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chore: Updating Weaviate Vector Store parameters format

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joaoguilhermeS 2024-06-22 17:46:13 -03:00 • committed by Gabriel Luiz Freitas Almeida
commit 98497a376b
1 changed files with 20 additions and 26 deletions
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46
src/backend/base/langflow/components/vectorstores/Weaviate.py
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@ -20,18 +20,13 @@ class WeaviateVectorStoreComponent(LCVectorStoreComponent):
SecretStrInput(name="api_key", display_name="API Key", required=False),
StrInput(name="index_name", display_name="Index Name", required=True),
StrInput(name="text_key", display_name="Text Key", value="text", advanced=True),
HandleInput(name="embedding", display_name="Embedding", input_types=["Embeddings"]),
MultilineInput(name="search_query", display_name="Search Query"),
DataInput(
name="vector_store_inputs",
display_name="Vector Store Inputs",
name="ingest_data",
display_name="Ingest Data",
is_list=True,
),
BoolInput(
name="add_to_vector_store",
display_name="Add to Vector Store",
info="If true, the Vector Store Inputs will be added to the Vector Store.",
),
MultilineInput(name="search_input", display_name="Search Input"),
HandleInput(name="embedding", display_name="Embedding", input_types=["Embeddings"]),
IntInput(
name="number_of_results",
display_name="Number of Results",
@ -52,22 +47,21 @@ class WeaviateVectorStoreComponent(LCVectorStoreComponent):
else:
client = weaviate.Client(url=self.url)
if self.add_to_vector_store:
documents = []
for _input in self.vector_store_inputs or []:
if isinstance(_input, Data):
documents.append(_input.to_lc_document())
else:
documents.append(_input)
documents = []
for _input in self.ingest_data or []:
if isinstance(_input, Data):
documents.append(_input.to_lc_document())
else:
documents.append(_input)
if documents and self.embedding:
return Weaviate.from_documents(
client=client,
index_name=self.index_name,
documents=documents,
embedding=self.embedding,
by_text=self.search_by_text,
)
if documents and self.embedding:
return Weaviate.from_documents(
client=client,
index_name=self.index_name,
documents=documents,
embedding=self.embedding,
by_text=self.search_by_text,
)
return Weaviate(
client=client,
@ -80,9 +74,9 @@ class WeaviateVectorStoreComponent(LCVectorStoreComponent):
def search_documents(self) -> List[Data]:
vector_store = self._build_weaviate()
if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():
if self.search_query and isinstance(self.search_query, str) and self.search_query.strip():
docs = vector_store.similarity_search(
query=self.search_input,
query=self.search_query,
k=self.number_of_results,
)