# AnythingLLM

> Point it at your documents and get a private assistant over them

Category: Self hosted AI workspaces (https://aiarabicdev.com/ai-workspaces)
Canonical page: https://aiarabicdev.com/ai-workspaces/anything-llm
Tags: rag, documents, self-hosted, workspace, chat

AnythingLLM is a self hosted application built around retrieval over your own material: drop in documents, and it handles the chunking, the embeddings and the vector store, then answers over them. It runs as a desktop app or a server with workspaces and users.

## Facts

- Licence: MIT
- Language: JavaScript
- Cost: Free core, paid tiers exist
- Self hostable: yes
- Added: 2026-08-24
- Last checked: 2026-08-24

## Links

- Website: https://anythingllm.com
- Source: https://github.com/Mintplex-Labs/anything-llm

## It hides the parts nobody enjoys

Retrieval sounds simple and is mostly plumbing: chunk sizes, embedding models, a vector database, and the glue between them. AnythingLLM makes reasonable choices for all of it so you can find out whether retrieval helps your case before spending a week assembling one.

Workspaces are the useful organising idea. Each has its own documents and its own thread, so a set of contracts and a set of technical docs stay separate rather than blending into one confused context.

## Where the ceiling is

Convenient defaults are still defaults. When answers are poor, the levers you want are the chunking strategy and the retrieval logic, and those are less exposed here than in a pipeline you assembled yourself.

The desktop application is the fastest way to evaluate it. Treat that as the trial and the server deployment as the real thing, because they are not equally suited to more than one person.

## Reach for it when

- you want to know whether retrieval helps before building one
- the documents must stay on infrastructure you control
- you need separate contexts for separate bodies of material

## Watch out for

- the retrieval internals are less exposed than a pipeline you built, which limits how far you can tune it
- a hosted cloud offering is sold alongside the open source project
- answer quality depends on the embedding and chat models you configure, so judge those separately

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