Self-Hosted / Projects / AnythingLLM

AnythingLLM
StableSpecs verified October 10, 2026 · against vv1.17.0
Overview
Self-hosted private AI workspace for document chat and local agents.
AnythingLLM is a self-hosted AI workspace for people who want to chat with their documents, use language models, and build agent workflows without putting every prompt and file into a single hosted AI service.
Why people choose AnythingLLM
The broader search intent is a private ChatGPT, local AI, or self-hosted document-chat alternative. AnythingLLM brings workspaces, document knowledge, model connections, web search, agents, and desktop or Docker deployment into one product instead of requiring a separate frontend for each local model.
What is included
Official product and documentation pages cover document knowledge, web scraping and search, dynamic model selection, background jobs, custom agent skills, a developer API, desktop apps, mobile access, and meeting assistance. Exact model providers and feature availability depend on the edition and configuration.
Requirements and tradeoffs
The Docker guide requires persistent storage and warns that data is lost if the storage volume is omitted. The published container runs as UID/GID 1000, and the docs call out AVX2 requirements for the default vector database plus extra configuration when connecting to services such as Ollama. Local models improve control but still require suitable CPU, GPU, memory, and disk.
Best fit
Choose AnythingLLM when you want a general private AI interface with document retrieval and agent features. A smaller chat frontend may be easier for one model, while a hosted AI service may be simpler if you do not want to operate storage, models, updates, and access controls.
Interface previews
Screenshots of the AnythingLLM interface.
Feature support
| Feature | Support |
|---|---|
| Document knowledge and RAG chatOfficial product and documentation pages describe document knowledge and workspace chat. | Supported |
| Web scraping and searchThe product site lists web scraping and search as built-in capabilities. | Supported |
| Multiple LLM providersAnythingLLM supports configurable model connections; the exact provider list changes over time. | Supported |
| Custom agent skills and toolsOfficial pages describe custom agent skills, tool building, and developer API access. | Supported |
| Docker self-hostingThe official Docker guide provides a published image and a local container path. | Supported |
| Desktop and mobile clientsThe official product site documents desktop downloads and a mobile experience. | Supported |
| Local model supportLocal providers can be connected, but model performance and hardware requirements depend on the selected runtime. | Partial support |
| Meeting transcription and summariesThe product site describes on-device meeting assistance; confirm edition and current feature availability before relying on it. | Partial support |
Community signals
- Stars
- 66.9k
- Forks
- 7.5k
- Open issues
- 332
- Last commit
- 2d ago
- Latest release
- v1.17.0
- Repo created
- Jun 2023
Includes open pull requests
1w ago
Refreshed nightly from the GitHub API.
Questions
What is AnythingLLM used for?
AnythingLLM is used for chatting with documents, searching the web, connecting language models, and building AI agent workflows in a private workspace.
Is AnythingLLM a self-hosted ChatGPT alternative?
It can cover private chat and document-question answering use cases, but it is better understood as a configurable AI workspace that can connect to local or hosted models.
Can AnythingLLM run in Docker?
Yes. The official documentation provides a Docker image and a local Docker command for running the application.
Does AnythingLLM need persistent storage?
Yes. The Docker guide says the storage mount is required; without it, application data can be lost when the container restarts.
Can AnythingLLM use Ollama or local models?
AnythingLLM can connect to local model providers such as Ollama, but the exact setup and model requirements depend on the provider and hardware.
Does AnythingLLM require AVX2?
The official Docker troubleshooting guide says the default vector database requires AVX2. Older CPUs or virtual machines that hide AVX2 may need an alternative configuration.
Is AnythingLLM fully private?
Self-hosting can keep data on your infrastructure, but privacy depends on model providers, web search, telemetry, remote integrations, and how the deployment is exposed.
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