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
  • 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! 🎉