+c.u(t),f=new Error;c.l(n,r=>{if(c.o(e,t)&&(0!==(a=e[t])&&(e[t]=void 0),a)){var o=r&&("load"===r.type?"missing":r.type),n=r&&r.target&&r.target.src;f.message="Loading chunk "+t+" failed.\n("+o+": "+n+")",f.name="ChunkLoadError",f.type=o,f.request=n,a[1](f)}},"chunk-"+t,t)}},c.O.j=t=>0===e[t];var t=(t,r)=>{var a,o,n=r[0],f=r[1],i=r[2],d=0;if(n.some(t=>0!==e[t])){for(a in f)c.o(f,a)&&(c.m[a]=f[a]);if(i)var u=i(c)}for(t&&t(r);d -Deploy with Docker | OpenRAG - +Install with Docker | OpenRAG + -

Deploy with Docker

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

+

Install with Docker

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

  • docker-compose.yml is an OpenRAG deployment with GPU support for accelerated AI processing.

    @@ -31,7 +31,7 @@ They deploy the same applications and containers, but to different environments.
  • Create an OpenAI API key. This key is required to start OpenRAG, but you can choose a different model provider during Application Onboarding.
  • Optional: GPU support requires an NVIDIA GPU with CUDA support and compatible NVIDIA drivers installed on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment.
-

Deploy OpenRAG with Docker Compose​

+

Install OpenRAG with Docker Compose​

To install OpenRAG with Docker Compose, do the following:

  1. @@ -67,7 +67,7 @@ Both Docker deployments depend on docling serve to be running on po 
    Status: running
    Endpoint: http://127.0.0.1:5001
    Docs: http://127.0.0.1:5001/docs
    PID: 27746
  2. -

    Deploy OpenRAG with Docker Compose based on your deployment type.

    +

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

    For GPU-enabled systems, run the following commands:

    docker compose build
    docker compose up -d

    For environments without GPU support, run:

    @@ -93,12 +93,10 @@ Both Docker deployments depend on docling serve to be running on po 
    uv run python scripts/docling_ctl.py stop

    Application onboarding​

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

    -

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

    -

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

    -

    The language model can be changed later in Settings, but the embeddings model cannot be changed later.

    +

    Values from onboarding can be changed later in the OpenRAG Settings page.

      -
    1. Enable Get API key from environment variable to automatically enter your key from the TUI-generated .env file.
      2. +
    2. Enable Get API key from environment variable to automatically enter your key from the TUI-generated .env file. +Alternatively, paste an OpenAI API key into the field.
    3. Under Advanced settings, select your Embedding Model and Language Model.
    4. To load 2 sample PDFs, enable Sample dataset. This is recommended, but not required.
      5. @@ -137,7 +135,7 @@ Documents stored in the ./documents directory will persist, since t

      Remove all containers and data (destructive)​

      Completely remove your OpenRAG installation and delete all data. This deletes all of your data, including OpenSearch data, uploaded documents, and authentication.

      -
      docker compose down --volumes --remove-orphans --rmi local
      docker system prune -f
  • +
    docker compose down --volumes --remove-orphans --rmi local
    docker system prune -f
  • © 2025 OpenRAG
diff --git a/get-started/tui/index.html b/get-started/tui/index.html index 5a44da7c..4a7e6614 100644 --- a/get-started/tui/index.html +++ b/get-started/tui/index.html @@ -4,14 +4,14 @@ Terminal User Interface (TUI) commands | OpenRAG - + -

Terminal User Interface (TUI) commands

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

+

Terminal User Interface (TUI) commands

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

OpenRAG TUI Interface

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

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

diff --git a/index.html b/index.html index 0084606c..c50b77dd 100644 --- a/index.html +++ b/index.html @@ -4,14 +4,14 @@ 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:

    diff --git a/ingestion/index.html b/ingestion/index.html index e43df297..885da908 100644 --- a/ingestion/index.html +++ b/ingestion/index.html @@ -4,7 +4,7 @@ Docling Ingestion | OpenRAG - + diff --git a/install/index.html b/install/index.html index a950475c..424105a3 100644 --- a/install/index.html +++ b/install/index.html @@ -4,14 +4,14 @@ Install OpenRAG | OpenRAG - + -

    Install OpenRAG

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

    +

    Install OpenRAG

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

    If you prefer running Docker commands and manually editing .env files, see Deploy with Docker.

    Prerequisites​

      @@ -81,8 +81,9 @@ When startup is complete, the TUI displays the following:

      Paste your OpenAI API key in the OpenAI API key field.

    • -

      Add your client and secret values for Google, Azure, or AWS OAuth. -These values can be found in your OAuth provider.

      +

      Add your client and secret values for Google or Microsoft OAuth. +These values can be found with your OAuth provider. +For more information, see the Google OAuth client or Microsoft Graph OAuth client documentation.

    • The OpenRAG TUI presents redirect URIs for your OAuth app. @@ -100,13 +101,18 @@ When startup is complete, the TUI displays the following:

    • To open the OpenRAG application, click Open App, press 6, or navigate to http://localhost:3000. -You will be presented with your provider's OAuth sign-in screen, and be redirected to the redirect URI after sign-in. -Continue with Application Onboarding.

      +You are presented with your provider's OAuth sign-in screen. +After sign-in, you are redirected to the redirect URI.

      Two additional variables are available for Advanced Setup:

      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.

      +Supported webhook endpoints:

      +
        +
      • Google Drive: /connectors/google_drive/webhook
        • +
      • OneDrive: /connectors/onedrive/webhook
        • +
      • SharePoint: /connectors/sharepoint/webhook
        • +

    • Continue with Application Onboarding.

      @@ -114,12 +120,10 @@ For example, for Google Drive file synchronization the webhook URL is /con

    Application onboarding​

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

    -

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

    -

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

    -

    The language model can be changed later in Settings, but the embeddings model cannot be changed later.

    +

    Values from onboarding can be changed later in the OpenRAG Settings page.

      -
    1. Enable Get API key from environment variable to automatically enter your key from the TUI-generated .env file.
      2. +
    2. Enable Get API key from environment variable to automatically enter your key from the TUI-generated .env file. +Alternatively, paste an OpenAI API key into the field.
    3. Under Advanced settings, select your Embedding Model and Language Model.
    4. To load 2 sample PDFs, enable Sample dataset. This is recommended, but not required.
      5. @@ -143,7 +147,7 @@ OpenRAG retrieves the available models from your Ollama server. This is recommended, but not required.
    5. Click Complete.
    6. Continue with the Quickstart.
      7. -
  • © 2025 OpenRAG
diff --git a/knowledge/index.html b/knowledge/index.html index f6c46912..88a2522d 100644 --- a/knowledge/index.html +++ b/knowledge/index.html @@ -4,7 +4,7 @@ OpenSearch Knowledge | OpenRAG - + @@ -29,7 +29,7 @@ The file is loaded into your OpenSearch database, and appears in the Knowledge p

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

Ingest files through OAuth connectors​

-

OpenRAG supports Google Drive, OneDrive, and AWS S3 as OAuth connectors for seamless document synchronization.

+

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

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

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

To add an OAuth connector to OpenRAG, do the following. diff --git a/quickstart/index.html b/quickstart/index.html index 36735abc..f2a4ac7f 100644 --- a/quickstart/index.html +++ b/quickstart/index.html @@ -4,14 +4,14 @@ 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
    • @@ -47,9 +47,7 @@ If you aren't getting the results you need, you can further tune the knowle

    Swap out the language model to modify agent behavior​

    To modify the knowledge ingestion or Agent behavior, click Settings.

    -

    In this example, you'll try a different LLM to demonstrate how the Agent's response changes. -You can only change the Language model, and not the Model provider that you started with in OpenRAG. -If you're using Ollama, you can use any installed model.

    +

    In this example, you'll try a different LLM to demonstrate how the Agent's response changes.

    1. To edit the Agent's behavior, click Edit in Langflow. @@ -122,7 +120,7 @@ The following is an example of a response from running the Simple Agent<

  • © 2025 OpenRAG
diff --git a/reference/configuration/index.html b/reference/configuration/index.html index 5f12444e..0d67ec74 100644 --- a/reference/configuration/index.html +++ b/reference/configuration/index.html @@ -4,7 +4,7 @@ Environment variables | OpenRAG - + diff --git a/support/troubleshoot/index.html b/support/troubleshoot/index.html index 416d9c22..5ba3dac8 100644 --- a/support/troubleshoot/index.html +++ b/support/troubleshoot/index.html @@ -4,7 +4,7 @@ Troubleshoot | OpenRAG - +