Text2SQL using Amazon Bedrock forked from https://github.com/kevmyung/text-to-sql-bedrock/tree/main
This repository contains multiple labs focused on implementing Text-to-SQL using various tools and techniques. Below are the details for each lab included in this repository.
In this lab, you'll learn how to set up and use Amazon S3 and Athena to query data using SQL.
lab1_text2sql_s3_athena/1.basic-athena.ipynb: Jupyter notebook to set up the S3 and Athena.2.advanced-athena.ipynb: Jupyter notebook to run SQL queries on data stored in S3 using Athena.
This lab focuses on implementing Text-to-SQL functionality with different approaches.
lab2_text2sql_implementation/1.chain_agent_sample.ipynb: Sample notebook demonstrating chain & agent.2.function_calling_sample.ipynb: Sample notebook demonstrating function calling.
This lab involves preparing the schema documents for Text-to-SQL applications.
lab3_text2sql_schema_preparation/1.sample_queries.ipynb: Jupyter notebook for preparing the sample query documents.2.detailed_schema.ipynb: Jupyter notebook for preparing the detailed schema documents.
In this lab, you will create a Text-to-SQL application.
lab4_text2sql_app/1.setup-streamlit.ipynb: Jupyter notebook for developing the Text-to-SQL application.demo-app.py: Sample Application (main)src/...: Custom libraries for Text2SQL app.
In this lab, you will build a cyclic workflow using LangGraph
lab5_text2sql_langgraph/1.text2sql_langgraph.ipynb: Jupyter notebook for developing the Text-to-SQL workflow using LangGraph.
Refer to SETUP.md for instructions on how to set up the environment and dependencies for running the labs.
cloudformation/: Directory containing CloudFormation templates for setting up resources.


