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| # 📈 StockSignalAI | |
| AI-powered stock analysis and signal generation tool using Streamlit. | |
| --- | |
| ## 🚀 Features | |
| - Live stock data via Yahoo Finance | |
| - Technical indicators (e.g., RSI, MACD, EMA) | |
| - ML-based trading signal generator | |
| - Model training and evaluation | |
| - Interactive UI with Streamlit | |
| - SQLite-based data storage | |
| --- | |
| ## ⚙️ Setup Instructions | |
| ### 1. Clone the Repository | |
| ```bash | |
| git clone https://github.com/yourusername/StockSignalAI.git | |
| cd StockSignalAI | |
| ## 2. Create Virtual Environment (optional but recommended) | |
| python3 -m venv venv | |
| source venv/bin/activate # For macOS/Linux | |
| venv\Scripts\activate # For Windows | |
| 3. Install Dependencies | |
| pip install -r requirements.txt | |
| If you don’t have a requirements.txt, you can create one: | |
| txt | |
| Copy | |
| Edit | |
| yfinance | |
| pandas | |
| numpy | |
| matplotlib | |
| scikit-learn | |
| streamlit | |
| ta | |
| Save the above as requirements.txt, then run: | |
| pip install -r requirements.txt | |
| 🖥️ Run the App | |
| Use Streamlit, not Python directly: | |
| streamlit run app.py | |
| 💡 If Port 8501 is Busy | |
| streamlit run app.py --server.port 8888 | |
| 🧠 Notes | |
| Session State Initialization | |
| Before using any Streamlit session state variables (like model), initialize them at the start of the app: | |
| if "model" not in st.session_state: | |
| st.session_state.model = None | |
| Add similar blocks for other keys like data, stock_symbol, etc. | |
| 🗃️ Database Tables Used | |
| Your app uses the following tables: | |
| stock_data | |
| technical_indicators | |
| trading_signals | |
| model_metrics | |
| Ensure your SQLite DB or ORM setup creates them before use. | |
| 🔧 Project Structure (Example) | |
| StockSignalAI/ | |
| ├── app.py | |
| ├── requirements.txt | |
| ├── data/ | |
| │ └── stocks.db | |
| ├── models/ | |
| │ └── trained_models.pkl | |
| └── README.md | |
| 📌 | |
| TODO / Future Enhancements | |
| Add backtesting module | |
| Save models per stock - this is done | |
| Upload and analyze user CSV data | |
| Add performance metrics dashboard | |
| Email/SMS alerts on new signals | |
| 🙌 Acknowledgments | |
| yfinance | |
| ta-lib | |
| Streamlit | |
| scikit-learn | |