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_TOtaint 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.
