{"id":20461283,"url":"https://github.com/infectedduck/realtimesentiment","last_synced_at":"2026-06-01T02:31:00.751Z","repository":{"id":252962441,"uuid":"842034547","full_name":"InfectedDuck/RealTimeSentiment","owner":"InfectedDuck","description":"A Flask-based web application that leverages BERT for real-time sentiment analysis. Users can input text to detect emotional tones—such as joy, anger, and sadness—and receive a detailed sentiment score. 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Built with Flask and integrated with the BERT-based sentiment analysis API, this project provides real-time emotional insights into user-provided text. It showcases the ability to develop scalable, responsive web applications that leverage machine learning models for real-world applications.\n\n## Features\n\n- **Real-Time Sentiment Analysis**: Detects and evaluates emotions in text, including positive, negative, and neutral sentiments.\n- **User-Friendly Interface**: An intuitive web interface built with HTML and Bootstrap for easy interaction and clear presentation of results.\n- **Robust Backend**: Flask-based API endpoint for processing sentiment analysis requests and handling responses.\n- **Error Handling and Logging**: Comprehensive error handling and logging for tracking and debugging issues.\n- **Unit Testing**: Includes test cases to ensure accurate sentiment classification and robustness of the application.\n\n## Technology Stack\n\n- **Backend**: Flask, Python\n- **Sentiment Analysis**: BERT-based NLP API\n- **Frontend**: HTML, Bootstrap, JavaScript\n- **Testing**: unittest\n\n## Installation\n\n1. **Clone the Repository**:\n    ```bash\n    git clone https://github.com/InfectedDuck/emotion-detection-system.git\n    cd emotion-detection-system\n    ```\n\n2. **Install Dependencies**:\n    Ensure you have `Python 3.7+` and `pip` installed.\n    ```bash\n    pip install -r requirements.txt\n    ```\n\n3. **Run the Flask App**:\n    ```bash\n    python app.py\n    ```\n\n4. **Run Unit Tests**:\n    ```bash\n    python -m unittest discover\n    ```\n\n## Usage\n1. Open your web browser and navigate to `http://127.0.0.1:5000`.\n2. Enter the text you want to analyze in the provided textarea.\n3. Click on **\"Run Sentiment Analysis\"** to get the sentiment results.\n4. View the sentiment label and score displayed on the results page.\n\n## Code Structure\n- **app.py**: Flask application configuration and routes.\n- **sentiment_analyzer.py**: Sentiment analysis logic interacting with the BERT-based API.\n- **index.html**: User interface for text input and displaying results.\n- **tests.py**: Unit tests for validating sentiment analysis functionality.\n\n## License\nThis project is licensed under the Apache License 2.0. See the [LICENSE](LICENSE) file for details. \u003cbr\u003e\nThis project is made as a part of IBM Course.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finfectedduck%2Frealtimesentiment","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finfectedduck%2Frealtimesentiment","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finfectedduck%2Frealtimesentiment/lists"}