github.com/danny-avila/LibreChat ↗
Enhanced ChatGPT Clone: Features Agents, MCP, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active.
An animated visualization of danny-avila/LibreChat's Git history from October 2022 to January 2025, built by 190 contributors. The codebase reached 17,219 lines, mostly TypeScript. The video runs 1 minute 24 seconds.
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Language
TypeScript
Contributors
190
Lines of Code
17,219
From
2022-10-20
To
2025-01-22
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About danny-avila/LibreChat
LibreChat is a self-hosted, open-source AI chat platform that consolidates multiple major AI providers—including OpenAI, Claude, Google Gemini, Azure, AWS Bedrock, DeepSeek, and many others—into a single unified interface. Built with TypeScript, it offers a ChatGPT-inspired UI with advanced capabilities designed for both casual users and enterprises who want control over their AI infrastructure.
The platform provides extensive features beyond basic chat, including a Code Interpreter for sandboxed execution across multiple programming languages, AI Agents for building custom assistants with no-code configuration, Model Context Protocol (MCP) support for tool integration, and Code Artifacts for creating interactive React components and diagrams directly within conversations. It supports multimodal interactions with image analysis and file uploads, web search capabilities, speech-to-text and text-to-speech, image generation through multiple providers, and conversation management tools like message forking and resumable streams that sync across tabs and devices.
LibreChat emphasizes privacy and flexibility through features like custom endpoints for any OpenAI-compatible API, comprehensive multi-user authentication with OAuth2 and LDAP support, conversation import/export, and extensive customization options. The platform supports over 30 languages and can be deployed locally or in the cloud with various configuration options including Docker, S3 with CloudFront, and reverse proxy setups. Active development and community contribution are central to the project, with detailed documentation and a translation program making it accessible to international audiences.
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