README.md

Multi-Agentic SQL Generator

The Multi-Agentic SQL Generator is a modular, multi-step system that translates natural language queries into SQL queries, validates and optimizes them, and then executes them against a SQLite database. The system leverages OpenAI's language models (via a LangGraph workflow) for query understanding, validation, and optimization. It also provides evaluation capabilities using RAGAS metrics (such as context precision and context recall) to assess performance and quality.

Capabilities

• Natural Language Query Understanding:
  Converts natural language queries into structured SQL metadata according to a predefined database schema.

• Query Validation:
  Checks the generated SQL for syntax errors and security risks (e.g., harmful operations like DROP, DELETE).

• Query Optimization:
  Optimizes SQL queries for performance, ensuring only the necessary columns, joins, and filtering conditions are included.

• SQL Execution:
  Executes the optimized SQL query against a SQLite database and returns the results.

• Evaluation with RAGAS Metrics:
  Evaluates the generated output using metrics like:

  • Faithfulness: How closely the output matches the expected result.
  • Answer Relevancy: How well the result addresses the user query.
  • Context Precision: Whether the query returns only the necessary data.
  • Context Recall: Whether the query returns all required data.

• Extensibility and Deployment:
  Easily integrable with front-end frameworks (e.g., Chainlit) and deployable on platforms like Hugging Face Spaces.

Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/multi-agent-sql-generator.git
   cd multi-agent-sql-generator