gen_ai_hub.document_grounding.clients.pipeline_api_client module

Pipeline API client for Document Grounding.

This module provides the PipelineAPIClient class for managing document vectorization pipelines. Pipelines automate the process of fetching documents from data repositories, preprocessing and chunking content, generating semantic embeddings, and storing them in HANA Vector Store.

Supported data repositories:

  • Microsoft SharePoint

  • AWS S3

  • SFTP

API Reference: https://api.sap.com/api/DOCUMENT_GROUNDING_API/resource/Pipelines

class gen_ai_hub.document_grounding.clients.pipeline_api_client.PipelineAPIClient(proxy_client: GenAIHubProxyClient | None = None)

Bases: object

The Pipelines API creates and manages vector stores based on documents from user data repositories: S3, SFTP, and Microsoft SharePoint. Each pipeline represents a configured end-to-end process including the following steps:

  • Fetches documents from a supported data source

  • Preprocesses and chunks the document content, and generates semantic embeddings. Semantic embeddings are multidimensional representations of textual information.

  • Stores semantic embeddings into the HANA Vector Store

The Pipeline API is compatible with the following data repositories:

  • Microsoft SharePoint

  • AWS S3

  • SFTP

See https://api.sap.com/api/DOCUMENT_GROUNDING_API/resource/Pipelines

__init__(proxy_client: GenAIHubProxyClient | None = None)

Initializes the PipelineAPIClient

Parameters:

proxy_client (Optional[GenAIHubProxyClient], optional) – proxy client to use for requests, defaults to None

create_pipeline(pipeline_request: MSSharePointPipelineCreateRequest | S3PipelineCreateRequest | SFTPPipelineCreateRequest) → PipelineIdResponse

Create a document vectorization pipeline

Parameters:

pipeline_request (CreatePipelineRequest) – The object containing the pipeline configuration.

Returns:

ID of the created pipeline

Return type:

PipelineIdResponse

get_pipelines(top: int | None = None, skip: int | None = None, count: bool | None = None) → GetPipelinesResponse

Get all pipelines.

Returns:

Get all pipelines

Return type:

GetPipelinesResponse

get_pipeline_by_id(pipeline_id: str) → BasePipelineResponse

Get details of a pipeline by pipeline id.

Parameters:

pipeline_id (str) – Pipeline ID

Returns:

Details of the pipeline

Return type:

BasePipelineResponse

delete_pipeline_by_id(pipeline_id: str) → Response

Delete a pipeline by pipeline id

Parameters:

pipeline_id (str) – ID of the pipeline to delete

Returns:

Response of the delete operation

Return type:

requests.Response

get_pipeline_status(pipeline_id: str) → GetPipelineStatusResponse

Get pipeline status by pipeline id

Parameters:

pipeline_id (str) – Pipeline ID

Returns:

Status of the pipeline

Return type:

GetPipelineStatusResponse

search_pipelines(body: SearchPipelineRequest) → SearchPipelinesResponse

Pipeline Search by Metadata

Parameters:

body (SearchPipelineRequest) – The search request object containing metadata filters.

Returns:

Search results containing matching pipelines.

Return type:

SearchPipelinesResponse

get_pipeline_executions(pipeline_id: str, last_execution: bool | None = None, top: int | None = None, skip: int | None = None, count: bool | None = None) → GetPipelineExecutionsResponse

Get Pipeline Executions

Parameters:

  • pipeline_id (str) – Pipeline ID

  • last_execution (Optional[bool], optional) – flag to get only the last execution, defaults to None

  • top (Optional[int], optional) – number of executions to retrieve, defaults to None

  • skip (Optional[int], optional) – number of executions to skip, defaults to None

  • count (Optional[bool], optional) – flag to include count of total executions, defaults to None

Returns:

Pipeline Executions

Return type:

GetPipelineExecutionsResponse

get_pipeline_execution_by_id(pipeline_id: str, execution_id: str) → PipelineExecution

Get Pipeline Execution by ID

Parameters:

  • pipeline_id (str) – Pipeline ID

  • execution_id (str) – Execution ID

Returns:

Pipeline Execution

Return type:

PipelineExecution

get_execution_documents(pipeline_id: str, execution_id: str, top: int | None = None, skip: int | None = None, count: bool | None = None) → DocumentsStatusResponse

Get Documents for a Pipeline Execution

Parameters:

  • pipeline_id (str) – Pipeline ID

  • execution_id (str) – Execution ID

  • top (Optional[int], optional) – the maximum number of documents to return, defaults to None

  • skip (Optional[int], optional) – number of documents to skip, defaults to None

  • count (Optional[bool], optional) – flag to include count of total documents, defaults to None

Returns:

Documents for the Pipeline Execution

Return type:

DocumentsStatusResponse

get_execution_document_by_id(pipeline_id: str, execution_id: str, document_id: str) → Document

Get Document by ID for a Pipeline Execution

Returns:

Document for the Pipeline Execution

Return type:

Document

get_pipeline_documents(pipeline_id: str, top: int | None = None, skip: int | None = None, count: bool | None = None) → DocumentsStatusResponse

Get Documents for a Pipeline

Parameters:

  • pipeline_id (str) – Pipeline ID

  • top (Optional[int], optional) – the maximum number of documents to return, defaults to None

  • skip (Optional[int], optional) – number of documents to skip, defaults to None

  • count (Optional[bool], optional) – flag to include count of total documents, defaults to None

Returns:

Documents for the Pipeline

Return type:

DocumentsStatusResponse

get_pipeline_document_by_id(pipeline_id: str, document_id: str) → Document

Get Document by ID for a Pipeline

Parameters:

  • pipeline_id (str) – Pipeline ID

  • document_id (str) – Document ID

Returns:

Document for the Pipeline

Return type:

Document

trigger_pipeline(request: ManualPipelineTrigger) → Response

Trigger Pipeline Manually

Parameters:

request (ManualPipelineTrigger) – The manual trigger request object.

Returns:

Response of the trigger operation

Return type:

requests.Response