LlamaIndex (GPT Index) - Complete Tutorial and Semantic Search Implementation

Learn how to build semantic search applications and question-answering systems using Llama Index (formerly GPT Index) in this comprehensive tutorial. Master the fundamentals of Llama Index through step-by-step introduction and explore semantic search capabilities in depth. Build a practical "Talk to Wikipedia" application using Streamlit, GPT-3, and OpenAI embeddings in Python with VS Code. Discover how to synthesize answers across multiple vector indices using Llama Index's composable graph functionality. Explore advanced techniques for generating near-perfect Llama Index code with GPT-4 using vector databases from documentation, enabling you to create sophisticated AI-powered applications that can query and reason over large document collections.

Syllabus

Llama Index ( GPT Index) step by step introduction
Llama index (GPT index) Semantic Search in depth
Gpt index "Talk to Wikipedia" App with Streamlit, Gpt 3. OpenAI embeddings in Python, VS Code
Synthesize answers over multiple individual Vector Indices with Llama index composable graph
GPT-4 Codes near perfect Llama Index code using Vector DB from documentation