GPT-4 Codes Near Perfect Llama Index Code Using Vector DB from Documentation

Learn how to create a comprehensive dataset of the Llama-Index documentation by crawling the website, extracting self-sufficient code blocks with explanations, and embedding the information for similarity search. Explore the process of using GPT-4 to generate complete Llama index applications from simple descriptions. Discover techniques for efficient documentation crawling, code extraction, and embedding creation. Gain insights into building powerful search capabilities using vector databases and similarity search algorithms. Follow along with code overviews and explanations for each step of the process, including documentation crawling, cleaning, code extraction, and embedding file creation. Understand the differences between including and excluding API references in your dataset. Access additional resources and code downloads to further enhance your learning experience.

Intro
DEMO
Code Download
Documentation Crawler Code overview
Docs cleaner code overview
Code Extractor explanation and review
With vs Without API reference?
Embedding file code overview
Building Llama index applications file review