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Harrison Chase
2023-09-19 16:30:27 -07:00
parent 235cdb118d
commit bbe8efcf91
1 changed files with 10 additions and 4 deletions
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14
libs/langchain/langchain/vectorstores/vald.py
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@@ -221,15 +221,21 @@ class Vald(VectorStore):
query: str,
k: int = 4,
fetch_k: int = 20,
lambda_mult: float = 0.5,
radius: float = -1.0,
epsilon: float = 0.01,
timeout: int = 3000000000,
lambda_mult: float = 0.5,
**kwargs: Any,
) -> List[Document]:
emb = self._embedding.embed_query(query)
docs = self.max_marginal_relevance_search_by_vector(
emb, k, fetch_k, radius, epsilon, timeout, lambda_mult
emb,
k=k,
fetch_k=fetch_k,
radius=radius,
epsilon=epsilon,
lambda_mult=lambda_mult,
timeout=timeout,
)
return docs
@@ -239,10 +245,10 @@ class Vald(VectorStore):
embedding: List[float],
k: int = 4,
fetch_k: int = 20,
lambda_mult: float = 0.5,
radius: float = -1.0,
epsilon: float = 0.01,
timeout: int = 3000000000,
lambda_mult: float = 0.5,
**kwargs: Any,
) -> List[Document]:
try:
@@ -262,7 +268,7 @@ class Vald(VectorStore):
stub = object_pb2_grpc.ObjectStub(channel)
docs_and_scores = self.similarity_search_with_score_by_vector(
embedding, fetch_k, radius, epsilon, timeout
embedding, fetch_k=fetch_k, radius=radius, epsilon=epsilon, timeout=timeout
)
docs = []