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* 🛡️ feat: Reject chat messages matching configured credential patterns
Adds an opt-in `messagePiiFilter` middleware mounted on the agent
chat route ahead of `moderateText`. When the configured patterns
match the user's input the request is refused with 400, so the
credential never reaches OpenAI moderation, the model, or MongoDB.
Three starter patterns ship by default and operators can subset
them or add their own regex via `customPatterns` in librechat.yaml.
* 🧪 test: Memoize compiled patterns + add middleware spec
Memoize the compiled pattern array via a WeakMap keyed by the
messagePiiFilter config object so repeat requests against the same
config skip the per-request RegExp construction. Cache entries are
released automatically when the config object itself rotates.
Adds packages/api/src/middleware/messagePiiFilter.spec.ts covering
the default-starter rejections, the starterPatterns subset and
empty-array semantics, customPatterns matching layered on top of and
in place of the starters, the no-config and empty-text pass-through
paths, and a memoization regression check.
* 🛡️ fix: Skip invalid customPattern regexes instead of crashing the request
Admin DB overrides for `messagePiiFilter.customPatterns` reach
`req.config` via `mergeConfigOverrides`, which deep-merges raw
override values without re-running `configSchema`. A typo'd regex
like `(` would slip past the YAML-load validation and throw inside
`new RegExp(...)` during `compile()`, returning 500 for every chat
request until the operator rolled the override back.
Wrapped the per-pattern compile in a try/catch that logs the
invalid pattern id + reason and skips it, so other valid patterns
(starters and other custom entries) keep filtering. Added a
regression test alongside the existing spec.
* 🛡️ feat: Extend PII filter to OpenAI-compatible and Responses agent APIs
The chat-route middleware operates on `req.body.text`, but the remote
agent API endpoints (`/api/agents/v1/chat/completions`,
`/api/agents/v1/responses`) accept the same prompt content as a
`messages` array or an `input` field. A caller using their API key
could send a credential-shaped value through either route and bypass
the configured PII filter even though they share the same agent and
model backbone the middleware is meant to guard.
Factored out `findPiiMatchInMessages`, a tolerant walker that handles
both `content: string` and `content: ContentPart[]` user-message
shapes against the same compiled, cached pattern list. Wired it into
the OpenAI-compat controller after agent lookup and into the
Responses controller right after `convertToInternalMessages`. Each
returns the endpoint's native 400 error shape
(`sendErrorResponse` / `sendResponsesErrorResponse`) with the
`message_pii_filter_block` code when a user message matches.
* 🩹 test: Add findPiiMatchInMessages to OpenAI + Responses controller mocks
The OpenAI-compat and Responses controller specs mock `@librechat/api`
with a hand-listed object. The new `findPiiMatchInMessages` export
wired into both controllers in 3ea35af9a was missing from those
mocks, so the production lookup returned undefined and the controllers
threw at request time under jest. Added the missing entries (default
mock: returns null so the handlers fall through to the existing happy
paths). All 278 agents-controller tests pass locally.
* 🧹 refactor: Namespace messagePiiFilter under messageFilter.pii + fix import order
Renames the yaml field `messagePiiFilter` to `messageFilter.pii`, the
module to `messageFilterPii`, the factory to `createMessageFilterPii`,
the type to `MessageFilterPiiConfig`, and the error code to
`message_filter_pii_block`. The wrapper `messageFilter` namespace
gives future safety filters (e.g. `messageFilter.toxicity`) a place
to plug in without restructuring the config later. The
`findPiiMatchInMessages` helper kept its name because it already
describes what it does at the value level.
Also fixes import order Danny flagged on the OpenAI-compatible and
Responses controllers: `findPiiMatchInMessages` was appended at the
bottom of two `require('@librechat/api')` destructures rather than
placed in the length-sorted slot the house style expects.
* 🧹 chore: Length-sort the general require destructure in responses.js
Reorders the general sub-group inside the `require('@librechat/api')`
destructure shortest to longest so the whole block conforms to the
length-sort rule the file's `// Responses API` sub-group already
follows. Pure reorder, no other changes.
* 🧹 chore: Length-sort the defaultConfig block in AppService
Reorders the `defaultConfig` keys in `packages/data-schemas/src/app/service.ts`
shortest-line to longest-line, with the explicit-value entries
(`mcpConfig`, `fileStrategies`, `cloudfront`) trailing the shorthand
ones. Pure reorder, no behavior change.
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
-
🎨 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 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.