Full-Stack RAG with Next.js, Supabase & Gemini

Name: Full-Stack RAG with Next.js, Supabase & Gemini
Availability: InStock
Author: FreeAcademy

Advanced

Requires solid understanding. Complex topics.

Master the principles, architecture, and core components required to build production-ready RAG applications. Learn to create custom knowledge chatbots using Next.js, Supabase with pgvector, and Google's Gemini API. Perfect for JavaScript/Next.js developers who want to integrate advanced AI features.

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Course Content

7 modules • 17 lessons

Course Introduction

1 lesson

1.1

Welcome to Full-Stack RAG

Module 1: Foundational Theory - LLMs, Vectors, and RAG

3 lessons

2.1

Understanding Retrieval-Augmented Generation (RAG)

2.2

Full-Stack RAG with Next.js, Supabase & Gemini

Course Content

Course Introduction

Welcome to Full-Stack RAG

Module 1: Foundational Theory - LLMs, Vectors, and RAG

Understanding Retrieval-Augmented Generation (RAG)

The Role of Vector Embeddings

Architectural Overview: The Next.js & Supabase Stack

Module 2: The Indexing Phase - Building the Knowledge Base

Document Preparation: The Art of Chunking

Vectorization and Storage

Supabase Search Functionality (Postgres RPC)

Module 3: The RAG Core - Retrieval & Generation

Retrieval Science: Finding Context

Prompt Engineering for Grounding

The Generation Phase: Calling Gemini

Module 4: Building the Production-Ready Chat Architecture

Frontend and Backend Communication

Security and Row-Level Access

Attribution and Citations

Module 5: Optimization and Advanced RAG Techniques

Improving Retrieval Quality

Conversational RAG

Performance and Cost Optimization

Course Conclusion

Final Project and Next Steps