Thu, Mar 7, 202450:00LangGraphRAGInference
A LangGraph RAG Agent with Ollama and SurrealDB
Watch on YouTubeFrom the full recording of the nightRecorded at AIMUG, Mar 7, 2024
Write-up
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
- Google Drive setup
- LangGraph configuration
- RAG pipeline creation
- Multi-modal integration
- Agent orchestration
- 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
