gen_ai_hub.document_grounding.models.pipeline module

Pydantic models for Pipeline API.

This module defines data models for the Pipeline API, which manages document vectorization pipelines from various data sources (Microsoft SharePoint, AWS S3, SFTP).

Model categories:

• Pipeline configuration models (create/get requests and responses)

• Pipeline execution models (tracking pipeline runs)

• Document models (tracking document processing status)

• Search and metadata models (filtering pipelines by metadata)

• Trigger models (manual pipeline execution)

All models use Pydantic for validation and serialization.

class gen_ai_hub.document_grounding.models.pipeline.MetaData(*, destination: str)

Bases: BaseModel

destination: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.SharePointSite(*, name: str, includePaths: List[str] | None = None)

Bases: BaseModel

name: str

includePaths: List[str] | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.SharePointConfig(*, site: SharePointSite)

Bases: BaseModel

site: SharePointSite

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.MSSharePointConfiguration(*, destination: str, sharePoint: SharePointConfig)

Bases: BaseModel

destination: str

sharePoint: SharePointConfig

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.CommonConfiguration(*, destination: str)

Bases: BaseModel

destination: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.MSSharePointPipelineCreateRequest(*, type: Literal['MSSharePoint'] = 'MSSharePoint', configuration: MSSharePointConfiguration, metadata: MetaData | None = None)

Bases: BaseModel

type: Literal['MSSharePoint']

configuration: MSSharePointConfiguration

metadata: MetaData | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.S3PipelineCreateRequest(*, type: Literal['S3'] = 'S3', configuration: CommonConfiguration, metadata: MetaData | None = None)

Bases: BaseModel

type: Literal['S3']

configuration: CommonConfiguration

metadata: MetaData | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.SFTPPipelineCreateRequest(*, type: Literal['SFTP'] = 'SFTP', configuration: CommonConfiguration, metadata: MetaData | None = None)

Bases: BaseModel

type: Literal['SFTP']

configuration: CommonConfiguration

metadata: MetaData | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.PipelineIdResponse(*, pipelineId: str)

Bases: BaseModel

pipelineId: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.BasePipelineResponse(*, id: str, type: str, metadata: MetaData | None = None)

Bases: BaseModel

id: str

type: str

metadata: MetaData | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.MSSharePointConfigurationGetResponse(*, destination: str, sharePoint: SharePointConfig)

Bases: BaseModel

destination: str

sharePoint: SharePointConfig

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.MSSharePointPipelineGetResponse(*, id: str, type: Literal['MSSharePoint'] = 'MSSharePoint', metadata: MetaData | None = None, configuration: MSSharePointConfigurationGetResponse)

Bases: BasePipelineResponse

type: Literal['MSSharePoint']

configuration: MSSharePointConfigurationGetResponse

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

id: str

metadata: MetaData | None

class gen_ai_hub.document_grounding.models.pipeline.S3PipelineGetResponse(*, id: str, type: Literal['S3'] = 'S3', metadata: MetaData | None = None, configuration: CommonConfiguration)

Bases: BasePipelineResponse

type: Literal['S3']

configuration: CommonConfiguration

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

id: str

metadata: MetaData | None

class gen_ai_hub.document_grounding.models.pipeline.SFTPPipelineGetResponse(*, id: str, type: Literal['SFTP'] = 'SFTP', metadata: MetaData | None = None, configuration: CommonConfiguration)

Bases: BasePipelineResponse

type: Literal['SFTP']

configuration: CommonConfiguration

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

id: str

metadata: MetaData | None

class gen_ai_hub.document_grounding.models.pipeline.GetPipelinesResponse(*, count: int | None, resources: List[Annotated[MSSharePointPipelineGetResponse | S3PipelineGetResponse | SFTPPipelineGetResponse, FieldInfo(annotation=NoneType, required=True, discriminator='type')]])

Bases: BaseModel

count: int | None

resources: List[Annotated[MSSharePointPipelineGetResponse | S3PipelineGetResponse | SFTPPipelineGetResponse, FieldInfo(annotation=NoneType, required=True, discriminator='type')]]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.GetPipelineStatusResponse(*, lastStarted: str | None, status: str | None)

Bases: BaseModel

lastStarted: str | None

status: str | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.DataRepositoryMetadataItem(*, key: str, value: List[str])

Bases: BaseModel

key: str

value: List[str]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.SearchPipelineRequest(*, dataRepositoryMetadata: List[DataRepositoryMetadataItem])

Bases: BaseModel

dataRepositoryMetadata: List[DataRepositoryMetadataItem]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.SearchPipelineData(*, pipelineId: str)

Bases: BaseModel

pipelineId: str

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.SearchPipelinesResponse(*, count: int | None, resources: List[SearchPipelineData])

Bases: BaseModel

count: int | None

resources: List[SearchPipelineData]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.PipelineExecutionStatus(*values)

Bases: str, Enum

NEW = 'NEW'

UNKNOWN = 'UNKNOWN'

INPROGRESS = 'INPROGRESS'

FINISHED = 'FINISHED'

FINISHED_WITH_ERRORS = 'FINISHEDWITHERRORS'

TIMEOUT = 'TIMEOUT'

class gen_ai_hub.document_grounding.models.pipeline.PipelineExecution(*, id: str, status: PipelineExecutionStatus | None = None, createdAt: datetime | None = None, modifiedAt: datetime | None = None)

Bases: BaseModel

id: str

status: PipelineExecutionStatus | None

createdAt: datetime | None

modifiedAt: datetime | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.GetPipelineExecutionsResponse(*, count: int | None, resources: List[PipelineExecution])

Bases: BaseModel

count: int | None

resources: List[PipelineExecution]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.DocumentStatus(*values)

Bases: str, Enum

TO_BE_PROCESSED = 'TO_BE_PROCESSED'

INDEXED = 'INDEXED'

REINDEXED = 'REINDEXED'

DEINDEXED = 'DEINDEXED'

FAILED = 'FAILED'

FAILED_TO_BE_RETRIED = 'FAILED_TO_BE_RETRIED'

TO_BE_SCHEDULED = 'TO_BE_SCHEDULED'

class gen_ai_hub.document_grounding.models.pipeline.Document(*, id: str, status: DocumentStatus | None = None, viewLocation: str | None = None, downloadLocation: str | None = None, absoluteUrl: str | None = None, title: str | None = None, metadataId: str | None = None, createdTimestamp: datetime | None = None, lastUpdatedTimestamp: datetime | None = None)

Bases: BaseModel

id: str

status: DocumentStatus | None

viewLocation: str | None

downloadLocation: str | None

absoluteUrl: str | None

title: str | None

metadataId: str | None

createdTimestamp: datetime | None

lastUpdatedTimestamp: datetime | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.DocumentsStatusResponse(*, count: int | None, resources: List[Document])

Bases: BaseModel

count: int | None

resources: List[Document]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class gen_ai_hub.document_grounding.models.pipeline.ManualPipelineTrigger(*, pipelineId: str, metadataOnly: bool | None = None)

Bases: BaseModel

pipelineId: str

metadataOnly: bool | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].