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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
ff9d89540c
* 🎯 feat: Render Tool Intent as the Live Tool-Call Label The tool_intents capability injects a model-authored `intent` sentence as the FIRST key of a tool call's args, and the SDK's coding tools carry it natively — but no client component ever read it, so cards kept showing their generic labels ("Running command") while the intent streamed by unused. A shared useToolCallIntent hook extracts the intent from streaming args via parseJsonField's partial-JSON fallback, so the label renders from the first delta — before any other arg exists — and keeps updating as it streams. When present, the intent replaces the generic in-progress label and persists as the settled label (completion is a UI state, not a tense change, matching the SDK's applyOutcome design). Cancelled, error, and background states keep their existing precedence. Wired into BashCall, ExecuteCode, the generic ToolCall (MCP, actions, plugin tools), ReadFileCall, SkillCall, and FileAuthoringCall. Non-string `intent` business params are ignored. SubagentCall keeps its verb+name header design for a follow-up. * 🎯 fix: Harden Intent Label Extraction per Review Gate the label on intent being the FIRST args key (the label contract's first-position rule), so a tool's own business param named intent — e.g. a CRM's {"q":"acme","intent":"billing_inquiry"} — no longer renders as the status label. Bound the label to a single 256-char line before it reaches ProgressText's nowrap layout, mirroring the SDK's outcome-label cap. Decode the full JSON escape set in parseJsonField's streaming fallback (\t \r \b \f \/ and \uXXXX with surrogate pairs) so a partial label renders exactly as its settled JSON.parse form; stream-edge incompletions (dangling escape, partial \uXX, split surrogate) are held back rather than shown. Wire web_search into the intent label: Part.tsx now passes toolCall.args and the WebSearch card prefers the intent for its progress and completed texts — it carries intent natively but never received args at all. * 🎯 fix: Round-2 Review — Stable Live Region, Split Low Surrogates, Specialized Cards Keep the aria-live region on its stable generic value while the intent streams: an atomic polite region re-announces the whole growing sentence on every delta otherwise. The settled intent is still announced once via the finished text. Hold back a decoded high surrogate while its low-surrogate escape is still streaming (\ud83d\u, \ud83d\ude0), not only when the high half ends the value exactly; a complete following escape composes the pair on the next iteration, and a lone surrogate followed by ordinary text stays emitted, matching JSON.parse. Thread args into the specialized cards for explicitly opted-in tools: RetrievalCall (file_search) and the image-gen cards (image_gen_oai, image_edit_oai, gemini_image_gen) now resolve the intent for their progress and settled labels, with the image phase texts as fallback. * 🎯 fix: Round-3 Review — Live-Region Settled Announcements & Remaining Cards Announce the settled intent once through the aria-live regions of RetrievalCall, the image-gen card, and WebSearch, while each region keeps a stable generic value during streaming (WebSearch was still piping the growing intent into its atomic region on every delta). Pass object-valued args through Part.tsx to the image-gen card instead of coercing them to '' — persisted/completed calls carry object args, so the first-key intent was invisible on reload. Guard complete serialized args against non-string intents: parseJsonField's JSON branch would coerce {"intent":{...}} into "[object Object]"; the hook now type-checks the parsed field, matching the object-args path. Wire the subagent card: the SDK-native subagent intent now leads its header, without overriding error or cancellation framing. * 🎯 fix: Round-4 Review — Constant-Cost Extraction, Final-Search Settling, Safe Truncation Replace the hook's JSON.parse-per-delta with a single anchored regex over a bounded 2 KB head window: the first-position contract lets one match do the business-param gating and the value capture (complete or streaming), so per-delta cost stays constant while a large code/content argument streams behind the label. A non-string first-key intent never matches the opening quote, keeping the round-3 guard without parsing. Settle a web search that is the message's final part once submission ends: `complete` previously required !isLast permanently, so the last-part case shimmered forever and never announced its settled intent. Back the truncation cut off a high surrogate so a bounded multilingual label never ends in a replacement glyph before the ellipsis. * 🎯 fix: Round-5 Review — Keep Terminal Lone Surrogates in Settled Values Thread value completeness from the extractor into the escape decoder: a captured closing quote means the value is settled, so the stream-edge hold-backs (partial \uXX, high-surrogate deferral) no longer apply and a value genuinely ending in a lone high surrogate keeps its final code unit, matching JSON.parse and the object-args rendering. Streaming callers keep the hold-back behavior unchanged. |
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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
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- 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
- Open-Source & Self-Hostable: powered by ClickHouse/code-interpreter
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🔦 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
- Skills: Create reusable
SKILL.mdinstruction bundles for manual, automatic, or always-on agent workflows - Subagents: Delegate focused work to isolated child agent runs with their own context windows
- 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
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💾 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
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💬 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 🗃️
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🌎 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
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🧠 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
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🗣️ 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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🎛️ Admin Panel:
- Browser-based UI to manage users, groups, roles, and configuration overrides
- Edit settings and per-role/group permissions live, without redeploying
- Bundled with the Docker Compose stacks for one-command setup
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⚙️ Configuration & Deployment:
- Configure Proxy, Reverse Proxy, Docker, & many Deployment options
- Use S3 with CloudFront for stable media links, edge delivery, signed cookies, and secured downloads
- Use completely local or deploy on the cloud
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📖 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.