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TradingAgents - Docker Setup Guide

This directory contains the Docker setup for running TradingAgents with a FastAPI backend and Next.js frontend.

🚀 Quick Start

Prerequisites

Docker and Docker Compose installed
OpenAI API Key
Alpha Vantage API Key (optional, for enhanced data)

Environment Setup

Copy your .env file in the project root with your API keys:

OPENAI_API_KEY=your_openai_api_key_here
ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here

Running with Docker

Build and start all services:

docker-compose up --build

Access the application:
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- API Documentation: http://localhost:8000/docs
Stop the services:

docker-compose down

📁 Project Structure

TradingAgents/
├── backend/              # FastAPI backend
│   ├── app/
│   │   ├── api/         # API routes
│   │   ├── models/      # Pydantic models
│   │   ├── services/    # Business logic
│   │   └── core/        # Configuration
│   ├── requirements.txt
│   └── Dockerfile
├── frontend/            # Next.js frontend
│   ├── app/            # Next.js pages
│   ├── components/     # React components
│   ├── lib/            # Utilities and API client
│   ├── hooks/          # Custom React hooks
│   └── Dockerfile
├── tradingagents/      # Core TradingAgents package
└── docker-compose.yml  # Docker orchestration

🔧 Backend API

Available Endpoints

GET /api/health - Health check
GET /api/config - Get configuration options
POST /api/analyze - Run trading analysis
GET /api/tickers - Get popular tickers

Example API Request

curl -X POST http://localhost:8000/api/analyze \
  -H "Content-Type: application/json" \
  -d '{
    "ticker": "NVDA",
    "analysis_date": "2024-05-10",
    "research_depth": 1
  }'

🎨 Frontend Features

Modern UI: Built with Next.js, React, and shadcn/ui
Type Safety: Full TypeScript support
Responsive Design: Works on desktop and mobile
Real-time Updates: Live analysis status
Rich Visualizations: Interactive reports and decisions

🛠️ Development

Running Backend Only

cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload

Running Frontend Only

cd frontend
npm install
npm run dev

📊 Using the Application

Navigate to http://localhost:3000
Click "Start Analysis" or go to the Analysis page
Configure your analysis parameters:
- Stock ticker (e.g., NVDA, AAPL)
- Analysis date
- Research depth (1-5)
- LLM models
Click "Run Analysis"
Wait for the multi-agent analysis to complete
Review the trading decision and detailed reports

🔐 Security Notes

Never commit .env files with real API keys
Use environment variables for sensitive data
The backend validates all inputs using Pydantic
CORS is configured for frontend-backend communication

🐛 Troubleshooting

Backend Issues

Check logs: docker-compose logs backend
Verify API keys are set correctly
Ensure port 8000 is not in use

Frontend Issues

Check logs: docker-compose logs frontend
Verify backend is running
Ensure port 3000 is not in use

Network Issues

Restart Docker: docker-compose down && docker-compose up
Check network: docker network ls
Verify services can communicate: docker-compose exec frontend ping backend

📝 License

This project follows the same license as TradingAgents.

🤝 Contributing

See the main README.md for contribution guidelines.

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