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chore: Updating Courchbase Vector Store parameters format

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joaoguilhermeS 2024-06-22 16:46:28 -03:00 • committed by Gabriel Luiz Freitas Almeida
commit a97b5eee75
1 changed files with 27 additions and 39 deletions
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66
src/backend/base/langflow/components/vectorstores/Couchbase.py
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@ -12,29 +12,26 @@ from langflow.schema import Data
class CouchbaseVectorStoreComponent(LCVectorStoreComponent): class CouchbaseVectorStoreComponent(LCVectorStoreComponent):
display_name = "Couchbase" display_name = "Couchbase"
description = "Couchbase Vector Store with search capabilities" description = "Couchbase Vector Store with search capabilities"
documentation = "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/couchbase" documentation = "https://python.langchain.com/v0.1/docs/integrations/document_loaders/couchbase/"
icon = "Couchbase" icon = "Couchbase"
inputs = [ inputs = [
StrInput(name="couchbase_connection_string", display_name="Couchbase Cluster connection string", required=True), SecretStrInput(
name="couchbase_connection_string", display_name="Couchbase Cluster connection string", required=True
),
StrInput(name="couchbase_username", display_name="Couchbase username", required=True), StrInput(name="couchbase_username", display_name="Couchbase username", required=True),
SecretStrInput(name="couchbase_password", display_name="Couchbase password", required=True), SecretStrInput(name="couchbase_password", display_name="Couchbase password", required=True),
StrInput(name="bucket_name", display_name="Bucket Name", required=True), StrInput(name="bucket_name", display_name="Bucket Name", required=True),
StrInput(name="scope_name", display_name="Scope Name", required=True), StrInput(name="scope_name", display_name="Scope Name", required=True),
StrInput(name="collection_name", display_name="Collection Name", required=True), StrInput(name="collection_name", display_name="Collection Name", required=True),
StrInput(name="index_name", display_name="Index Name", required=True), StrInput(name="index_name", display_name="Index Name", required=True),
HandleInput(name="embedding", display_name="Embedding", input_types=["Embeddings"]), MultilineInput(name="search_query", display_name="Search Query"),
DataInput( DataInput(
name="vector_store_inputs", name="ingest_data",
display_name="Vector Store Inputs", display_name="Ingest Data",
is_list=True, is_list=True,
), ),
BoolInput( HandleInput(name="embedding", display_name="Embedding", input_types=["Embeddings"]),
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"),
IntInput( IntInput(
name="number_of_results", name="number_of_results",
display_name="Number of Results", display_name="Number of Results",
@ -66,33 +63,24 @@ class CouchbaseVectorStoreComponent(LCVectorStoreComponent):
except Exception as e: except Exception as e:
raise ValueError(f"Failed to connect to Couchbase: {e}") raise ValueError(f"Failed to connect to Couchbase: {e}")
if self.add_to_vector_store: documents = []
documents = [] for _input in self.ingest_data or []:
for _input in self.vector_store_inputs or []: if isinstance(_input, Data):
if isinstance(_input, Data): documents.append(_input.to_lc_document())
documents.append(_input.to_lc_document())
else:
documents.append(_input)
if documents:
couchbase_vs = CouchbaseVectorStore.from_documents(
documents=documents,
cluster=cluster,
bucket_name=self.bucket_name,
scope_name=self.scope_name,
collection_name=self.collection_name,
embedding=self.embedding,
index_name=self.index_name,
)
else: else:
couchbase_vs = CouchbaseVectorStore( documents.append(_input)
cluster=cluster,
bucket_name=self.bucket_name, if documents:
scope_name=self.scope_name, couchbase_vs = CouchbaseVectorStore.from_documents(
collection_name=self.collection_name, documents=documents,
embedding=self.embedding, cluster=cluster,
index_name=self.index_name, bucket_name=self.bucket_name,
) scope_name=self.scope_name,
collection_name=self.collection_name,
embedding=self.embedding,
index_name=self.index_name,
)
else: else:
couchbase_vs = CouchbaseVectorStore( couchbase_vs = CouchbaseVectorStore(
cluster=cluster, cluster=cluster,
@ -108,9 +96,9 @@ class CouchbaseVectorStoreComponent(LCVectorStoreComponent):
def search_documents(self) -> List[Data]: def search_documents(self) -> List[Data]:
vector_store = self._build_couchbase() vector_store = self._build_couchbase()
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( docs = vector_store.similarity_search(
query=self.search_input, query=self.search_query,
k=self.number_of_results, k=self.number_of_results,
) )