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fix(rag): normalize vector search to distance semantics

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youhuanghe
2026-03-12 12:33:09 +00:00
parent d7df1f05d1
commit 077e631c13
1 changed files with 2 additions and 2 deletions
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4
src/langbot/pkg/vector/mgr.py
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@@ -100,7 +100,7 @@ class VectorDBManager:
) -> list[dict]: ) -> list[dict]:
"""Proxy: Search vectors. """Proxy: Search vectors.
Returns a list of dicts with keys: 'id', 'score', 'metadata'. Returns a list of dicts with keys: 'id', 'distance', 'metadata'.
The underlying VectorDatabase.search returns Chroma-style format: The underlying VectorDatabase.search returns Chroma-style format:
{ 'ids': [['id1']], 'distances': [[0.1]], 'metadatas': [[{}]] } { 'ids': [['id1']], 'distances': [[0.1]], 'metadatas': [[{}]] }
""" """
@@ -130,7 +130,7 @@ class VectorDBManager:
parsed_results.append( parsed_results.append(
{ {
'id': id_val, 'id': id_val,
'score': r_dists[i] if r_dists and i < len(r_dists) else 0.0, 'distance': r_dists[i] if r_dists and i < len(r_dists) else 0.0,
'metadata': r_metas[i] if r_metas and i < len(r_metas) else {}, 'metadata': r_metas[i] if r_metas and i < len(r_metas) else {},
} }
) )