Skip to main content

LangGraph RAG Integration

Lab Overview​

Learn how to integrate RAG with Google Drive using LangGraph, enabling sophisticated document processing and multi-modal capabilities.

Lab Materials​

Key Topics​

  • LangGraph fundamentals
  • Google Drive integration
  • RAG implementation
  • Multi-modal processing
  • CSV data handling

Features​

  • Document integration
  • Graph-based workflows
  • Multi-modal capabilities
  • Data processing
  • Agent orchestration

Technical Components​

  • LangGraph setup
  • Google Drive API
  • RAG pipeline
  • Agent configuration
  • Data processing tools

Implementation Steps​

  1. Google Drive setup
  2. LangGraph configuration
  3. RAG pipeline creation
  4. Multi-modal integration
  5. Agent orchestration
  6. Testing and validation

Best Practices​

  • Graph design patterns
  • Agent coordination
  • Error handling
  • Performance optimization
  • Security considerations

Prerequisites​

  • Google Colab account
  • OpenAI API key
  • Google Drive access
  • Docker Desktop
  • Basic understanding of:
    • LangChain concepts
    • Graph theory
    • Python programming

Resources​