An open-source, production-ready AI Agent platform for building, running, and sharing real tool-using agents
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Login |
Chat |
Streaming |
Skills |
MCP Config |
Share |
Roles |
Settings |
Feedback |
Mobile |
Tablet |
Shared Session |
LambChat is built for teams who want more than a chatbot UI. It gives you a complete AI Agent system with model management, MCP connectivity, skills, storage, sharing, approvals, and deployment-ready backend/frontend infrastructure in one project.
- Built for real execution — agents can reason, call tools, use sub-agents, stream progress, and work with human approval when needed.
- Ready for operations — includes auth, RBAC, encrypted secrets, tracing, health checks, sandbox integration, and distributed config sync.
- Designed for extensibility — custom agents, MCP tools, skills, model providers, channels, persona presets, and storage backends can all be extended cleanly.
- Product-grade UX — polished chat UI, file previews, project folders, sharing, feedback, responsive layouts, and multilingual support.
| # | Case | Description | Demo |
|---|---|---|---|
| 1 | Supply Chain PDF Report | Generates a polished PDF efficiency report with charts, benchmark comparisons, and delivery, inventory, fulfillment, and logistics analysis from a single prompt. | View Session |
| 2 | Godfather Fan Website | Builds a responsive English promo site for The Godfather trilogy with a cinematic visual direction, marquee hero section, generated images, and multi-device polish. | View Session |
| 3 | Story Breakdown from Image | Understands visual input, identifies the stories shown in an image, and produces detailed plot-by-plot explanations with multimodal reasoning. | View Session |
| 4 | EV Market Trend Analysis | Turns recent 2025-2026 electric vehicle data into a structured market analysis covering growth, regional performance, and key industry takeaways. | View Session |
🤖 Agent Runtime
- deepagents Architecture — Compiled graph runtime with fine-grained state management
- Multi-Agent Types — Core, fast, and search agents
- Plugin System —
@register_agent("id")decorator for custom agents - Streaming Output — Native SSE support
- Sub-agents — Multi-level delegation
- Thinking Mode — Extended thinking for Anthropic models
- Human-in-the-Loop — Approval system with countdown timer, auto-extension, and urgent-state styling
- Persona Presets — Reusable persona configuration with permissions and runtime binding
🧠 Model, Memory, and Skills
- Multi-Provider Models — OpenAI, Anthropic, Google Gemini, and Kimi
- Full CRUD — Create, edit, delete, reorder, and batch import models via UI
- Channel Routing — Route the same model through different channels with
model_id - Role-based Access —
MODEL_ADMINpermission and per-role model visibility - Cross-session Memory — Native MongoDB-backed memory system
- Dual Skills Storage — File system plus MongoDB backup
- GitHub Sync — Import custom skills from GitHub
- Skill Marketplace — Browse, install, publish, and manage skills in bulk
🔌 Tools, MCP, and Execution
- System + User MCP — Global and per-user MCP configuration
- Encrypted Storage — API keys encrypted at rest
- Dynamic Tool Caching — Cache MCP tools with manual refresh
- Multiple Transports — SSE and HTTP
- Permission Control — Transport-level access policies
- Sandbox Integration — Daytona and E2B execution support
- Built-in Tools — File reveal, project reveal, upload URL, env vars, audio transcription, persona preset tools, and more
📁 Product Features
- File Library — Browse revealed files with code preview, favorites, and project-based filtering
- Rich Previews — PDF, Word, Excel, PPT, Markdown, Mermaid, Excalidraw, images, and video playback
- Project Folders — Organize sessions into projects with drag-and-drop
- Session Sharing — Generate public share links for conversations
- Feedback — Thumbs rating, text comments, session linking, and run-level stats
- Notifications — In-app notification storage and delivery hooks
🔐 Infra, Realtime, and Frontend
- Realtime — Redis + MongoDB dual-write, WebSocket, auto-reconnect, and shared-session updates
- Security — JWT, RBAC, bcrypt, OAuth (Google/GitHub/Apple), email verification, CAPTCHA, and sandbox controls
- Observability — LangSmith tracing, structured logging, health checks, and distributed memory diagnostics
- Channels — Native Feishu integration plus an extensible multi-channel architecture
- Frontend Stack — React 19, Vite 6, TailwindCSS 3.4, dark/light theme, rich content rendering, and responsive multi-device layouts
- i18n — English, Chinese, Japanese, Korean, and Russian
Multiple setting categories can be configured through the 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 and security policies |
| Sandbox | Code sandbox settings (Daytona / E2B) |
| Skills | Skill system config |
| Tools | Tool system settings |
| Tracing | LangSmith and tracing |
| User | User management, registration, default role |
| Memory | Memory system (native) |
- Python 3.12+ · Node.js 18+ · pnpm · MongoDB · Redis
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-pnpm # Install pnpm if not present
make install && make dev📝 Required Configuration
Edit the .env file with the following recommended settings:
# Recommended: Set a stable JWT secret (auto-generated on each restart if unset, invalidating existing sessions)
JWT_SECRET_KEY=your-stable-secret-key
# Recommended: Set MCP encryption salt (auto-generated on each restart if unset, invalidating saved MCP configs)
MCP_ENCRYPTION_SALT=your-stable-encryption-salt
# Optional: Configure MongoDB connection
MONGODB_URL=mongodb://localhost:27017
MONGODB_DB=agent_state
MONGODB_USERNAME=admin
MONGODB_PASSWORD=your-mongo-password
# Optional: Configure Redis connection
REDIS_URL=redis://localhost:6379/0
REDIS_PASSWORD=your-redis-password::: tip LLM models are configured through the Model Config UI after deployment — no environment variables needed. :::
make format # Format (ruff format)
make lint # Lint (ruff check)
make typecheck # Type check (mypy)
make check-all # Run all checks (lint + typecheck + test)src/
├── agents/ # Agent implementations and runtime graphs
├── api/ # FastAPI routes, admin endpoints, middleware
├── infra/ # Core services: auth, llm, mcp, tools, storage, tasks, sharing, memory
├── kernel/ # Schemas, config, constants, and shared types
└── skills/ # Built-in skills
frontend/
├── src/components/ # UI components, panels, and landing sections
├── src/hooks/ # Frontend hooks
├── src/i18n/ # Locale files
└── src/styles/ # Shared styles and design tokens
tests/ # Backend and integration tests
deploy/ # Docker deployment assets
MIT — Project name "LambChat" and its logo may not be changed or removed.