Project: Full RAG Implementation in LangGraph

Description

Description: The final step! We implement a full Retrieval-Augmented Generation (RAG) workflow. Learn how to ingest documents into a FAISS vector database, normalize embeddings, and coordinate multiple agents to produce high-quality research reports. Chapters: 0:00 Capstone Workflow Walkthrough 1:35 Designing the Project State 2:45 Setting up the Vector Database (FAISS) 4:10 Understanding Embedding Normalization (L2) 5:30 Building the Retrieval Helper Function 7:00 Defining the Summarizer and Writer Nodes 9:15 The Router Agent Logic 10:45 Final Graph Compilation and Multi-Agent Run 13:00 Results: Researching LangGraph & Vector DBs #RAG #FAISS #LangGraph #VectorDatabase #AIAgents #Python