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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
181d705579
* 🧹 fix: Prune Orphaned File References on File Deletion Deleting a file via the Manage Files tab left its file_id in every agent's tool_resources.*.file_ids. Stubs accumulate until the frontend dedupe keys them as duplicates and blocks all new uploads (issue #12776). - Add removeAgentResourceFilesFromAllAgents in packages/data-schemas: a single updateMany/$pullAll across every EToolResources category. - Invoke it from processDeleteRequest after db.deleteFiles so every referencing agent is cleaned up, not just the one passed in req.body. - Wrap the cleanup in try/catch so a stale agent update cannot mask a successful file deletion. * 🧼 fix: Prune Orphaned File References on Agent Update Already-affected agents would stay broken even after the delete-time fix: the stubs sit on the agent document until something strips them. Heal them on the next save (issue #12776). - Add collectToolResourceFileIds + stripFileIdsFromToolResources helpers in @librechat/api — centralizing the tool_resources traversal used by the controller and the follow-up migration script. - In updateAgentHandler, check the effective tool_resources against the files collection. When orphans are found, either strip them from the incoming tool_resources (if the update sets them) or run the bulk cleanup (if the update leaves tool_resources untouched). * 🧰 chore: Add Migration to Clean Up Orphaned Agent File References Complements the delete-time and save-time fixes by healing agents that already accumulated orphan stubs before the upgrade (issue #12776). The script is idempotent — re-running it on a clean database is a no-op. - Add config/migrate-orphaned-agent-files.js following the existing migrate-*.js convention: --dry-run by default omitted (writes by default) and --batch-size= tuning knob. Streams agents via cursor. - Register migrate:orphaned-agent-files and :dry-run npm scripts. - Reuse collectToolResourceFileIds from @librechat/api so migration and runtime share the same traversal logic. * 🩹 fix: Address Codex/Copilot Review on Orphaned Agent File Cleanup Refines the #12776 fix series based on automated review feedback. - Scope save-time pruning to the current agent only. When a PATCH carries tool_resources, strip orphans from the incoming payload and pay the DB round-trip only then. Removes the collection-wide updateMany previously triggered when tool_resources was absent (Codex P2 / Copilot). - Wrap the orphan check in try/catch so a transient db.getFiles failure can't turn a good save into a 500 (comprehensive review #1). - Replace Object.values(EToolResources) casts with an explicit list of agent-side categories in both orphans.ts and agent.ts. code_interpreter belongs to the Assistants API and isn't a key of AgentToolResources — including it was a type lie and generated dead MongoDB clauses (comprehensive review #3, #8). - Export TOOL_RESOURCE_KEYS from @librechat/api and consume it in the migration script, dropping one duplicated definition (#4). - Cap migration results.details at 50 sample entries so the memory footprint stays bounded on deployments with thousands of corrupted agents (Codex P3). - Add migrate:orphaned-agent-files:batch npm script to match the convention set by migrate-agent-permissions / migrate-prompt-permissions (#7). - Add controller-level tests covering the three orphan-pruning paths: strip from incoming tool_resources, leave alone when tool_resources is absent, swallow db.getFiles errors and still save (#6). - Back pre-existing "should validate tool_resources in updates" test's file_ids with real File docs — the new pruning would otherwise strip them, and that test is about OCR conversion / schema filtering, not file existence. Register the File model in beforeAll so the fixture works. * 🩹 fix: Tighten TOOL_RESOURCE_KEYS Type and Align Migration Sample Output Two follow-ups from the second review pass. - Type data-schemas' TOOL_RESOURCE_KEYS as ReadonlyArray<keyof AgentToolResources> instead of readonly string[]. Data-schemas depends on data-provider, so the import is clean. Catches typos and aligns with the matching export in @librechat/api — doesn't guarantee exhaustiveness, but that's a TypeScript limitation, not a workspace one. - Align the migration's console output with DETAIL_SAMPLE_LIMIT: print every collected detail (up to 50) and, when more agents were affected than the sample size allowed, show a truncation notice. The old hard cap of 25 meant affected agents in the 26-50 range were collected but never shown. * ✅ test: Add Integration Coverage for Orphan Cleanup Paths (#12776) Exercise the delete-time and migration paths end-to-end against a real in-memory Mongo. Catches integration bugs the isolated unit tests on each layer couldn't. - api/server/services/Files/process.integration.spec.js — the primary repro: seed an Agent + File, call processDeleteRequest, assert the file_id disappears from every referencing agent's tool_resources while unrelated agents stay untouched. Also covers the no-op case and confirms a failure in the new cleanup step cannot roll back the file deletion itself. - api/test/migrate-orphaned-agent-files.spec.js — drives the migration module: --dry-run reports without writing, apply mode prunes across every tool_resource category, re-running is idempotent, and DETAIL_SAMPLE_LIMIT caps the in-memory sample on wide corruption. Mocks only the connect helper (the spec owns the mongoose instance) so the real migration code path — cursor, $pullAll, reduce — runs. * 🔒 fix: Run Orphan Cleanup Migration in System Tenant Context Codex P2 catch: under TENANT_ISOLATION_STRICT=true, the migration throws on the very first Agent.countDocuments() because the tenant isolation plugin fail-closes on queries without tenant context — which makes migrate:orphaned-agent-files unusable on the exact deployments most likely to have accumulated corruption. - Wrap the scan/prune body in runAsSystem so queries bypass the tenant filter (SYSTEM_TENANT_ID sentinel). The migration legitimately needs cross-tenant visibility — this is the same pattern seedDatabase and the S3 refresh job already use. - Add a regression test that spies on Agent.countDocuments() and asserts the active tenantStorage context is SYSTEM_TENANT_ID during the call. Pins the wrap against future regressions without the brittleness of toggling the strict-mode env var (which caches on first read). Note: the delete-time and save-time paths already run inside an authenticated HTTP request where tenantStorage.run is set by auth middleware, so the cleanup naturally scopes to the current tenant — which is the correct behavior there since file ownership is tenant-scoped. * 🧹 chore: Drop Unused path Import From Process Integration Spec Leftover from an earlier iteration that resolved the migration path via path.resolve before I switched to a relative require. The import does nothing now — removing it. |
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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
-
🔦 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
-
💾 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
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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
-
🗣️ 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
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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
-
📖 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.