{"id":26832716,"url":"https://github.com/abhay-kanwasi/sentiment-dashboard","last_synced_at":"2026-04-27T23:34:47.180Z","repository":{"id":285105536,"uuid":"957084419","full_name":"Abhay-Kanwasi/Sentiment-Dashboard","owner":"Abhay-Kanwasi","description":"Comprehensive solution for sentiment analysis, combining a FastAPI backend with a React frontend. 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The application allows users to upload CSV files containing product reviews, analyze the sentiment using a pre-trained DistilBERT model, and visualize the results through an interactive dashboard. The application consists of two main components:\n\n1. **Backend API**: Built using FastAPI, providing endpoints for sentiment analysis of text data.\n2. **Frontend Dashboard**: A user-friendly interface (built with React or similar framework) that visualizes the sentiment analysis results.\n\n## Features\n\n- **Sentiment Analysis API**:\n  - Analyze text data from CSV files.\n  - Supports batch processing of reviews.\n  - Provides detailed sentiment results including confidence scores.\n  - Returns summary statistics and visualizable data.\n\n- **Dashboard Features**:\n  - File upload functionality for CSV files.\n  - Visual representations of sentiment data through charts.\n  - Tabular view of processed reviews with sentiment labels.\n  - Summary statistics dashboard.\n\n## Installation\n\n### Backend Setup\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/Abhay-Kanwasi/Sentiment-Dashboard.git\n   \n   cd Sentiment Dashboard/backend\n   ```\n\n2. Create and activate a virtual environment (recommended):\n   ```bash\n   python -m venv venv\n   source venv/bin/activate  # On macOS/Linux\n   # OR\n   .\\venv\\Scripts\\activate  # On Windows\n   ```\n\n3. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n### Frontend Setup\n\n1. Navigate to the frontend directory:\n   ```bash\n   cd Sentiment Dashboard/frontend\n   ```\n\n2. Install dependencies:\n   ```bash\n   npm install\n   ```\n\n## Usage\n\n### Running the Backend\n\n1. Start the FastAPI server:\n   ```bash\n   uvicorn app.main:app --reload\n   ```\n\n   The API will be available at `http://localhost:8000`.\n\n### Running the Frontend\n\n1. Start the frontend development server:\n   ```bash\n   npm run dev\n   ```\n\n   The dashboard will be available at `http://localhost:3000`.\n\n## API Documentation\n\n### `/analyze` Endpoint\n\n- **Method**: POST\n- **Description**: Analyzes the sentiment of product reviews provided in a CSV file.\n- **Request Body**:\n  - `file`: CSV file containing a 'review' column with text data.\n- **Response**:\n  ```json\n  {\n    \"summary\": {\n      \"positive_count\": int,\n      \"negative_count\": int,\n      \"positive_avg_confidence\": float,\n      \"negative_avg_confidence\": float,\n      \"total_reviews\": int\n    },\n    \"reviews\": [\n      {\n        \"review\": str,\n        \"sentiment\": str,\n        \"confidence\": float\n      }\n    ]\n  }\n  ```\n\n## Contributing\n\n1. Fork the repository.\n2. Create a new branch for your feature or bug fix.\n3. Commit your changes with clear commit messages.\n4. Push to the branch.\n5. Open a Pull Request against the `main` branch.\n\n\n## Future Improvements\n\n- Add more detailed error handling and validation.\n- Implement user authentication for access control.\n- Add support for different types of input files and data sources.\n- Enhance the dashboard with additional visualizations and interactive features.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhay-kanwasi%2Fsentiment-dashboard","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhay-kanwasi%2Fsentiment-dashboard","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhay-kanwasi%2Fsentiment-dashboard/lists"}