Code-Graph-RAG FAQs

Question 1

How does Code-Graph-RAG enable natural language interaction with my codebase?

Accepted Answer

It translates natural language questions into executable Cypher queries using AI (supporting OpenAI, Google Gemini, Ollama), allowing you to ask about code structure, dependencies, and functionality in plain English.

Question 2

What is the role of the knowledge graph in Code-Graph-RAG?

Accepted Answer

The knowledge graph, powered by Memgraph, stores your codebase's entire structure, relationships, and metadata. This interconnected representation is crucial for accurate retrieval-augmented generation (RAG) and precise AI interactions.

Question 3

What is Code-Graph-RAG and what does it do?

Accepted Answer

Code-Graph-RAG is an AI-powered system designed to analyze multi-language codebases, build comprehensive knowledge graphs of their structure and relationships, and enable natural language querying and advanced editing of the code.

Question 4

Which programming languages does Code-Graph-RAG support?

Accepted Answer

It provides robust multi-language support for various programming languages including Python, C++, Java, Rust, and TypeScript, leveraging Tree-sitter AST parsing for deep analysis.

Question 5

Can I edit code using Code-Graph-RAG?

Accepted Answer

Yes, Code-Graph-RAG offers advanced AI-powered code editing features, including surgical replacements based on AST, visual diff previews, and exact block modifications, all controllable via natural language.

Code-Graph-RAG

Code-Graph-RAG

Key Features

Use Cases

Key Features

Use Cases