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TGO Introduction
TGO is an open-source AI agent customer service platform dedicated to helping enterprises “Build AI Agent Teams for Customer Service”. It integrates multi-channel access, agent orchestration, knowledge base management (RAG), and human agent collaboration.
🚀 Quick Start
One-Click Deployment
Run the following command on your server to check requirements, clone the repository, and start the services:
REF=latest curl -fsSL https://raw.githubusercontent.com/tgoai/tgo/main/bootstrap.sh | bash
For users in China (using Gitee and Aliyun mirrors):
REF=latest curl -fsSL https://gitee.com/tgoai/tgo/raw/main/bootstrap_cn.sh | bash
Local Development
Start the full development environment with Docker Compose:
cp .env.dev.example .env.dev
make dev
Useful variants:
make dev PROFILES=monitoring
make dev DISABLE=tgo-rag-beat,tgo-workflow-worker
For more details, please visit the Documentation.
✨ Features
🤖 AI Agent Orchestration
- Multi-Agent Support - Configure multiple AI agents for different business scenarios
- Multi-Model Integration - Connect with various LLM providers (OpenAI, Anthropic, etc.)
- Streaming Response - Real-time AI responses via SSE for smooth conversation experience
- Context Memory - Maintain conversation history for coherent dialogue
📚 Knowledge Base (RAG)
- Document Knowledge Base - Upload documents to enhance AI response accuracy
- Q&A Knowledge Base - Create question-answer pairs for quick knowledge expansion
- Website Knowledge Base - Crawl website content to keep information up-to-date
- Smart Retrieval - Vector-based semantic search for precise answers
- Tool Store - Rich library of MCP tools, enable on demand
- Custom Tools - Project-level tool configuration and management
- OpenAPI Schema - Auto-parse schemas to generate interactive forms
🌐 Multi-Channel Access
- Web Widget - Embeddable chat widget for websites
- WeChat Integration - Official Account and Mini Program support
- Unified Management - Manage all channels from a single dashboard
💬 Real-time Communication
- WuKongIM Integration - Stable and reliable instant messaging
- WebSocket Connection - Efficient bidirectional communication
- Message Sync - Read/unread status, delivery confirmation
- Rich Media - Support for text, images, files and more
👥 Human-AI Collaboration
- Smart Handoff - Seamlessly transfer to human agents when needed
- Visitor Management - Collect visitor info, assign sessions, track history
- Agent Workspace - Unified interface for human agents
- Structured Display - Render orders, products, logistics as beautiful cards
- Rich Components - Order cards, logistics tracking, product display, price comparison
- Action Protocol - Standardized URI protocol for interactions
📦 Repository Structure
| Repository |
Description |
Tech Stack |
| tgo-ai |
AI/ML operations service for managing agents, tool bindings, knowledge bases, and usage analytics |
Python / FastAPI |
| tgo-api |
Core business logic service handling user management, visitor tracking, assignment, and communication |
Python / FastAPI |
| tgo-cli |
CLI tool & MCP Server enabling AI agents to execute customer service operations with 40+ built-in tools |
TypeScript / Node.js |
| tgo-device-agent |
Embedded agent running on managed devices providing file and shell capabilities via TCP JSON-RPC |
Go |
| tgo-device-control |
Device control service managing TCP/JSON-RPC connections for remote device management with MCP Agent |
Python / FastAPI |
| tgo-platform |
Multi-channel message intake service supporting WeChat, Feishu, DingTalk, Telegram, Slack, email, etc. |
Python / FastAPI |
| tgo-plugin-runtime |
Plugin lifecycle management and execution service with dynamic tool synchronization |
Python / FastAPI |
| tgo-rag |
RAG service providing document processing, hybrid semantic/full-text search, and async processing |
Python / FastAPI |
| tgo-web |
Admin frontend with real-time chat, AI agent management, knowledge base, and MCP tool integration |
TypeScript / React 19 |
| tgo-workflow |
AI Agent workflow execution engine supporting DAG topology with LLM, API, condition, and tool nodes |
Python / FastAPI |
| Repository |
Description |
Tech Stack |
| tgo-widget-js |
Embeddable customer service chat widget (Intercom-style) for websites |
TypeScript / React 18 |
| tgo-widget-ios |
Native iOS customer service chat SDK with SwiftUI views and UIKit bridging |
Swift / SwiftUI |
| tgo-widget-flutter |
Cross-platform customer service chat widget for iOS and Android |
Dart / Flutter |
| tgo-widget-cli |
Visitor-facing CLI tool & MCP Server providing customer service interface |
TypeScript / Node.js |
| tgo-widget-miniprogram |
WeChat Mini Program chat widget component with AI streaming responses and Markdown rendering |
TypeScript |
🏗️ System Architecture
Product Preview
|
|
Dashboard
 |
Agent Orchestration
 |
Knowledge Base
 |
Q&A Debugging
 |
MCP Tools
 |
Platform Admin
 |
System Requirements
- CPU: >= 4 Core
- RAM: >= 8 GiB
- OS: macOS / Linux / WSL2
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