GraphRAG Crash Course (Generative AI)

RAG is amongst the most important concepts in Generative AI that help you to talk to your external files like CSV, JSON, PDF, YouTube videos, etc.

GraphRAG is an advanced version of standard RAG that uses Knowledge Bases instead of vector similarity and vector DBs for retrieval from external documents, making the retrieval more comprehensive and wholesome.

This crash course helps beginners to get started with GraphRAG using LangChain.

This course comprises Theoretical explanations and video lectures alongside codes to practice covering

1. Theory:

• What is GraphRAG?
• How does RAG work?
• What is a Knowledge Graph?
• Issues with standard RAG
• How does GraphRAG work?
• Example Workflow
• Global Search vs. Local Search in GraphRAG

2. Codes (jupyter notebooks)

• GraphRAG using LangChain
• GraphRAG for CSV file
• GraphRAG for JSON file
• GraphRAG Knowledge Base Creation & Visualization
• GraphRAG vs standard RAG comparison (on text data)
• Llama 3.1 for GraphRAG
• Improving GraphRAG using LangGraph
• GraphRAG issues demonstrated
• Hybrid RAG

Alongside video tutorials playlist.

Hope this crash course helps you learn GraphRAG!