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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
94c73123ee
* 🛡️ fix: Cap Default Limit on Agent List Queries (#13363) `GET /api/agents` accepted unbounded requests: when the client omitted `limit`, the value flowed straight into `getListAgentsByAccess`, which set `isPaginated = false` and issued an uncapped MongoDB query. Combined with the unindexed `findPubliclyAccessibleResources` AclEntry scan run on every request, this produced 10-19s response times and stalled the connection pool on instances with 100+ agents. - Default `limit` to 100 in the route handler so client requests without `?limit=` paginate by default. - Default `limit` to 100 in `getListAgentsByAccess` itself as defense-in-depth. The function already caps numeric limits at 100, so there is no client-facing change. - Pass `limit: null` explicitly in the actions route, which legitimately needs the full editable-agent set, to preserve its existing behavior. - Add regression tests covering the default cap and the explicit unbounded opt-out. * 🛡️ fix: Avoid agent-list regression for users with 100+ agents Codex review pointed out that capping `getListAgentsByAccess` at 100 silently truncated agents past the first page for the four consumers (`useAgentsMap`, `AgentSelect`, `ModelSelectorContext`, `useMentions`) that read `res.data` without following `has_more`/`after`. - Raise the function's hard cap from 100 to 1000 to match `MAX_AVATAR_REFRESH_AGENTS`, the realistic upper bound the avatar-refresh path already assumes. (Side effect: the avatar refresh call site was silently being capped at 100 by the old normalize step.) - In `useListAgentsQuery`, merge `limit: 1000` into params so the four consumers above get the user's full accessible set in a single round-trip instead of needing cursor pagination. - Route handler default stays at 100 as defense-in-depth for any other caller that omits `limit`. - Add a regression test asserting an explicit `limit` above 100 now returns the full set instead of being clipped. * 🪢 fix: Keep agent-list cache key stable for mutations Codex P2 review noted that folding `limit: 1000` into the cache key broke `allAgentViewAndEditQueryKeys` in `Agents/mutations.ts`, which references `[QueryKeys.agents, { requiredPermission }]` directly across eight mutation handlers. After my prior change the cached entry lived under `[QueryKeys.agents, { limit: 1000, requiredPermission }]`, so create/update/delete/avatar/action mutations stopped updating the list the four consumer hooks render — and with `refetchOnMount` and focus/ reconnect refetches disabled, the UI would stay stale until something else triggered a fetch. Split the merged limit out of the cache key: the request to `dataService.listAgents` still uses `requestParams` (with the default limit applied), but the React Query cache key uses the caller's `params` as-is. The mutation cache updates land again, and the request still returns the user's full accessible set in one round-trip. * 🛡️ fix: Index AclEntry and paginate agent list internally (#13363) Completes the perf fix for #13363 properly — resolves both the unbounded ACL scans Copilot flagged and Codex's tension between "show all agents" and "don't bypass the server cap". Backend: - Add a compound index on `{ principalType, resourceType, permBits, resourceId }` to the AclEntry schema. This is the index missing for `findPublicResourceIds` and the public branch of the `$or` in `findAccessibleResources`, both of which previously fell back to a collection scan on every `GET /api/agents`. Adds an `explain`-based regression test asserting the public query no longer COLLSCANs. Client: - Rewrite `useListAgentsQuery` to follow the server's cursor pagination internally and concatenate every page into a single flat `AgentListResponse`. Consumers (`useAgentsMap`, `AgentSelect`, `ModelSelectorContext`, `useMentions`) get the user's complete accessible-agent set without any of them needing to learn about cursors, and each individual request uses the server's default page size (so the route's 100-default defense-in-depth fires for real). Cache key shape is unchanged, so the eight mutation handlers in `Agents/mutations.ts` keep matching `allAgentViewAndEditQueryKeys` and update the cached list as before. - Drop the `FULL_AGENT_LIST_LIMIT = 1000` injection added in the previous commit — no longer needed once pagination handles the full set, and removing it stops bypassing the route default. * 🧹 fix: CI fallout from C-done-properly refactor - Collapse multi-line `fetchAllAgentPages` signature in queries.ts so prettier stops complaining. - In the new public-principal index test, grant one ACL entry before calling `.explain()` so the collection exists (otherwise mongo returns `nonExistentNamespace` and there is no winning plan to inspect). - Cast the `.explain('queryPlanner')` result to a typed shape — the mongoose return type doesn't expose `queryPlanner` directly and was failing the TypeScript check. * 🧪 fix: Test the AclEntry public-principal index via hint, not planner choice The previous test asserted the query planner did not pick COLLSCAN for the public-principal lookup. That assertion fails on small collections (under the planner's collection-size heuristic) — the index exists and is usable, but with a single document in the test the planner correctly chooses COLLSCAN as the cheaper plan. Reshape the assertion: 1. Confirm the new compound index is actually declared by inspecting `collection.indexes()` after `syncIndexes()`. 2. Force the planner to that index via `.hint()` and assert the winning plan is `IXSCAN` — proves the index is real and serves this query shape, without depending on collection-size heuristics. * 🧹 chore: Slim down verbose comments The JSDoc and inline comments added across the perf fix had drifted into multi-paragraph rationale better suited to the PR description than the source. Collapse to single-line JSDoc that just describes what each piece does; drop the inline comment in `actions.js` entirely — the call is self-evident. |
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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
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🎨 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
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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 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.