Vector API client for Document Grounding.
 
This module provides the VectorAPIClient class for managing vector-based document
collections and performing semantic searches. The Vector API enables creating,
retrieving, updating, and deleting collections, as well as managing documents
within those collections.
 
Key capabilities:
    - Collection management (create, read, update, delete)
    - Document management within collections
    - Semantic vector search across collections
    - Collection status tracking (creation/deletion)
 
API Reference: https://api.sap.com/api/DOCUMENT_GROUNDING_API/resource/Vector

Modules
		humps requests

Classes
		builtins.object VectorAPIClient   class VectorAPIClient(builtins.object)     VectorAPIClient(proxy_client: Optional[gen_ai_hub.proxy.gen_ai_hub_proxy.client.GenAIHubProxyClient] = None)   The Vector API provides management and search capabilities for vector-based document collections.   It enables creating, retrieving, updating, and deleting collections, as well as managing documents and performing semantic vector searches within those collections.   Reference: https://api.sap.com/api/DOCUMENT_GROUNDING_API/resource/Vector     Methods defined here: __init__(self, proxy_client: Optional[gen_ai_hub.proxy.gen_ai_hub_proxy.client.GenAIHubProxyClient] = None) Initializes the VectorAPIClient   :param proxy_client: Optional proxy client to use for requests :type proxy_client: Optional[GenAIHubProxyClient], optional create_collection(self, collection_request: gen_ai_hub.document_grounding.models.vector.CollectionCreateRequest) -> requests.models.Response Create a new collection.   :param collection_request: The object containing the collection configuration. :type collection_request: CollectionCreateRequest :return: requests.Response empty object with 202 status code :rtype: requests.Response create_documents(self, collection_id: str, request: gen_ai_hub.document_grounding.models.vector.DocumentsCreateRequest) -> gen_ai_hub.document_grounding.models.vector.DocumentsListResponse Create documents in a collection.   :param collection_id: The ID of the collection to add documents to. :type collection_id: str :param request: The object containing the documents to create. :type request: DocumentsCreateRequest :return: A DocumentsListResponse object containing the created documents :rtype: DocumentsListResponse delete_collection(self, collection_id: str) -> requests.models.Response Delete collection by ID.   :param collection_id: The ID of the collection to delete. :type collection_id: str :return: requests.Response empty object with 204 status code :rtype: requests.Response delete_document(self, collection_id: str, document_id: str) -> requests.models.Response Delete a document from a collection.   :param collection_id: The ID of the collection to delete the document from. :type collection_id: str :param document_id: The ID of the document to delete. :type document_id: str :return: requests.Response empty object with 204 status code :rtype: requests.Response get_collection_by_id(self, collection_id: str) -> gen_ai_hub.document_grounding.models.vector.Collection Get collection details by ID.   :param collection_id: The ID of the collection to retrieve. :type collection_id: str :return: A Collection object containing the collection details :rtype: Collection get_collection_creation_status(self, collection_id: str) -> typing.Annotated[gen_ai_hub.document_grounding.models.vector.CollectionCreatedResponse | gen_ai_hub.document_grounding.models.vector.CollectionPendingResponse, FieldInfo(annotation=NoneType, required=True, discriminator='status')] Get creation status for a collection.   :param collection_id: The ID of the collection to retrieve the creation status for. :type collection_id: str :return: A CollectionCreationStatusResponse object containing the creation status :rtype: CollectionCreationStatusResponse get_collection_deletion_status(self, collection_id: str) -> typing.Annotated[gen_ai_hub.document_grounding.models.vector.CollectionDeletedResponse | gen_ai_hub.document_grounding.models.vector.CollectionPendingResponse, FieldInfo(annotation=NoneType, required=True, discriminator='status')] Get deletion status for a collection.   :param collection_id: The ID of the collection to retrieve the deletion status for. :type collection_id: str :return: A CollectionDeletionStatusResponse object containing the deletion status :rtype: CollectionDeletionStatusResponse get_collections(self, top: Optional[int] = None, skip: Optional[int] = None, count: Optional[bool] = None) -> gen_ai_hub.document_grounding.models.vector.CollectionsListResponse Get all collections.   :param top: the number of collections to retrieve, defaults to None :type top: Optional[int], optional :param skip: the number of collections to skip, defaults to None :type skip: Optional[int], optional :param count: whether to include the total count of collections, defaults to None :type count: Optional[bool], optional :return: A CollectionsListResponse object containing the list of collections :rtype: CollectionsListResponse get_document_by_id(self, collection_id: str, document_id: str) -> gen_ai_hub.document_grounding.models.vector.Document Get a document by ID from a collection.   :param collection_id: The ID of the collection to retrieve the document from. :type collection_id: str :param document_id: The ID of the document to retrieve. :type document_id: str :return: A Document object containing the document details :rtype: Document get_documents(self, collection_id: str, top: Optional[int] = None, skip: Optional[int] = None, count: Optional[bool] = None) -> gen_ai_hub.document_grounding.models.vector.DocumentsResponse Get documents from a collection.   :param collection_id: The ID of the collection to retrieve documents from. :type collection_id: str :param top: the number of documents to retrieve, defaults to None :type top: Optional[int], optional :param skip: the number of documents to skip, defaults to None :type skip: Optional[int], optional :param count: whether to include the total count of documents, defaults to None :type count: Optional[bool], optional :return: A DocumentsResponse object containing the list of documents :rtype: DocumentsResponse search(self, request: gen_ai_hub.document_grounding.models.vector.TextSearchRequest) -> gen_ai_hub.document_grounding.models.vector.VectorSearchResults Perform semantic search in vector collections.   :param request: The object containing the search parameters. :type request: TextSearchRequest :return: A VectorSearchResults object containing the search results :rtype: VectorSearchResults update_documents(self, collection_id: str, request: gen_ai_hub.document_grounding.models.vector.DocumentsUpdateRequest) -> gen_ai_hub.document_grounding.models.vector.DocumentsListResponse Update documents in a collection.   :param collection_id: The ID of the collection to update documents in. :type collection_id: str :param request: The object containing the documents to update. :type request: DocumentsUpdateRequest :return: A DocumentsListResponse object containing the updated documents :rtype: DocumentsListResponse Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined)

Data
		CollectionCreationStatusResponse = typing.Annotated[gen_ai_hub.document_grounding.m...NoneType, required=True, discriminator='status')] CollectionDeletionStatusResponse = typing.Annotated[gen_ai_hub.document_grounding.m...NoneType, required=True, discriminator='status')] Optional = typing.Optional PATH_DOCUMENT_GROUNDING_VECTOR = '/lm/document-grounding/vector'