diff --git a/src/backend/base/langflow/components/embeddings/AstraVectorize.py b/src/backend/base/langflow/components/embeddings/AstraVectorize.py index f098828a1..8c9e6d974 100644 --- a/src/backend/base/langflow/components/embeddings/AstraVectorize.py +++ b/src/backend/base/langflow/components/embeddings/AstraVectorize.py @@ -1,6 +1,6 @@ from typing import Any from langflow.custom import Component -from langflow.inputs.inputs import DictInput, SecretStrInput, StrInput, MessageTextInput +from langflow.inputs.inputs import DictInput, SecretStrInput, MessageTextInput from langflow.template.field.base import Output @@ -14,30 +14,30 @@ class AstraVectorize(Component): MessageTextInput( name="provider", display_name="Provider name", - info='The embedding provider to use.', + info="The embedding provider to use.", ), MessageTextInput( name="model_name", display_name="Model name", - info='The embedding model to use.', + info="The embedding model to use.", ), DictInput( name="authentication", display_name="Authentication", - info='Authentication parameters. Use the Astra Portal to add the embedding provider integration to your Astra organization.', - is_list=True + info="Authentication parameters. Use the Astra Portal to add the embedding provider integration to your Astra organization.", + is_list=True, ), SecretStrInput( name="provider_api_key", display_name="Provider API Key", - info='An alternative to the Astra Authentication that let you use directly the API key of the provider.' + info="An alternative to the Astra Authentication that let you use directly the API key of the provider.", ), DictInput( name="model_parameters", display_name="Model parameters", - info='Additional model parameters.', + info="Additional model parameters.", advanced=True, - is_list=True + is_list=True, ), ] outputs = [ @@ -51,7 +51,7 @@ class AstraVectorize(Component): "provider": self.provider, "modelName": self.model_name, "authentication": self.authentication, - "parameters": self.model_parameters + "parameters": self.model_parameters, }, - "collection_embedding_api_key": self.provider_api_key + "collection_embedding_api_key": self.provider_api_key, } diff --git a/src/backend/base/langflow/components/helpers/IDGenerator.py b/src/backend/base/langflow/components/helpers/IDGenerator.py index fa8805583..72a944f71 100644 --- a/src/backend/base/langflow/components/helpers/IDGenerator.py +++ b/src/backend/base/langflow/components/helpers/IDGenerator.py @@ -1,5 +1,5 @@ import uuid -from typing import Optional, Any, +from typing import Any, Optional from langflow.custom import CustomComponent from langflow.schema.dotdict import dotdict @@ -10,10 +10,7 @@ class UUIDGeneratorComponent(CustomComponent): description = "Generates a unique ID." def update_build_config( # type: ignore - self, - build_config: dotdict, - field_value: Any, - field_name: Optional[str] = None, + self, build_config: dotdict, field_value: Any, field_name: Optional[str] = None ): if field_name == "unique_id": build_config[field_name]["value"] = str(uuid.uuid4()) diff --git a/src/backend/base/langflow/components/prototypes/__init__.py b/src/backend/base/langflow/components/prototypes/__init__.py index 8624865a2..89c14f7e9 100644 --- a/src/backend/base/langflow/components/prototypes/__init__.py +++ b/src/backend/base/langflow/components/prototypes/__init__.py @@ -1,4 +1,4 @@ -µfrom .ConditionalRouter import ConditionalRouterComponent +from .ConditionalRouter import ConditionalRouterComponent from .FlowTool import FlowToolComponent from .Listen import ListenComponent from .Notify import NotifyComponent diff --git a/src/backend/base/langflow/components/vectorstores/AstraDB.py b/src/backend/base/langflow/components/vectorstores/AstraDB.py index adcd546de..58e1d19ef 100644 --- a/src/backend/base/langflow/components/vectorstores/AstraDB.py +++ b/src/backend/base/langflow/components/vectorstores/AstraDB.py @@ -159,10 +159,12 @@ class AstraVectorStoreComponent(LCVectorStoreComponent): embedding_dict = {"embedding": self.embedding} else: from astrapy.info import CollectionVectorServiceOptions + dict_options = self.embedding.get("collection_vector_service_options", {}) - dict_options["authentication"] = {k: v for k, v in dict_options.get("authentication", {}).items() if k and v} - dict_options["parameters"] = {k: v for k, v in dict_options.get("parameters", {}).items() if - k and v} + dict_options["authentication"] = { + k: v for k, v in dict_options.get("authentication", {}).items() if k and v + } + dict_options["parameters"] = {k: v for k, v in dict_options.get("parameters", {}).items() if k and v} embedding_dict = { "collection_vector_service_options": CollectionVectorServiceOptions.from_dict(dict_options), "collection_embedding_api_key": self.embedding.get("collection_embedding_api_key"),