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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
374ed8df14
* 🛤️ fix: Render a Single-Agent Group as Sequential Content A multi-agent graph assigns a parallel group id to every starting node (`MultiAgentGraph.computeParallelCapability`), so an ordinary agent that merely has other agents loaded carries a `groupId` on its OWN run steps and on every content part built from them. `groupId` is not evidence of parallel execution. The client treated `groupId != null` as parallel content in four places, so an ordinary turn: - rendered inside a `SiblingHeader` lane box, restating the message's own sender and adding a redundant branch control - lost tool grouping, activity-label headers and client-synthesized phase folds, because lanes render raw parts - widened the message row for columns that never arrive - rendered the one group repeatedly when phase markers split it, since each segment runs its own `ParallelContentRenderer` `~/utils/lanes.ts` adds `hasParallelLanes` / `MIN_PARALLEL_LANES`: a group backed by one agent is not a comparison, so it renders exactly like content with no group id at all. `groupParallelContent` demotes such a group into the sequential flow, and `ContentParts`, `useContentMetadata`, `MultiMessage` and `groupActivityPhases`'s `foldable` all ask the shared predicate. Fixing it client-side repairs persisted history too. Two adjacent bugs the demotion exposed in `ParallelContentRenderer`: a sequential part landing between the lanes' first and last index was dropped from the message entirely, and a section holding only placeholders rendered every part twice. Five existing fixtures asserted the parallel path with a single agent (some with a string `groupId` that never matched `groupId?: number`); they now carry a second agent so they keep testing lanes. * 🧹 refactor: Narrow the Lane Part Instead of Asserting Its Shape `TMessageContentParts` already carries `agentId`, so the assertion was only standing in for the undefined check the optional chain now does. * 🧵 fix: Keep Lane Identity and Transcript Order Across Sections Two P2s from review, both about content that a lane group does not own. **Lane cardinality belongs to the message, not the slice.** A completed server phase marker partitions the transcript, and `renderSegment` hands each slice to its own `ContentPartsBody`. A slice can hold one agent of a genuine two-agent group while its sibling slice holds the other, so counting agents locally demoted both and dropped the `SiblingHeader` that told the reader which agent produced which answer. `parallelLaneGroups` resolves the group ids once over the whole message; every slice and `groupParallelContent` now ask that verdict instead of recounting. **Sequential content between two sections rendered after both.** The before/after split was global: with group 1, an ordinary part, then group 2, the part fell into `after` and the transcript read group 1, group 2, part. Sequential parts are now laid out around EACH section, so the part renders in place. A part landing inside a section's own index range still falls to the next block — it has no column and no slot inside one, which is the tradeoff the earlier `>= minParallelIdx` bound already made to stop dropping it entirely. * 🔢 fix: Count Only Attributed Lanes, and Scan for Them Once Round 2 of review, two findings. **An unattributed part is not a second agent.** `agentId` and `groupId` are independently optional on a run step — `getStepMetadata` builds both from whatever the step carries and the writer sets each only when present — so a group can hold a part the server never attributed. It shares the `unknown` sentinel column, and counting that sentinel let one agent plus one metadata-less part pass the two-lane threshold, leaving exactly the single-agent turn this branch exists to demote in the parallel UI. `attributedLaneCount` discounts the sentinel, `groupParallelContent` counts claimed columns the same way, and the sentinel is now one exported constant instead of a literal on each side. **One lane scan per render, not two.** `groupActivityPhases` was scanning the whole message for lanes to decide `foldable` while `ContentParts` was scanning it again for `parallelLaneGroups`, on a path that re-runs for every streamed delta. The scan is now computed once and handed down; a set built from the same content answers `foldable` by its size. * 🧮 fix: Ignore Handoff Markers in Lanes, and Scan a Message Once Round 3 of review, two findings. **A handoff marker is not a second lane.** `useStepHandler` stamps an `AGENT_UPDATE` part with `{ agentId: <destination>, groupId: 1 }` even though the destination's own run steps carry no group id, so a single-lane graph that later hands off held two agent ids in one group: the run's output became one column and the marker became the other, at the exact point the handoff happened. `isLaneMarkerPart` keeps a marker from claiming a lane, and `groupParallelContent` mirrors it — a column claims its lane only when it holds output, except a placeholder column, which claims with no parts at all so a dual run shows both agents from the first render. **One scan per message, not three.** `MultiMessage`, `useContentMetadata` and `ContentParts` each traverse the same array in a single render pass, allocating a map and a set per call, and `content` is rebuilt on every streamed delta. `laneAgentsByGroup` now memoizes on the content array itself: the three callers collapse to one traversal, and the cache is exactly as fresh as the render, since a delta that kept the array identity would not re-render either. Entries die with the array that keys them. |
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LibreChat
English · 中文
🚀 What's New in v0.8.8-rc2
- Agent run control: Interrupt an Agent before visible answer text, steer runs with files and quoted excerpts, durably queue follow-ups, and recover saved partial work with Keep going or Answer now.
- Agent activity: Optional generated labels group reasoning and tool work, fold completed groups into live phase cards, keep generated files visible, summarize multi-step phases, and show the current reasoning direction.
- Human-in-the-loop Agents: Stream up to four related questions, pause for input or tool approval, and resume durably.
- Unified Agent Builder: Configure Skills, MCP, Code Interpreter, orchestration, Programmatic Tool Calling, model-spec controls, and per-tool background and intent settings in one Tools marketplace; Skills can be enabled for standalone runtime authoring without exposing the existing catalog.
- Durable Agent automation: Authenticated Agent Events support bound child actors, expected-action receipts, per-actor mailboxes, event batching, durable human pauses, and automatic detached Actions across built-in stream stores.
- Deeper Subagent history: Browse branch-aware child turns with bounded reasoning and stable live event views, load earlier activity, inspect event details, continue completed child chats, and automatically wake saved parent Agents when detached work settles.
- Background tools: Eligible Code Interpreter, MCP, Plugin, and Action tools can run while an Agent keeps working, with automatic delivery for supported completions and polling controls when needed.
- Code Interpreter workflows: Sandbox images return as viewable artifacts; highly experimental stateful sessions add scoped managed, attached, or personal environments, per-message file downloads, and guarded file-write and command permissions.
- Agent extensibility: Experimental Agent Plugins bundle deployment Skills, MCP servers, and opt-in command hooks; saved Agent teams run as isolated Subagent graphs.
- Scheduled Chats (experimental): Run saved Agents with presets or custom cron, selectable time zones, multi-day weekly cadence, and optional Chat Project destinations.
- Memory and context: Agents can use optionally isolated memory, preserve adaptive context fading across turns, and show categorized current-window usage, tokens, and optional cost.
- Editable long pastes: Long pasted text becomes an editable attachment that can be moved back into the composer; attachment-only turns and reliable Upload as Text downloads are also supported.
- Projects, settings, and navigation: Search conversation titles and message contents, manage project chats, use searchable settings and shortcuts, pin chats, choose clock/week conventions, and navigate faster on mobile.
- Sharing and artifacts: Stable shared links support personal copies; fullscreen previews, Mermaid export, PowerPoint templates, shell scripts, and original Office downloads expand file workflows.
- Web search: Keenable adds keyless search and page fetch, while SearXNG and Tavily gain richer controls and all web-tool egress uses stronger SSRF protection.
- Security and authentication: Default HTTP security headers, opt-in nonce CSP, authenticated local images, per-user Code Interpreter JWTs, stable SAML identity binding, live-session OpenID token refresh, and retired JWT-secret rejection harden deployments.
- Models and reasoning: Added GPT-5.6 with Responses reasoning controls, Claude Fable 5.1, Opus 5, and Sonnet 5, plus Gemini 3.8/3.7/3.6 Flash and Gemini 3.5 Flash-Lite.
- Langfuse observability: Configure encrypted in-app connections, tenant fanout, authenticated gateways, export-decision telemetry, and authorized session links in chats and shared views.
- Administration: Source-aware content filters can audit or block model-bound data, while tenant Insights, delegated configuration, encrypted secrets, and expiring violation scores improve operations.
- Streaming and reliability: Adaptive smoothing, Redis delta batching and failover recovery, automatic generation protocol v2, live MCP catalog refresh, Agent circuit breakers, and DocumentDB support improve long runs and scaled deployments.
Read the full v0.8.8-rc2 changelog.
✨ 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 - 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 🗃️
-
🌎 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
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🔍 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
-
⚙️ 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.