This project compares Python and Node.js for identifying Data Structures and Algorithms (DSA) concepts from algorithmic problem statements using OpenAI's GPT models. By building backend services in both languages, the system processes user queries (e.g., from LeetCode) and analyzes the underlying DSA topics. The project leverages OpenAI's API to enhance the analysis of natural language questions and generate accurate, detailed insights about the required DSA concepts for solving the problem.
The system follows a modular architecture, with separate services for OpenAI integration and business logic. Each version (Python and Node.js) features components like a controller to handle API requests, a service layer for interacting with OpenAI's models, and a data layer to manage the context and insights related to DSA topics. This allows for a performance comparison between the two technologies in the context of AI-driven backend processing.