RAG w/o APIs: When Function Calling Talks to Your Browser
Hosted by Jason Liu and Michael Struwig
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What you'll learn
Browser-Centric RAG Implementation
Students will understand how to architect RAG systems with the browser as the primary retrieval engine.
Client-Side Function Execution
Students will learn to implement function calling patterns where LLMs return instructions executed locally by clients.
WYSIWYG Data Integration for LLMs
Students will discover techniques to leverage browser-accessible data sources for more responsive AI interactions.
Why this topic matters
Client-first RAG architecture lets browsers connect AI directly to user data, enabling faster development and more secure integrations. This approach streamlines prototyping and respects data boundaries—skills crucial for building modern AI applications that work seamlessly with existing systems.
You'll learn from
Jason Liu
Consultant at the intersection of Information Retrieval and AI
Jason has built search and recommendation systems for the past 6 years. He has consulted and advised a dozens startups in the last year to improve their RAG systems. He is the creator of the Instructor Python library.
Michael Struwig
Head of AI at OpenBB
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