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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
7581540ab6
* 🔌 refactor: Decouple bash_tool from Per-User CODE_API_KEY
Phase 4 of Agent Skills umbrella (#12625): gate bash_tool and skill
file priming on the `execute_code` capability only. Thread a boolean
`codeEnvAvailable` through `enrichWithSkillConfigurable` and
`primeInvokedSkills` in place of the old per-user `codeApiKey` +
`loadAuthValues` plumbing. The sandbox API key is the LibreChat-
hosted service key — system-level, not a user secret — so the
per-user lookup was legacy; when needed, it's read directly from
`process.env[EnvVar.CODE_API_KEY]` inside the capability gate.
`handleSkillToolCall` and `primeInvokedSkills` gate sandbox uploads
on `codeEnvAvailable` first, preventing skill-file uploads to the
sandbox when an agent has `execute_code` disabled even if the env
var happens to be set. The agents library resolves the env key
itself for `bash_tool`, so `ToolService.js` drops the
`loadAuthValues` lookup and the "Code execution is not available"
placeholder tool in favor of a plain `createBashExecutionTool({})`
with a loud error log if the env var is missing.
Also fixes a pre-existing `appConfig`-undefined lint error in
`responses.js`/`createResponse` that surfaced when this file was
touched (declares `const appConfig = req.config` at function top,
matching the existing pattern in other controllers).
Preserves the `skillPrimedIdsByName` threading added by Phase 3/5/6
and all Phase 3/5/6 call-site signatures. Adds
`skillConfigurable.spec.ts` (5 cases pinning the new surface) and
`skillFiles.spec.ts` (4-way matrix of capability × env key for
`primeInvokedSkills`).
* 🧪 refactor: Address Codex Review Feedback
Resolves findings from the second codex review on #12712:
- MAJOR: `handlers.spec.ts` now covers the `codeEnvAvailable` gate in
`handleSkillToolCall` across three cases (gate off, gate on + env
set, gate on + env unset). The gate is the critical regression
prevention — a future edit that drops it would silently re-enable
sandbox uploads for agents with `execute_code` disabled.
- MINOR: Hoist `codeEnvAvailable` and `skillPrimedIdsByName` out of
`loadTools` closures in `openai.js` and `responses.js`. Both values
are fixed once `initializeAgent` resolves, so recomputing them on
every tool execution was wasted work. `responses.js` shares a single
pair between its streaming and non-streaming branches.
- MINOR: `skillFiles.spec.ts` now has a test that exercises the full
upload path end-to-end with real file records, asserting
`batchUploadCodeEnvFiles` is called with the env-sourced apiKey and
the correct file set (including the synthetic `SKILL.md`).
- NIT: Finish the `appConfig` extraction in `responses.js/createResponse`
— replaces the remaining `req.config` references with `appConfig` for
consistency with the pattern in other controllers.
No behavioral changes beyond what was already in place; this is
coverage and readability polish.
* 🧷 test: Tighten Spec Hygiene Per Codex Nit Feedback
Round-3 codex review flagged two NITs on the test code added in the
previous commit:
- Replace `_id: 'skill-id' as unknown as never` in the new
`makeSkillHandlerWithFiles` helper with a real `Types.ObjectId`,
matching the pattern used by the primed-skill tests further up in
the same file (and by `skillFiles.spec.ts`). The `never` cast
hides the fact that `_id` really is a string / ObjectId at runtime.
- Replace the ad-hoc `{ on, pipe, read }` stub with a real
`Readable.from(Buffer.from(''))` in the upload-path test. The stub
worked only because `batchUploadCodeEnvFiles` is mocked and never
iterates the stream; `Readable.from` satisfies the same contract
and is robust to any future partial-real replacement of the upload
function.
Pure test-hygiene improvements; no runtime code touched.
* 🧹 chore: Remove Duplicate appConfig Declaration After Rebase
The upstream `
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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
-
🎨 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 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.