mirror of
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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
c570517768
* fix(data-schemas): refresh FerretDB harness model coverage, fix compile errors, add bulkWrite differentials Track 2 of the search-stack plan (PLAN.md "FerretDB track"): - Replace the three hand-rolled 29-model MODEL_SCHEMAS maps in multiTenancy/sharding/orgOperations.ferretdb.spec.ts with a shared getModelSchemas(mongoose) helper (misc/ferretdb/schemas.ts) derived from the live createModels() registry, so coverage tracks all 37 current models automatically instead of drifting. Matches the reference pattern in misc/documentdb/compat.documentdb.spec.ts. - Fix the 3 compile-broken specs this uncovered: all three imported a `projectSchema` from '~/schema' that no longer exists (superseded by `chatProjectSchema`), which `tsc --noEmit` flags as TS2724 but the babel-based jest transform silently let through as `undefined`. Removing the hand-rolled maps removes the bad import as a side effect; verified clean with tsc across misc/ferretdb and misc/documentdb. - Add misc/ferretdb/bulkWrite.ferretdb.spec.ts: differential specs for the five bulkWrite flows the plan names as actually at risk (import via bulkSaveConvos/bulkSaveMessages, bulkWriteAclEntries, bulkIncrementTagCounts, Transaction.insertMany, file-TTL bulkWrite via extendFilesTTL). Each flow runs identical operations against a real mongodb-memory-server (always) and, when FERRETDB_URI is set, against FerretDB, asserting normalized result equality. Multi-document transactions already degrade via the existing supportsTransactions probe — not duplicated here. - Land the Spike A BSON-legibility findings (bson-legibility.md, bson-inventory.txt) from the bson-legibility-spike-6e38de worktree so decision 2's evidence is in-repo. Verified against a real FerretDB 2.7.0 + postgres-documentdb 17 stack (docker compose -f misc/ferretdb/docker-compose.ferretdb.yml): all 10 harness spec files pass individually, including all 10 bulkWrite.ferretdb tests (5 mongodb-memory-server baselines + 5 FerretDB differentials). Full packages/data-schemas src/ suite (1907 tests) unaffected. * 📝 docs: make the BSON projection findings self-contained The doc was written for readers who already knew the internal shorthand — it opened on "Spike A executed, Spike B scoped" and referred to Options 1/2/3 and "the handoff" without ever defining them, so a reader arriving from the repo could not follow the argument or act on the recommendation. Reframed around what the document actually investigates: the question is stated up front, the three candidate mechanisms are named in a table before they are compared, and the recommendation refers to them by name. No findings, numbers, or SQL changed. * 📝 docs: drop internal planning references from spec header * fix(data-schemas): keep FerretDB harness schema derivation side-effect free `getModelSchemas()` derived its map by calling `createModels(mongoose)`, which carried three consequences the harness did not want: - Model creation applies the tenant-isolation plugin to the module-level schema singletons, so every harness read and write inherited middleware that throws under `TENANT_ISOLATION_STRICT=true`. - Registering on the default connection meant the benchmark's own `mongoose.connect()` auto-created 37 collections in the URI's base database, adding a database and dozens of collections to the very catalog metrics it measures. - The unfiltered registry provisioned app-wide control-plane models (`SystemGrant`, `AuditLog`, `SkillSyncCredential`, `SkillSyncStatus`) into every org database. The helper now builds the registry on a throwaway Mongoose instance, returns schemas rebuilt from their own definition, options, and declared indexes, skips the four app-wide models (validated against the registry so a rename fails loudly), and memoizes the result. Also in this pass: - The "adds a new collection" migration test used `AuditLog`, which provisioning had already created, so it silently reused the production model and ignored its proposed schema. It now uses a fixture model absent from the registry and asserts the collection is missing beforehand and carries the proposed compound index afterwards. - `bulkWrite` flows run inside `runAsSystem()`; they drive production methods unscoped, as a cross-tenant maintenance job does, and otherwise fail closed under strict tenant isolation. - Phase 2's sparse-index assertion pinned a count the User schema no longer declares; it now checks that each index type round-trips. |
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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
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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.