Stock Sentiment Analyzer

Introducing the Stock Sentiment Analyzer, your OMI powered market insight tool. This tool will provide real-time sentiment analysis on individual stocks.

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Stock Sentiment Analyzer with OMI

Stock Sentiment Analyzer is a Flask-based web application designed to simplify stock sentiment analysis. It integrates OpenAI’s GPT-3.5-turbo for natural language processing and Alpha Vantage to fetch real-time sentiment data, empowering users with actionable insights from stock-related queries.

Features

  • NLP for Stock Queries: Extracts stock symbols from natural language inputs.
  • Sentiment Analysis: Fetches and analyzes sentiment data for stocks via Alpha Vantage.
  • Validation: Validates stock tickers against Yahoo Finance for accuracy.
  • Cooldown Mechanism: Limits API calls to prevent excessive usage.
  • User Interface: Clean, responsive design built with Tailwind CSS.
  • Error Handling: Robust error management with detailed logging.

Getting Started

Prerequisites

  • Python 3.10 or higher
  • OpenAI API key
  • Alpha Vantage API key

Installation

  1. Clone the repository: bash git clone https://github.com/your-username/stock-sentiment-analyzer.git cd stock-sentiment-analyzer
  2. Install dependencies: bash pip install -r requirements.txt
  3. Set up environment variables by creating a .env file: env OPENAI_API_KEY=your_openai_api_key ALPHAVANTAGE_KEY=your_alpha_vantage_api_key
  4. Run the application: bash python app.py
  5. Access the application: Open your browser and navigate to http://127.0.0.1:5000.

API Endpoints

POST /webhook

  • Description: Accepts user queries and responds with sentiment insights.
  • Request Body: json { "id": "session_id", "structured": { "overview": "Analyze the Apple stock for me" } }
  • Response: json { "message": "Stock: AAPL, Sentiment: Positive" }

GET /

  • Description: Displays the homepage with application instructions.

Project Structure

.
├── app.py                # Main Flask application
├── templates/
│   └── index.html        # Frontend HTML templates
├── static/
│   └── css/              # Tailwind CSS styles
├── requirements.txt      # Python dependencies
├── .env                  # Environment variables
├── README.md             # Project documentation
└── LICENSE               # License information

Built With

  • Flask: Python web framework.
  • OpenAI GPT-3.5-turbo: For natural language processing.
  • Alpha Vantage API: Real-time stock sentiment analysis.
  • Yahoo Finance API: Ticker symbol validation.
  • Tailwind CSS: Frontend design and styling.
  • Tenacity: Retry mechanism for API calls.

Contributing

We welcome contributions! To contribute:

  1. Fork the repository.
  2. Create a new branch (git checkout -b feature-name).
  3. Commit your changes (git commit -m 'Add new feature').
  4. Push to the branch (git push origin feature-name).
  5. Open a pull request.

License

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

Disclaimer

The sentiment analysis provided is for informational purposes only and should not be considered financial advice. Please consult a financial advisor before making investment decisions.

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