DSPy: Develop a RAG app using DSPy, Weaviate, and FastAPI

About this course

Learn to build a comprehensive full-stack Retrieval Augmented Generation (RAG) application from scratch using cutting-edge technologies like FastAPI, Weaviate, DSPy, and React. In this hands-on course, you will master the process of developing a robust backend with FastAPI, handling document uploads and parsing with DSPy, and managing vector data storage using Weaviate. You'll also create a responsive React frontend to provide users with an interactive interface. By the end of the course, you'll have the practical skills to develop and deploy AI-powered applications that leverage retrieval-augmented generation techniques for smarter data handling and response generation.

Here's the structured outline of your course with sections and lectures:

Section 1: Introduction

Lecture 1: Introduction

Lecture 2: Extra: Learn to Build an Audio AI Assistant

Lecture 3: Building the API with FastAPISection 2: File UploadLecture 4: Basic File Upload RouteLecture 5: Improved Upload Route

Section 3: Parsing Documents

Lecture 6: Parsing Text Documents

Lecture 7: Parsing PDF Documents with OCR

Section 4: Vector Database, Background Tasks, and Frontend

Lecture 8: Setting Up a Weaviate Vector StoreLecture 9: Adding Background TasksLecture 10: The Frontend, Finally!

Section 5: Extra - Build an Audio AI Assistant

Lecture 11: What You Will BuildLecture 12: The Frontend

Lecture 13: The BackendLecture 14: The End

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