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# 📚 Document Q&A System
A powerful document question-answering system built with LlamaIndex and Gradio. Upload your documents and ask questions about them using state-of-the-art AI models.
## Features
🔍 **Smart Document Processing**: Automatically processes various document formats (PDF, TXT, DOCX, MD, CSV, JSON)
🤖 **Multiple AI Models**: Choose from GPT-4o, Claude 3.5 Sonnet, Llama 3.1, Mistral, and more
📊 **Performance Monitoring**: Track response times and query statistics
🎯 **Source Attribution**: See which document sections were used to generate answers
⚙️ **Customizable Settings**: Adjust temperature, token limits, and retrieval parameters
🔒 **Secure API Key Management**: Use environment variables or direct input
## How to Use
### 1. Upload Documents
- Go to the "Upload Documents" tab
- Select your files (PDF, TXT, DOCX, MD, CSV, JSON)
- Click "Process Documents" to create the searchable index
### 2. Configure Settings
- Add your OpenRouter API key (or set as HF Space secret)
- Choose your preferred AI model
- Adjust parameters like temperature and max tokens
### 3. Ask Questions
- Enter your question in the "Ask Questions" tab
- Click "Ask Question" to get AI-powered answers
- View sources and performance metrics
## API Key Setup
You can provide your OpenRouter API key in two ways:
1. **Direct Input**: Enter it in the "API Key" field in the interface
2. **Environment Variable**: Set `OPENROUTER_API_KEY` as a Hugging Face Space secret
Get your API key from [OpenRouter](https://openrouter.ai/)
## Best Practices for Questions
- 🎯 **Be specific**: "What does the author say about climate change?" vs "Tell me about climate"
- 📚 **Ask about concepts**: "What is the main methodology discussed?"
- 🔍 **Use comparative questions**: "How do different studies approach this topic?"
- 📊 **Request analysis**: "What are the key findings presented?"
- 🏛️ **Ask about methodology**: "What research methods are used?"
## Available Models
- **GPT-4o**: Best overall performance, most accurate
- **GPT-4o Mini**: Faster, cost-effective option
- **Claude 3.5 Sonnet**: Excellent reasoning and analysis
- **Claude 3 Haiku**: Fast and efficient
- **Llama 3.1 70B/8B**: Open source, strong performance
- **Mistral Large**: Strong multilingual capabilities
- **Gemini Pro**: Google's advanced model
## Technical Details
Built with:
- **LlamaIndex**: Document indexing and retrieval
- **Gradio**: Web interface
- **OpenRouter**: Multi-model API access
- **HuggingFace Embeddings**: Text vectorization
- **BGE-small-en-v1.5**: Efficient embedding model
## Performance
- Vector-based semantic search for accurate retrieval
- Cached indexing for fast subsequent queries
- Configurable chunk sizes and overlap for optimal results
- Real-time performance monitoring
## Development
To run locally:
```bash
git clone <your-repo>
cd document-qa-system
pip install -r requirements.txt
python app.py
```
## License
This project is open source and available under the MIT License.
## Support
For issues or questions, please check the Help tab in the application or create an issue in the repository. |