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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
3f0a1ec8d9
* 🛡️ fix: Run message-filter PII patterns on a linear-time regex engine The messageFilter.pii middleware compiled admin-configured customPatterns with the native RegExp engine and ran them synchronously against every message on the shared event loop, so a catastrophic-backtracking pattern such as (a+)+$ could stall the entire process (native RegExp takes tens of seconds at roughly 32 characters) and take the instance down for every user. Compile these patterns with RE2JS, a linear-time RE2 port with no native addon, so catastrophic backtracking is impossible regardless of the pattern rather than something the code tries to detect. Patterns using features RE2 does not support, such as backreferences, fail to compile and are dropped and logged exactly as an invalid pattern already is. The filter only tests for a match, so this is a drop-in engine swap with no behavior change for valid patterns. * 🛡️ fix: Reject RE2-incompatible messageFilter patterns at config load The customPatterns regex was validated with native RegExp at config load, but the runtime now compiles it with a linear-time engine (RE2) that does not support backreferences or lookaround. Such a pattern passed validation, then failed to compile and was silently dropped at request time, quietly removing PII protection after upgrade. Reject backreferences and lookaround during config validation with an explicit message, and document RE2 syntax in the example config instead of "JavaScript-flavor". The runtime engine remains the authoritative boundary and still drops-and-logs anything this load-time check misses. * 🧹 test: Use direct MessageFilterPiiConfig annotations in the PII specs The added ReDoS cases satisfy the exported MessageFilterPiiConfig type directly, so the `as unknown as` assertions were unnecessary. Annotate the config objects directly, matching the repo's type-safety guidance. * 🧹 fix: Reject named backreferences in messageFilter patterns at config load Extend the config-load check to also reject named backreferences (\k<name>), which are valid JavaScript regex but unsupported by the linear-time runtime engine, so they surface at load rather than being dropped at request time. Together with the existing numeric-backreference and lookaround checks this covers the RE2-incompatible construct set; the runtime engine remains authoritative. * 🛡️ fix: Preserve Unicode whitespace matching in messageFilter starter patterns RE2's \s is ASCII-only, so after the engine swap the built-in api-key and Bearer starters no longer matched a secret separated by non-ASCII whitespace (e.g. a non-breaking space), which native RegExp did match. Broaden the whitespace classes to [\s\p{Zs}] so those patterns keep their original coverage, and add a regression test for a non-breaking-space separator. * 🛡️ fix: Validate messageFilter patterns with the RE2 engine at config load Replace the syntax blacklist (numeric/named backreferences, lookaround) with authoritative validation: config load now compiles each custom pattern with the same linear-time engine the runtime uses, so any RE2-incompatible construct (including control escapes like \cA) is rejected at load with a clear error instead of being silently dropped at request time. The validator is swappable and defaults to native RegExp so browser builds add no engine; the server wires the RE2-backed check at startup via configureMessageFilterRegexValidator in both entry points. * 🛡️ fix: Match the full whitespace set in messageFilter starter patterns RE2's `\s` omits the vertical tab and `\p{Zs}` omits U+2028, U+2029, and U+FEFF, so a separator built from one of those characters slipped past the `api-key` and `Bearer` starter patterns and reached the model. Broaden the starter whitespace class to the full JavaScript whitespace set so those separators are covered again. * fix: fail closed when messageFilter.pii compiles to zero patterns DB and admin config overrides bypass the RE2 schema validation (it only runs at YAML load), so an override whose only pattern is RE2-incompatible was dropped at compile time, left zero patterns, and let the request through. compile() now returns a failClosed flag when a config declared patterns but every one failed to compile; the middleware returns 400 and findPiiMatchInMessages returns a distinct misconfigured match that the OpenAI and Responses controllers surface with an admin-facing message. * 🛡️ fix: Fail closed when any messageFilter.pii custom pattern drops compile() previously set failClosed only when every pattern dropped (patterns.length === 0 && dropped > 0). With the default starters present, a single RE2-incompatible custom override incremented dropped but left patterns.length > 0, so the filter silently enforced only the surviving subset and text matching only the dropped rule passed. failClosed now keys off dropped > 0, so any dropped custom pattern blocks with the misconfigured 400. YAML patterns are RE2-validated at load, so dropped stays 0 for valid configs and only unvalidated DB or admin overrides can trip it. Reframed the two keeps-others-active specs to assert fail-closed and added a default-starters partial-drop regression. * 🧹 fix: Correct the misconfigured JSDoc and drop redundant casts in the PII specs The misconfigured flag now means any configured custom pattern failed to compile, not that every pattern failed, so its JSDoc on PiiMatch is updated to match. The partial-drop regressions now use direct MessageFilterPiiConfig annotations instead of as-unknown-as casts, keeping the specs type-checked, consistent with the rest of the suite. |
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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
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- 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
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💾 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
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💬 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
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🧠 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
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- 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
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🗣️ 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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🎛️ 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
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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.