Developer combines vector search with knowledge graphs for better code retrieval

A developer found that relying solely on vector search for retrieving information from codebases was insufficient because it primarily matches text and fails to capture the crucial relationships and connections within the code. To address this, the developer integrated a knowledge graph alongside vector search. This hybrid approach uses vector search and BM25 for initial localization of relevant code chunks, followed by graph traversal to map out call paths, inheritance, and other explicit code relationships, thereby providing more comprehensive answers. AI

IMPACT Hybrid retrieval systems combining vector search with graph traversal may improve code understanding and developer productivity.

RANK_REASON Developer describes a technical implementation for improving code retrieval, which is a tool-level improvement.

Read on dev.to — LLM tag →

• BM25
• retrieval-augmented generation

• infra
• other

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