[{"data":1,"prerenderedAt":115},["ShallowReactive",2],{"seo-verification":3,"marketplace-app-en-anything-llm":6},{"google":4,"bing":5},"EycwPY2XMyTkVzas3n1ygeNJFGAH513qrMjfDljzsMQ","",{"slug":7,"slugs":8,"categorySlugs":9,"name":13,"description":14,"phase":15,"unavailableReason":16,"docsUrl":17,"logo":18,"github":19,"tagline":20,"longDescription":21,"features":22,"useCases":31,"steps":41,"faq":60,"specs":76,"compatibleOs":86,"relatedApps":87,"relatedPosts":108,"category":112},"anything-llm",{"fr":7,"en":7,"ar":7},{"fr":10,"en":11,"ar":12},"ia","artificial-intelligence","الذكاء-الاصطناعي","AnythingLLM","Open-source AI workspace with built-in RAG, AI agents, and multi-model chat. Connect your own documents, use any LLM — hosted privately on your VPS.",1,null,"https:\u002F\u002Fservorbit.com\u002Fblog\u002Fhow-to-host-anythingllm-on-a-vps","https:\u002F\u002Fcdn.jsdelivr.net\u002Fgh\u002Fselfhst\u002Ficons\u002Fsvg\u002Fanythingllm.svg","https:\u002F\u002Fgithub.com\u002FMintplex-Labs\u002Fanything-llm","Private AI workspace with RAG and agents — your documents, your models, your server.","AnythingLLM is an all-in-one open-source AI application that turns your documents into a private, queryable knowledge base. It ships as a single Docker image that runs on any 2 GB VPS and connects to whichever LLM you already use — Ollama (local), OpenAI, Anthropic, Mistral, LiteLLM, and more.\n\nThe built-in RAG engine ingests PDFs, Word docs, plain text, code repositories, YouTube transcripts, Notion pages, and Confluence spaces, then chunks, embeds, and indexes them into an integrated LanceDB vector store. Each workspace is isolated: different documents, different LLM, different system prompt. Ask a question and AnythingLLM retrieves the relevant chunks, passes them as context to your model, and returns a cited answer.\n\nAnythingLLM also ships a no-code AI agent builder: string together web search, code execution, document retrieval, and external API calls without writing a line of code. User management with roles (admin, manager, default) makes it suitable for team deployments. MIT-licensed and 62k+ GitHub stars as of July 2026.",[23,24,25,26,27,28,29,30],"Built-in RAG: ingest PDFs, Word docs, TXT, code repos, YouTube, Confluence, Notion, and more","Connect any LLM: Ollama, OpenAI, Anthropic, Mistral, Azure OpenAI, LiteLLM, Groq, and local models","No-code AI agent builder with web search, code execution, and API call tools","Multi-workspace isolation: separate documents, LLM, and system prompt per workspace","Multi-user with roles: admin, manager, default user — team-ready out of the box","REST API: embed AnythingLLM into your own products via a documented HTTP API","Pluggable vector store: built-in LanceDB (zero setup) or connect Qdrant, Pinecone, Chroma, Weaviate","Zero telemetry, MIT licence, fully air-gap capable",[32,35,38],{"title":33,"body":34},"Internal knowledge base","Upload your SOPs, contracts, and technical docs. Your team asks questions in natural language and gets accurate, cited answers — without sending any data to OpenAI.",{"title":36,"body":37},"Developer assistant","Ingest your codebase, architecture docs, and API references. Use AnythingLLM as a private coding assistant that knows your stack and answers in context.",{"title":39,"body":40},"Customer-facing AI","Expose AnythingLLM's REST API to power an AI chat widget on your product, trained exclusively on your own documentation.",[42,45,48,51,54,57],{"title":43,"body":44},"Order a ServOrbit VPS","AnythingLLM itself makes do with about 512 MB of RAM. Sizing depends on the model: with an external API (OpenAI, Anthropic, Mistral), 2 GB is more than enough; with Ollama installed on the same VPS and a 7-billion-parameter model, count on 8 GB in total. Plan disk space for your documents and their vectors.",{"title":46,"body":47},"Deploy from the Marketplace","In your ServOrbit client area: Marketplace → AI → AnythingLLM → Deploy. The `mintplexlabs\u002Fanythingllm:latest` image (about 700 MB) is pulled once and the container starts within seconds on port 3001. The named volume `anythingllm-storage` keeps all of your documents, your settings and the SQLite database.",{"title":49,"body":50},"Sign in for the first time","There are no credentials to hand over to you: this installation starts in single-user mode with NO password. Open it straight away, finish the setup wizard, then go to Settings and turn on “Password Protect Instance” — until you do, anyone who reaches the address can read your documents and change your settings.",{"title":52,"body":53},"Create the administrator account on first access","Open the application in your browser. With a domain attached, the address is `https:\u002F\u002F\u003Cyour-domain>`; without a domain there is no public address: open an SSH tunnel with `ssh -L 3001:127.0.0.1:3001 root@\u003Cyour-vps-ip>`, then go to `http:\u002F\u002Flocalhost:3001` — 3001 is the catalogue port, use the one shown on your app's card in the client area. AnythingLLM detects a fresh install and guides you through creating the first administrator account; that is also the moment when the JWT secret used to sign every user session is set. No domain is required for this step.",{"title":55,"body":56},"Connect a model provider","Go to Settings → LLM Provider. Choose Ollama if it runs on the same VPS, OpenAI by entering your API key, or any other supported provider. AnythingLLM tests the connection before saving. By pointing it at LiteLLM, you will be able to change provider later without touching your workspaces.",{"title":58,"body":59},"Create a workspace and upload your documents","Click New Workspace, give it a name (“Product documentation”, for instance), then drop in your PDFs or paste a URL. AnythingLLM chunks the content, computes the vectors and stores them in LanceDB. Ask your first question: the system retrieves the relevant passages and passes them on to your model. Then create the accounts for your team and assign their roles.",[61,64,67,70,73],{"q":62,"a":63},"What is AnythingLLM?","AnythingLLM is a self-hosted AI workspace that combines document RAG, multi-model chat, and AI agents in a single Docker container. You upload your documents, connect any LLM provider, and interact with your data in natural language — everything stays on your server.",{"q":65,"a":66},"What LLMs does AnythingLLM support?","Ollama (local models), OpenAI, Anthropic, Azure OpenAI, Mistral, Google Gemini, LiteLLM, Cohere, TogetherAI, Groq, Llama.cpp, and more. You can switch providers per workspace without losing your documents.",{"q":68,"a":69},"What is the minimum RAM?","AnythingLLM itself needs ~512 MB RAM. For document embeddings and inference, you need an LLM: if you use Ollama locally with a 7B model, plan for 8 GB total. If you use an external API (OpenAI, Anthropic), 2 GB RAM is sufficient.",{"q":71,"a":72},"Can it handle large document collections?","Yes. AnythingLLM uses LanceDB for its built-in vector store, which scales to millions of vectors on a single VPS. For very large collections you can swap the vector store to Qdrant, Pinecone, or Weaviate in Settings → Vector DB.",{"q":74,"a":75},"Is AnythingLLM free?","The self-hosted version is MIT-licensed and completely free. Mintplex Labs also offers a cloud-hosted plan and a desktop app, but everything you need for a private deployment is in the open-source Docker image.",{"ram":77,"cpu":78,"stack":79,"port":85},"512 MB (2 GB+ with local Ollama)","1 vCPU",[80,81,82,83,84],"Docker","Node.js","Python","SQLite","LanceDB","3001",[],[88,96,102],{"name":89,"slug":90,"categorySlug":11,"categoryName":91,"categoryColor":92,"logo":93,"tagline":94,"description":95},"Open WebUI","open-webui","Artificial Intelligence","text-purple-400 bg-purple-500\u002F10","https:\u002F\u002Fcdn.jsdelivr.net\u002Fgh\u002Fselfhst\u002Ficons\u002Fsvg\u002Fopen-webui.svg","Web interface for your LLMs — Ollama, OpenAI, Mistral — hosted on your own server.","Web interface to interact with your local or remote LLMs. Your data stays on your infrastructure — no third party involved.",{"name":97,"slug":98,"categorySlug":11,"categoryName":91,"categoryColor":92,"logo":99,"tagline":100,"description":101},"Ollama","ollama","https:\u002F\u002Fcdn.simpleicons.org\u002Follama","Run open-source LLMs on your VPS — OpenAI-compatible API, zero per-token cost.","Run open-source LLMs locally via a dead-simple API. Pull Llama 3, Mistral, Qwen or DeepSeek in one command — OpenAI-compatible, zero per-token cost.",{"name":103,"slug":104,"categorySlug":11,"categoryName":91,"categoryColor":92,"logo":105,"tagline":106,"description":107},"Dify","dify","https:\u002F\u002Fcdn.jsdelivr.net\u002Fgh\u002Fselfhst\u002Ficons\u002Fsvg\u002Fdify.svg","Build LLM applications with drag-and-drop — chatbots, agents, RAG pipelines — no backend required.","Build LLM applications visually: chatbots, RAG agents, pipelines — without writing any backend code.",[109,110,111],"heberger-anythingllm-vps","heberger-open-webui","heberger-ollama-vps",{"key":10,"slug":11,"name":91,"objective":113,"icon":114,"color":92},"Build, host and run AI solutions.","ai",1787661757565]