Project Completed. Now I’m Going to Break It Down.

Project Completed. Now I’m Going to Break It Down.
I recently finished building a full-stack semantic search engine — not just keyword search, but real context-aware search✨
Before I start sharing how each part works, here’s the big picture:
🔎 What it does
Parses any website into semantic HTML chunks (≤500 tokens)
Uses AI embeddings to understand meaning, not keywords
Returns top-10 relevant results with 0–100% match scores
Keeps the original HTML structure intact on output
⚙️ Tech behind it
Backend: Django 5 + Django REST Framework
Frontend: React 18 + Vite
AI/ML: Sentence-Transformers + BERT tokenizer
Vector DB: Milvus Lite (with smart fallback)
💡 Favorite part
If Milvus isn’t available, the system doesn’t break — it automatically switches to in-process cosine similarity without changing the output. No failures, just graceful fallback.
🎥 In the next posts, I’ll share:
2: Technical Deep Dive - NLP Pipeline
3: React Architecture Excellence
4: Django REST API Best Practices
Stay tuned. This one’s going to be fun. 🔥
hashtag#SemanticSearch hashtag#AI hashtag#Python hashtag#Django hashtag#React hashtag#MachineLearning hashtag#FullStackDevelopment