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Testing Guide for integrate-to-app-local Branch

🚀 Quick Start

1. Pull the Branch

git fetch origin
git checkout integrate-to-app-local

2. Install Dependencies (if needed)

pip install -r requirements.txt

3. Start the App

python app_local.py

4. Open Browser

Visit: http://localhost:8080

✅ Test Checklist

PSA Video Features (NEW)

Test 1: Video Generation

  1. In chat, type: "Create a PSA video about air quality in California"
  2. ✅ Expect: Response says "I'll generate a health alert video... 60 seconds"
  3. ✅ Expect: After ~60 seconds, video appears with player
  4. ✅ Expect: Message asks "Would you like me to post this to Twitter?"

Test 2: Twitter Posting

  1. After video appears, type: "Yes, post to Twitter"
  2. ✅ Expect: Loading message (60-90 seconds)
  3. ✅ Expect: Success message with tweet URL
  4. ✅ Verify: Only ONE tweet created (duplicate fix)
  5. ✅ Check: https://twitter.com/AI_mmunity for the posted video

Existing Features (Regression Testing)

Test 3: Infectious Diseases (Real Data)

  1. Ask: "What infectious diseases were reported in California in 2024?"
  2. ✅ Expect: Real CDC data (should show ~1908 cases)
  3. ✅ Verify: Says "CDC BEAM Dashboard" (NOT "Demo Mode")

Test 4: Historical Air Quality (Real Data)

  1. Ask: "What was the air quality in California in 2021?"
  2. ✅ Expect: Real EPA data with PM2.5 concentration
  3. ✅ Verify: Says "EPA Historical Air Quality Dataset"

Test 5: Current Air Quality

  1. Ask: "What's the current air quality in San Francisco?"
  2. ✅ Expect: Live AQI data from AirNow API

Test 6: Location Services

  1. Select different state from dropdown
  2. Select different city
  3. ✅ Verify: Charts update, location badge shows

Test 7: Weather & Pollen

  1. Set location to a city with ZIP
  2. ✅ Verify: Weather card shows temperature, humidity, wind
  3. ✅ Verify: Pollen card shows UPI and pollen types

Test 8: Community Reporting

  1. Click "Report an Issue" (if available in UI)
  2. Fill out form with test data
  3. Upload an image
  4. ✅ Verify: Submission successful
  5. ✅ Verify: AI analysis appears

Test 9: Officials Dashboard

  1. Navigate to /officials-dashboard
  2. ✅ Verify: Dashboard loads
  3. ✅ Verify: Reports table shows data
  4. Test filters, export features

🔍 What to Look For

✅ Good Signs

  • Video generates in ~60 seconds
  • Only ONE tweet is posted
  • Real data appears (not "Demo Mode")
  • All charts and maps load
  • No console errors
  • /health endpoint shows all services enabled

⚠️ Warning Signs

  • "Demo Mode" in responses (means BigQuery failed)
  • Multiple tweets for same video
  • 404 errors for any API endpoints
  • Charts not loading
  • Video not appearing after 90 seconds

🐛 Known Issues

Non-Critical

  1. Air quality city-specific queries may ask for more details

    • Workaround: Use state-level queries ("California" not "San Francisco")

  2. Video Manager requires full restart to initialize

    • If PSA feature shows "disabled", restart Flask

Fixed in This Branch

  • ✅ BigQuery queries now work (replaced ADK toolset)
  • ✅ Disease data returns real CDC data
  • ✅ Air quality returns real EPA data
  • ✅ Duplicate Twitter posting prevented

📊 Expected Terminal Output

Successful Video Generation

[PSA-VIDEO] Video generation requested for: California
[VIDEO_MANAGER] Task created: abc12345
[VEO3] Calling Veo 3.0 Fast API...
[VEO3] Video generation started!
...
[VEO3] Uploaded to GCS: gs://...
[VIDEO_MANAGER] Task abc12345 updated: complete

Successful Twitter Posting

[TWITTER] ===== Twitter Posting Request =====
[TWITTER] Video URL: https://storage.googleapis.com/...
[TWITTER] Downloading video...
[TWITTER] SUCCESS: Downloaded...
[TWITTER] Uploading video...
[TWITTER] SUCCESS: Video uploaded! Media ID: ...
[TWITTER] Posting tweet...
[TWITTER] SUCCESS: Tweet posted!
[TWITTER] URL: https://twitter.com/AI_mmunity/status/...

Real BigQuery Data

[DISEASE] Executing BigQuery query...
[DISEASE] Query returned 50 rows from CDC BEAM dataset

NOT:

[DISEASE] Falling back to mock data

🎯 Integration Summary

Main App: app_local.py (unified app)
Branch: integrate-to-app-local
Total Endpoints: 32 (28 original + 4 PSA video)
Breaking Changes: 0
New Dependencies: None (all existing)

Key Features:

  • ✅ PSA video generation (Veo 3.1)
  • ✅ Twitter integration (OAuth)
  • ✅ Real CDC disease data (226K rows)
  • ✅ Real EPA air quality data
  • ✅ All original team features preserved

📞 Support

Issues? Check:

  1. .env has all required API keys
  2. Flask is running (python app_local.py)
  3. /health endpoint shows all services enabled
  4. Browser console for JavaScript errors

Questions? See:

  • INTEGRATION_COMPLETE.md - Implementation details
  • PSA_VIDEO_INTEGRATION_PLAN.md - Original plan
  • Terminal logs for debugging

Happy Testing! 🎉