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chore: Updating Cassandra Vector Store parameters format

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joaoguilhermeS 2024-06-22 16:20:09 -03:00 • committed by Gabriel Luiz Freitas Almeida
commit 49ca6c5bf1
1 changed files with 24 additions and 37 deletions
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61
src/backend/base/langflow/components/vectorstores/Cassandra.py
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@ -41,7 +41,7 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
name="keyspace",
display_name="Keyspace",
info="Optional key space within Astra DB. The keyspace should already be created.",
advanced=True,
advanced=False,
),
IntInput(
name="ttl_seconds",
@ -70,18 +70,13 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
value="Sync",
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",
@ -107,33 +102,25 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
token=self.token,
)
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 = []
if documents:
table = Cassandra.from_documents(
documents=documents,
embedding=self.embedding,
table_name=self.table_name,
keyspace=self.keyspace,
ttl_seconds=self.ttl_seconds,
batch_size=self.batch_size,
body_index_options=self.body_index_options,
)
for _input in self.ingest_data or []:
if isinstance(_input, Data):
documents.append(_input.to_lc_document())
else:
table = Cassandra(
embedding=self.embedding,
table_name=self.table_name,
keyspace=self.keyspace,
ttl_seconds=self.ttl_seconds,
body_index_options=self.body_index_options,
setup_mode=self.setup_mode,
)
documents.append(_input)
if documents:
table = Cassandra.from_documents(
documents=documents,
embedding=self.embedding,
table_name=self.table_name,
keyspace=self.keyspace,
ttl_seconds=self.ttl_seconds,
batch_size=self.batch_size,
body_index_options=self.body_index_options,
)
else:
table = Cassandra(
embedding=self.embedding,
@ -149,10 +136,10 @@ class CassandraVectorStoreComponent(LCVectorStoreComponent):
def search_documents(self) -> List[Data]:
vector_store = self._build_cassandra()
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():
try:
docs = vector_store.similarity_search(
query=self.search_input,
query=self.search_query,
k=self.number_of_results,
)
except KeyError as e: