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How does hybrid search rank code?
The retrieval pipeline combines lexical and vector candidates with reciprocal-rank fusion, then expands high-confidence symbols through the dependency graph.
hybrid.ts:84–112
Results are deduplicated by chunk identity before the final relevance sort.
For investigative queries, neighboring callers and callees are added within a bounded graph depth.
Repository-first intelligence
From Git URL to explainable answers.
Connect
Add a public or private GitHub repository.
Index
AST-aware chunks, symbols, embeddings, and relationships.
Understand
Ask questions with answers grounded in exact source lines.
Designed for trust
Every answer has a path back to source.
RepoMind keeps retrieval visible: strategy, files, symbols, timing, and exact line citations are first-class product data.
Hybrid retrieval
Vector, lexical, graph, and reranking strategies.
Code graph
Explore callers, callees, imports, and symbol relationships.
Commit-aware
Every index is tied to branch and commit metadata.
Evaluation built in
Measure hit rate, citation quality, latency, and confidence.