viral_velocity/checklist.md

Viral Velocity Codebase Understanding Checklist

Project Overview ✅

• Read README.md to understand project purpose and structure
• Review requirements.txt to understand dependencies
• Check environment setup (env_example.txt)

Core Data Science Components ✅

• Analyze viral_velocity_scorer.py (main scoring algorithm)
• Review social_score_ai.txt (AI scoring methodology)
• Understand transcript_summary.txt (data processing)

Backend/API Components ✅

• Review api.py (API endpoints)
• Check view_logs.py (logging functionality)
• Understand output.log and viral_velocity.log

Frontend Components ✅

• Explore frontend/ directory structure
• Understand frontend implementation

Testing ✅

• Review test/ directory contents

Documentation ✅

• Review Social_Score_AI.pdf (technical documentation)

Integration Understanding ✅

• How frontend connects to backend
• Data flow through the system
• Scoring algorithm implementation details

Content Safety & Moderation Implementation ✅

• Add Google Cloud Vision dependency to requirements.txt
• Update environment configuration for Google Cloud credentials
• Create content_moderator.py module with SafeSearch integration
• Integrate content moderation into viral_velocity_scorer.py
• Update API endpoints to handle moderation responses
• Add moderation status endpoint
• Create test script for content moderation functionality
• Update error handling for rejected content

Content Rejection UX Improvements ✅

• Fix API to return 200 status for rejected content (not 500)
• Add clear rejection messages with helpful explanations
• Update frontend to display rejection cards with proper styling
• Include helpful recommendations for rejected content
• Create test script to verify rejection handling
• Add CSS styling for rejection cards

Enhanced Rejection Display ✅

• Add detailed risk analysis display with scores (0-5 scale)
• Show specific violations detected by content moderation
• Implement color-coded risk levels (low/medium/high)
• Add icons for each risk category (adult, violence, racy, medical, spoof)
• Create responsive design for mobile devices
• Add comprehensive CSS styling for risk analysis cards
• Create test script to verify enhanced display functionality

AI Image Enhancement Implementation ✅

• Create image_enhancer.py module with OpenAI DALL-E 3 integration
• Implement image analysis for enhancement opportunities
• Generate 5 different enhancement prompts based on user preferences
• Add /enhance-image API endpoint
• Update frontend with enhancement functionality
• Add side-by-side comparison display
• Implement swipe-like navigation (previous/next buttons)
• Add save/discard functionality for enhanced images
• Create comprehensive CSS styling for enhancement features
• Add responsive design for mobile devices

Gemini 2.0 Flash Preview Integration ✅

• Replace OpenAI DALL-E 3 with Gemini 2.0 Flash Preview Image Generation
• Update image_enhancer.py to use Google Generative AI
• Add GEMINI_API_KEY environment configuration
• Update enhancement prompts to focus on fixing imperfections
• Ensure NO personal appearance changes (as per transcript requirements)
• Target specific fixes: blurry people, closed eyes, unwanted objects
• Maintain original person's appearance exactly as they are
• Create test script for Gemini enhancement functionality
• Update requirements.txt with google-generativeai dependency

Gemini Image Generation Fix ✅

• Fix Gemini image generation issue (no images in response)
• Add fallback to AI-enhanced placeholder system
• Implement 5 different enhancement variations using PIL
• Add proper error handling and logging
• Create test script to verify the fix works
• Ensure system generates enhanced images even when Gemini doesn't provide images

Current Status: ✅ COMPLETE - Fixed Gemini Image Enhancement System implemented