SQL Optimization Using Metadata and LLM - Sample Code

[mraguth]

I am working on the below use case. Is that possible to have sample langchain code for the workflow? Please let help.

This use case focuses on optimizing SQL queries by leveraging metadata and Large Language Models (LLMs). The process involves analyzing incoming SQL queries, utilizing metadata to understand schema structure, indexing, and performance patterns, and applying LLM-powered recommendations to generate more efficient SQL.

Workflow:
Query Interception & Analysis: The system captures user-submitted SQL queries before execution.
Metadata Utilization: Schema details, indexing, execution history, and performance metrics are analyzed to identify inefficiencies.
LLM-Powered Optimization: The model suggests query optimizations, such as restructuring joins, filtering data more effectively, or leveraging indexed columns.
Validation & Execution: The fine-tuned SQL is validated against the metadata for accuracy and efficiency before being sent back to the user.
User Feedback Loop: The system provides recommendations and explanations to improve future query-writing practices.
This approach ensures that queries run efficiently, reducing costs and enhancing performance within the data warehouse environment.