[{"data":1,"prerenderedAt":116},["ShallowReactive",2],{"seo-verification":3,"blog-heberger-anythingllm-vps-en":6},{"google":4,"bing":5},"EycwPY2XMyTkVzas3n1ygeNJFGAH513qrMjfDljzsMQ","",{"id":7,"slug":8,"title":9,"excerpt":10,"readTime":11,"views":12,"isPinned":13,"publishedAt":14,"category":15,"categories":21,"featuredImage":23,"bgImage":24,"posterImage":25,"relatedSolution":26,"intro":28,"sections":29,"ctaTitle":72,"ctaBody":73,"ctaButton":74,"ctaUrl":75,"relatedPosts":76},9,"heberger-anythingllm-vps","How to Host AnythingLLM on a VPS","Host AnythingLLM on your VPS for a private RAG assistant over your documents. Docker, workspaces, reverse proxy and SSL explained.",8,533,false,"2026-06-11T00:00:00+00:00",{"id":16,"name":17,"slug":18,"color":19,"icon":20},1,"Artificial Intelligence","intelligence-artificielle","bg-purple-500\u002F10 text-purple-400","ia",[22],{"id":16,"name":17,"slug":18,"color":19,"icon":20},null,"\u002Fblog\u002Fcovers\u002Fbg.svg","\u002Fblog\u002Fcovers\u002Fheberger-anythingllm-vps-poster.svg",{"categorySlug":20,"appSlug":27},"anythingllm","AnythingLLM turns your internal documents into a chat-queryable knowledge base, with multi-user management and isolated workspaces. By hosting it on your VPS, you get a private ChatGPT connected to your own files, without handing your confidential PDFs to an external service. Here is how to do it.",[30,34,44,47,69],{"type":31,"title":32,"body":33},"h2","Why self-host AnythingLLM on a VPS","AnythingLLM is first and foremost a complete RAG engine: document ingestion, chunking, vectorization, semantic search and generation, all within a multi-user interface. The heart of the matter is the data: financial reports, contracts, product documentation, support knowledge base. On a VPS, the document embedder, the vector database (LanceDB built in by default) and the conversations stay in your volumes. You control who accesses which workspace, you choose the LLM (cloud API or local model), and you avoid the ingestion quotas of SaaS offerings. For an agency managing several clients, each workspace becomes a watertight silo on infrastructure you control.",{"type":35,"title":36,"items":37},"ul","The concrete benefits of a self-hosted AnythingLLM",[38,39,40,41,42,43],"Confidential documents indexed locally, never sent to a third-party ingestion service.","Workspaces partitioned by client or team, with role management.","Vector database of your choice: embedded LanceDB, or external Chroma\u002FQdrant on the same VPS.","Connection to any LLM provider, including a local Ollama for zero-cloud.","No limit on the number of documents or pages ingested.","Simple backup: the entire state fits in a single `storage` volume to archive.",{"type":31,"title":45,"body":46},"Hardware and software requirements","The AnythingLLM container is reasonable, but embedding large corpora consumes CPU and RAM. Aim for 2 vCPU \u002F 2 GB of RAM to start, and 4 vCPU \u002F 8 GB if you index thousands of documents or use a local embedding model. Plan for 15 to 20 GB of disk, because vectors and the document cache grow quickly. Docker and Docker Compose are required, along with a subdomain (e.g. chat.your-domain.com) and port 443 open. If you stick with cloud APIs for inference, keep your keys handy; for fully local, plan for extra RAM for the model.",{"type":48,"title":49,"steps":50},"steps","Deploy AnythingLLM with Docker and HTTPS",[51,54,57,60,63,66],{"title":52,"body":53},"Initialize the environment","Over SSH, create `mkdir -p \u002Fopt\u002Fanythingllm\u002Fstorage && cd \u002Fopt\u002Fanythingllm`. Adjust the permissions of the `storage` folder that will host the vector database and the documents: `chmod -R 777 storage` (the container runs with a dedicated UID).",{"title":55,"body":56},"Write the docker-compose and the .env","Use the `mintplexlabs\u002Fanythingllm` image, map the internal port `3001`, mount `.\u002Fstorage:\u002Fapp\u002Fserver\u002Fstorage`, and point the `STORAGE_DIR` variable. In a `.env` file, define `JWT_SECRET` and the chosen LLM provider (`LLM_PROVIDER`, associated keys).",{"title":58,"body":59},"Start and create the admin account","Run `docker compose up -d`. On first local access on port `3001`, AnythingLLM guides you to create the administrator account and configure the embedding model and the LLM.",{"title":61,"body":62},"Set up the reverse proxy","With Nginx Proxy Manager or Caddy, route `chat.your-domain.com` to `localhost:3001` and enable Let's Encrypt. Remember to increase `client_max_body_size` on the proxy side to allow uploading large documents.",{"title":64,"body":65},"Create a first workspace","In the interface, create a workspace, drag in a few PDFs, run the embedding then test a question. Check that the answers properly cite the sources extracted from your files.",{"title":67,"body":68},"Enable multi-user mode","In the settings, switch to multi-user mode, invite your collaborators and assign roles. Restrict each user to only the workspaces that concern them.",{"type":70,"body":71},"tip","For large corpora, don't stick with embedded LanceDB: deploy Qdrant in a neighboring container and point AnythingLLM to it via the internal Docker network. Qdrant handles millions of vectors better, offers metadata filtering and remains independently queryable, which makes debugging your semantic searches easier.","Your private AI knowledge base on a ServOrbit Cloud VPS","The ServOrbit Cloud VPS provides the storage and RAM needed to index your documents and run AnythingLLM in full confidentiality. Scale on demand as your corpus grows.","Start my Cloud VPS","\u002Fvps-cloud",[77,90,104],{"id":16,"slug":78,"title":79,"excerpt":80,"readTime":81,"views":82,"isPinned":13,"publishedAt":83,"category":84,"categories":85,"featuredImage":23,"bgImage":24,"posterImage":87,"relatedSolution":88},"heberger-open-webui","How to Host Open WebUI on a VPS","A complete guide to deploying Open WebUI on your own VPS. Keep control of your data, avoid cloud API costs, and access your LLMs from a clean web interface.",6,3200,"2026-06-01T00:00:00+00:00",{"id":16,"name":17,"slug":18,"color":19,"icon":20},[86],{"id":16,"name":17,"slug":18,"color":19,"icon":20},"\u002Fblog\u002Fcovers\u002Fheberger-open-webui-poster.svg",{"categorySlug":20,"appSlug":89},"open-webui",{"id":91,"slug":92,"title":93,"excerpt":94,"readTime":95,"views":96,"isPinned":13,"publishedAt":97,"category":98,"categories":99,"featuredImage":23,"bgImage":24,"posterImage":101,"relatedSolution":102},2,"deployer-dify-vps","Deploying Dify on a VPS: AI Workflows Under Control","Install Dify on a ServOrbit VPS to build agents, chatflows and AI apps without losing control of your data.",7,2480,"2026-02-11T00:00:00+00:00",{"id":16,"name":17,"slug":18,"color":19,"icon":20},[100],{"id":16,"name":17,"slug":18,"color":19,"icon":20},"\u002Fblog\u002Fcovers\u002Fdeployer-dify-vps-poster.svg",{"categorySlug":20,"appSlug":103},"dify",{"id":81,"slug":105,"title":106,"excerpt":107,"readTime":108,"views":109,"isPinned":13,"publishedAt":14,"category":110,"categories":111,"featuredImage":23,"bgImage":24,"posterImage":113,"relatedSolution":114},"openclaw-vps","Deploying OpenClaw on a VPS","A guide to deploying OpenClaw on your own VPS. Keep control of your AI agents and your data within your own infrastructure.",5,422,{"id":16,"name":17,"slug":18,"color":19,"icon":20},[112],{"id":16,"name":17,"slug":18,"color":19,"icon":20},"\u002Fblog\u002Fcovers\u002Fopenclaw-vps-poster.svg",{"categorySlug":20,"appSlug":115},"openclaw",1785628433374]