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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.
https://librechat.ai/
aianthropicartifactsawsazurechatgptchatgpt-cloneclaudeclonedeepseekgeminigooglegpt-5librechatmcpo1openairesponses-apivisionwebui
738003b220
* 🛡️ fix: Install global `unhandledRejection` handler Node 15+ terminates the process by default when a promise rejection goes unhandled. Under MCP OAuth reconnect storms and streamable-HTTP transport resets, fire-and-forget async paths can emit transient rejections (ECONNRESET, token refresh races) that would otherwise silently kill the server — no uncaught exception log, no OOM signal. Register a listener so these paths log and the process keeps serving other requests. Refs: #12078 * 🔧 fix: Guard MCP OAuth reconnect fire-and-forget calls `OAuthReconnectionManager.tryReconnect` awaits `getServerConfig` outside its inner try/catch, so a rejection from the registry (or any throw before the guarded block) would escape the fire-and-forget `void` call sites and propagate as an unhandled rejection — the failure mode behind the silent crashes reported in #12078. Route both call sites through a `safeTryReconnect` wrapper that attaches a terminal `.catch` so unexpected rejections are surfaced via the logger instead. Refs: #12078 * 🧹 fix: Address review findings on MCP OAuth reconnect crash fix - Move `getServerConfig` inside `tryReconnect`'s try/catch so the registry rejection path is handled by the inner cleanup (the structural root cause behind the silent crash). The outer `safeTryReconnect` wrapper remains as defense-in-depth. - Extract the failed-reconnect cleanup as a private `cleanupOnFailedReconnect` method and invoke it from `safeTryReconnect`'s catch as well, so any rejection that does escape the inner try (e.g. a future regression) still resets tracker state instead of leaving the server stuck in `active` for the full `RECONNECTION_TIMEOUT_MS` window. - Update the regression test to assert tracker state is cleaned up (`isActive` cleared, `isFailed` set, `disconnectUserConnection` called) so it can detect the stale-state failure mode it was meant to guard against. - Forward non-Error rejection reasons as-is in the global handler so structured payloads like `{ code: "ECONNRESET", errno: -104 }` survive instead of being collapsed to "[object Object]" by `String()`. Refs: #12078, review of #12812 * 🚑 fix: Restore fail-fast on boot rejection in primary server entry `startServer()` was invoked bare in `api/server/index.js`. Before installing the global `unhandledRejection` handler, a startup rejection (`connectDb`, `getAppConfig`, `performStartupChecks`) terminated the process via Node's default — Kubernetes / the orchestrator restarted the pod immediately. After the handler was added, the same rejection was caught and logged, then the process kept running half-initialized (no HTTP listener) until the liveness probe eventually timed out — slow, indirect recovery instead of a fast restart. Wrap `startServer()` with the same `.catch(() => process.exit(1))` pattern already used in `experimental.js` so boot failures fail-fast. Refs: #12078, codex review of #12812 * 🚑 fix: Fail-fast on post-listen init failure in both server entries The `app.listen` callback in `index.js` and `experimental.js` is async and awaits `initializeMCPs`, `initializeOAuthReconnectManager`, and `checkMigrations`. The callback's promise is detached from `startServer().catch(...)` (the outer catch only sees errors that occurred before `app.listen` was called), so without explicit handling those init rejections used to terminate the process via Node's default and now would be swallowed by the new `unhandledRejection` handler — leaving the HTTP server listening (and passing liveness probes) while MCP / OAuth / migration state is broken. Wrap the post-listen init block in a try/catch that logs and calls `process.exit(1)` so initialization failures stay fail-fast. Refs: #12078, codex review of #12812 |
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LibreChat
English · 中文
✨ Features
-
🖥️ UI & Experience inspired by ChatGPT with enhanced design and features
-
🤖 AI Model Selection:
- Anthropic (Claude), AWS Bedrock, OpenAI, Azure OpenAI, Google, Vertex AI, OpenAI Responses API (incl. Azure)
- Custom Endpoints: Use any OpenAI-compatible API with LibreChat, no proxy required
- Compatible with Local & Remote AI Providers:
- Ollama, groq, Cohere, Mistral AI, Apple MLX, koboldcpp, together.ai,
- OpenRouter, Helicone, Perplexity, ShuttleAI, Deepseek, Qwen, and more
-
- Secure, Sandboxed Execution in Python, Node.js (JS/TS), Go, C/C++, Java, PHP, Rust, and Fortran
- Seamless File Handling: Upload, process, and download files directly
- No Privacy Concerns: Fully isolated and secure execution
-
🔦 Agents & Tools Integration:
- LibreChat Agents:
- No-Code Custom Assistants: Build specialized, AI-driven helpers
- Agent Marketplace: Discover and deploy community-built agents
- Collaborative Sharing: Share agents with specific users and groups
- Flexible & Extensible: Use MCP Servers, tools, file search, code execution, and more
- Compatible with Custom Endpoints, OpenAI, Azure, Anthropic, AWS Bedrock, Google, Vertex AI, Responses API, and more
- Model Context Protocol (MCP) Support for Tools
- LibreChat Agents:
-
🔍 Web Search:
- Search the internet and retrieve relevant information to enhance your AI context
- Combines search providers, content scrapers, and result rerankers for optimal results
- Customizable Jina Reranking: Configure custom Jina API URLs for reranking services
- Learn More →
-
🪄 Generative UI with Code Artifacts:
- Code Artifacts allow creation of React, HTML, and Mermaid diagrams directly in chat
-
🎨 Image Generation & Editing
- Text-to-image and image-to-image with GPT-Image-1
- Text-to-image with DALL-E (3/2), Stable Diffusion, Flux, or any MCP server
- Produce stunning visuals from prompts or refine existing images with a single instruction
-
💾 Presets & Context Management:
- Create, Save, & Share Custom Presets
- Switch between AI Endpoints and Presets mid-chat
- Edit, Resubmit, and Continue Messages with Conversation branching
- Create and share prompts with specific users and groups
- Fork Messages & Conversations for Advanced Context control
-
💬 Multimodal & File Interactions:
- Upload and analyze images with Claude 3, GPT-4.5, GPT-4o, o1, Llama-Vision, and Gemini 📸
- Chat with Files using Custom Endpoints, OpenAI, Azure, Anthropic, AWS Bedrock, & Google 🗃️
-
🌎 Multilingual UI:
- English, 中文 (简体), 中文 (繁體), العربية, Deutsch, Español, Français, Italiano
- Polski, Português (PT), Português (BR), Русский, 日本語, Svenska, 한국어, Tiếng Việt
- Türkçe, Nederlands, עברית, Català, Čeština, Dansk, Eesti, فارسی
- Suomi, Magyar, Հայերեն, Bahasa Indonesia, ქართული, Latviešu, ไทย, ئۇيغۇرچە
-
🧠 Reasoning UI:
- Dynamic Reasoning UI for Chain-of-Thought/Reasoning AI models like DeepSeek-R1
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🎨 Customizable Interface:
- Customizable Dropdown & Interface that adapts to both power users and newcomers
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- Never lose a response: AI responses automatically reconnect and resume if your connection drops
- Multi-Tab & Multi-Device Sync: Open the same chat in multiple tabs or pick up on another device
- Production-Ready: Works from single-server setups to horizontally scaled deployments with Redis
-
🗣️ Speech & Audio:
- Chat hands-free with Speech-to-Text and Text-to-Speech
- Automatically send and play Audio
- Supports OpenAI, Azure OpenAI, and Elevenlabs
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📥 Import & Export Conversations:
- Import Conversations from LibreChat, ChatGPT, Chatbot UI
- Export conversations as screenshots, markdown, text, json
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🔍 Search & Discovery:
- Search all messages/conversations
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👥 Multi-User & Secure Access:
- Multi-User, Secure Authentication with OAuth2, LDAP, & Email Login Support
- Built-in Moderation, and Token spend tools
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⚙️ Configuration & Deployment:
- Configure Proxy, Reverse Proxy, Docker, & many Deployment options
- Use completely local or deploy on the cloud
-
📖 Open-Source & Community:
- Completely Open-Source & Built in Public
- Community-driven development, support, and feedback
For a thorough review of our features, see our docs here 📚
🪶 All-In-One AI Conversations with LibreChat
LibreChat is a self-hosted AI chat platform that unifies all major AI providers in a single, privacy-focused interface.
Beyond chat, LibreChat provides AI Agents, Model Context Protocol (MCP) support, Artifacts, Code Interpreter, custom actions, conversation search, and enterprise-ready multi-user authentication.
Open source, actively developed, and built for anyone who values control over their AI infrastructure.
🌐 Resources
GitHub Repo:
- RAG API: github.com/danny-avila/rag_api
- Website: github.com/LibreChat-AI/librechat.ai
Other:
- Website: librechat.ai
- Documentation: librechat.ai/docs
- Blog: librechat.ai/blog
📝 Changelog
Keep up with the latest updates by visiting the releases page and notes:
⚠️ Please consult the changelog for breaking changes before updating.
⭐ Star History
✨ Contributions
Contributions, suggestions, bug reports and fixes are welcome!
For new features, components, or extensions, please open an issue and discuss before sending a PR.
If you'd like to help translate LibreChat into your language, we'd love your contribution! Improving our translations not only makes LibreChat more accessible to users around the world but also enhances the overall user experience. Please check out our Translation Guide.
💖 This project exists in its current state thanks to all the people who contribute
🎉 Special Thanks
We thank Locize for their translation management tools that support multiple languages in LibreChat.