InsightRAG_Chatbot / DEPLOYMENT.md
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# 🚀 Hugging Face Spaces Deployment Guide
## Quick Deployment Steps
### 1. Create a New Space
- Go to [Hugging Face Spaces](https://huggingface.co/spaces)
- Click "Create new Space"
- Choose "Streamlit" as the SDK
- Set visibility (Public/Private)
### 2. Upload Files
Upload these files to your Space:
- `app.py` (main Streamlit application)
- `requirements.txt` (dependencies)
- `README.md` (documentation)
### 3. Set Environment Variables
- Go to Settings → Secrets
- Add `GOOGLE_API_KEY` with your Gemini API key
- The app will automatically use this environment variable
### 4. Deploy
- Push your code to the Space
- The app will automatically build and deploy
- Wait for the build to complete (usually 2-3 minutes)
### 5. Test Your App
- Open your Space URL
- Enter your Gemini API key in the sidebar
- Click "Initialize RAG System"
- Start chatting!
## Important Notes
- **API Key**: Make sure to set `GOOGLE_API_KEY` in Space secrets
- **Memory**: The app will create a Chroma database in memory
- **Performance**: First initialization may take a few minutes
- **Limits**: Hugging Face Spaces have resource limits
## Troubleshooting
### Build Fails
- Check `requirements.txt` for correct package versions
- Ensure all imports are available
### Runtime Errors
- Verify API key is set correctly
- Check logs in the Space interface
- Ensure all dependencies are installed
### Performance Issues
- Reduce the number of documents processed
- Use smaller embedding models
- Optimize the RAG pipeline
## Customization
You can customize the app by:
- Modifying the UI in `app.py`
- Changing the embedding model
- Adjusting the RAG pipeline parameters
- Adding new features
Happy deploying! 🎉