STREAMLIT_DEPLOYMENT.md

Streamlit Deployment Guide

Deploy to Streamlit Community Cloud

Follow the same pattern as the NLP project:

1. Push to GitHub

Make sure your code is in a GitHub repository:

cd "/Users/tay/Development/portfolio projects/cv200"
# If not already a git repo, initialize and push to GitHub
git remote add origin https://github.com/your-username/cv200.git
git push -u origin main

2. Deploy on Streamlit Cloud

1. Go to Streamlit Community Cloud:

   • Visit https://share.streamlit.io/
   • Sign in with GitHub
   • Click "New app"

2. Configure deployment:

   • Repository: Select your GitHub repo (the one with streamlit_app.py)
   • Branch: main (or your branch)
   • Main file path: streamlit_app.py
   • Python version: 3.9 or 3.10

3. Set Secrets (optional but recommended):

   • Click "Advanced settings"
   • Add secret: API_URL = https://solarevat-cv200.hf.space
   • This allows the app to use your HF Spaces API

4. Deploy:

   • Click "Deploy"
   • Streamlit will automatically:
     • Install dependencies from requirements-streamlit.txt
     • Run streamlit run streamlit_app.py
   • Your app will be live at: https://your-app-name.streamlit.app

3. Verify Deployment

• Open your Streamlit app URL
• Upload a pet image
• Verify it calls your HF Spaces API correctly

Local Testing

Before deploying, test locally:

cd "/Users/tay/Development/portfolio projects/cv200"
pip install -r requirements-streamlit.txt
streamlit run streamlit_app.py

Then open http://localhost:8501 in your browser.

Update API URL

If your API URL is different, edit streamlit_app.py:

API_URL = "https://your-actual-url.hf.space"

Features

• ✅ Image upload with preview
• ✅ Top 5 predictions with confidence scores
• ✅ Progress bars for visual feedback
• ✅ Sidebar with API information
• ✅ Error handling
• ✅ Responsive design

Notes

• The Streamlit app calls your HF Spaces API
• Make sure CORS is enabled in your API (already done)
• The app doesn't need the model files - it just calls the API
• Much simpler than managing HTML/JavaScript!