SQL to Natural Language Converter

Project Description

An NLP pipeline that translates SQL queries into human-readable natural language questions using Transformer-based models like T5.

Key Features

• Automated conversion of SQL queries to natural language questions
• Modular architecture for scalability and maintainability
• Comprehensive logging and error handling using Loguru
• Postprocessing steps to enhance output quality
• Evaluation metrics including BLEU, METEOR, and ROUGE-L

Challenges and Solutions

Integrating multiple models into a cohesive pipeline was challenging, especially ensuring data flow consistency and handling model dependencies. I addressed this by implementing robust error handling and modularizing the code for better manageability.