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Yanyutin753/LambChat

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🐑 LambChat

A production-ready AI Agent system built with FastAPI + deepagents

Python React FastAPI deepagents MongoDB Redis License

English · 简体中文 · Contributing


📸 Screenshots

Login
Login
Chat
Chat
Streaming
Streaming
Skills
Skills
MCP
MCP Config
Share
Share
Roles
Roles
Settings
Settings
Feedback
Feedback
Mobile
Mobile
Tablet
Tablet
Shared
Shared Session

🎬 Use Cases

# Case Description Demo
1 PDF Report Generation Agent reads skill instructions → installs dependencies → generates 8 charts → writes LaTeX source → compiles into a 14-page PDF business report. Zero human intervention. View Session
2 PPT Presentation Agent independently creates a 14-page business PPT with data tables, charts, analysis cards, and action roadmap based on supply chain data. View Session
3 Static Blog Site Builds a complete blog (5 pages + 8 sample articles) with tag filtering, pagination, responsive layout, and interactive effects. 10 subtasks all completed automatically. View Session

🏗️ Architecture

Architecture

✨ Features

🤖 Agent System
  • deepagents Architecture — Compiled graph with fine-grained state management
  • Multi-Agent Types — Core / Fast / Search agents
  • Plugin System@register_agent("id") decorator for custom agents
  • Streaming Output — Native SSE support
  • Sub-agents — Multi-level nesting
  • Thinking Mode — Extended thinking for Anthropic models
  • Human-in-the-Loop — Approval system with countdown timer, auto-extension, and urgent state styling
🧠 Model Management
  • Multi-Provider — OpenAI, Anthropic, Google Gemini, Kimi (Moonshot)
  • Full CRUD — Create, edit, delete, batch import models via UI with per-model config (api_key, api_base, temperature, max_tokens)
  • Channel Routing — Same model from multiple channels via model_id routing
  • Role-based AccessMODEL_ADMIN permission, per-role model visibility control
  • Per-user Preferences — Default model selection persists across sessions
  • Live Config Sync — Distributed Redis pub/sub for real-time model updates
  • Drag-and-Drop — Reorder models in the selector
🔌 MCP Integration
  • System + User Level — Global and per-user MCP configs
  • Encrypted Storage — API keys encrypted at rest
  • Dynamic Caching — Tool caching with manual refresh
  • Multiple Transports — SSE / HTTP
  • Permission Control — Transport-level access control
  • Import/Export — Bulk MCP configuration management
🛠️ Skills System
  • Dual Storage — File system + MongoDB backup
  • Access Control — User-level permissions
  • GitHub Sync — Import skills from GitHub repos
  • Skill Creator — Built-in creation toolkit with evaluation tools
  • Marketplace — Browse, install, and publish skills
  • Batch Operations — Enable/disable/delete skills in bulk
💬 Feedback · 📁 Files · 🔄 Realtime · 🔐 Auth · ⚙️ Tasks · 📊 Observability
  • Feedback — Thumbs rating, text comments, session-linked, run-level stats
  • File Library — Browse revealed files, code preview, organized file management with grid/list views, favorites, and project-based filtering
  • Documents — PDF / Word / Excel / PPT / Markdown / Mermaid / Excalidraw preview + image viewer
  • Cloud Storage — S3 / OSS / MinIO / COS integration, drag & drop upload, presigned URLs
  • Project Folders — Organize sessions into projects with drag-and-drop
  • Session Sharing — Generate public share links for conversations
  • Realtime — Dual-write (Redis + MongoDB), WebSocket, auto-reconnect, session sharing
  • Security — JWT, RBAC (35+ permissions across 15 groups), bcrypt, OAuth (Google/GitHub/Apple), email verification, CAPTCHA, sandbox
  • Tasks — Concurrency control, cancellation, heartbeat, pub/sub notifications
  • Observability — LangSmith tracing, structured logging, health checks
  • Channels — Feishu (Lark) native integration with model selector, project binding, and time-based session titles; extensible multi-channel system
🎨 Frontend
  • React 19 + Vite 6 + TailwindCSS 3.4
  • ChatGPT-style interface with dark/light theme
  • Glass Design System — Consistent glass-shell/glass-card styling across all panels
  • i18n — English, Chinese, Japanese, Korean, Russian
  • Responsive — Mobile, tablet, desktop with unified component rendering
  • Rich Content — KaTeX math, syntax highlighting, Mermaid diagrams, table copy/CSV export, image preview lightbox, line-highlighted code viewer
  • Tool Panels — Slide-up tool result panels with center/sidebar view modes and block preview portal
  • Skeleton Loading — Skeleton components for better perceived performance
  • Landing Page — Premium blog-style landing with scroll-reveal animations and section tracking

⚙️ Configuration

14+ setting categories configurable via UI or environment variables:

Category Description
Frontend Default agent, welcome suggestions, UI preferences
Agent Debug mode, logging level
Model Multi-provider model management, per-model config, channel routing
Session Session management, message history, SSE cache
Database MongoDB connection, optional PostgreSQL
Storage Persistent storage, S3/OSS/MinIO/COS
Security Encryption & security policies
Sandbox Code sandbox settings (Daytona / E2B)
Skills Skill system config
Tools Tool system settings
Tracing LangSmith & tracing
User User management, registration, default role
Memory Memory system (native / hindsight / memu)

🚀 Quick Start

Prerequisites

  • Python 3.12+ · Node.js 18+ · MongoDB · Redis

Setup

git clone https://github.com/Yanyutin753/LambChat.git
cd LambChat

# Docker (recommended)
cd deploy && cp .env.example .env   # Edit with your config
docker compose up -d

# Or local development
cp .env.example .env   # Edit with your config
make install && make dev

→ Open http://localhost:8000

Code Quality

ruff format src/    # Format
ruff check src/     # Lint
mypy src/           # Type check

Project Structure

src/
├── agents/          # Agent implementations (core, fast, search)
├── api/             # FastAPI routes & middleware
│   ├── routes/      # 27 route modules (auth, chat, mcp, skills, model, etc.)
│   ├── admin/       # Admin API endpoints
│   └── agent/       # Agent configuration & model management
├── infra/           # Infrastructure services
│   ├── agent/       # Agent config & events
│   ├── auth/        # JWT, OAuth, RBAC, CAPTCHA
│   ├── backend/     # LLM backend abstraction
│   ├── channel/     # Multi-channel (Feishu, etc.)
│   ├── email/       # Email service (Resend)
│   ├── envvar/      # User environment variables
│   ├── feedback/    # Feedback system
│   ├── folder/      # Project folder management
│   ├── llm/         # LLM integration (OpenAI, Anthropic, Gemini, Kimi)
│   ├── memory/      # Cross-session memory (native, hindsight, memu)
│   ├── model/       # Model management with encryption & pub/sub sync
│   ├── mcp/         # MCP protocol
│   ├── role/        # RBAC roles
│   ├── sandbox/     # Sandbox execution (Daytona / E2B)
│   ├── session/     # Session management (dual-write)
│   ├── settings/    # Settings storage + pub/sub sync
│   ├── share/       # Share links
│   ├── skill/       # Skills system
│   ├── storage/     # MongoDB, Redis, PostgreSQL, S3
│   ├── task/        # Task management
│   ├── tool/        # Tool registry & MCP client
│   ├── tracing/     # LangSmith tracing
│   ├── upload/      # File upload handling
│   ├── revealed_file/  # File library
│   └── websocket/   # WebSocket & rate limiter
├── kernel/          # Core schemas, config, types
└── skills/          # Built-in skills

⭐ Star History

Star History Chart

📄 License

MIT — Project name "LambChat" and its logo may not be changed or removed.


Made with ❤️ by Clivia

📧 3254822118@qq.com · GitHub

About

LambChat — A multi-tenant AI Agent Harness Platform. Skills + MCP dual-engine powered, built for scale and isolation. SSE real-time streaming, multi-modal document intelligence, JWT/RBAC enterprise security, and GitHub-connected Skill marketplace.

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