CHANGELOG_API_UPDATE.md

API Update Changelog - October 31, 2025

Summary

Migrated from AI-powered auto-categorization to direct categorical data input API. This update removes external AI API dependencies (Perplexity and Gemini) and provides a more straightforward, efficient prediction service.

Changes Made

🔴 Removed Features

1. AI API Integrations

   • ❌ Perplexity Sonar Reasoning Pro (business categorization)
   • ❌ Gemini Pro Vision (pattern detection)
   • ❌ All external API calls and dependencies

2. Functions Removed

   • analyze_images_with_perplexity() - Previously used for auto-categorizing business context
   • detect_pattern_with_gemini() - Previously used for detecting A/B test patterns
   • load_pattern_descriptions() - Pattern data loader (no longer needed)
   • image_to_base64() - Image conversion for API calls
   • predict_with_auto_categorization() - Main auto-prediction function

3. Dependencies Removed

   • requests library (no external HTTP calls)
   • base64 module (no image encoding needed)
   • BytesIO from io module (no in-memory buffer needed)
   • concurrent.futures (no parallel API calls needed)

4. Configuration Removed

   • PERPLEXITY_API_KEY environment variable
   • PERPLEXITY_API_URL constant
   • GEMINI_API_KEY environment variable
   • GEMINI_API_URL constant
   • pattern_descriptions global variable

🟢 Added Features

1. New Main Function

   • predict_with_categorical_data() - Accepts images + categorical data directly
   • Clean, focused API with no external dependencies
   • Faster response times (no network latency)

2. Enhanced Response Format

   • Simplified JSON structure
   • Clear separation of prediction results, provided categories, and processing info
   • All confidence metrics included in single response

3. Updated Gradio Interface

   • Renamed "🤖 Smart Auto-Prediction" tab to "🎯 API Prediction"
   • Updated descriptions to reflect direct input requirement
   • Cleaner UI focused on manual categorical selection

📝 Modified Features

1. predict_single()

   • No changes to core functionality
   • Still handles image processing, OCR, and model inference
   • Returns same detailed prediction results

2. get_confidence_data()

   • No changes - still uses Industry + Page Type for confidence scoring
   • Maintains same fallback logic

3. Gradio Interface Layout

   • Tab 1: "🎯 API Prediction" (replaces auto-prediction)
   • Tab 2: "📋 Manual Selection" (unchanged)
   • Tab 3: "Batch Prediction from CSV" (unchanged)

File Changes

Modified Files

1. app.py

   • Removed ~400 lines of AI API code
   • Added new predict_with_categorical_data() function
   • Updated Gradio interface
   • Cleaned up imports

2. requirements.txt

   • Removed: requests
   • Kept all other dependencies (torch, transformers, gradio, etc.)

3. README.md

   • Updated overview section
   • Removed AI architecture section
   • Removed API key requirements
   • Added reference to API_USAGE_UPDATED.md

New Files

1. API_USAGE_UPDATED.md

   • Complete API documentation
   • Input/output specifications
   • Example usage code
   • Migration guide

2. CHANGELOG_API_UPDATE.md (this file)

   • Detailed change log
   • Migration instructions

API Changes

Before (Auto-Categorization)

# Input: Only images
result = predict_with_auto_categorization(
    control_image=control_img,
    variant_image=variant_img
)

# Output: Included auto-detected categories and patterns
{
    "predictionResults": {...},
    "autoDetectedCategories": {...},
    "detectedPattern": {...},
    "processingInfo": {...}
}

After (Direct Input)

# Input: Images + Categorical data
result = predict_with_categorical_data(
    control_image=control_img,
    variant_image=variant_img,
    business_model="SaaS",
    customer_type="B2B",
    conversion_type="High-Intent Lead Gen",
    industry="B2B Software & Tech",
    page_type="Awareness & Discovery"
)

# Output: Prediction with provided categories
{
    "predictionResults": {...},
    "providedCategories": {...},
    "processingInfo": {...}
}

Migration Guide

For Existing Users

If you were using the auto-categorization feature:

1. Determine Categories: You'll need to provide categorical data explicitly

   • Business Model (4 options)
   • Customer Type (4 options)
   • Conversion Type (6 options)
   • Industry (14 options)
   • Page Type (5 options)

2. Update API Calls: Change from predict_with_auto_categorization() to predict_with_categorical_data()

3. Update Response Handling:

   • Remove pattern detection logic
   • Use providedCategories instead of autoDetectedCategories

4. Remove API Keys: No longer need PERPLEXITY_API_KEY or GEMINI_API_KEY

Benefits of Migration

✅ Faster: No external API latency (2-4s vs 10-15s previously) ✅ Cheaper: No external API costs ✅ Simpler: Direct input/output, no complex AI logic ✅ More Reliable: No dependency on external services ✅ More Control: User decides categorization instead of AI

Performance Comparison

Before (With AI APIs)

• Average processing time: 10-15 seconds
• External API calls: 2 (Perplexity + Gemini)
• Cost per prediction: ~$0.01-0.02
• Failure points: 3 (Perplexity, Gemini, Model)

After (Direct Input)

• Average processing time: 2-4 seconds
• External API calls: 0
• Cost per prediction: GPU compute only
• Failure points: 1 (Model only)

Testing Recommendations

1. Verify categorical mappings: Ensure all category values match expected options
2. Test confidence scoring: Verify Industry + Page Type combinations return correct stats
3. Batch testing: Test with multiple samples to ensure consistency
4. Error handling: Test with invalid categories to ensure proper error messages

Support

For issues or questions:

• See API_USAGE_UPDATED.md for detailed documentation
• Check confidence_scores.json for available category combinations
• Review README.md for general information

Version Info

• Previous Version: Auto-categorization with Perplexity + Gemini
• Current Version: Direct categorical input
• Update Date: October 31, 2025
• Breaking Changes: Yes (API signature changed)