Coder Buddy – An Agentic AI-Powered Python Development Assistant for Code Review, Code Generation, and Automated Mini Project Building

Abstract: The growing demand for intelligent programming assistants has led to the development of agentic AI systems that can autonomously plan and execute multi-step development tasks. This paper presents Coder Buddy, an agentic AI application designed to assist Python developers with three core capabilities: automated code review, prompt-based code generation, and complete mini project building. The system combines rule-based static analysis with Large Language Models (LLMs) to deliver accurate, context-aware feedback and generate production-ready Python code. A key feature of the system is its ability to auto-detect user intent and dynamically generate either CLI or GUI (Streamlit-based) projects with proper folder structure, dependency files, and runnable output. The application is built using Python and Streamlit, and maintains session-based history for all interactions. Evaluation across simulated development scenarios demonstrates the system's effectiveness in improving code quality, reducing development time, and supporting learning and rapid prototyping.

Keywords: Agentic AI, Code Review, Code Generation, Large Language Models, Python, Streamlit, AST Analysis, Mini Project Builder, Automated Software Development