* 🐛 fix: Prevent Infinite Render Loop on Code-Execution File Preview Loading a conversation that contains a large (>1MB) code-execution office file crashed the whole app with React error #185 ("Maximum update depth exceeded") on hard refresh. Root cause (client-only): the terminal-write effect in useAttachmentPreviewSync writes the resolved preview record back into messageAttachmentsMap with a fresh object identity on every run, and `attachment` is in the effect's dependency array. useAttachments re-derives `attachment` ({...db, ...liveEntry}) with a new identity on every map write, so once polling resolves (pending -> ready on a loaded conversation) the effect ping-pongs forever: setAttachmentsMap -> re-derive -> effect -> setAttachmentsMap. Only files large/slow enough to defer extraction are persisted at status: 'pending', which is why small documents never triggered it. Fix: an idempotency gate that bails before setAttachmentsMap when the merged attachment already carries the resolved status/text/textFormat/ previewError. The write happens once and then settles. Tests: - useAttachmentPreviewSync.loop.spec.tsx wires the real useAttachments -> hook feedback to reproduce the loop (verified to throw #185 without the gate, settle with it). - e2e/specs/mock/attachment-preview-loop.spec.ts loads a conversation with a pending code-exec attachment whose preview resolves ready and asserts the app does not crash. Closes #13916 * 🔧 feat: Make Office Preview Extraction Cap Configurable (default 2MB) The inline code-execution preview extraction ceiling was a hardcoded 1MB constant (MAX_TEXT_EXTRACT_BYTES). Office/text artifacts over that skip the inline preview and resolve to "Preview unavailable" (download-only). Make it configurable via FILE_PREVIEW_MAX_EXTRACT_BYTES and raise the default to 2MB so larger documents get an inline preview out of the box. The rendered HTML remains independently capped at MAX_TEXT_CACHE_BYTES (512KB), so image-heavy files over that still fall back to the existing "preview too large" banner rather than rendering unbounded output. - resolveMaxTextExtractBytes(env) parses the override, falling back to 2MB on missing/non-numeric/non-positive values (warns on invalid). - Documented in .env.example next to the other file-size limits. - Unit tests cover default, valid override, fractional flooring, and invalid fallback. * 🐛 fix: Guard sub-byte preview cap from flooring to zero A fractional FILE_PREVIEW_MAX_EXTRACT_BYTES in (0, 1) passed the positive-number check then floored to 0, making MAX_TEXT_EXTRACT_BYTES zero and treating every non-empty artifact as oversized. Floor first, then require the result to be >= 1 byte before accepting it; otherwise fall back to the 2 MB default. Adds coverage for the sub-byte case. * ✅ test: Make exported-ceiling assertion env-independent The "exported ceiling" assertion compared MAX_TEXT_EXTRACT_BYTES to a literal 2 MB, but that const is initialized from FILE_PREVIEW_MAX_EXTRACT_BYTES at module load — so the suite would falsely fail when run with the override set. Assert the export tracks resolveMaxTextExtractBytes(env) for the current environment instead; the undefined-case test continues to pin the 2 MB default. |
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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
- Open-Source & Self-Hostable: powered by ClickHouse/code-interpreter
-
🔦 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
-
🎛️ 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
-
⚙️ 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.