Back to Projects
Generative AIintermediate

Realtime Source Code Analyzer

Source Code Analyzer is a generative AI–powered application that lets users point a GitHub repository at the system and then ask natural-language questions about that codebase. The system clones the repo, indexes Python source files, embeds them in a vector store, and answers questions using retrieval-augmented generation (RAG) with conversational memory. Target users: Developers, researchers, and technical reviewers who want to explore or understand unfamiliar Python repositories without reading every file.

10 lectures

What You Will Learn

Master building Retrieval-Augmented Generation (RAG) pipelines for code understanding.
Implement a web application using Flask for serving UI and chat/ingestion APIs.
Understand document loading, chunking, and embedding workflows with LangChain.
Gain experience integrating embeddings and chat models for semantic search and Q&A.
Develop vector store operations using ChromaDB for persistent code indexing.
Implement conversational memory for multi-turn code Q&A using LangChain chains.

System Architecture

Realtime Source Code Analyzer Architecture Diagram

High-level architecture overview of the Realtime Source Code Analyzer .

What You'll Build

  • A "Source Code Analysis" application capable of answering natural-language questions about any Python GitHub repository.
  • A RAG pipeline that clones repositories, indexes Python source files, and retrieves relevant code chunks for context.
  • A Flask backend that serves a web interface for repository URL submission and chat-based Q&A.
  • A vector database (ChromaDB) for semantic search over code chunks.
  • A conversational Q&A system with memory for follow-up questions.
Premium
One Subscription. 40+ Projects. Unlimited Access.
AccessMobile & Web