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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
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* 🧠 fix: Replay DeepSeek `reasoning_content` via OpenRouter DeepSeek's thinking-mode API rejects multi-turn tool-calling requests unless `reasoning_content` from each tool-bearing assistant message is replayed verbatim, returning HTTP 400 "The `reasoning_content` in the thinking mode must be passed back to the API." The agents SDK already handles this for direct `Providers.DEEPSEEK`, but DeepSeek models routed via OpenRouter use `Providers.OPENROUTER` — `formatAgentMessages` skipped the reasoning-preservation branch, and `ChatOpenRouter` left `includeReasoningContent` unset, so the field silently dropped on every subsequent turn. Add `isDeepSeekReasoningProvider(provider, model)` and use it in two places: (1) `getOpenAILLMConfig` flips `includeReasoningContent: true` when OpenRouter is dispatching a `deepseek/*` model so the LangChain client emits the field on assistant turns that have non-empty `additional_kwargs.reasoning_content`, and (2) `AgentClient` spoofs the provider hint to `Providers.DEEPSEEK` when calling `formatAgentMessages`, triggering the SDK's existing `preserveReasoningContent` path that re-attaches the field to reconstructed tool-bearing AIMessages. The downstream `_convertMessagesToOpenAIParams` is already gated on non-empty `reasoning_content`, so the flag is a no-op outside thinking mode. Resolves #13366. * fix: Harden DeepSeek detection against OpenRouter routing edges Address three Codex review findings on #13368: 1. Strip OpenRouter's `~` latest-routing prefix before applying the DeepSeek model regex. `~deepseek-chat` and `~deepseek/r1` were previously left unmatched because the regex's start/`/` boundary only saw the `~`. Mirror the SDK's `normalizeOpenRouterModel()` here and in `getOpenAILLMConfig`. 2. Add a custom-endpoint fallback: when the model id carries the unambiguous `deepseek/...` OpenRouter namespace, accept it regardless of the resolved provider. Covers the case where a user configures OpenRouter under a non-standard endpoint name and `initializeAgent` normalizes the unknown provider to `openai`, stranding the spoof. Bare `deepseek-*` ids still require an explicit DeepSeek/OpenRouter provider so unrelated endpoints labelling a model `deepseek-r1` don't trigger. 3. Inspect every agent in `this.agentConfigs` when deciding whether to spoof the format provider. Multi-agent handoff runs feed all agents' messages through one `formatAgentMessages` call, so a DeepSeek handoff under a non-DeepSeek primary previously lost its persisted reasoning_content too. Also addresses Copilot's review note: only pass the options object to `formatAgentMessages` when the DeepSeek spoof is actually needed, preserving the pre-fix behavior for everyone else. * fix: Extend DeepSeek reasoning_content fix to OpenAI-compat agent paths Address two more Codex P2 findings on #13368: 1. `getOpenAILLMConfig` no longer gates `includeReasoningContent` on `useOpenRouter`. Any DeepSeek-style model id (with `~` latest-routing prefix stripped) is sufficient. This re-aligns the LLM gate with `AgentClient`'s formatter spoof, which already treats a `deepseek/*` id as authoritative — so a custom-named OpenRouter endpoint or a DeepSeek-compatible proxy gets the field both attached to history AND serialized to the wire. Direct `ChatDeepSeek` ignores the flag (its own conversion path hardcodes `includeReasoningContent: true`), so this is a harmless no-op there. 2. Thread the same `Providers.DEEPSEEK` formatter hint through `api/server/controllers/agents/openai.js` and `responses.js` (the OpenAI-/Responses-compatible serving paths). Without it those paths restored `additional_kwargs.reasoning_content` only in `AgentClient` while the LLM config flipped `includeReasoningContent` on for them too — so DeepSeek tool turns served from those endpoints would still ship requests with the flag set but no field present, hitting the same second-turn 400. The `needsDeepSeekFormatHint` helper in `openai.js` mirrors `AgentClient`'s per-agent check. * fix: Tighten DeepSeek detection and cover handoff sub-agents Address four more Codex P2 findings on #13368: - Tighten the DeepSeek model regex to `^deepseek(?:[-/]|$)/i` (anchored to start). Rejects cloned/distilled slugs like `mistral/deepseek-distilled-foo` and `community/deepseek-r1` that previously matched via the `(?:^|/)` alternation, which could attach the DeepSeek-only `reasoning_content` field on proxies that don't accept it. - Anchoring also collapses the namespace-only fallback into the same pattern, so bare `deepseek-chat` / `deepseek-reasoner` on a custom OpenAI-compatible DeepSeek proxy are now recognized — fixing the asymmetry where `getOpenAILLMConfig` would flip `includeReasoningContent` for those bare ids but `AgentClient` wouldn't pass the formatter hint. - Extend `needsDeepSeekFormatHint` in `openai.js` (and the inline check in `responses.js`) to walk `handoffAgentConfigs` too. In multi-agent runs where the primary isn't DeepSeek but a connected handoff agent is, the SDK's `formatAgentMessages` previously dropped the handoff's persisted reasoning_content before the next tool turn, preserving the 400 the PR was meant to prevent. - Mirror the regex change in `getOpenAILLMConfig`. Out of scope: the OpenAI-compatible serving paths still don't preserve incoming `reasoning_content`/`reasoning` fields in `convertMessages`, nor does the Responses API persist reasoning in `saveResponseOutput`. Those are deeper persistence/conversion fixes worth a separate PR. * test: Allow includeReasoningContent for Azure-serverless DeepSeek CI surfaced a backward-compat expectation that snapshotted the pre-fix behavior. Azure-serverless DeepSeek deployments (e.g. `DeepSeek-R1`) forward to the same DeepSeek thinking-mode tool-call contract, so the LLM gate now correctly flips `includeReasoningContent: true` for them too. The downstream gate on a non-empty `additional_kwargs.reasoning_content` keeps this a no-op outside thinking mode. * chore: Trim noisy comments Per CLAUDE.md ("self-documenting code; no inline comments narrating what code does"), strip the multi-paragraph rationale that crept into the DeepSeek reasoning_content fix. The commit history and PR description carry the why; the code says the what. Keeps one single-line JSDoc on `isDeepSeekReasoningProvider` (linking to the DeepSeek docs) and a `(#13366)` tag on each opt-in site so future readers can find the context. * revert: Drop non-functional DeepSeek hint from OpenAI-compat serving paths Codex's later review passes correctly flagged that threading the DeepSeek formatter hint through openai.js (`/v1/chat/completions`) and responses.js (`/v1/responses`) doesn't actually fix the second-turn 400 in those paths. Empirical check against the real SDK confirmed the gap is deeper and pre-existing: formatAgentMessages(payload, ..., { provider: DEEPSEEK }) where payload is the `convertMessages`/`convertInputToMessages` output shape (string content + TOP-LEVEL `tool_calls`) produces NO tool-bearing AIMessage at all — `formatAssistantMessage` only reconstructs tool calls from `tool_call`-typed *content parts*, never a top-level `tool_calls` field. So those serving paths don't reconstruct tool-call history (let alone reasoning) regardless of the hint. The Responses persistence layer likewise stores only output text, not tool calls or reasoning. Making those paths work requires reworking the wire->internal message conversion (and Responses persistence) to emit content-part arrays — a broad, pre-existing concern beyond this issue and risky to land here. Rather than ship a hint that looks like a fix but is inert, revert the serving-path changes and scope this PR to the validated AgentClient chat path (the actual surface in #13366). Reverts the openai.js/responses.js threading and their spec mocks to main. Keeps the AgentClient fix, `isDeepSeekReasoningProvider`, the `getOpenAILLMConfig` flag, and the type. |
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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
- 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
-
💾 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
-
🎨 Customizable Interface:
- Customizable Dropdown & Interface that adapts to both power users and newcomers
-
- 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
-
📥 Import & Export Conversations:
- Import Conversations from LibreChat, ChatGPT, Chatbot UI
- Export conversations as screenshots, markdown, text, json
-
🔍 Search & Discovery:
- Search all messages/conversations
-
👥 Multi-User & Secure Access:
- Multi-User, Secure Authentication with OAuth2, LDAP, & Email Login Support
- Built-in Moderation, and Token spend tools
-
⚙️ 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
-
📖 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.