Update setup_mode to "Sync" in AstraDBVectorStoreComponent (#1670)
* Update setup_mode to "Sync" in AstraDBVectorStoreComponent * Fix search_kwargs default value in PineconeSearch and QdrantSearch components
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9 changed files with 21 additions and 10 deletions
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@ -71,6 +71,8 @@ class PineconeSearchComponent(PineconeComponent, LCVectorStoreComponent):
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)
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if not vector_store:
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raise ValueError("Failed to load the Pinecone index.")
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if search_kwargs is None:
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search_kwargs = {}
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return self.search_with_vector_store(
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vector_store=vector_store,
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@ -86,12 +86,13 @@ class QdrantSearchComponent(QdrantComponent, LCVectorStoreComponent):
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port=port,
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prefer_grpc=prefer_grpc,
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prefix=prefix,
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search_kwargs=search_kwargs,
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timeout=timeout,
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url=url,
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)
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if not vector_store:
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raise ValueError("Failed to load the Qdrant index.")
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if search_kwargs is None:
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search_kwargs = {}
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return self.search_with_vector_store(
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vector_store=vector_store,
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@ -105,7 +105,7 @@ class AstraDBVectorStoreComponent(CustomComponent):
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bulk_insert_batch_concurrency: Optional[int] = None,
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bulk_insert_overwrite_concurrency: Optional[int] = None,
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bulk_delete_concurrency: Optional[int] = None,
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setup_mode: str = "Async",
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setup_mode: str = "Sync",
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pre_delete_collection: bool = False,
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metadata_indexing_include: Optional[List[str]] = None,
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metadata_indexing_exclude: Optional[List[str]] = None,
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@ -1,7 +1,7 @@
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from typing import List, Optional
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from langchain_community.vectorstores.mongodb_atlas import MongoDBAtlasVectorSearch
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from langflow.field_typing import Embeddings, NestedDict
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from langflow.field_typing import Embeddings
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from langflow.interface.custom.custom_component import CustomComponent
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from langflow.schema.schema import Record
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@ -4,7 +4,7 @@ from langchain.schema import BaseRetriever
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from langchain_community.vectorstores import VectorStore
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from langchain_community.vectorstores.qdrant import Qdrant
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from langflow.field_typing import Embeddings, NestedDict
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from langflow.field_typing import Embeddings
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from langflow.interface.custom.custom_component import CustomComponent
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from langflow.schema.schema import Record
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@ -5,7 +5,7 @@ from langchain_community.vectorstores import VectorStore
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from langchain_community.vectorstores.supabase import SupabaseVectorStore
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from supabase.client import Client, create_client
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from langflow.field_typing import Embeddings, NestedDict
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from langflow.field_typing import Embeddings
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from langflow.interface.custom.custom_component import CustomComponent
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from langflow.schema.schema import Record
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File diff suppressed because one or more lines are too long
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@ -211,7 +211,7 @@ def create_super_user(
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return super_user
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def create_user_longterm_token(db: Session = Depends(get_session)) -> dict:
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def create_user_longterm_token(db: Session = Depends(get_session)) -> tuple[UUID, dict]:
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settings_service = get_settings_service()
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username = settings_service.auth_settings.SUPERUSER
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password = settings_service.auth_settings.SUPERUSER_PASSWORD
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@ -7,12 +7,13 @@ from typing import Any, List, Optional, Tuple, Type
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import orjson
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import yaml
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from langflow.services.settings.constants import VARIABLES_TO_GET_FROM_ENVIRONMENT
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from loguru import logger
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from pydantic import field_validator, validator
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from pydantic.fields import FieldInfo
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from pydantic_settings import BaseSettings, EnvSettingsSource, PydanticBaseSettingsSource, SettingsConfigDict
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from langflow.services.settings.constants import VARIABLES_TO_GET_FROM_ENVIRONMENT
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# BASE_COMPONENTS_PATH = str(Path(__file__).parent / "components")
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BASE_COMPONENTS_PATH = str(Path(__file__).parent.parent.parent / "components")
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@ -27,9 +28,16 @@ def is_list_of_any(field: FieldInfo) -> bool:
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Returns:
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bool: True if the field is a list or a list of any type, False otherwise.
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"""
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if field.annotation is None:
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return False
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try:
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if hasattr(field.annotation, "__args__"):
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union_args = field.annotation.__args__
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else:
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union_args = []
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return field.annotation.__origin__ == list or any(
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arg.__origin__ == list for arg in field.annotation.__args__ if hasattr(arg, "__origin__")
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arg.__origin__ == list for arg in union_args if hasattr(arg, "__origin__")
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)
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except AttributeError:
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return False
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