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

Description

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

1. Lecture 1: Introduction

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

3. Lecture 3: Building the API with FastAPI

   
   

Section 2: File Upload

1. Lecture 4: Basic File Upload Route

2. Lecture 5: Improved Upload Route

Section 3: Parsing Documents

1. Lecture 6: Parsing Text Documents

2. Lecture 7: Parsing PDF Documents with OCR

Section 4: Vector Database, Background Tasks, and Frontend

1. Lecture 8: Setting Up a Weaviate Vector Store

2. Lecture 9: Adding Background Tasks

3. Lecture 10: The Frontend, Finally!

Section 5: Extra - Build an Audio AI Assistant

1. Lecture 11: What You Will Build

2. Lecture 12: The Frontend

3. Lecture 13: The Backend

4. Lecture 14: The End

Who this course is for:

• Backend Developers wanting to learn how to build APIs with FastAPI and integrate AI-driven features like document parsing and vector search.
• Full-Stack Developers seeking to gain practical experience in combining a React frontend with an AI-powered backend.
• Data Scientists and AI Practitioners who want to explore new ways to implement retrieval-augmented generation models for real-world applications.
• AI Enthusiasts curious about vector databases like Weaviate and the emerging field of RAG, with the motivation to learn and build AI-based apps from scratch.