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Update query to return embedding: Sequence[float] in QueryResult… #71

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Update query to return embedding: Sequence[float] in QueryResult… #71

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7 changes: 6 additions & 1 deletion tidb_vector/integrations/vector_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
import logging
import enum
import uuid
from typing import Type, Tuple, Any, Dict, Generator, Iterable, List, Optional
from typing import Sequence, Type, Tuple, Any, Dict, Generator, Iterable, List, Optional

import sqlalchemy
from sqlalchemy.orm import Session, declarative_base
Expand Down Expand Up @@ -73,6 +73,7 @@ class QueryResult:
document: str
metadata: dict
distance: float
embedding: Sequence[float]


class TiDBVectorClient:
Expand Down Expand Up @@ -303,6 +304,7 @@ def query(
metadata=doc.meta,
id=doc.id,
distance=doc.distance,
embedding=doc.embedding,
)
for doc in relevant_docs
]
Expand All @@ -326,6 +328,7 @@ def _vector_search(
self._table_model.id,
self._table_model.meta,
self._table_model.document,
self._table_model.embedding,
self.distance_strategy(query_embedding).label("distance"),
)
.filter(filter_by)
Expand All @@ -342,6 +345,7 @@ def _vector_search(
self._table_model.id,
self._table_model.meta,
self._table_model.document,
self._table_model.embedding,
self.distance_strategy(query_embedding).label("distance"),
)
.order_by(sqlalchemy.asc("distance"))
Expand All @@ -354,6 +358,7 @@ def _vector_search(
subquery.c.id,
subquery.c.meta,
subquery.c.document,
subquery.c.embedding,
subquery.c.distance,
)
.filter(filter_by)
Expand Down