Explore the power of Retrieval-Augmented Generation (RAG) in AI development through this comprehensive tutorial video. Learn how to equip AI agents with a "second brain" for enhanced data processing and context utilization. Discover the fundamentals of RAG, its implementation using PyAutogen, RetrieveChat, and Flaml AutoML, and practical examples showcasing code generation, question-answering, and complex query handling. Gain insights into environment setup, API key management, and RAG component configuration for optimal performance. Perfect for AI enthusiasts, developers, and anyone interested in advancing their understanding of AI's evolving capabilities.
AutoGen RAG - Creating AI Agents with a Second Brain
Overview
Syllabus
- Introduction to RAG and its Importance
- What is RAG? An Overview
- Setting Up Your RAG Environment
- Implementing RAG: First Steps
- Examples: Code Generation and Q&A with RAG
- Advanced Techniques: Human Feedback and Multihop Questions
- Conclusion and What's Next
Taught by
Mervin Praison
