Overview

Code-Graph-RAG revolutionizes how you interact with your codebase. It transforms your multi-language monorepo into a queryable knowledge graph, powered by AI and sophisticated parsing. Understand, navigate, and even edit your code with unprecedented ease, using natural language prompts.

Key Features

• Unified Monorepo Understanding: Integrates diverse languages (Python, TypeScript, Java, C++, Go, Rust, and more) into a single, coherent knowledge graph.
• AI-Powered Code Interaction: Ask complex questions about your codebase in plain English and receive grounded, accurate answers.
• Intelligent Code Editing: Edit code surgically via an AI agent, with AST-based patching and a preview of changes before they're committed.
• Structural Analysis & Optimization: Detect dead code, optimize against best practices, and perform structural searches and rewrites using AST patterns.
• Data-Flow Tracing: Follow the path of data through your code with FLOWS_TO taint edges, enhancing security and debugging.
• Extensible Language Support: Easily add new languages through a pluggable AST-grep tier.

Typical Use Cases

• Rapid Onboarding: Quickly get new team members up to speed by letting them query and explore the codebase naturally.
• Complex System Analysis: Understand intricate dependencies and data flows within large, multi-language projects.
• Automated Code Refactoring: Safely and efficiently refactor codebases at scale, improving maintainability and performance.
• Security Auditing: Identify vulnerabilities by tracing data flows and understanding code structure.
• Developer Productivity Boost: Streamline common tasks like finding specific functions, understanding code intent, and optimizing code segments.