Using LlamaIndex to add personal data to LLMs

LlamaIndex is a popular retrieval-augmented generation (RAG) framework for integrating personal or domain-specific data with large language models (LLMs). It simplifies the development of AI applications like QA chatbots and data retrieval systems by providing tools for data ingestion, processing, and query workflows. This post details how to set up LlamaIndex using Python, including practical steps for data preparation, API integration, and model querying. It also compares LlamaIndex with other RAG tools like LangChain and Vellum, highlighting their unique features and use cases.