AnythingLLM: The all-in-one AI app you were looking for.
Chat with your docs, use AI Agents, hyper-configurable, multi-user, & no fustrating set up required.

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A full-stack application that enables you to turn any document, resource, or piece of content into context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions.

AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open source LLMs and vectorDB solutions to build a private ChatGPT with no compromises that you can run locally as well as host remotely and be able to chat intelligently with any documents you provide it.

AnythingLLM divides your documents into objects called workspaces. A Workspace functions a lot like a thread, but with the addition of containerization of your documents. Workspaces can share documents, but they do not talk to each other so you can keep your context for each workspace clean.

Some cool features of AnythingLLM

• Multi-user instance support and permissioning
• Agents inside your workspace (browse the web, run code, etc)
• Custom Embeddable Chat widget for your website
• Multiple document type support (PDF, TXT, DOCX, etc)
• Manage documents in your vector database from a simple UI
• Two chat modes conversation and query. Conversation retains previous questions and amendments. Query is simple QA against your documents
• In-chat citations
• 100% Cloud deployment ready.
• "Bring your own LLM" model.
• Extremely efficient cost-saving measures for managing very large documents. You'll never pay to embed a massive document or transcript more than once. 90% more cost effective than other document chatbot solutions.
• Full Developer API for custom integrations!

Language Learning Models:

• Any open-source llama.cpp compatible model
• OpenAI
• OpenAI (Generic)
• Azure OpenAI
• Anthropic
• Google Gemini Pro
• Hugging Face (chat models)
• Ollama (chat models)
• LM Studio (all models)
• LocalAi (all models)
• Together AI (chat models)
• Perplexity (chat models)
• OpenRouter (chat models)
• Mistral
• Groq
• Cohere
• KoboldCPP
• LiteLLM
• Text Generation Web UI

Embedder models:

• AnythingLLM Native Embedder (default)
• OpenAI
• Azure OpenAI
• LocalAi (all)
• Ollama (all)
• LM Studio (all)
• Cohere

Audio Transcription models:

• AnythingLLM Built-in (default)
• OpenAI

TTS (text-to-speech) support:

• Native Browser Built-in (default)
• OpenAI TTS
• ElevenLabs

STT (speech-to-text) support:

• Native Browser Built-in (default)

Vector Databases:

• LanceDB (default)
• Astra DB
• Pinecone
• Chroma
• Weaviate
• QDrant
• Milvus
• Zilliz

This monorepo consists of three main sections:

• frontend: A viteJS + React frontend that you can run to easily create and manage all your content the LLM can use.
• server: A NodeJS express server to handle all the interactions and do all the vectorDB management and LLM interactions.
• collector: NodeJS express server that process and parses documents from the UI.
• docker: Docker instructions and build process + information for building from source.
• embed: Code specifically for generation of the embed widget.

Mintplex Labs & the community maintain a number of deployment methods, scripts, and templates that you can use to run AnythingLLM locally. Refer to the table below to read how to deploy on your preferred environment or to automatically deploy.

Docker	AWS	GCP	Digital Ocean	Render.com

Railway	RepoCloud

or set up a production AnythingLLM instance without Docker →

• yarn setup To fill in the required .env files you'll need in each of the application sections (from root of repo).
  • Go fill those out before proceeding. Ensure server/.env.development is filled or else things won't work right.
• yarn dev:server To boot the server locally (from root of repo).
• yarn dev:frontend To boot the frontend locally (from root of repo).
• yarn dev:collector To then run the document collector (from root of repo).

Learn about documents

Learn about vector caching

• create issue
• create PR with branch name format of <issue number>-<short name>
• yee haw let's merge

AnythingLLM by Mintplex Labs Inc contains a telemetry feature that collects anonymous usage information.

• VectorAdmin: An all-in-one GUI & tool-suite for managing vector databases.
• OpenAI Assistant Swarm: Turn your entire library of OpenAI assistants into one single army commanded from a single agent.

Copyright © 2024 Mintplex Labs.
This project is MIT licensed.