mirror of
https://github.com/danny-avila/LibreChat.git
synced 2026-08-28 12:44:28 +00:00
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
cc813f430e
* 🎯 feat: Tool Intent Label Capability (tool_intents) Adds the fourth member of the per-tool capability family (defer_loading, allowed_callers, run_in_background): an admin capability AgentCapabilities.tool_intents plus a per-tool tool_options[name].describe_intent flag. Opted-in tools get an optional intent string injected as the FIRST property of their schema — one model-authored sentence per call, streamed to the client as the call's live status label (args already reach the client verbatim, so no new event plumbing). Native host tools (web_search, create_file/edit_file, set_memory/delete_memory, ask_user_question) default on while the capability is enabled; explicit false opts out. SDK-native intent schemas (@librechat/agents coding suite) are recognized and left alone. - packages/api/src/agents/intent.ts: structural sibling of background.ts — first-key non-mutating injection with registry parity (covers deferred/tool_search discovery), eligibility and PTC-only skips, arg read/strip helpers, self-spawn strip for defs and registry, ephemeral/model-spec synthesis with a tool_options merge so the background and intent toggles compose. - handlers.ts: intent runs BEFORE background injection so the label stays the first streamed key when a tool carries both (pinned by test); the arg is stripped before invocation unless the tool's own schema declares it, on both the foreground and background-dispatch paths; PTC target schemas are sanitized like background's. - Capability plumbing through all four routes (endpoint initialize, openai + responses controllers, the exported OpenAI-compatible service) plus handoff discovery and added-convo agents, and the intentToolNames execution channel via configurable. - describe_intent on toolOptionsSchema (all three written-out Zod annotations), ToolOptions, TEphemeralAgent, TModelSpec (+ zod), and data-schemas doc comments (tool_options is Mixed — no migration). - intent.spec.ts: 28 tests cloned from background.spec.ts structure, including the intent+background key-order composition. * 🧯 fix: Codex Review — Opt-Out Strips SDK-Native Intent, Skip mcp_all Placeholders - An explicit describe_intent: false now REMOVES an SDK-native intent property from the definition and registry entry, so the per-tool opt-out actually disables the arg's token cost for tools like web_search that carry the schema natively (SDK bodies tolerate its absence). Previously the early return left the property in place. - synthesizeIntentToolOptions skips lazily-expanded mcp_all placeholders instead of recording options under names that applyIntentLabels' exact-name matching can never match, and documents the limitation (parity with synthesizeBackgroundToolOptions). The P1 about the client not rendering the label is the documented slicing: the UI streaming-label PR follows once #14391's ToolCallGroup changes merge — args already reach the client, so that slice is purely rendering. * 🧯 fix: Codex Re-Review — Label Marker Guard, Capability Kill Switch, Late Defs, Service Threading - removeIntentParam is now marker-guarded (the label contract's opening instruction discriminates it), so an MCP/action tool's own business `intent` parameter is never stripped by an opt-out or the disabled path — previously an explicit false could remove a real, possibly required argument. - New sanitizeIntentLabels pass runs AFTER every registration step (the skill catalog appends its SDK definition post-injection): with tool_intents disabled it strips SDK-native intent labels from all definitions and registry entries, making the capability a real kill switch over their token cost; with it enabled it enforces explicit per-tool opt-outs on late-registered definitions. - ask_user_question removed from the native default-on set: its graph tool is rebuilt in run.ts from its own Zod schema (also the HITL card's wire shape), so definition-level injection never reached the model. Its intent support lands with the HITL slice, which threads the label into the interrupt payload deliberately. - The exported OpenAI-compatible service now threads intentToolNames into the run configurable, so the executor's PTC path can strip host-injected intent schemas on that route like the in-repo controllers do. * 🧯 fix: Codex Round 2 — Post-Skill Injection, PTC Native Strip, Service Boundary, Honest Docs - Intent injection now runs LAST in initializeAgent, after the skill catalog — which both appends its own definition and REPLACES upgraded ones (skill-aware read_file), clobbering an earlier injection while intentToolNames still listed the tool. Injection PREPENDS while background APPENDS, so intent stays the first schema property under the new ordering (pinned by a reverse-order composition test). - The PTC target-schema strip is now marker-guarded strip-ALL: SDK- native intent labels (which are deliberately never in intentToolNames) are removed from sandbox-advertised schemas alongside host-injected ones; business intent params survive. - toolIntentsAvailable on the exported service documents the loader boundary: a custom LoadToolsFn returning only structured instances bypasses definition/registry injection and sanitize by construction. - librechat.example.yaml describes tool_intents as backend groundwork with UI rendering in an upcoming release rather than promising a live label today. * 📦 chore: bump `@librechat/agents` to v3.3.6 Brings in the SDK half of tool intent labels (danny-avila/agents#347, #349): intent-first schemas on the coding suite across all three engines, plus web_search / subagent / skill / tool_search, and the outcome / outcome_patch result channel. Activates three host paths that were inert while no SDK tool shipped an `intent` property — verified against the real 3.3.6 schemas: - capability OFF now strips SDK-native labels (a real admin kill switch) - explicit `describe_intent: false` removes them per tool - host injection stays idempotent against an SDK schema, keeping `intent` first and never double-injecting * 🔬 test: Real-Provider Verification for Tool Intent Labels Adds the live check the unit tests structurally cannot perform: whether a real model actually authors the injected arg, places it FIRST, and gives sibling calls to one tool distinct labels. Reuses the existing real-provider harness (in-memory Mongo, seeded user, credential neutralizer) and the existing stdio MCP fixture as a genuine tool, so no external service is involved. - e2e/config/librechat.real.yaml: adds the e2e-memory MCP server and the tool_intents capability, giving the real model something to call. The sibling spec asserts only relative token growth, so the extra schemas do not perturb it. - e2e/playwright.config.real.ts: optional Langfuse passthrough. The LANGFUSE_* keys match the credential-neutralizer pattern and were being blanked before the server booted; they are preserved explicitly, read from the invoking environment only, and never written to the generated config. - e2e/specs/real/tool-intents.spec.ts: two facts stored in one turn, both through the same tool, asserting intent is the first key of each call and that the two labels differ. Args are read from persistence rather than the DOM deliberately — no UI renders the label yet, and persistence is what a reloaded conversation and the trace both read. First run against claude-haiku-4-5 produced 'Recording the location of the OAuth callback router' and 'Recording the location of the MCP connection pool configuration' — distinct, first-position, no tool name. Also updates tool-intent-spec.md: records the 3.3.7 removal of the tense verb map with the evidence that motivated it, the trimmed description and the marker's role as an API, and a new mandatory requirement that client-side label rendering be gated on a server-sent signal rather than the presence of an intent key (a tool's own business 'intent' parameter would otherwise render as a status label). * 📦 chore: bump `@librechat/agents` to v3.3.7 and dedupe the intent contract Picks up danny-avila/agents#353: the tense verb map is gone (a bare intent now displays unchanged, with completion carried by UI state), the model-facing description is trimmed 502 → 289 chars, and both the marker and the description are exported. Stops redeclaring the SDK contract here: - INTENT_LABEL_MARKER is imported instead of duplicated as a string literal. Every removal path in this module keys on it, and a local copy that drifted from the SDK's would make them all stop recognizing SDK-native labels — failing OPEN, with labels left in schemas and per-tool opt-outs silently inert. - INTENT_DESCRIPTION is imported too, so host-injected tools and SDK-native tools present the model with one identical instruction. Keeping the old local copy would also have meant host-injected tools still paying ~126 tokens per schema while SDK tools paid ~72. Verified live against real Anthropic after the trim: two sibling calls to one MCP tool produced 'Storing the OAuth callback router file location' and 'Storing the MCP connection pool configuration file location' — first-position and distinct, so the shorter description holds compliance. |
||
|---|---|---|
| .devcontainer | ||
| .do/gitnexus | ||
| .github | ||
| .husky | ||
| .vscode | ||
| api | ||
| client | ||
| config | ||
| e2e | ||
| helm | ||
| otel/langfuse-fanout | ||
| packages | ||
| redis-config | ||
| scripts | ||
| skill | ||
| src/tests | ||
| utils | ||
| .dockerignore | ||
| .env.example | ||
| .gitattributes | ||
| .gitignore | ||
| .nvmrc | ||
| .prettierrc | ||
| AGENTS.md | ||
| bun.lock | ||
| CLAUDE.md | ||
| deploy-compose.langfuse-fanout.yml | ||
| deploy-compose.yml | ||
| docker-compose.langfuse-fanout.yml | ||
| docker-compose.override.yml.example | ||
| docker-compose.yml | ||
| Dockerfile | ||
| Dockerfile.multi | ||
| eslint.config.mjs | ||
| librechat.example.yaml | ||
| LICENSE | ||
| package-lock.json | ||
| package.json | ||
| rag.yml | ||
| README.md | ||
| README.zh.md | ||
| tool-intent-spec.md | ||
| turbo.json | ||
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.