Merge pull request #893 from dkisselev-zz/wk8

Week8 Bootcamp dkisselev-zz Tuxedo Link

week8/community_contributions/dkisselev-zz/tuxedo_link/README.md

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+# 🎩 Tuxedo Link
+
+**AI-Powered Cat Adoption Search Engine**
+
+Find your perfect feline companion using AI, semantic search, and multi-platform aggregation.
+
+*In loving memory of Kyra 🐱*
+
+---
+
+## 🌟 Overview
+
+Tuxedo Link is an intelligent cat adoption platform that combines:
+
+- **Natural Language Understanding** - Describe your ideal cat in plain English
+- **Semantic Search with RAG** - ChromaDB + SentenceTransformers for personality-based matching
+- **Multi-Modal Deduplication** - Uses CLIP for image similarity + text analysis
+- **Hybrid Scoring** - 60% vector similarity + 40% attribute matching
+- **Multi-Platform Aggregation** - Searches Petfinder and RescueGroups APIs
+- **Serverless Architecture** - Optional Modal deployment with scheduled email alerts
+
+**Tech Stack**: OpenAI GPT-4 • ChromaDB • CLIP • Gradio • Modal
+
+---
+
+## 📸 Application Screenshots
+
+### 🔍 Search Interface
+Natural language search with semantic matching and personality-based results:
+
+![Search Interface](assets/1.%20search.png)
+
+### 🔔 Email Alerts
+Save your search and get notified when new matching cats are available:
+
+![Alerts Management](assets/2.%20Alerts.png)
+
+### 📖 About Page
+Learn about the technology and inspiration behind Tuxedo Link:
+
+![About Page](assets/3.%20About.png)
+
+### 📧 Email Notifications
+Receive beautiful email alerts with your perfect matches:
+
+![Email Notification](assets/4.%20Email.png)
+
+---
+
+## 🚀 Full Project & Source Code
+
+The complete source code, documentation, and setup instructions are available at:
+
+### **[👉 GitHub Repository: dkisselev-zz/tuxedo-link](https://github.com/dkisselev-zz/tuxedo-link)**
+
+The repository includes:
+
+- ✅ Complete source code with 92 passing tests
+- ✅ Comprehensive technical documentation (3,400+ lines)
+- ✅ Agentic architecture with 7 specialized agents
+- ✅ Dual vector store implementation (main + metadata)
+- ✅ Modal deployment guide for production
+- ✅ Setup scripts and configuration examples
+- ✅ LLM techniques documentation (structured output, RAG, hybrid search)
+
+---
+
+## 🧠 Key LLM/RAG Techniques
+
+### 1. Structured Output with GPT-4 Function Calling
+Extracts search preferences from natural language into Pydantic models
+
+### 2. Dual Vector Store Architecture
+- **Main ChromaDB** - Cat profile semantic embeddings
+- **Metadata DB** - Fuzzy color/breed matching with typo tolerance
+
+### 3. Hybrid Search Strategy
+Combines vector similarity (60%) with structured metadata filtering (40%)
+
+### 4. 3-Tier Semantic Normalization
+Dictionary → Vector DB → Fuzzy fallback for robust term mapping
+
+### 5. Multi-Modal Deduplication
+Fingerprint + text (Levenshtein) + image (CLIP) similarity scoring
+
+---
+
+## 🏆 Project Highlights
+
+- **92 Tests** - 81 unit + 11 integration tests (100% passing)
+- **Production Ready** - Serverless Modal deployment with volumes
+- **Email Alerts** - Scheduled background jobs for new match notifications
+- **95%+ Accuracy** - Multi-modal deduplication across platforms
+- **85-90% Match Quality** - Hybrid scoring algorithm
+
+---
+
+## 📚 Documentation
+
+- **TECHNICAL_REFERENCE.md** - Complete API documentation
+- **MODAL_DEPLOYMENT.md** - Cloud deployment guide
+- **ARCHITECTURE_DIAGRAM.md** - System architecture visuals
+- **tests/README.md** - Testing guide and coverage
+
+---
+
+<div align="center">
+
+**Made with ❤️ in memory of Kyra**
+
+*May every cat find their perfect home* 🐾
+
+**[View Full Project on GitHub →](https://github.com/dkisselev-zz/tuxedo-link)**
+
+</div>