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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
c00acb36a0
* 🌌 feat: Add GPT-6 Astra Support Registers OpenAI's GPT-6 Astra (`gpt-6-astra`) as a first-class model on the canonical OpenAI endpoint. Every model-specific behavior Astra requires — Responses routing for tool calls, stripping the sampling and logprob parameters it rejects, and substituting the `none`/`minimal` reasoning efforts it does not accept — lands in `@librechat/agents` (danny-avila/agents#506) rather than here. None of it is expressible at configuration time: tools bind after `getOpenAIConfig` runs, and LangChain's request builders emit `temperature`/`top_p` from instance fields regardless of what this layer sets. Keeping it in the SDK also means the routing gate can be the documented rule (tools present) instead of the over-approximation the config-time GPT-5.6 path is forced into. What is left here is registration: - 1,050,000-token context window and 128K max output - Model dropdown (config.ts) and the `OPENAI_MODELS` example - Standard pricing: $10/M input, $1/M cached input, $12.50/M cache writes, $50/M output - The >272K long-context tier, which LibreChat already supports through `premiumTokenValues`/`premiumCacheTokenValues`: 2x input and cache rates and 1.5x output for the full request Batch/Flex (50%) and Fast mode (2x) have no representation in the pricing model today and are not introduced here; they apply per-request rather than per-model, so they need a request-shape signal this layer does not yet carry. Tests pin the pricing against the documented multipliers rather than restating the literals — cache writes as 1.25x input, and the premium tier as 2x/1.5x of standard — plus threshold behavior either side of 272K, and that `gpt-6-astra` resolves to its own key for snapshots and provider-prefixed ids instead of collapsing onto a shorter `gpt-6` match. Resolves #15560 Ref: https://developers.openai.com/api/docs/models/gpt-6-astra Ref: https://developers.openai.com/api/docs/guides/latest-model * 🧪 test: Guard the GPT-6 Astra Max Output Entry [Copilot] The Astra tests asserted the context window but not the 128K max output added alongside it in `anthropicMaxOutputs`' OpenAI counterpart, so that entry could regress silently. The gpt-5.6 tier test above covers both, and the delete-the-fix check showed the gap: removing the source entries failed only the context assertions. Assert `getModelMaxOutputTokens` alongside `getModelMaxTokens`, and fold the snapshot/prefix cases into one loop so both dimensions are covered for every id shape rather than only the bare one. Verified by deleting just the max-output entry: both Astra tests now fail where previously neither did. * 🪧 feat: Declare the First-Party OpenAI Endpoint to the Agents SDK The agents SDK gates GPT-6 Astra's request constraints — Responses-only tool calls, rejected sampling parameters, unsupported reasoning efforts — on knowing it is talking to the first-party OpenAI surface, and defaults them off. It takes that as a declaration rather than inferring it, because a base URL cannot answer the question: only this layer knows whether a URL is a faithful first-party route, a gateway, or a proxy with its own semantics. That decision already exists here, in `isCanonicalOpenAIBaseURL`, used by the GPT-5.6 Responses default. Declaring it from the same checks keeps it in one place instead of duplicating it downstream where the two could drift — and if the endpoint logic ever moves, it moves once. `firstPartyEndpoint` is declared on `OAIClientOptions` alongside the other agents SDK fields this layer already sets (`promptCache`, `_lc_stream_delay`, `includeReasoningContent`), so it typechecks against the current published SDK and is consumed once the SDK release lands. Two backward-compatibility expectations gain the field. That is the intended signal: they assert the full emitted config precisely so a new field cannot slip through unnoticed. * 🗂 fix: Keep GPT-6 Astra Out of the Assistants Catalogs [Codex P2] `sharedOpenAIModels` feeds `defaultModels[assistants]` and `[azureAssistants]` as well as the OpenAI and agents catalogs. Astra serves tool calls only from the Responses API, and the Assistants endpoints do not route through `getOpenAILLMConfig`, so listing it there offered a configuration the provider rejects. Astra now sits in its own `responsesOnlyOpenAIModels` list, spread into the OpenAI and agents catalogs only. Agents keeps it deliberately: that path does go through `getOpenAILLMConfig`. * 🎚 fix: Route GPT-6 Astra to the Responses API at Config Time [Codex P1] `max_tokens` was shaped into `max_completion_tokens` here, from `llmConfig.useResponsesApi`, while the agents SDK switched Astra to the Responses API later at invocation time — so the request reached an endpoint expecting `max_output_tokens` and was rejected. Deciding the API here fixes that, and generalizes: any field whose shape depends on the endpoint has the same problem, so the choice has to precede the shaping. It also lands before Azure replaces `llmConfig.model` with a deployment name, which is the only point that still knows the real model id. Unlike the GPT-5.6 rule above, this does not depend on reasoning parameters. Astra serves tool calls only from Responses, and OpenAI recommends Responses for it generally, so a static decision loses nothing — which was the reason the SDK was deciding it dynamically. The existing guards carry over: OpenRouter, custom gateways, and an explicit `dropParams` opt-out keep their configured path. The agents SDK is still required, for the request shaping Astra needs on either API (danny-avila/agents#506); it no longer decides routing. * 🏷 fix: Record the Served Model Before Azure Overwrites It [Codex P1] `llmConfig.model` is unconditionally replaced with the Azure deployment name, so the agents SDK received an alias and could not tell which model it was talking to — a deployment not literally named `gpt-6-astra` got none of the request shaping Astra requires. Records the real id in `servedModel` immediately before the overwrite, which is the last point that still knows it. The SDK prefers it over `model` when deciding which model-specific constraints apply (danny-avila/agents#506). Set for every first-party Azure request rather than only Astra: "what this deployment serves" is a fact this layer knows and the SDK decides what to do with, and keeping model-specific knowledge out of here is the point of the split. The backward-compatibility expectation gains the field, which is that test doing its job. * 🎛 fix: Do Not Let a reasoning_effort Drop Disable Astra Routing [Codex P1] The Astra routing reused the GPT-5.6 opt-out wholesale, which treats `dropParams: ['reasoning_effort']` as opting out of the Responses API. That holds for the 5.6 default, which routes *because* of reasoning — removing the effort removes its reason to route. Astra's routing is not reasoning-driven, so a rule clearing an unsupported stored effort silently put it back on Chat Completions, where its tool calls fail. Astra now honors only an explicit `useResponsesApi` drop. Reusing the guard without re-deriving whether each clause applied was the error. * ✂️ fix: Scope GPT-6 Astra to the First-Party OpenAI Endpoint [Codex P1 + P2] Two findings, both Azure, resolved by removing the Azure support rather than extending it. Azure's first-party hosts do not satisfy `isCanonicalOpenAIBaseURL`, so a configured `*.openai.azure.com` was neither routed to Responses nor declared first-party; and moving Astra out of `sharedOpenAIModels` also removed it from the Azure chat fallback, since `getOpenAIModels({ azure: true })` resolves through `defaultModels[azureAssistants]`. Both are moot once the scope is right: OpenAI does not document Astra as available on Azure OpenAI. Its model page lists the API and OpenAI's own subscription plans, with no third-party cloud surface. The Azure handling was support for a deployment the model is not documented to reach, and it produced most of the review findings on this branch and its agents SDK counterpart. Routing and the first-party declaration are now scoped to `EModelEndpoint.openAI`, and the Azure-only `servedModel` recording is gone along with its SDK counterpart. Astra staying out of the Azure catalogs is now the intended outcome rather than a regression. * 🚫 fix: Keep Astra Out of the Initial Azure Catalog [Codex P1] `initialModelsConfig` feeds the OpenAI catalog to Azure OpenAI as well, so scoping Astra to the first-party OpenAI endpoint left it advertised on Azure anyway — and being first in the list, it could become the default selection where no prior choice exists. The server's Azure fallback already excludes it, so the client would offer a model the server then rejects. The Azure initial catalog now uses the OpenAI list minus the Responses-only models, following the same scoping decision the routing guard makes. The initial Assistants catalog was already safe: `fitlerAssistantModels` requires `gpt-4` or `gpt-3.5`, which Astra does not match. Pinned that in a test rather than leaving it to a regex written for another purpose. * ⬆️ chore: Bump `@librechat/agents` to 3.7.20 for GPT-6 Astra Constraints |
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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
-
💾 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
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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
-
👥 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.