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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
530a935a74
* 🎨 feat: Color the Context Gauge by Category and Collapse its Breakdown The context window bar becomes a stacked meter — one hue per category — and the breakdown collapses behind a disclosure so the gauge alone is the default view. The collapse choice persists per user. Adds a categorical series scale (`rgb-series-1`…`rgb-series-7`) to the versioned theme registry, so themes and `REACT_APP_THEME_SERIES_*` can retint it. Hues are anchored on LibreChat's own brand tokens; every step was computed rather than picked, by enumerating slot orderings and snapping each step until all gates passed in both modes: worst adjacent CVD ΔE 12.4 light / 13.0 dark (target 8) worst adjacent normal-vision 19.0 light / 19.0 dark (floor 15) contrast all 14 steps ≥ 3:1 on both the popover surface and the meter track Slot order is the colour-vision-deficiency safety mechanism, not cosmetics. Reserved status colors are never reused for series identity, and the circular composer gauge is deliberately untouched — it answers "how close am I to the limit", which stays a status question. - `SegmentedMeter` + `MeterSwatch` land beside `Progress` in `@librechat/client`, owning the 2px surface gaps, rounded ends, the min-width floor, and the hatch. The category-to-slot mapping stays feature-local: the palette is theme data, the mapping is not. - Every present category gets a 2px floor so a 251-token row cannot render as 0.09px; the shortfall comes out of free space, never another category. - Deferred tools keep their family's hue and add a 135° hatch, so a hue never means two things. Segments are reordered to put each deferred pair beside its parent, which is also the adjacency the palette was validated on. - Messages is drawn as a translucent fill with a solid edge: it is the only category the user grows, and the form difference doubles as secondary encoding. - A row carries a swatch if and only if it is a segment. The estimate path knows the total but not the composition, so it keeps a single unsegmented fill. - Usage totals gain a "Totals" heading, and row text lifts to primary ink on hover/focus. - The popover widens 256px → 288px to absorb the chevron and the legend swatches. Guardrails: the series scale is held to the 3:1 mark floor on both surfaces, the app CSS defaults are held in step with the runtime themes, and each slot is asserted to resolve to a Tailwind utility backed by its CSS variable. * 🐛 fix: Address Codex Review on the Segmented Context Gauge Three P2 findings, all confirmed. **Gaps inflated the fill.** Segment widths were percentages of the whole track while `gap-[2px]` was added on top, so the gaps ate into the free-space remainder instead of living inside the filled region. Measured on the real component: a window at 47.2% painted 55.6% full, and the bar read full at ~94%. Each segment now surrenders its share of the gap budget, so fills plus gaps span exactly the used fraction. Same case now paints 50.2%. The residual 3.0pp is the `SEGMENT_MIN` floor doing its job — five sub-pixel categories rounded up to 2px each. That overshoot is deliberate and bounded, it comes out of free space rather than a neighbouring category, and the doc comment now states the magnitude instead of leaving it implicit. **No reference-theme test.** The suite only exercised the bundled token tables, so it could not detect the shared component becoming coupled to LibreChat's values. Adds a deliberately different reference `ThemeDefinition` and asserts the registry accepts it, the values reach the applied CSS variables, and every rendered mark takes its colour from those variables — no literal colours in the tree. `SegmentedMeter.tsx` also joins the shared-primitive colour guardrail. **Series tokens missing from the public maps.** `IThemeVariables` and `IThemeColors` are exported for downstream consumers to type their CSS-variable and Tailwind maps, and would have rejected the new keys. Adds the series entries to both, plus a compile-time guard in the registry so a slot added to one map and missed in another fails the build. The guard deliberately lives in `registry.ts`, not the spec: `tsconfig.json` excludes `*.spec.ts`, so an assertion there is never checked by the build — verified by removing a key from each map in turn and confirming the error. * ✅ fix: Expand the Breakdown in the Context Gauge e2e Specs `e2e/specs/mock/usage.spec.ts` asserts on rows that now sit behind the disclosure, so four tests failed on the collapsed default. My miss — I updated the component spec and never grepped for e2e coverage. `openBreakdown` now expands the detail after opening, so every caller that reads a row keeps working; the helper is idempotent, since a reload restores an already-expanded preference. The one inline `gauge.click()` that duplicated the helper now uses it. Adds the case the regression should have been caught by, and which only e2e can reach: the popover opens to the gauge alone with no detail mounted, expanding reveals the labelled Totals section, and the choice survives a real reload through localStorage without a second click. `e2e/specs/real/usage.spec.ts` reads the totals the same way. It also hovered rather than clicked, which never opened the popover at all — hover surfaces only the compact snapshot tooltip, as the mock spec asserts. |
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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
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🔦 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.