DocumentModelDetails Class

Document model info.

Readonly variables are only populated by the server, and will be ignored when sending a request.

Constructor

DocumentModelDetails(*args: Any, **kwargs: Any)

Variables

Name	Description
model_id	str Unique document model name. Required.
description	str Document model description.
created_date_time	datetime Date and time (UTC) when the document model was created. Required.
expiration_date_time	datetime Date and time (UTC) when the document model will expire.
api_version	str API version used to create this document model.
tags	dict[str, str] List of key-value tag attributes associated with the document model.
build_mode	str or DocumentBuildMode Custom document model build mode. Known values are: "template", "neural", and "generative".
azure_blob_source	AzureBlobContentSource Azure Blob Storage location containing the training data. Either azureBlobSource or azureBlobFileListSource must be specified.
azure_blob_file_list_source	AzureBlobFileListContentSource Azure Blob Storage file list specifying the training data. Either azureBlobSource or azureBlobFileListSource must be specified.
classifier_id	str For composed models, the custom classifier to split and classify the input file.
split	str or SplitMode For composed models, the file splitting behavior. Known values are: "auto", "none", and "perPage".
doc_types	dict[str, DocumentTypeDetails] Supported document types.
warnings	list[Warning] List of warnings encountered while building the model.
training_hours	float Number of V100-equivalent GPU hours consumed for model training.

Methods

as_dict	Return a dict that can be JSONify using json.dump.
clear
copy
get
items
keys
pop
popitem
setdefault
update
values

as_dict

Return a dict that can be JSONify using json.dump.

as_dict(*, exclude_readonly: bool = False) -> Dict[str, Any]

Keyword-Only Parameters

Name	Description
exclude_readonly	bool Whether to remove the readonly properties. Default value: False

Returns

Type	Description
dict	A dict JSON compatible object

clear

clear() -> None

copy

copy() -> Model

get

get(key: str, default: Any = None) -> Any

Parameters

Name	Description
key Required
default	Default value: None

items

items() -> ItemsView[str, Any]

keys

keys() -> KeysView[str]

pop

pop(key: str, default: ~typing.Any = <object object>) -> Any

Parameters

Name	Description
key Required
default

popitem

popitem() -> Tuple[str, Any]

setdefault

setdefault(key: str, default: ~typing.Any = <object object>) -> Any

Parameters

Name	Description
key Required
default

update

update(*args: Any, **kwargs: Any) -> None

values

values() -> ValuesView[Any]

Attributes

api_version

API version used to create this document model.

api_version: str | None

azure_blob_file_list_source

Azure Blob Storage file list specifying the training data. Either azureBlobSource or azureBlobFileListSource must be specified.

azure_blob_file_list_source: _models.AzureBlobFileListContentSource | None

azure_blob_source

Azure Blob Storage location containing the training data. Either azureBlobSource or azureBlobFileListSource must be specified.

azure_blob_source: _models.AzureBlobContentSource | None

build_mode

"template", "neural", and "generative".

build_mode: str | _models.DocumentBuildMode | None

classifier_id

For composed models, the custom classifier to split and classify the input file.

classifier_id: str | None

created_date_time

Date and time (UTC) when the document model was created. Required.

created_date_time: datetime

description

Document model description.

description: str | None

doc_types

Supported document types.

doc_types: Dict[str, _models.DocumentTypeDetails] | None

expiration_date_time

Date and time (UTC) when the document model will expire.

expiration_date_time: datetime | None

model_id

Unique document model name. Required.

model_id: str

split

"auto", "none", and "perPage".

split: str | _models.SplitMode | None

tags

List of key-value tag attributes associated with the document model.

tags: Dict[str, str] | None

training_hours

Number of V100-equivalent GPU hours consumed for model training.

training_hours: float | None

warnings

List of warnings encountered while building the model.

warnings: List[_models.Warning] | None