Are you looking for a step-by-step guide on how to build and deploy Retrieval-Augmented Generation (RAG) systems? I can outline a blueprint covering:
- Data Ingestion & Preprocessing (Scraping, chunking, embedding)
- Vector Database Setup (FAISS, Pinecone, Weaviate, etc.)
- Retrieval Pipeline (Similarity search, reranking)
- LLM Integration (OpenAI, Llama, or custom models)
- Deployment (API, streamlit app, LangChain, FastAPI)
Let me know if you need a high-level overview or a hands-on tutorial! 🚀