Intelligent code assistant using retrieval-augmented generation and Ollama framework

The Self-Correcting Code Assistant, Alpha, is designed to make the software development experience better by providing real-time analysis, correction, and explanation of code. Alpha ap-plies machine learning, natural language processing (NLP), retrieval-augmented generation (RAG), and static code analysis, to identify and correct both syntactic and logical errors, and provides context aware suggestions and optimization based on best practices reflecting current coding practices. Alpha encompasses both the backend built with Fast API, and the frontend built with React, so it can all be accessed in a responsive full-stack architecture that enables developers to use the assistant in whatever developer environment they choose. Alpha's capabilities are driven by a modular AI pipeline that leverages large language models (LLMs), which is further enhanced through FAISS-based vector search and retrieval, which retrieves grounded, relevant code examples.Alpha acts as a contextual coding mentor, identifying inefficiencies, flagging higher-level design considerations, and providing assistance in making stylistic im-rovements that enhance code maintainability and readability. Because of its focus on clarity, explainability, and reliability of the system, Alpha is usable for developers of all levels of experience, which includes students and educators, as well as more experienced developers who want to use AI to assist in debugging or refactoring their code.