AI Trader Frontend

A Streamlit dashboard application for visualizing trading account information and positions from the Alpaca Trading API. The dashboard displays portfolio value, positions, profit/loss metrics, and trading diary entries.

📊 Features

• Real-time Account Data: View portfolio value, cash balance, and buying power
• Positions Tracking: Monitor your positions with detailed information on current prices, market values, and profit/loss
• Trading Diary: Keep track of your trading thoughts and strategies with date-organized diary entries
• Collapsible Interface: Clean UI with collapsible diary sections and intuitive navigation

🛠️ Installation

1. Clone the repository:

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

2. Create and activate 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 in a .env file:

   ALPACA_API_KEY=your_api_key
   ALPACA_SECRET_KEY=your_secret_key
   ALPACA_PAPER=true  # Use paper trading account
   

🚀 Usage

1. Run the Streamlit dashboard:

   cd dashboard
   streamlit run app.py

2. Update portfolio data:

   cd dashboard/update_jobs
   python positions_job.py

3. Deploy to Streamlit Cloud:

   • Connect your GitHub repository to Streamlit Cloud
   • Set the main file path as dashboard/app.py
   • Add your environment variables (ALPACA_API_KEY, ALPACA_SECRET_KEY, ALPACA_PAPER)

4. Automated Data Updates: This project includes a GitHub Actions workflow that automatically updates portfolio data every 15 minutes.

   To set up automated updates:

   • Push this repository to GitHub
   • Add your Alpaca API keys as GitHub secrets:
     • ALPACA_API_KEY
     • ALPACA_SECRET_KEY
     • ALPACA_PAPER (optional, defaults to true)
   • The workflow will run every 15 minutes, fetch new data, and commit it to your repository
   • Streamlit Cloud will automatically use the latest data

📁 Project Structure

• dashboard/app.py - Main Streamlit application
• dashboard/data/snapshots/ - JSON files of account snapshots
• dashboard/data/diary/ - Markdown files for trading diary entries
• dashboard/update_jobs/positions_job.py - Job for fetching data from Alpaca API

📝 Data Format

• Snapshots: JSON files with naming pattern {agent_name}_{YYYYMMDD_HHMMSS}.json
• Diary Entries: Markdown files with naming pattern {agent_name}_{YYYY-MM-DD}.md

🔑 Environment Variables

• ALPACA_API_KEY: API key for Alpaca
• ALPACA_SECRET_KEY: Secret key for Alpaca
• ALPACA_PAPER: Whether to use paper trading (default: true)

📸 Screenshots

🔄 Data Flow

Alpaca Trading API → positions_job.py → JSON snapshots → app.py → Dashboard UI

📄 License

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

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check the issues page.

🙏 Acknowledgements

• Alpaca API - For providing the trading API
• Streamlit - For the awesome dashboard framework
• Pandas - For data manipulation capabilities