🤖 StockCrew AI - Multi-Agent Stock Trading System

An intelligent multi-agent system powered by CrewAI and Google Gemini that analyzes stock market data and provides actionable trading recommendations.

🌟 Features

• Multi-Agent Architecture: Specialized AI agents working together

  • 📊 Analyst Agent: Performs in-depth stock analysis using real-time market data
  • 💼 Trader Agent: Makes strategic Buy/Sell/Hold decisions based on analysis

• Real-Time Market Data: Fetches live stock prices and metrics using Yahoo Finance

• AI-Powered Insights: Leverages Google Gemini 2.0 Flash for intelligent decision-making

• Automated Workflow: Seamless task orchestration between agents

🏗️ Architecture

┌─────────────────────┐
│   User Input        │
│   (Stock Symbol)    │
└──────────┬──────────┘
           │
           ▼
┌─────────────────────────────────────┐
│         Stock Crew                  │
│  ┌────────────────────────────┐    │
│  │   Analyst Agent            │    │
│  │   - Fetches stock data     │    │
│  │   - Analyzes trends        │    │
│  │   - Provides insights      │    │
│  └──────────┬─────────────────┘    │
│             │                       │
│             ▼                       │
│  ┌────────────────────────────┐    │
│  │   Trader Agent             │    │
│  │   - Reviews analysis       │    │
│  │   - Makes trade decision   │    │
│  │   - Recommends action      │    │
│  └────────────────────────────┘    │
└─────────────────────────────────────┘
           │
           ▼
┌─────────────────────┐
│   Trading Report    │
│   (Buy/Sell/Hold)   │
└─────────────────────┘

🚀 Getting Started

Prerequisites

• Python 3.8+
• Google Gemini API Key
• Internet connection for real-time data

Installation

1. Clone the repository

   git clone https://github.com/yourusername/stockcrew-ai.git
   cd stockcrew-ai

2. Create a virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Set up environment variables

   Create a .env file in the project root:

   GEMINI_API_KEY=your_gemini_api_key_here

   To get a Gemini API key:

   • Visit Google AI Studio
   • Sign in with your Google account
   • Generate a new API key

Usage

Run the main script with a stock symbol:

# Edit main.py to change the stock symbol
python main.py

Example Output:

Stock: TSLA
Price: 245.32 USD
Change: +5.67 (+2.37%)

Analysis Summary:
- Current Price: Strong upward momentum
- Volume: Above average trading activity
- Recommendation: BUY - Positive trend indicators

Trading Decision: BUY

📁 Project Structure

stockcrew-ai/
├── agents/
│   ├── analyst_agent.py      # Financial analysis agent
│   └── trader_agent.py        # Trading decision agent
├── tasks/
│   ├── analyse_task.py        # Stock analysis task definition
│   └── trade_task.py          # Trading decision task definition
├── tools/
│   └── stock_research_tool.py # Yahoo Finance integration
├── crew.py                    # Crew orchestration
├── main.py                    # Entry point
├── requirements.txt           # Python dependencies
├── .env                       # API keys (not in repo)
├── .gitignore                 # Git ignore rules
└── README.md                  # This file

🛠️ Components

Agents

Analyst Agent

• Role: Financial Market Analyst
• Tools: Live Stock Information Tool (Yahoo Finance)
• Temperature: 0.3 (balanced creativity/consistency)
• Function: Analyzes stock performance, trends, and key metrics

Trader Agent

• Role: Strategic Stock Trader
• Tools: None (uses analysis from Analyst Agent)
• Temperature: 0.2 (more deterministic)
• Function: Makes Buy/Sell/Hold recommendations

Tools

Live Stock Information Tool

• Fetches real-time stock data from Yahoo Finance
• Returns: Current price, daily change, percentage change
• Parameters: Stock ticker symbol (e.g., AAPL, TSLA, MSFT)

🧪 Example Notebook

The project includes pydantic_agentic_ai.ipynb demonstrating:

• Pydantic AI agent creation
• Weather forecast tool integration (example)
• Async execution patterns

🔧 Customization

Changing the Stock Symbol

Edit main.py:

if __name__ == "__main__":
    run("AAPL")  # Change to any valid ticker

Adjusting Agent Behavior

Modify temperature settings in agent files:

model_client = LLM(
    model="gemini/gemini-2.0-flash",
    api_key=GEMINI_API_KEY,
    temperature=0.3,  # Lower = more deterministic
    max_tokens=2048
)

Adding New Tools

Create a new tool in tools/:

from crewai.tools import tool

@tool("Your Tool Name")
def your_tool(param: str) -> str:
    """Tool description"""
    # Implementation
    return result

📊 Supported Stock Symbols

Any stock symbol available on Yahoo Finance, including:

• US Stocks: AAPL, GOOGL, MSFT, TSLA, AMZN
• Indian Stocks: RELIANCE.NS, TCS.NS, INFY.NS
• Crypto: BTC-USD, ETH-USD

⚠️ Disclaimer

This tool is for educational and research purposes only.

• Not financial advice
• Always do your own research
• Consult a licensed financial advisor before making investment decisions
• Past performance doesn't guarantee future results
• The developers are not responsible for any financial losses

🤝 Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• CrewAI - Multi-agent framework
• Google Gemini - AI model
• yfinance - Yahoo Finance data
• LiteLLM - LLM integration

📧 Contact

Suraj Kumar - @yourhandle

Project Link: https://github.com/yourusername/stockcrew-ai

---

⭐ If you found this project helpful, please give it a star!