Deployment Guide for David Van Dijcke’s Econometric Research Assistant

Overview

This assistant specializes in David Van Dijcke’s econometric research, emphasizing his contributions to functional data analysis, optimal transport, and causal inference methods. The assistant is optimized for the 2025-26 economics job market.

Key Features

• Econometric Focus: Emphasizes David’s methodological contributions
• Job Market Ready: Highlights R3D paper and econometric innovations
• Technical Accuracy: Detailed information about functional data analysis and optimal transport
• Policy Applications: Shows how methods apply to real-world big data problems

Deployment Options

Option 1: Hugging Face Spaces (Recommended)

1. Create a new Space:
   • Go to https://huggingface.co/new-space
   • Choose Gradio SDK
   • Set to Public
2. Upload files:
   • app.py (the main application)
   • requirements.txt
   • documents/ folder with PDFs
3. Add Google API Key (for best performance):
   • Go to Space Settings > Repository secrets
   • Add secret: GOOGLE_API_KEY
   • Get key from: https://aistudio.google.com/app/apikey
4. The Space will auto-deploy

Option 2: Local Development

# Clone the repository
git clone https://huggingface.co/spaces/dvdijcke/david-research-assistant

# Install dependencies
pip install -r requirements.txt

# Set up environment
echo "GOOGLE_API_KEY=your_key_here" > .env

# Run the app
python app.py

Performance Optimization

Using Google Gemini (Recommended)

• Model: Gemini 2.0 Flash (falls back to 1.5 Flash)
• Cost: ~$0.001-0.005 per conversation
• Quality: High accuracy, understands technical econometric concepts
• Setup: Just add GOOGLE_API_KEY to environment

Without API Key

• Falls back to limited mode
• Lower quality responses
• Still functional but less accurate

Content Updates

To update research information:

1. Edit app.py and modify the research_info section:
   • Update paper titles and descriptions
   • Add new methodological contributions
   • Update job market status
2. Update paper summaries in the paper_summaries section:
   • Add new papers
   • Update findings
   • Emphasize econometric innovations
3. Add new PDFs to documents/ folder:
   • Job market paper should be prominently featured
   • Include recent working papers
   • CV should be up to date

Testing

Run the test script to verify functionality:

python test_assistant.py

Key things to verify:

• Correctly identifies David as an econometrician
• Accurately describes R3D and other papers
• Emphasizes methodological contributions
• Links theory to applications

Common Issues

1. “No module named ‘langchain’“
   • Solution: pip install -r requirements.txt
2. Slow responses
   • Add Google API key for faster Gemini responses
   • Check if vector store cache exists
3. Incorrect information
   • Update the context in app.py
   • Ensure PDFs are loading correctly
   • Check paper summaries are accurate

Customization

Adjusting the tone:

Edit the prompt in generate_response() to adjust formality and focus.

Adding new examples:

Update the examples list in create_gradio_interface().

Changing the model:

Modify the genai.GenerativeModel() initialization to use different models.

Monitoring

• Check Space logs for errors
• Monitor API usage in Google AI Studio
• Test with various econometric questions regularly

Support

For issues or updates:

• Check Hugging Face Space logs
• Verify API key is correctly set
• Ensure all PDFs are in the documents folder