================================================================================ AI USAGE REPORT (SUMMARY) Cloudzy AI Challenge - Photo Album Management System ================================================================================ PROJECT OVERVIEW ================ AI-enhanced photo management system with semantic search, album summarization, and image generation capabilities. ================================================================================ AI MODELS USED ================================================================================ 1. IMAGE EMBEDDING: intfloat/multilingual-e5-large - Location: cloudzy/ai_utils.py (ImageEmbeddingGenerator) - Purpose: Convert photo metadata into 1024-d vectors for similarity search - Used in: Photo upload, semantic search, album clustering 2. SUMMARIZATION: facebook/bart-large-cnn - Location: cloudzy/ai_utils.py (TextSummarizer) - Purpose: Generate summaries of photo clusters - Used in: /albums endpoint (creates album descriptions) 3. IMAGE ANALYSIS: Google Gemini 2.0-flash - Location: cloudzy/agents/image_analyzer_2.py (ImageAnalyzerAgent) - Purpose: Analyze images and generate detailed descriptions - Used in: /generate-similar-image endpoint (Step 1) 4. IMAGE GENERATION: black-forest-labs/FLUX.1-dev - Location: cloudzy/inference_models/text_to_image.py (TextToImageGenerator) - Purpose: Generate high-quality images from text prompts - Used in: /generate-similar-image endpoint (Step 3) ================================================================================ MANUAL VS AI-GENERATED ================================================================================ MANUAL WORK (100% Developer-Written): ✓ Database schema, API routes, file management ✓ FastAPI application setup and middleware ✓ Error handling and validation logic ✓ File upload service and utilities ✓ FAISS vector search implementation HYBRID (Manual Integration + AI Models): ✓ ImageEmbeddingGenerator: Text → 1024-d embeddings (AI model) ✓ TextSummarizer: Metadata → album summary (AI model) ✓ ImageAnalyzerAgent: Image → description (AI model) ✓ TextToImageGenerator: Prompt → generated image (AI model) AI-GENERATED CONTENT: ✓ Embedding vectors (semantic representations) ✓ Album summaries (cluster descriptions) ✓ Image descriptions (visual analysis) ✓ Generated images (from text prompts) ================================================================================ NEW ENDPOINT: /generate-similar-image ================================================================================ Endpoint: POST /generate-similar-image Location: cloudzy/routes/generate.py Workflow: 1. User uploads an image 2. ImageAnalyzerAgent analyzes it → gets description 3. TextToImageGenerator creates new image from description 4. Returns generated image URL + description Response: { "description": "Detailed image analysis from Gemini", "generated_image_url": "http://127.0.0.1:8000/uploads/generated_20241025_123456_789.png", "message": "Similar image generated successfully" } Performance: ~40-75 seconds per request - Image analysis: ~5-10s (Gemini) - Image generation: ~30-60s (FLUX.1-dev) ================================================================================ PROMPTS USED IN PROJECT ================================================================================ 1. IMAGE ANALYSIS PROMPT (ImageAnalyzerAgent - Gemini): Location: cloudzy/agents/image_analyzer_2.py "Describe this image in a way that could be used as a prompt for generating a new image inspired by it. Focus on the main subjects, composition, style, mood, and colors. Avoid mentioning specific names or exact details — instead, describe the overall aesthetic and atmosphere so the result feels similar but not identical." 2. IMAGE GENERATION PROMPT: - Input: Description from ImageAnalyzerAgent (above) - Model: FLUX.1-dev (black-forest-labs/FLUX.1-dev) - Location: cloudzy/inference_models/text_to_image.py - Strategy: Direct prompt passing to image generation model ================================================================================ ENVIRONMENT VARIABLES ================================================================================ Required: - HF_TOKEN: Hugging Face API key (embeddings, summarization) - GEMINI_API_KEY: Google Gemini API key (image analysis) - HF_TOKEN_1: Alternative HF token (image generation) - APP_DOMAIN: App URL (default: http://127.0.0.1:8000/) ================================================================================ KEY DECISIONS ================================================================================ 1. Used FLUX.1-dev for high-quality image generation (vs Stable Diffusion) 2. Composable pipeline: ImageAnalyzer → TextToImageGenerator (reusable components) 3. Graceful error handling with fallbacks when APIs unavailable 4. Temporary file handling: saves uploads locally for Gemini analysis ================================================================================ SUMMARY ================================================================================ This project integrates 4 AI models responsibly: - Embeddings for semantic search - Summarization for album descriptions - Vision AI for image analysis - Generative AI for image creation All manual work handles infrastructure, logic, validation, and error handling. AI models are called for their specialized tasks only. New capability: Generate creative image variations from uploaded photos using intelligent analysis + high-quality generation pipeline. ================================================================================