# Mintplex-Labs/anything-llm

Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience

Repository: https://github.com/Mintplex-Labs/anything-llm
Canonical: https://ross.abutalabs.com/products/anything-llm
Homepage: https://anythingllm.com
Language: JavaScript
License: MIT
License Family: permissive
Topics: rag, localai, vector-database, llm, ai-agents, multimodal, no-code, agent-harness, agentic-ai, hermes-agent, local-ai, open-claw, self-hosted-ai, agent-computer, computer-use, agent-orchestration
Last push: 2026-08-26T22:13:37+00:00

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 97, longevity 84
- inputs: {"age_days": 1187, "days_push": 7, "days_rel": 20, "gap_med": 20.5, "n_releases_24m": 29}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 65257, forks 7192 (observed 2026-08-28T04:12:19.274100+00:00)

## What it is
AnythingLLM is an all-in-one, local-first AI application for chatting with your documents, running AI agents, and building workflows entirely on your own device or self-hosted server. It supports multiple LLM providers (Ollama, LM Studio, OpenAI, Anthropic, etc.), vector databases, multi-user access, and a developer API, with desktop, Docker, and cloud deployment options.

## Use cases
- chat with my pdf documents locally
- run a private AI assistant without cloud API keys
- build a RAG knowledge base from my files
- self-host a multi-user AI chat for my team
- run AI agents that use my local documents
- transcribe and summarize meetings on-device
- deploy a private ChatGPT alternative on Docker
- connect Ollama or LM Studio to a nice chat UI

## When to choose
- you want a private, local-first AI assistant with no data leaving your machine
- you need document Q&A (RAG) with a polished UI out of the box
- you want multi-user workspaces and self-hosting via Docker
- you want agent capabilities, web scraping, and custom tools without writing code

## When to avoid
- you need a lightweight library or SDK to embed RAG into your own codebase
- you require fine-grained programmatic control over the RAG pipeline internals
- you only need a raw LLM inference server rather than a full application

## Facets
- artifact type: application
- maturity: active
- function: rag, chatbot, agent-framework, llm-inference, vector-database, chat-interface, web-scraping, speech-recognition, self-hosted
- domain: artificial-intelligence, large-language-models, chatbots, self-hosted, privacy, developer-tools
- platform: windows, self-hosted, cross-platform
- tags: local-ai, on-device-ai, multi-user, no-code-agents, document-chat, ollama, lm-studio, mit-license, retrieval-augmented-generation, ai-agents, macos, linux, docker, desktop, web-server

## Member repositories
- Mintplex-Labs/anything-llm (main) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:19.274100+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:17:24.393269+00:00, confidence not recorded.
  - readme: https://github.com/Mintplex-Labs/anything-llm (fetched 2026-08-28T04:12:19.274100+00:00, sha cccdf83d6ebd)
  - homepage: https://anythingllm.com (fetched 2026-08-28T17:54:21.246740+00:00, sha 80f9430ed39b)
  - site_page: https://docs.anythingllm.com/pro/overview (fetched 2026-08-28T17:54:21.255368+00:00, sha 30e4bc3deb42)
  - site_page: https://docs.anythingllm.com (fetched 2026-08-28T17:54:21.257306+00:00, sha 2cbd018288f9)
  - site_page: https://docs.anythingllm.com/chatting-with-documents/introduction (fetched 2026-08-28T17:54:21.259233+00:00, sha 88416a914085)
  - site_page: https://docs.anythingllm.com/pro/magic-echo (fetched 2026-08-28T17:54:21.261190+00:00, sha df9d10dc3357)
  - site_page: https://docs.anythingllm.com/installation-docker/quickstart (fetched 2026-08-28T17:54:21.263199+00:00, sha 03e0d46a98a5)
  - site_page: https://docs.anythingllm.com/changelog/overview (fetched 2026-08-28T17:54:21.264995+00:00, sha 3be6fd67bdb7)
  - site_page: https://docs.anythingllm.com/installation-desktop/privacy (fetched 2026-08-28T17:54:21.266776+00:00, sha 17cd630c5240)
  - site_page: https://docs.anythingllm.com/installation-desktop/terms (fetched 2026-08-28T17:54:21.268714+00:00, sha be8df0424a16)
- Data as of 2026-08-30T08:39:29.467469+00:00.