{"id":21519736,"url":"https://github.com/an0te/kwclustering","last_synced_at":"2026-05-16T18:33:56.105Z","repository":{"id":252786073,"uuid":"841451954","full_name":"an0te/kwclustering","owner":"an0te","description":"This tool allows you to classify and analyze keywords using OpenAI's GPT model. 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Whether you're dealing with large datasets or just a few keywords, this tool helps you organize and gain insights from your data with ease.\n\n## Features\n\n- **Upload and Analyze**: Upload a CSV file with keywords (and optionally,their search volumes) or enter keywords manually.\n- **Custom Categories**: Define your own categories, including descriptions and example keywords, to tailor the classification to your needs.\n- **Visualization**: Get visual insights into the distribution of keywords across categories using interactive charts.\n- **Download Results**: Easily download the classification results as a CSV file for further analysis.\n\n## Technology Stack\n\n- **Streamlit**: For creating the interactive web application interface.\n- **Pandas**: For data manipulation and processing.\n- **OpenAI API**: For keyword classification using GPT.\n- **Plotly**: For generating interactive visualizations.\n- **Logging**: For monitoring and troubleshooting the classification process.\n\n## Prerequisites\n\n- **Python 3.8+**\n- **OpenAI API Key**: You'll need an OpenAI API key to use the classification features.\n\n## Installation\n\n1. **Clone the repository**:\n   ```bash\n   git clone https://github.com/an0te/kwclustering\n   cd keyword-classifier\n   ```\n\n2. **Install dependencies**:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. **Set up your OpenAI API key**:\n   - You'll be prompted to enter your API key within the Streamlit app.\n\n## Usage\n\n1. **Run the Streamlit app**:\n   ```bash\n   streamlit run app.py\n   ```\n\n2. **Upload or Enter Keywords**:\n   - Choose to either upload a CSV file containing your keywords or manually enter them.\n   \n3. **Define Categories**:\n   - Specify the categories for classification, including descriptions and example keywords.\n\n4. **Analyze Keywords**:\n   - Click the \"Analyze Keywords\" button to start the classification process.\n\n5. **Visualize and Download Results**:\n   - View the classification results in an interactive format and download them as a CSV file.\n\n## Example Usage\n\n1. **Upload CSV File**:\n   - Select a CSV file with keywords.\n   - Choose the columns for keywords and search volumes (optional).\n\n2. **Manual Keyword Input**:\n   - Enter your keywords directly into the text area.\n\n3. **Define Categories**:\n   - Enter category names, descriptions, and example keywords.\n\n4. **Run Analysis**:\n   - Start the analysis and view the results in the form of bar charts and a downloadable CSV file.\n\n## Logging\n\n- The application logs important events, errors, and progress details to the terminal to assist with monitoring and debugging.\n\n## Contributions\n\nFeel free to fork this repository, submit pull requests, or report issues. Contributions are always welcome!\n\n## License\n\nThis project is licensed under the MIT License.\n\n## Contact\n\nFor any questions or feedback, please reach out \n\n---\n\nDeveloped with ❤️ by Andreas\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fan0te%2Fkwclustering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fan0te%2Fkwclustering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fan0te%2Fkwclustering/lists"}