End to End RAG System with Hybrid Search and Streamlit | Day 16 | Day 47/365 скачать в хорошем качестве

End to End RAG System with Hybrid Search and Streamlit | Day 16 | Day 47/365

Day 16 of 30 Days of Understanding the Modern AI Stack. Today we build a complete Hybrid RAG system from scratch. This is not just a chatbot. We implement: • Document ingestion • Semantic chunking • Embedding generation using SentenceTransformers • Vector storage using Chroma • Hybrid retrieval (semantic + keyword scoring) • Grounded answer generation using Gemini • Python UI using Streamlit The system retrieves relevant context first, then generates an answer based only on retrieved chunks. This is how modern AI assistants are built in production. You will see the full architecture, the retrieval pipeline, and the working demo. 🔗 GitHub Repository Full source code available here(it is a different project but yeah the same thing): https://github.com/iamjustkrishna/Leg... 🧠 What You’ll Learn • How embeddings power semantic search • Why hybrid search improves retrieval precision • How to combine vector similarity with keyword scoring • How RAG systems prevent hallucination • How to build a complete pipeline end to end Next in the series we will learn more.