This document provides an overview of Langchain and LlamaIndex for building applications using large language models, and includes hands-on exercises for setting up SQLite databases and using Langchain and LlamaIndex to query text data. Resources are also listed for documentation and templates related to Langchain and LlamaIndex.

1. Langchain vs LlamaIndex for
Application Building

2. Large Language Models - Overview

3. Langchain - Overview

4. LlamaIndex - Overview
LlamaIndex is an orchestration framework that simplifies the integration of
private data with public data for building applications using Large Language
Models (LLMs). It provides tools for data ingestion, indexing, and querying.

5. Hands-On – SQLite Database Setup

6. Hands-On – SQLite Database Setup

7. Hands-On – Langchain (Text-to-SQL)

8. Hands-On – Langchain (Text-to-SQL)

9. Hands-On – Langchain (Text-to-SQL)

10. Hands-On – Llamaindex (Text-to-SQL)

11. Hands-On – Llamaindex (Text-to-SQL)

12. Hands-On – Llamaindex (Text-to-SQL)

13. Resources:
• https://python.langchain.com/docs/get_started/introduction  Langchain Documentation
• templates.langchain.com/top  Langchain Templates
• https://leanpub.com/langchain/read  Langchain and LlamaIndex Projects Lab eBook
• https://llamahub.ai/  Llama Templates
• https://docs.llamaindex.ai/en/stable/index.html  Llamaindex Documentation