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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
f7e47f6012
* chore: Update `@librechat/agents` to v3.1.71-dev.0 across package-lock and package.json files This commit updates the version of the `@librechat/agents` package from `3.1.70` to `3.1.71-dev.0` in the `package-lock.json` and relevant `package.json` files. Additionally, it marks several dependencies as peer dependencies, ensuring better compatibility and integration across the project. * 🔗 feat: Enable Tool-Output References for bash_tool when codeenv is on Wires `@librechat/agents`' `RunConfig.toolOutputReferences` into `createRun()` and the bash tool's LLM-facing description, gated by the per-agent `effectiveCodeEnvAvailable` flag. The feature auto-activates for any run where the bash tool is actually registered; SDK defaults (~400 KB per output, 5 MB total) match the shell-safe budget. No new env var or yaml capability — piggybacks on the existing `execute_code` gate. - `tools.ts`: replace the module-level `BASH_TOOL_DEF` constant with a per-call `buildBashToolDef` that wraps `buildBashExecutionToolDescription`. Description now includes the `{{tool<idx>turn<turn>}}` reference syntax guide iff the new `enableToolOutputReferences` param is true. - `initialize.ts`: pass `enableToolOutputReferences: effectiveCodeEnvAvailable` into `registerCodeExecutionTools`. - `run.ts`: add `codeEnvAvailable?: boolean` to `RunAgent`, compute the flag from `agents[*].codeEnvAvailable`, and conditionally spread `toolOutputReferences: { enabled: true }` into `Run.create`. * 🧪 test: Cover tool-output references gating end-to-end - `tools.spec.ts`: 3 new cases asserting `bash_tool.description` contains `{{tool<idx>turn<turn>}}` iff `enableToolOutputReferences` is true (and unset → false). - `run-summarization.test.ts`: 4 new cases asserting `Run.create` is invoked with `toolOutputReferences: { enabled: true }` iff at least one `RunAgent.codeEnvAvailable === true`. Covers the present / absent / unset / multi-agent-OR cases. - `initialize.test.ts` + `skills.test.ts`: extend the existing `@librechat/agents` jest mocks with a `buildBashExecutionToolDescription` stub so suites stay green when the on-disk SDK lags the published 3.1.71-dev.0 export. * chore: Update `@librechat/agents` version to `3.1.71-dev.1` in package-lock and package.json files This commit updates the version of the `@librechat/agents` package from `3.1.71-dev.0` to `3.1.71-dev.1` across the relevant package files. This change ensures consistency and incorporates any updates or fixes from the new version. * 🪢 fix: Walk Subagents in toolOutputReferences run-level gate Codex P2 review on PR #12830: the run-level `enableToolOutputReferences` flag only inspected the top-level `agents` array. A parent agent without `execute_code` that spawns a subagent that *does* have it left the SDK's tool-output reference registry inactive for the run, so the subagent's `bash_tool` calls saw `{{tool<idx>turn<turn>}}` placeholders pass through to the shell unsubstituted. Replace `agents.some(a => a.codeEnvAvailable === true)` with a recursive `anyAgentHasCodeEnv` helper that walks `subagentAgentConfigs` transitively. Cycle-safe via a `visited` set, mirroring the existing `buildSubagentConfigs.ancestors` pattern in the same module. The bash tool *description* stays per-agent in `initializeAgent` (only agents with bash actually registered learn the `{{…}}` syntax), so broadening the run-level gate doesn't broaden the model-facing surface — it just lets the SDK's shared registry serve every `ToolNode` the run compiles, which is exactly the contract the SDK already implements. Tests cover three new cases: parent-off / subagent-on, parent-off / child-off / grandchild-on (transitive descent past one level), and a cyclic A↔B tree with neither codeenv-enabled (asserts both termination and absence of `toolOutputReferences`). Existing single-agent and multi-agent tests stay valid since the new helper returns `true` whenever the previous `.some(...)` did. * chore: Update `@librechat/agents` version to `3.1.71` in package-lock and package.json files This commit updates the version of the `@librechat/agents` package from `3.1.71-dev.1` to `3.1.71` across the relevant package files. This change ensures consistency and incorporates any updates or fixes from the stable release. * review: address audit findings on tool-output references PR Two findings from comprehensive PR review on #12830: #1 (MINOR) — `injectSkillCatalog` omitted `enableToolOutputReferences` when calling `registerCodeExecutionTools`, so its resulting `bash_tool` description always lacked the `{{tool<idx>turn<turn>}}` guide. Today this is a no-op because `initializeAgent` registers first and the registry `.has()` check makes the skills-path call a dedupe-only operation. But if call order ever flips (skills-first), the missing flag would silently ship a `bash_tool` without the syntax guide, and the `initializeAgent` pass would itself become the no-op — the feature would silently break with no visible error. Forward `enableToolOutputReferences: codeEnvAvailable === true` so both call sites produce identical tool definitions regardless of firing order. Defense-in-depth, not a current bug. Added a test in `skills.test.ts` that asserts the bash description contains the `{{tool<idx>turn<turn>}}` marker when `codeEnvAvailable` is on, exercising the skills caller end-to-end. #2 (NIT) — `buildBashToolDef` allocated + froze a fresh object on every agent init. Replaced with two module-level frozen singletons (`BASH_TOOL_DEF_WITH_OUTPUT_REFS`, `BASH_TOOL_DEF_WITHOUT_OUTPUT_REFS`) built once at module load via a `createBashToolDef` helper. The factory now picks the right cached reference instead of building. Restores the no-allocation intent of the original `BASH_TOOL_DEF` constant while keeping the per-agent gate behavior. Two new tests in `tools.spec.ts` pin the contract: identical-flag calls return reference-equal `bash_tool` defs across registries; opposite-flag calls return distinct frozen objects with the expected description content. |
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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.