Develop a RAG App Using DSPy, Weaviate, and FastAPI

Course Category: Generative AI

Course Description

In this module, you will learn how to build a Retrieval Augmented Generation (RAG) application using FastAPI, DSPy, and Weaviate. By the end of the course, you'll have developed a full RAG application with a React frontend that you will create from scratch. This comprehensive project will teach you how to integrate a powerful backend using FastAPI and manage data efficiently with Weaviate, a vector database. You'll also learn to handle file uploads and parse various document types to generate retrieval-augmented outputs using DSPy.

Enroll Now in Developing a RAG App Using DSPy, Weaviate, and FastAPI

Course Chapters

1. Introduction to the Course

   • Status: Free
   • Publication Status: Published
   • Description: An overview of the course and what you will learn in building a RAG application using FastAPI, DSPy, and Weaviate.

2. Building the API with FastAPI

   • Status: Published
   • Description: Learn how to set up and build the core API functionalities using FastAPI for your RAG app.

3. Basic File Upload Route

   • Status: Published
   • Description: Create a basic file upload route for your application to handle document uploads.

4. Improved Upload Route

   • Status: Published
   • Description: Enhance your file upload route with error handling and better user feedback.

5. Parsing Text Documents

   • Status: Published
   • Description: Learn how to parse plain text documents and extract meaningful content for your RAG app.

6. Parsing PDF Documents with OCR

   • Status: Published
   • Description: Incorporate Optical Character Recognition (OCR) to parse and retrieve data from PDF documents.

7. Setting Up a Weaviate Vector Store

   • Status: Published
   • Description: Set up and manage a Weaviate vector store to efficiently store and retrieve vectorized data.

8. Adding Background Tasks

   • Status: Published
   • Description: Implement background tasks in your FastAPI app to improve performance and handle time-consuming operations.

9. The Frontend, Finally!

   • Status: Published
   • Description: Build a React frontend for your RAG application, enabling users to interact with the system through a web interface.

This course is perfect for developers who want to build a full-stack RAG application, combining the power of FastAPI, DSPy, and Weaviate. By the end of the course, you will have gained practical experience in API development, vector storage, document parsing, and frontend development using React.

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