Project: Full RAG Implementation in LangGraph
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-Age…
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Chapters (9)
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
DeepCamp AI