Build 5 Advanced SQL Agents with LLMs

This project features a suite of 5 advanced AI-powered agents designed to assist with various SQL database tasks, leveraging OpenAI's LLMs.

Features

1. Text-to-SQL Generator: Converts natural language questions into executable SQL queries.
2. SQL Query Optimizer: Analyzes existing SQL queries and suggests performance optimizations.
3. SQL Explainer: Translates complex SQL queries into plain English explanations.
4. Database Documenter: Generates comprehensive markdown documentation for your database schema.
5. Data Analysis Assistant: Executes queries and provides AI-driven insights and visualization suggestions based on the results.

Setup

1. Clone the repository:

   git clone https://github.com/shravyayermalblueprints/Build_SQL_AI_AGENTS_WITH_LLM_Models.git
   cd Build_SQL_AI_AGENTS_WITH_LLM_Models

2. Install dependencies:

   pip install -r requirements.txt

3. Configure Environment:

   • Create a .env file in the root directory.
   • Add your OpenAI API Key:

     OPENAI_API_KEY=your_api_key_here
     DB_CONNECTION_STRING=sqlite:///sample.db

Usage

Run the agents using the CLI interface:

1. Text-to-SQL

python3 -m sql_agents.main text_to_sql --query "Show me all users"

2. Optimizer

python3 -m sql_agents.main optimizer --query "SELECT * FROM users WHERE name = 'Alice'"

3. Explainer

python3 -m sql_agents.main explainer --query "SELECT count(*) FROM users GROUP BY email"

4. Documenter

python3 -m sql_agents.main documenter

5. Analyst

python3 -m sql_agents.main analyst --query "SELECT * FROM users"

Project Structure

• sql_agents/agents/: Implementation of each agent.
• sql_agents/utils/: Utility functions (database connection).
• sql_agents/main.py: Main CLI entry point.