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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
083be12ddc
* 🛰️ ci: Publish Every Image Through One Native-ARM Workflow #15441 removed QEMU from the dev-branch image build and #15444 fixed the prefix-glob bug it shipped with. Both changes lived in one of five workflows that build images the same way; the other four still emulate arm64 with no layer cache and take 20-40 minutes. Rather than paste the pattern four more times, the build/merge logic moves to a reusable `docker-publish.yml` that every image workflow calls. #15444 is the argument for this: one wrong artifact-name expression would otherwise have needed correcting in five files, and the same prefix hazard exists in all of them (`librechat`/`librechat-api`, `librechat-dev`/`librechat-dev-api`, `lc-dev-staging`/`lc-dev-staging-api`). The shared implementation is the dev-branch one that already ran green, generalised only where callers differ. Callers pass what actually varies: - `images` — the target/file/image_name triples - `tag_suffixes` — newline-separated tags applied in both registries - `checkout_ref` / `build_branch` — main-image-workflow builds `main`, not the dispatch ref `main-image-workflow` and `tag-images` resolve their tags from git history, so each grew a small `resolve-tag(s)` job whose output feeds the publish. That also removes a duplicated `git fetch --tags` that previously ran once per matrix leg. Two details worth noting: - The digest-count assertion now derives its expected value from the `arches` input rather than a hard-coded 2, so the architecture list has a single source of truth shared by the build matrix and the merge guard. - Nothing is interpolated into a `run:` block any more; `build_branch` and the build digest arrive through `env`, so a ref name cannot reach a shell. Net 135 lines lighter, and QEMU no longer appears anywhere in .github/workflows. Workflow names are unchanged, so retry-docker-builds.yml still matches all five. * 🔗 fix: Pin Release Builds to One Commit and Survive Full Re-runs Review findings on the reusable publish workflow. **P1 — every build leg could resolve `main` separately.** `main-image-workflow` passed the symbolic ref `main` as `checkout_ref`, so the four build jobs each resolved it at whatever moment they were scheduled. If `main` advanced in between, the amd64 and arm64 halves of a release — or the API and application images — could be built from different commits and published under the same release and `latest` tags. `resolve-tag` now exports the commit it resolved the tag from, and the publish pins to that SHA. The single-job workflow this replaced checked out once, so this was a regression introduced by the split. `docker-publish` likewise now falls back to `github.sha` rather than passing an empty `ref` to `actions/checkout`, so callers that omit `checkout_ref` also get an immutable commit instead of relying on checkout's empty-ref handling. **P2 — digest artifacts on a full re-run.** `upload-artifact@v4` will not upload over an existing artifact name, and a full re-run keeps the run id, so a retry would fail before the merge could run. The suggested fix was to qualify the artifact name with `run_attempt`, but `retry-docker-builds` picks its endpoint by conclusion: `rerun` only when a job was cancelled, and `rerun-failed-jobs` otherwise. Under the latter the merge re-runs alone and must still find digests uploaded by the *previous* attempt's build legs, which a run_attempt-qualified name would hide — precisely the shape of the #15444 failure, where the builds passed and only the merge failed. `overwrite: true` resolves the conflict while keeping names stable across attempts. **Unreachable error branch.** `LATEST_TAG=$(git tag ... | grep ... | head -1)` under `set -euo pipefail` exits on grep's non-match, so the "No stable v<semver> tag found" message could never print. Added `|| true`, matching what `tag-images` already does. Pre-existing, carried over verbatim in the split. |
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LibreChat
English · 中文
🚀 What's New in v0.8.8-rc1
- Agent run control: Interrupt or steer an Agent mid-run, queue follow-up messages, and reclaim, edit, or escalate pending steers.
- Human-in-the-loop Agents: Agents stream question progress, ask up to four related questions in one form, pause for input or tool approval, and resume.
- Unified Agent Builder: A redesigned Tools marketplace brings together Skills, MCP, Code Interpreter, orchestration, Programmatic Tool Calling, model-spec controls, and per-tool background and intent settings.
- Readable Agent activity: Generated activity-group headers, parent phase summaries, and live tool intent labels make long reasoning and tool runs easier to scan.
- Code Interpreter workflows: Code and shell tools can run in the background, sandbox images return as viewable artifacts, and highly experimental stateful sessions can reuse prewarmed conversation workspaces.
- Agent extensibility: Experimental Agent Plugins can bundle deployment Skills, MCP servers, and opt-in command hooks, while explicit subagents initialize only when selected.
- Memory, context, and identity: Agents can manage memory with optional per-agent isolation, expose support contacts safely, and show a more faithful Context Usage gauge.
- Sharing and files: Shared conversations show a badge and update at a stable URL, while signed-in viewers can continue them as personal copies.
- Artifact workflows: Open previews fullscreen, work with PowerPoint
.potxtemplates across upload, search, and code execution, upload shell scripts across common MIME variants, export Mermaid diagrams as SVG or PNG, and download original Office files from the artifact panel. - Models and reasoning: Added GPT-5.6 with Responses API reasoning controls, Claude Opus 5 and Sonnet 5, Gemini 3.7 and 3.6 Flash, and Gemini 3.5 Flash-Lite.
- Langfuse observability: Configure encrypted Langfuse connections in-app, let authorized admins open sampled sessions directly, optionally fan out traces by tenant, and suppress central export per run.
- Administration and security: Delegate config sections, encrypt registered secrets, enforce SSRF checks for speech, OCR, and web tools, and generate unique temporary credentials when secrets are blank.
- Messages and navigation: Right-aligned user turns, unified multi-part editing, full-message copy, a dock-style message rail, virtualized search, smooth streaming, and faster Agent startup.
- Streaming and tool reliability: Adaptive provider smoothing, Redis delta batching, dynamic MCP tool refresh, parsed MCP response media types, runtime OAuth recovery, and Agent stream circuit breakers improve long-running workflows.
- Deployment and reliability: Added configurable HTTP timeouts, Amazon DocumentDB 5.0+ support, low-noise Redis and browser observability, and a rolling-upgrade-safe generation protocol.
Read the full v0.8.8-rc1 changelog.
✨ Features
-
🖥️ UI & Experience inspired by ChatGPT with enhanced design and features
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🤖 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
- 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 - Agent Plugins: Experimentally bundle deployment Skills and MCP servers into startup-loaded packages
- 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 create React, HTML, and Mermaid content directly in chat
- Open previews fullscreen and export Mermaid diagrams as SVG or PNG
-
🎨 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
-
🧠 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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🎛️ 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.