* 🐛 fix: resolve Action tools by exact tool name to prevent multi-action collision When two OpenAPI Actions on the same Agent share a hostname, the second action's entry overwrote the first in the encoded-domain Map and one action's tools silently disappeared from the LLM payload. The buggy resolution loop also used substring matching, which caused similar shadowing for any encoded-domain prefix overlap. This change builds a Map keyed on the full tool name (`<operationId>_action_<encoded-domain>`) directly, mirroring the exact lookup pattern that getActionToolDefinitions already uses. Each function in an action's spec gets its own slot, so two actions sharing a hostname no longer collide. Both the new and the legacy domain encodings are registered for each function so agents whose stored tool names predate the current encoding still resolve. Applied at all three call sites that had the buggy pattern: - processRequiredActions (assistants/threads path) - loadAgentTools (agent build path) - loadActionToolsForExecution (agent execution path) Adds three regression tests covering both ordering directions and the execution path. Tests fail without the fix and pass with it. * 🐛 fix: Normalize action tool name at lookup + cover assistants path Follow-up to the multi-action domain collision fix. Addresses PR #12594 review feedback: **Must-fix #1 — short-hostname lookup mismatch.** The toolToAction map is keyed on the `_`-collapsed domain, but `agent.tools` and `currentAction.tool` persist the raw `domainParser(..., true)` output, which for hostnames ≤ ENCODED_DOMAIN_LENGTH is a `---`-separated string (e.g. `medium---com`). Exact-match `Map.get()` missed those keys and silently dropped the tool. Fix: normalize every incoming tool name through a new `normalizeActionToolName` helper before the lookup in `loadAgentTools`, `processRequiredActions`, and `loadActionToolsForExecution`. **Must-fix #2 — assistants path coverage.** `processRequiredActions` received the same structural rewrite but had zero tests. Added a regression test under `multi-action domain collision regression` that drives two shared-hostname actions through the assistants path and asserts each tool reaches its own request builder. **Must-fix #3 — legacy encoding branch coverage.** The `if (legacyNormalized !== normalizedDomain)` registration was never exercised by any test. Added a test where `agent.tools` stores the legacy-format name and asserts it still resolves. **Should-fix #4 — DRY the registration loop.** Extracted `registerActionTools({ toolToAction, functionSignatures, normalizedDomain, legacyNormalized, makeEntry })`. All three call sites now share the same key-building logic; the key template lives in one place. **Should-fix #5 — remove stale optional chaining.** In `loadActionToolsForExecution`, `functionSignature?.description ?? ''` became `functionSignature.description` — `sig` is always defined by the iterator, matching the style of `loadAgentTools`. **Should-fix #6 — drop unreachable `!requestBuilder` guard.** Entries in `processRequiredActions` are now pre-built with `requestBuilder: requestBuilders[sig.name]`, which `openapiToFunction` always produces alongside the signature, so the guard is dead. **Should-fix #7 — unwrap `actionSetsData`.** It now holds a bare `Map` instead of `{ toolToAction }`; the sentinel `!actionSetsData` check still works because `new Map()` is truthy. Also added a short-hostname regression test (`loadAgentTools resolves raw ---separated tool names`) that reproduces Must-fix #1: it fails against the previous commit (0 create calls) and passes with the normalization in place. 41 tests, all passing. The 3 new regression tests are under `multi-action domain collision regression` and cover the assistants path, the legacy encoding branch, and the short-hostname lookup path. * 🐛 fix: Tighten registerActionTools key handling and assistants test Follow-up to |
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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
-
🔦 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
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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 🗃️
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🌎 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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⚙️ Configuration & Deployment:
- Configure Proxy, Reverse Proxy, Docker, & many Deployment options
- Use completely local or deploy on the cloud
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📖 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.