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--- |
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title: LLM Powered Database Chatbot |
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emoji: 🤖 |
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colorFrom: blue |
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colorTo: purple |
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sdk: gradio |
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sdk_version: 5.26.0 |
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app_file: app.py |
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pinned: false |
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space: Vashishta-S-2141/LLM_Powered_Database_Chatbot |
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license: mit |
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hardware: cpu |
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persistentStorage: true |
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--- |
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# 🤖 LLM Powered Database Chatbot |
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A powerful chatbot that can analyze your documents and data, providing insights and visualizations through natural language queries. |
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## Features |
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- **Document Analysis**: Upload and query PDFs, TXT, DOCX, CSV, and XLSX files |
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- **Data Visualization**: Generate interactive plots and charts from your data |
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- **Natural Language Interface**: Ask questions in plain English |
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- **Multiple Data Sources**: Work with both documents and structured data |
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- **Interactive Visualizations**: View and save your data visualizations |
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## How to Use |
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1. **Upload Documents**: |
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- Go to the "Document Upload" tab |
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- Upload your files (PDF, TXT, DOCX, CSV, or XLSX) |
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- Click "Process & Index Documents" |
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2. **Ask Questions**: |
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- Type your question in the chat interface |
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- The bot will analyze your documents and provide answers |
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- For data-related questions, it will generate visualizations |
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3. **View Visualizations**: |
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- Switch to the "Visualizations" tab to see your plots |
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- Use the buttons to save or clear visualizations |
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## Requirements |
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- Groq API key (set in environment variables) |
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- Python 3.8 or higher |
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## Local Development |
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1. Clone this repository |
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2. Install dependencies: |
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```bash |
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pip install -r requirements.txt |
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``` |
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3. Set up environment variables: |
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```bash |
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export GROQ_API_KEY=your_api_key_here |
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``` |
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4. Run the application: |
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```bash |
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python app.py |
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``` |
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## License |
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MIT License |
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## Author |
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Vashishta-S-2141 |
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## Technical Details |
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- Built with Python, Gradio, ChromaDB, and Groq API |
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- Uses vector embeddings for efficient document retrieval |
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- Deployed on Hugging Face Spaces |
