Files
2026-07-13 12:58:18 +08:00

262 lines
7.4 KiB
Markdown

# A2A + AG-UI Multi-Agent Starter
A minimal starter template for building multi-agent applications with **A2A Protocol** (Agent-to-Agent) and **AG-UI Protocol** (Agent-UI). This project demonstrates how to coordinate multiple AI agents across different frameworks (LangGraph and Google ADK) to solve tasks collaboratively.
![Screenshot of a demo](demo.png)
## Quick Start
### Prerequisites
- **Node.js** 18+
- **Python** 3.10+
- **Google API Key** - [Get one here](https://aistudio.google.com/app/apikey)
- **OpenAI API Key** - [Get one here](https://platform.openai.com/api-keys)
### Installation
1. **Install frontend dependencies:**
```bash
npm install
```
2. **Install Python dependencies:**
```bash
cd agents
python3 -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
cd ..
```
3. **Set up environment variables:**
```bash
cp .env.example .env
# Edit .env and add your API keys:
# GOOGLE_API_KEY=your_google_api_key
# OPENAI_API_KEY=your_openai_api_key
```
4. **Start all services:**
```bash
npm run dev
```
This will start:
- **UI**: http://localhost:3000
- **Orchestrator**: http://localhost:9000
- **Research Agent**: http://localhost:9001
- **Analysis Agent**: http://localhost:9002
## Usage
Try asking:
- "Research quantum computing"
- "Tell me about artificial intelligence"
- "Research renewable energy"
The orchestrator will:
1. Send your query to the **Research Agent** to gather information
2. Pass the research to the **Analysis Agent** for insights
3. Present a complete summary with both research and analysis
## Development Scripts
```bash
# Start everything
npm run dev
# Start individual services
npm run dev:ui # Next.js UI only
npm run dev:orchestrator # Orchestrator only
npm run dev:research # Research agent only
npm run dev:analysis # Analysis agent only
# Build for production
npm run build
# Lint code
npm run lint
```
## Customization
### Adding New Agents
1. **Create a new Python agent** in `agents/`:
- Implement A2A Protocol (see existing agents as examples)
- Choose a port (e.g., 9003)
- Define agent capabilities and skills
2. **Register in middleware** (`app/api/copilotkit/route.ts`):
```typescript
const newAgentUrl = "http://localhost:9003";
const a2aMiddlewareAgent = new A2AMiddlewareAgent({
agentUrls: [
researchAgentUrl,
analysisAgentUrl,
newAgentUrl, // Add here
],
// ...
});
```
3. **Add run script** in `package.json`:
```json
"dev:newagent": "python3 agents/new_agent.py"
```
4. **Update concurrently command** to include your new agent
### Changing UI
- **Main page**: Edit `app/page.tsx` for layout and result display
- **Chat**: Edit `components/chat.tsx` for chat behavior
- **Styling**: Edit `app/globals.css` and `tailwind.config.ts`
- **A2A badges**: Edit `components/a2a/` components
## What This Demonstrates
This starter shows how specialized agents built with different frameworks can communicate via the A2A protocol:
### Architecture
```
┌──────────────────────────────────────────┐
│ Next.js UI (CopilotKit) │
└────────────┬─────────────────────────────┘
│ AG-UI Protocol
┌────────────┴─────────────────────────────┐
│ A2A Middleware │
│ - Routes messages between agents │
└──────┬───────────────────────────────────┘
│ A2A Protocol
├─────► Research Agent (LangGraph)
│ - Gathers information
│ - Port 9001
└─────► Analysis Agent (ADK)
- Analyzes findings
- Port 9002
┌──────┴──────────┐
│ Orchestrator │
│ (ADK) │
│ Port 9000 │
└─────────────────┘
```
### Agents
1. **Orchestrator (ADK + AG-UI Protocol)**
- Receives requests from the UI
- Coordinates specialized agents
- Port: 9000
2. **Research Agent (LangGraph + A2A Protocol)**
- Gathers and summarizes information
- Returns structured JSON
- Port: 9001
3. **Analysis Agent (ADK + A2A Protocol)**
- Analyzes research findings
- Provides insights and conclusions
- Port: 9002
## Project Structure
```
starter/
├── app/
│ ├── api/copilotkit/route.ts # A2A middleware setup (KEY FILE!)
│ ├── layout.tsx # Root layout
│ ├── globals.css # Styles
│ └── page.tsx # Main UI
├── components/
│ ├── chat.tsx # Chat component with A2A visualization
│ └── a2a/ # A2A message components
│ ├── agent-styles.ts # Agent branding utilities
│ ├── MessageToA2A.tsx # Outgoing message badges
│ └── MessageFromA2A.tsx # Incoming message badges
├── agents/ # Python agents
│ ├── orchestrator.py # Orchestrator (ADK + AG-UI) - Port 9000
│ ├── research_agent.py # Research (LangGraph + A2A) - Port 9001
│ ├── analysis_agent.py # Analysis (ADK + A2A) - Port 9002
│ └── requirements.txt # Python dependencies
├── package.json # Frontend dependencies & scripts
├── .env.example # Environment variables template
└── README.md # This file
```
## Key Concepts
### AG-UI Protocol
The **AG-UI Protocol** standardizes communication between the frontend (CopilotKit) and agents. The orchestrator uses AG-UI to receive messages from the UI.
### A2A Protocol
The **A2A Protocol** standardizes agent-to-agent communication. The Research and Analysis agents use A2A to communicate with the orchestrator.
### A2A Middleware
The **A2A Middleware** (in `app/api/copilotkit/route.ts`) is the magic that connects everything:
- Wraps the orchestrator agent
- Registers A2A agents automatically
- Injects a `send_message_to_a2a_agent` tool into the orchestrator
- Routes messages between agents
## Troubleshooting
### Agents not connecting?
- Verify all services are running: `http://localhost:9000-9002`
- Check console for startup errors
### Missing API keys?
- Ensure `.env` file exists with `GOOGLE_API_KEY` and `OPENAI_API_KEY`
- Restart all services after adding keys
### Python import errors?
- Activate virtual environment: `source agents/.venv/bin/activate`
- Reinstall dependencies: `pip install -r agents/requirements.txt`
### Port conflicts?
- Change ports in `.env` file:
```
ORCHESTRATOR_PORT=9000
RESEARCH_PORT=9001
ANALYSIS_PORT=9002
```
## Learn More
- [AG-UI Protocol Documentation](https://docs.ag-ui.com)
- [A2A Protocol Specification](https://a2a-protocol.org)
- [Google ADK Documentation](https://google.github.io/adk-docs/)
- [LangGraph Documentation](https://langchain-ai.github.io/langgraph/)
- [CopilotKit Documentation](https://docs.copilotkit.ai)
## License
MIT