Steven Gonsalvez

Software Engineer

vitali87/code-graph-rag: The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

Why CEREBRO kept it

Knowledge graph RAG for codebases; coding agent tooling

The text below is an automated extraction of the article at https://github.com/vitali87/code-graph-rag, stored verbatim in the public cerebro-vault repository. Copyright remains with the original publisher (github.com).

Code-Graph-RAG parses a multi-language codebase with Tree-sitter, builds a knowledge graph of its structure in Memgraph, and lets you query, edit, and optimise that code in plain English. It works across a monorepo of mixed languages under one unified graph schema. - Release Automation: NEWS.mdand the README's "Latest News" section now refresh automatically on every release, keeping the changelog current without hand edits. - Ruby Support: Ruby joins the graph through a new pluggable ast-grep tier that adds a language from a single YAML pattern file, emitting Module,Function, andClassnodes plu

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