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chore: Make the private variable __vs to semi private #206

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chore: Make the private variable __vs to semi private
dishaprakash Apr 28, 2025
03450db
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dishaprakash Apr 28, 2025
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78 changes: 38 additions & 40 deletions langchain_postgres/v2/vectorstores.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ def __init__(self, key: object, engine: PGEngine, vs: AsyncPGVectorStore):
)

self._engine = engine
self.__vs = vs
self._vs = vs

@classmethod
async def create(
Expand Down Expand Up @@ -166,7 +166,7 @@ def create_sync(

@property
def embeddings(self) -> Embeddings:
return self.__vs.embedding_service
return self._vs.embedding_service

async def aadd_embeddings(
self,
Expand All @@ -178,7 +178,7 @@ async def aadd_embeddings(
) -> list[str]:
"""Add data along with embeddings to the table."""
return await self._engine._run_as_async(
self.__vs.aadd_embeddings(texts, embeddings, metadatas, ids, **kwargs)
self._vs.aadd_embeddings(texts, embeddings, metadatas, ids, **kwargs)
)

async def aadd_texts(
Expand All @@ -194,7 +194,7 @@ async def aadd_texts(
:class:`InvalidTextRepresentationError <asyncpg.exceptions.InvalidTextRepresentationError>`: if the `ids` data type does not match that of the `id_column`.
"""
return await self._engine._run_as_async(
self.__vs.aadd_texts(texts, metadatas, ids, **kwargs)
self._vs.aadd_texts(texts, metadatas, ids, **kwargs)
)

async def aadd_documents(
Expand All @@ -209,7 +209,7 @@ async def aadd_documents(
:class:`InvalidTextRepresentationError <asyncpg.exceptions.InvalidTextRepresentationError>`: if the `ids` data type does not match that of the `id_column`.
"""
return await self._engine._run_as_async(
self.__vs.aadd_documents(documents, ids, **kwargs)
self._vs.aadd_documents(documents, ids, **kwargs)
)

def add_embeddings(
Expand All @@ -222,7 +222,7 @@ def add_embeddings(
) -> list[str]:
"""Add data along with embeddings to the table."""
return self._engine._run_as_sync(
self.__vs.aadd_embeddings(texts, embeddings, metadatas, ids, **kwargs)
self._vs.aadd_embeddings(texts, embeddings, metadatas, ids, **kwargs)
)

def add_texts(
Expand All @@ -238,7 +238,7 @@ def add_texts(
:class:`InvalidTextRepresentationError <asyncpg.exceptions.InvalidTextRepresentationError>`: if the `ids` data type does not match that of the `id_column`.
"""
return self._engine._run_as_sync(
self.__vs.aadd_texts(texts, metadatas, ids, **kwargs)
self._vs.aadd_texts(texts, metadatas, ids, **kwargs)
)

def add_documents(
Expand All @@ -253,7 +253,7 @@ def add_documents(
:class:`InvalidTextRepresentationError <asyncpg.exceptions.InvalidTextRepresentationError>`: if the `ids` data type does not match that of the `id_column`.
"""
return self._engine._run_as_sync(
self.__vs.aadd_documents(documents, ids, **kwargs)
self._vs.aadd_documents(documents, ids, **kwargs)
)

async def adelete(
Expand All @@ -266,7 +266,7 @@ async def adelete(
Raises:
:class:`InvalidTextRepresentationError <asyncpg.exceptions.InvalidTextRepresentationError>`: if the `ids` data type does not match that of the `id_column`.
"""
return await self._engine._run_as_async(self.__vs.adelete(ids, **kwargs))
return await self._engine._run_as_async(self._vs.adelete(ids, **kwargs))

def delete(
self,
Expand All @@ -278,7 +278,7 @@ def delete(
Raises:
:class:`InvalidTextRepresentationError <asyncpg.exceptions.InvalidTextRepresentationError>`: if the `ids` data type does not match that of the `id_column`.
"""
return self._engine._run_as_sync(self.__vs.adelete(ids, **kwargs))
return self._engine._run_as_sync(self._vs.adelete(ids, **kwargs))

@classmethod
async def afrom_texts( # type: ignore[override]
Expand Down Expand Up @@ -572,7 +572,7 @@ def similarity_search(
) -> list[Document]:
"""Return docs selected by similarity search on query."""
return self._engine._run_as_sync(
self.__vs.asimilarity_search(query, k, filter, **kwargs)
self._vs.asimilarity_search(query, k, filter, **kwargs)
)

async def asimilarity_search(
Expand All @@ -584,18 +584,18 @@ async def asimilarity_search(
) -> list[Document]:
"""Return docs selected by similarity search on query."""
return await self._engine._run_as_async(
self.__vs.asimilarity_search(query, k, filter, **kwargs)
self._vs.asimilarity_search(query, k, filter, **kwargs)
)

# Required for (a)similarity_search_with_relevance_scores
def _select_relevance_score_fn(self) -> Callable[[float], float]:
"""Select a relevance function based on distance strategy."""
# Calculate distance strategy provided in vectorstore constructor
if self.__vs.distance_strategy == DistanceStrategy.COSINE_DISTANCE:
if self._vs.distance_strategy == DistanceStrategy.COSINE_DISTANCE:
return self._cosine_relevance_score_fn
if self.__vs.distance_strategy == DistanceStrategy.INNER_PRODUCT:
if self._vs.distance_strategy == DistanceStrategy.INNER_PRODUCT:
return self._max_inner_product_relevance_score_fn
elif self.__vs.distance_strategy == DistanceStrategy.EUCLIDEAN:
elif self._vs.distance_strategy == DistanceStrategy.EUCLIDEAN:
return self._euclidean_relevance_score_fn

async def asimilarity_search_with_score(
Expand All @@ -607,7 +607,7 @@ async def asimilarity_search_with_score(
) -> list[tuple[Document, float]]:
"""Return docs and distance scores selected by similarity search on query."""
return await self._engine._run_as_async(
self.__vs.asimilarity_search_with_score(query, k, filter, **kwargs)
self._vs.asimilarity_search_with_score(query, k, filter, **kwargs)
)

async def asimilarity_search_by_vector(
Expand All @@ -619,7 +619,7 @@ async def asimilarity_search_by_vector(
) -> list[Document]:
"""Return docs selected by vector similarity search."""
return await self._engine._run_as_async(
self.__vs.asimilarity_search_by_vector(embedding, k, filter, **kwargs)
self._vs.asimilarity_search_by_vector(embedding, k, filter, **kwargs)
)

async def asimilarity_search_with_score_by_vector(
Expand All @@ -631,7 +631,7 @@ async def asimilarity_search_with_score_by_vector(
) -> list[tuple[Document, float]]:
"""Return docs and distance scores selected by vector similarity search."""
return await self._engine._run_as_async(
self.__vs.asimilarity_search_with_score_by_vector(
self._vs.asimilarity_search_with_score_by_vector(
embedding, k, filter, **kwargs
)
)
Expand All @@ -647,7 +647,7 @@ async def amax_marginal_relevance_search(
) -> list[Document]:
"""Return docs selected using the maximal marginal relevance."""
return await self._engine._run_as_async(
self.__vs.amax_marginal_relevance_search(
self._vs.amax_marginal_relevance_search(
query, k, fetch_k, lambda_mult, filter, **kwargs
)
)
Expand All @@ -663,7 +663,7 @@ async def amax_marginal_relevance_search_by_vector(
) -> list[Document]:
"""Return docs selected using the maximal marginal relevance."""
return await self._engine._run_as_async(
self.__vs.amax_marginal_relevance_search_by_vector(
self._vs.amax_marginal_relevance_search_by_vector(
embedding, k, fetch_k, lambda_mult, filter, **kwargs
)
)
Expand All @@ -679,7 +679,7 @@ async def amax_marginal_relevance_search_with_score_by_vector(
) -> list[tuple[Document, float]]:
"""Return docs and distance scores selected using the maximal marginal relevance."""
return await self._engine._run_as_async(
self.__vs.amax_marginal_relevance_search_with_score_by_vector(
self._vs.amax_marginal_relevance_search_with_score_by_vector(
embedding, k, fetch_k, lambda_mult, filter, **kwargs
)
)
Expand All @@ -693,7 +693,7 @@ def similarity_search_with_score(
) -> list[tuple[Document, float]]:
"""Return docs and distance scores selected by similarity search on query."""
return self._engine._run_as_sync(
self.__vs.asimilarity_search_with_score(query, k, filter, **kwargs)
self._vs.asimilarity_search_with_score(query, k, filter, **kwargs)
)

def similarity_search_by_vector(
Expand All @@ -705,7 +705,7 @@ def similarity_search_by_vector(
) -> list[Document]:
"""Return docs selected by vector similarity search."""
return self._engine._run_as_sync(
self.__vs.asimilarity_search_by_vector(embedding, k, filter, **kwargs)
self._vs.asimilarity_search_by_vector(embedding, k, filter, **kwargs)
)

def similarity_search_with_score_by_vector(
Expand All @@ -717,7 +717,7 @@ def similarity_search_with_score_by_vector(
) -> list[tuple[Document, float]]:
"""Return docs and distance scores selected by similarity search on vector."""
return self._engine._run_as_sync(
self.__vs.asimilarity_search_with_score_by_vector(
self._vs.asimilarity_search_with_score_by_vector(
embedding, k, filter, **kwargs
)
)
Expand All @@ -733,7 +733,7 @@ def max_marginal_relevance_search(
) -> list[Document]:
"""Return docs selected using the maximal marginal relevance."""
return self._engine._run_as_sync(
self.__vs.amax_marginal_relevance_search(
self._vs.amax_marginal_relevance_search(
query, k, fetch_k, lambda_mult, filter, **kwargs
)
)
Expand All @@ -749,7 +749,7 @@ def max_marginal_relevance_search_by_vector(
) -> list[Document]:
"""Return docs selected using the maximal marginal relevance."""
return self._engine._run_as_sync(
self.__vs.amax_marginal_relevance_search_by_vector(
self._vs.amax_marginal_relevance_search_by_vector(
embedding, k, fetch_k, lambda_mult, filter, **kwargs
)
)
Expand All @@ -765,7 +765,7 @@ def max_marginal_relevance_search_with_score_by_vector(
) -> list[tuple[Document, float]]:
"""Return docs and distance scores selected using the maximal marginal relevance."""
return self._engine._run_as_sync(
self.__vs.amax_marginal_relevance_search_with_score_by_vector(
self._vs.amax_marginal_relevance_search_with_score_by_vector(
embedding, k, fetch_k, lambda_mult, filter, **kwargs
)
)
Expand All @@ -778,7 +778,7 @@ async def aapply_vector_index(
) -> None:
"""Create an index on the vector store table."""
return await self._engine._run_as_async(
self.__vs.aapply_vector_index(index, name, concurrently=concurrently)
self._vs.aapply_vector_index(index, name, concurrently=concurrently)
)

def apply_vector_index(
Expand All @@ -789,54 +789,52 @@ def apply_vector_index(
) -> None:
"""Create an index on the vector store table."""
return self._engine._run_as_sync(
self.__vs.aapply_vector_index(index, name, concurrently=concurrently)
self._vs.aapply_vector_index(index, name, concurrently=concurrently)
)

async def areindex(self, index_name: Optional[str] = None) -> None:
"""Re-index the vector store table."""
return await self._engine._run_as_async(self.__vs.areindex(index_name))
return await self._engine._run_as_async(self._vs.areindex(index_name))

def reindex(self, index_name: Optional[str] = None) -> None:
"""Re-index the vector store table."""
return self._engine._run_as_sync(self.__vs.areindex(index_name))
return self._engine._run_as_sync(self._vs.areindex(index_name))

async def adrop_vector_index(
self,
index_name: Optional[str] = None,
) -> None:
"""Drop the vector index."""
return await self._engine._run_as_async(
self.__vs.adrop_vector_index(index_name)
)
return await self._engine._run_as_async(self._vs.adrop_vector_index(index_name))

def drop_vector_index(
self,
index_name: Optional[str] = None,
) -> None:
"""Drop the vector index."""
return self._engine._run_as_sync(self.__vs.adrop_vector_index(index_name))
return self._engine._run_as_sync(self._vs.adrop_vector_index(index_name))

async def ais_valid_index(
self,
index_name: Optional[str] = None,
) -> bool:
"""Check if index exists in the table."""
return await self._engine._run_as_async(self.__vs.is_valid_index(index_name))
return await self._engine._run_as_async(self._vs.is_valid_index(index_name))

def is_valid_index(
self,
index_name: Optional[str] = None,
) -> bool:
"""Check if index exists in the table."""
return self._engine._run_as_sync(self.__vs.is_valid_index(index_name))
return self._engine._run_as_sync(self._vs.is_valid_index(index_name))

async def aget_by_ids(self, ids: Sequence[str]) -> list[Document]:
"""Get documents by ids."""
return await self._engine._run_as_async(self.__vs.aget_by_ids(ids=ids))
return await self._engine._run_as_async(self._vs.aget_by_ids(ids=ids))

def get_by_ids(self, ids: Sequence[str]) -> list[Document]:
"""Get documents by ids."""
return self._engine._run_as_sync(self.__vs.aget_by_ids(ids=ids))
return self._engine._run_as_sync(self._vs.aget_by_ids(ids=ids))

def get_table_name(self) -> str:
return self.__vs.table_name
return self._vs.table_name