jyapayne/langflow
1
0
Fork 0
Code Issues Pull requests Projects Releases 1 Packages Wiki Activity Actions

fix: Ensure ordering of astradb inputs (#4552)

Browse source
This commit is contained in:
Eric Hare 2024-11-12 14:45:04 -08:00 • committed by GitHub
commit 70ebfc44f1
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
1 changed files with 5 additions and 5 deletions
Download patch file Download diff file Expand all files Collapse all files

10
src/backend/base/langflow/components/vectorstores/astradb.py
View file

@ -98,7 +98,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
advanced=True,
),
DropdownInput(
name="embedding_service",
name="embedding_choice",
display_name="Embedding Model or Astra Vectorize",
info="Determines whether to use Astra Vectorize for the collection.",
options=["Embedding Model", "Astra Vectorize"],
@ -239,7 +239,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
return build_config
def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
if field_name == "embedding_service":
if field_name == "embedding_choice":
if field_value == "Astra Vectorize":
self.del_fields(build_config, ["embedding"])
@ -252,7 +252,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
real_time_refresh=True,
).to_dict()
self.insert_in_dict(build_config, "embedding_service", {"embedding_provider": new_parameter})
self.insert_in_dict(build_config, "embedding_choice", {"embedding_provider": new_parameter})
else:
self.del_fields(
build_config,
@ -273,7 +273,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
info="Allows an embedding model configuration.",
).to_dict()
self.insert_in_dict(build_config, "embedding_service", {"embedding": new_parameter})
self.insert_in_dict(build_config, "embedding_choice", {"embedding": new_parameter})
elif field_name == "embedding_provider":
self.del_fields(
@ -410,7 +410,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
msg = f"Invalid setup mode: {self.setup_mode}"
raise ValueError(msg) from e
if self.embedding_service == "Embedding Model":
if self.embedding_choice == "Embedding Model":
embedding_dict = {"embedding": self.embedding}
else:
from astrapy.info import CollectionVectorServiceOptions