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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/
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Danny Avila dc77b78d3e
🔇 refactor: Quiet Framework Logging in Unit Tests (#15363) 
* 🔇 refactor: Quiet Framework Logging in Unit Tests

Unit test output was overwhelmingly framework log lines rather than test
results. A `packages/api` run printed 9,076 lines for 434 suites; 1,596 of
them were the identical `at Console.log (winston/transports/console.js:87)`
frame that Jest staples onto every winston write.

Three causes:

- Each winston logger built its Console transport with a hard-coded
  `level: 'info'`. Winston resolves a transport's explicit level ahead of
  its parent's, so the logger's own `NODE_ENV`-derived `warn` never applied
  — in tests or in production. `CONSOLE_LOG_LEVEL` now drives it, defaulting
  to the previous `info` so deployments are unaffected. `meiliLogger` had
  the same hard-coded level and is routed through the same helper.
- `LOG_TO_FILE` defaults on, so every Jest worker opened DailyRotateFile
  transports. A run left `packages/api/logs/` holding a 107KB error log, a
  gzipped rotation, audit JSON, and — from fake-timer suites — files dated
  1969 and 2023.
- Client suites carried leftover debug `console.log` in shipped source
  (`Test mode. Skipping silent refresh.` alone accounted for 109 blocks)
  plus three test-harness defects whose React error dumps buried everything
  else: a markdown suite rendering Mermaid with no Router, a `~/Providers`
  mock missing `useSearchContext` (the component's own catch swallowed the
  throw, so the sources path was dead while the suite passed), and
  `getBoundingClientRect` stubs without `left`, which made a computed
  `right` NaN.

A shared `config/jest.setup.logging.cjs` sets the two env vars for both
backend workspaces. It sets env only and requires nothing: eagerly requiring
the logger froze `CREDS_KEY` into `encryptV3` before specs could set it and
broke five suites. `TEST_VERBOSE_LOGS=true` restores the logs for debugging.

Output per full run:

  packages/api           9,076 -> 770 lines   (winston lines 1,596 -> 0)
  packages/data-schemas  2,521 -> 946 lines   (winston lines   290 -> 0)
  client                10,384 -> 3,153 lines (console blocks  285 -> 74)

Test counts are unchanged: client 476 suites / 5,827 tests green, and the
Ariakit `act(...)` warnings the selector suites emitted are gone rather than
suppressed.

* 🔧 fix: Settle Shutdown Timers Before Counting Them

`destroy()` finishes cancelling its fenced retirement timers on the tick
after it resolves. The count only returned to the baseline because a console
write from the logger happened to yield first — silencing that logging left
four timers still pending at the assertion, deterministically failing the
suite in CI's sharded, coverage-enabled run.

Advance the fake clock by zero before counting, so the assertion proves the
timers were cancelled rather than that something incidental yielded.

* 🛡️ fix: Validate CONSOLE_LOG_LEVEL Instead of Trusting It

Winston resolves a level name against the logger's level map, so a name
outside it resolves to `undefined` and the transport drops every message.
Passing `CONSOLE_LOG_LEVEL` straight through meant a typo (`warning`) or a
stray space silently muted all console output — a misconfiguration that reads
as a dead deployment.

Validate against the level set, normalize case and whitespace, and fall back
to the default with a warning on the way past, since the logger cannot report
its own misconfiguration.

The level map itself was duplicated verbatim in both loggers; it now lives in
`utils` beside the validation that depends on it.

* 🎚️ fix: Let CONSOLE_LOG_LEVEL Outrank DEBUG_CONSOLE

`DEBUG_CONSOLE=true` forced the console transport to `debug`, so on those
deployments every non-`silent` value of `CONSOLE_LOG_LEVEL` was discarded —
`CONSOLE_LOG_LEVEL=error` still emitted debug and info, defeating the control
it advertises.

`DEBUG_CONSOLE` now only moves the *default* level and keeps choosing the debug
format, so an explicit level stays in charge of verbosity. With no explicit
level the resolved default is still `debug`, unchanged for existing setups.

Covers the wiring with a spec that re-imports the logger per environment,
rather than only testing the resolver in isolation.
2026-08-30 15:26:30 -04:00
.claude/skills
.devcontainer
.github
.husky
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api
client 🔇 refactor: Quiet Framework Logging in Unit Tests (#15363) 2026-08-30 15:26:30 -04:00
config 🔇 refactor: Quiet Framework Logging in Unit Tests (#15363) 2026-08-30 15:26:30 -04:00
e2e
helm
otel/langfuse-fanout
packages 🔇 refactor: Quiet Framework Logging in Unit Tests (#15363) 2026-08-30 15:26:30 -04:00
redis-config
scripts
search
skill
src/tests
utils
.dockerignore
.env.example 🔇 refactor: Quiet Framework Logging in Unit Tests (#15363) 2026-08-30 15:26:30 -04:00
.gitattributes
.gitignore
.nvmrc
.prettierrc
AGENTS.md
bun.lock
CLAUDE.md
CONTEXT.md
deploy-compose.langfuse-fanout.yml
deploy-compose.yml
docker-compose.langfuse-fanout.yml
docker-compose.override.yml.example
docker-compose.yml
Dockerfile
Dockerfile.multi
eslint.config.mjs
librechat.example.yaml
LICENSE
package-lock.json
package.json
rag.yml
README.md
README.zh.md
tool-intent-spec.md
turbo.json

README.md

LibreChat

English · 中文

Deploy on Railway Deploy on Zeabur Deploy on Sealos

Translation Progress

🚀 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 .potx templates 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

  • 🤖 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

  • 🔧 Code Interpreter API:

    • 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.md instruction 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

  • 🔍 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

  • 💾 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

  • 🎨 Customizable Interface:

    • Customizable Dropdown & Interface that adapts to both power users and newcomers

  • 🌊 Resumable Streams:

    • 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

  • 🔍 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

  • 🎛️ 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:

Other:

📝 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

Star History Chart

danny-avila%2FLibreChat | Trendshift ROSS Index - Fastest Growing Open-Source Startups in Q1 2024 | Runa Capital

✨ 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.

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