# coding=utf-8
# pylint: disable=too-many-lines
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) Python Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import datetime
from typing import Any, Dict, List, Literal, Mapping, Optional, TYPE_CHECKING, Union, overload
from .. import _model_base
from .._model_base import rest_discriminator, rest_field
from ._enums import OperationKind
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
from .. import models as _models
[docs]
class AddressValue(_model_base.Model): # pylint: disable=too-many-instance-attributes
"""Address field value.
:ivar house_number: House or building number.
:vartype house_number: str
:ivar po_box: Post office box number.
:vartype po_box: str
:ivar road: Street name.
:vartype road: str
:ivar city: Name of city, town, village, etc.
:vartype city: str
:ivar state: First-level administrative division.
:vartype state: str
:ivar postal_code: Postal code used for mail sorting.
:vartype postal_code: str
:ivar country_region: Country/region.
:vartype country_region: str
:ivar street_address: Street-level address, excluding city, state, countryRegion, and
postalCode.
:vartype street_address: str
:ivar unit: Apartment or office number.
:vartype unit: str
:ivar city_district: Districts or boroughs within a city, such as Brooklyn in New York City or
City
of Westminster in London.
:vartype city_district: str
:ivar state_district: Second-level administrative division used in certain locales.
:vartype state_district: str
:ivar suburb: Unofficial neighborhood name, like Chinatown.
:vartype suburb: str
:ivar house: Build name, such as World Trade Center.
:vartype house: str
:ivar level: Floor number, such as 3F.
:vartype level: str
"""
house_number: Optional[str] = rest_field(name="houseNumber")
"""House or building number."""
po_box: Optional[str] = rest_field(name="poBox")
"""Post office box number."""
road: Optional[str] = rest_field()
"""Street name."""
city: Optional[str] = rest_field()
"""Name of city, town, village, etc."""
state: Optional[str] = rest_field()
"""First-level administrative division."""
postal_code: Optional[str] = rest_field(name="postalCode")
"""Postal code used for mail sorting."""
country_region: Optional[str] = rest_field(name="countryRegion")
"""Country/region."""
street_address: Optional[str] = rest_field(name="streetAddress")
"""Street-level address, excluding city, state, countryRegion, and postalCode."""
unit: Optional[str] = rest_field()
"""Apartment or office number."""
city_district: Optional[str] = rest_field(name="cityDistrict")
"""Districts or boroughs within a city, such as Brooklyn in New York City or City
of Westminster in London."""
state_district: Optional[str] = rest_field(name="stateDistrict")
"""Second-level administrative division used in certain locales."""
suburb: Optional[str] = rest_field()
"""Unofficial neighborhood name, like Chinatown."""
house: Optional[str] = rest_field()
"""Build name, such as World Trade Center."""
level: Optional[str] = rest_field()
"""Floor number, such as 3F."""
@overload
def __init__(
self,
*,
house_number: Optional[str] = None,
po_box: Optional[str] = None,
road: Optional[str] = None,
city: Optional[str] = None,
state: Optional[str] = None,
postal_code: Optional[str] = None,
country_region: Optional[str] = None,
street_address: Optional[str] = None,
unit: Optional[str] = None,
city_district: Optional[str] = None,
state_district: Optional[str] = None,
suburb: Optional[str] = None,
house: Optional[str] = None,
level: Optional[str] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AnalyzeBatchDocumentsRequest(_model_base.Model):
"""Batch document analysis parameters.
All required parameters must be populated in order to send to server.
:ivar azure_blob_source: Azure Blob Storage location containing the batch documents. Either
azureBlobSource or azureBlobFileListSource must be specified.
:vartype azure_blob_source: ~azure.ai.documentintelligence.models.AzureBlobContentSource
:ivar azure_blob_file_list_source: Azure Blob Storage file list specifying the batch documents.
Either
azureBlobSource or azureBlobFileListSource must be specified.
:vartype azure_blob_file_list_source:
~azure.ai.documentintelligence.models.AzureBlobFileListContentSource
:ivar result_container_url: Azure Blob Storage container URL where analyze result files will be
stored. Required.
:vartype result_container_url: str
:ivar result_prefix: Blob name prefix of result files.
:vartype result_prefix: str
:ivar overwrite_existing: Overwrite existing analyze result files?.
:vartype overwrite_existing: bool
"""
azure_blob_source: Optional["_models.AzureBlobContentSource"] = rest_field(name="azureBlobSource")
"""Azure Blob Storage location containing the batch documents. Either
azureBlobSource or azureBlobFileListSource must be specified."""
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = rest_field(
name="azureBlobFileListSource"
)
"""Azure Blob Storage file list specifying the batch documents. Either
azureBlobSource or azureBlobFileListSource must be specified."""
result_container_url: str = rest_field(name="resultContainerUrl")
"""Azure Blob Storage container URL where analyze result files will be stored. Required."""
result_prefix: Optional[str] = rest_field(name="resultPrefix")
"""Blob name prefix of result files."""
overwrite_existing: Optional[bool] = rest_field(name="overwriteExisting")
"""Overwrite existing analyze result files?."""
@overload
def __init__(
self,
*,
result_container_url: str,
azure_blob_source: Optional["_models.AzureBlobContentSource"] = None,
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = None,
result_prefix: Optional[str] = None,
overwrite_existing: Optional[bool] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AnalyzeBatchOperationDetail(_model_base.Model):
"""Operation detail for a document in a batch analysis.
:ivar status: Analyze status. succeeded, failed, or skipped. Required. Known values are:
"notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar source_url: URL of the source document. Required.
:vartype source_url: str
:ivar result_url: URL of the analyze result JSON.
:vartype result_url: str
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
"""
status: Union[str, "_models.OperationStatus"] = rest_field()
"""Analyze status. succeeded, failed, or skipped. Required. Known values are: \"notStarted\",
\"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
source_url: str = rest_field(name="sourceUrl")
"""URL of the source document. Required."""
result_url: Optional[str] = rest_field(name="resultUrl")
"""URL of the analyze result JSON."""
error: Optional["_models.Error"] = rest_field()
"""Encountered error."""
@overload
def __init__(
self,
*,
status: Union[str, "_models.OperationStatus"],
source_url: str,
result_url: Optional[str] = None,
error: Optional["_models.Error"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AnalyzeBatchResult(_model_base.Model):
"""Batch document analysis result.
:ivar succeeded_count: Number of documents that completed with status succeeded. Required.
:vartype succeeded_count: int
:ivar failed_count: Number of documents that completed with status failed. Required.
:vartype failed_count: int
:ivar skipped_count: Number of documents that completed with status skipped. Required.
:vartype skipped_count: int
:ivar details: Operation detail for each document in the batch. Required.
:vartype details: list[~azure.ai.documentintelligence.models.AnalyzeBatchOperationDetail]
"""
succeeded_count: int = rest_field(name="succeededCount")
"""Number of documents that completed with status succeeded. Required."""
failed_count: int = rest_field(name="failedCount")
"""Number of documents that completed with status failed. Required."""
skipped_count: int = rest_field(name="skippedCount")
"""Number of documents that completed with status skipped. Required."""
details: List["_models.AnalyzeBatchOperationDetail"] = rest_field()
"""Operation detail for each document in the batch. Required."""
@overload
def __init__(
self,
*,
succeeded_count: int,
failed_count: int,
skipped_count: int,
details: List["_models.AnalyzeBatchOperationDetail"],
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AnalyzeBatchResultOperation(_model_base.Model):
"""Status and result of the analyze batch operation.
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar created_date_time: Date and time (UTC) when the operation was submitted. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar error: Encountered error during batch document analysis.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar result: Batch document analysis result.
:vartype result: ~azure.ai.documentintelligence.models.AnalyzeBatchResult
"""
status: Union[str, "_models.OperationStatus"] = rest_field()
"""Operation status. notStarted, running, completed, or failed. Required. Known values are:
\"notStarted\", \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
"""Date and time (UTC) when the operation was submitted. Required."""
last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
"""Date and time (UTC) when the status was last updated. Required."""
percent_completed: Optional[int] = rest_field(name="percentCompleted")
"""Operation progress (0-100)."""
error: Optional["_models.Error"] = rest_field()
"""Encountered error during batch document analysis."""
result: Optional["_models.AnalyzeBatchResult"] = rest_field()
"""Batch document analysis result."""
@overload
def __init__(
self,
*,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
percent_completed: Optional[int] = None,
error: Optional["_models.Error"] = None,
result: Optional["_models.AnalyzeBatchResult"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
class AnalyzeDocumentRequest(_model_base.Model):
"""Document analysis parameters.
:ivar url_source: Document URL to analyze. Either urlSource or base64Source must be specified.
:vartype url_source: str
:ivar bytes_source: Base64 encoding of the document to analyze. Either urlSource or
base64Source
must be specified.
:vartype bytes_source: bytes
"""
url_source: Optional[str] = rest_field(name="urlSource")
"""Document URL to analyze. Either urlSource or base64Source must be specified."""
bytes_source: Optional[bytes] = rest_field(name="base64Source", format="base64")
"""Base64 encoding of the document to analyze. Either urlSource or base64Source
must be specified."""
@overload
def __init__(
self,
*,
url_source: Optional[str] = None,
bytes_source: Optional[bytes] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AnalyzeResult(_model_base.Model): # pylint: disable=too-many-instance-attributes
"""Document analysis result.
:ivar api_version: API version used to produce this result. Required.
:vartype api_version: str
:ivar model_id: Document model ID used to produce this result. Required.
:vartype model_id: str
:ivar string_index_type: Method used to compute string offset and length. Required. Known
values are: "textElements", "unicodeCodePoint", and "utf16CodeUnit".
:vartype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
:ivar content_format: Format of the analyze result top-level content. Known values are: "text"
and "markdown".
:vartype content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
:ivar content: Concatenate string representation of all textual and visual elements in reading
order. Required.
:vartype content: str
:ivar pages: Analyzed pages. Required.
:vartype pages: list[~azure.ai.documentintelligence.models.DocumentPage]
:ivar paragraphs: Extracted paragraphs.
:vartype paragraphs: list[~azure.ai.documentintelligence.models.DocumentParagraph]
:ivar tables: Extracted tables.
:vartype tables: list[~azure.ai.documentintelligence.models.DocumentTable]
:ivar figures: Extracted figures.
:vartype figures: list[~azure.ai.documentintelligence.models.DocumentFigure]
:ivar sections: Extracted sections.
:vartype sections: list[~azure.ai.documentintelligence.models.DocumentSection]
:ivar key_value_pairs: Extracted key-value pairs.
:vartype key_value_pairs: list[~azure.ai.documentintelligence.models.DocumentKeyValuePair]
:ivar styles: Extracted font styles.
:vartype styles: list[~azure.ai.documentintelligence.models.DocumentStyle]
:ivar languages: Detected languages.
:vartype languages: list[~azure.ai.documentintelligence.models.DocumentLanguage]
:ivar documents: Extracted documents.
:vartype documents: list[~azure.ai.documentintelligence.models.Document]
:ivar warnings: List of warnings encountered.
:vartype warnings: list[~azure.ai.documentintelligence.models.Warning]
"""
api_version: str = rest_field(name="apiVersion")
"""API version used to produce this result. Required."""
model_id: str = rest_field(name="modelId")
"""Document model ID used to produce this result. Required."""
string_index_type: Union[str, "_models.StringIndexType"] = rest_field(name="stringIndexType")
"""Method used to compute string offset and length. Required. Known values are: \"textElements\",
\"unicodeCodePoint\", and \"utf16CodeUnit\"."""
content_format: Optional[Union[str, "_models.ContentFormat"]] = rest_field(name="contentFormat")
"""Format of the analyze result top-level content. Known values are: \"text\" and \"markdown\"."""
content: str = rest_field()
"""Concatenate string representation of all textual and visual elements in reading
order. Required."""
pages: List["_models.DocumentPage"] = rest_field()
"""Analyzed pages. Required."""
paragraphs: Optional[List["_models.DocumentParagraph"]] = rest_field()
"""Extracted paragraphs."""
tables: Optional[List["_models.DocumentTable"]] = rest_field()
"""Extracted tables."""
figures: Optional[List["_models.DocumentFigure"]] = rest_field()
"""Extracted figures."""
sections: Optional[List["_models.DocumentSection"]] = rest_field()
"""Extracted sections."""
key_value_pairs: Optional[List["_models.DocumentKeyValuePair"]] = rest_field(name="keyValuePairs")
"""Extracted key-value pairs."""
styles: Optional[List["_models.DocumentStyle"]] = rest_field()
"""Extracted font styles."""
languages: Optional[List["_models.DocumentLanguage"]] = rest_field()
"""Detected languages."""
documents: Optional[List["_models.Document"]] = rest_field()
"""Extracted documents."""
warnings: Optional[List["_models.Warning"]] = rest_field()
"""List of warnings encountered."""
@overload
def __init__(
self,
*,
api_version: str,
model_id: str,
string_index_type: Union[str, "_models.StringIndexType"],
content: str,
pages: List["_models.DocumentPage"],
content_format: Optional[Union[str, "_models.ContentFormat"]] = None,
paragraphs: Optional[List["_models.DocumentParagraph"]] = None,
tables: Optional[List["_models.DocumentTable"]] = None,
figures: Optional[List["_models.DocumentFigure"]] = None,
sections: Optional[List["_models.DocumentSection"]] = None,
key_value_pairs: Optional[List["_models.DocumentKeyValuePair"]] = None,
styles: Optional[List["_models.DocumentStyle"]] = None,
languages: Optional[List["_models.DocumentLanguage"]] = None,
documents: Optional[List["_models.Document"]] = None,
warnings: Optional[List["_models.Warning"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AnalyzeResultOperation(_model_base.Model):
"""Status and result of the analyze operation.
:ivar status: Operation status. notStarted, running, succeeded, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar created_date_time: Date and time (UTC) when the analyze operation was submitted.
Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar error: Encountered error during document analysis.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar analyze_result: Document analysis result.
:vartype analyze_result: ~azure.ai.documentintelligence.models.AnalyzeResult
"""
status: Union[str, "_models.OperationStatus"] = rest_field()
"""Operation status. notStarted, running, succeeded, or failed. Required. Known values are:
\"notStarted\", \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
"""Date and time (UTC) when the analyze operation was submitted. Required."""
last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
"""Date and time (UTC) when the status was last updated. Required."""
error: Optional["_models.Error"] = rest_field()
"""Encountered error during document analysis."""
analyze_result: Optional["_models.AnalyzeResult"] = rest_field(name="analyzeResult")
"""Document analysis result."""
@overload
def __init__(
self,
*,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
error: Optional["_models.Error"] = None,
analyze_result: Optional["_models.AnalyzeResult"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AuthorizeClassifierCopyRequest(_model_base.Model):
"""Request body to authorize document classifier copy.
All required parameters must be populated in order to send to server.
:ivar classifier_id: Unique document classifier name. Required.
:vartype classifier_id: str
:ivar description: Document classifier description.
:vartype description: str
:ivar tags: List of key-value tag attributes associated with the document classifier.
:vartype tags: dict[str, str]
"""
classifier_id: str = rest_field(name="classifierId")
"""Unique document classifier name. Required."""
description: Optional[str] = rest_field()
"""Document classifier description."""
tags: Optional[Dict[str, str]] = rest_field()
"""List of key-value tag attributes associated with the document classifier."""
@overload
def __init__(
self,
*,
classifier_id: str,
description: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AuthorizeCopyRequest(_model_base.Model):
"""Request body to authorize document model copy.
All required parameters must be populated in order to send to server.
:ivar model_id: Unique document model name. Required.
:vartype model_id: str
:ivar description: Document model description.
:vartype description: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
"""
model_id: str = rest_field(name="modelId")
"""Unique document model name. Required."""
description: Optional[str] = rest_field()
"""Document model description."""
tags: Optional[Dict[str, str]] = rest_field()
"""List of key-value tag attributes associated with the document model."""
@overload
def __init__(
self,
*,
model_id: str,
description: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AzureBlobContentSource(_model_base.Model):
"""Azure Blob Storage content.
:ivar container_url: Azure Blob Storage container URL. Required.
:vartype container_url: str
:ivar prefix: Blob name prefix.
:vartype prefix: str
"""
container_url: str = rest_field(name="containerUrl")
"""Azure Blob Storage container URL. Required."""
prefix: Optional[str] = rest_field()
"""Blob name prefix."""
@overload
def __init__(
self,
*,
container_url: str,
prefix: Optional[str] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class AzureBlobFileListContentSource(_model_base.Model):
"""File list in Azure Blob Storage.
:ivar container_url: Azure Blob Storage container URL. Required.
:vartype container_url: str
:ivar file_list: Path to a JSONL file within the container specifying a subset of documents.
Required.
:vartype file_list: str
"""
container_url: str = rest_field(name="containerUrl")
"""Azure Blob Storage container URL. Required."""
file_list: str = rest_field(name="fileList")
"""Path to a JSONL file within the container specifying a subset of documents. Required."""
@overload
def __init__(
self,
*,
container_url: str,
file_list: str,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class BoundingRegion(_model_base.Model):
"""Bounding polygon on a specific page of the input.
:ivar page_number: 1-based page number of page containing the bounding region. Required.
:vartype page_number: int
:ivar polygon: Bounding polygon on the page, or the entire page if not specified.
Coordinates specified relative to the top-left of the page. The numbers
represent the x, y values of the polygon vertices, clockwise from the left
(-180 degrees inclusive) relative to the element orientation. Required.
:vartype polygon: list[float]
"""
page_number: int = rest_field(name="pageNumber")
"""1-based page number of page containing the bounding region. Required."""
polygon: List[float] = rest_field()
"""Bounding polygon on the page, or the entire page if not specified.
Coordinates specified relative to the top-left of the page. The numbers
represent the x, y values of the polygon vertices, clockwise from the left
(-180 degrees inclusive) relative to the element orientation. Required."""
@overload
def __init__(
self,
*,
page_number: int,
polygon: List[float],
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class BuildDocumentClassifierRequest(_model_base.Model):
"""Request body to build a new custom document classifier.
All required parameters must be populated in order to send to server.
:ivar classifier_id: Unique document classifier name. Required.
:vartype classifier_id: str
:ivar description: Document classifier description.
:vartype description: str
:ivar base_classifier_id: Base classifierId on top of which to train the classifier.
:vartype base_classifier_id: str
:ivar doc_types: List of document types to classify against. Required.
:vartype doc_types: dict[str,
~azure.ai.documentintelligence.models.ClassifierDocumentTypeDetails]
:ivar allow_overwrite: Allow overwriting an existing classifier with the same name.
:vartype allow_overwrite: bool
"""
classifier_id: str = rest_field(name="classifierId")
"""Unique document classifier name. Required."""
description: Optional[str] = rest_field()
"""Document classifier description."""
base_classifier_id: Optional[str] = rest_field(name="baseClassifierId")
"""Base classifierId on top of which to train the classifier."""
doc_types: Dict[str, "_models.ClassifierDocumentTypeDetails"] = rest_field(name="docTypes")
"""List of document types to classify against. Required."""
allow_overwrite: Optional[bool] = rest_field(name="allowOverwrite")
"""Allow overwriting an existing classifier with the same name."""
@overload
def __init__(
self,
*,
classifier_id: str,
doc_types: Dict[str, "_models.ClassifierDocumentTypeDetails"],
description: Optional[str] = None,
base_classifier_id: Optional[str] = None,
allow_overwrite: Optional[bool] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class BuildDocumentModelRequest(_model_base.Model):
"""Request body to build a new custom document model.
All required parameters must be populated in order to send to server.
:ivar model_id: Unique document model name. Required.
:vartype model_id: str
:ivar description: Document model description.
:vartype description: str
:ivar build_mode: Custom document model build mode. Required. Known values are: "template",
"neural", and "generative".
:vartype build_mode: str or ~azure.ai.documentintelligence.models.DocumentBuildMode
:ivar azure_blob_source: Azure Blob Storage location containing the training data. Either
azureBlobSource or azureBlobFileListSource must be specified.
:vartype azure_blob_source: ~azure.ai.documentintelligence.models.AzureBlobContentSource
:ivar azure_blob_file_list_source: Azure Blob Storage file list specifying the training data.
Either
azureBlobSource or azureBlobFileListSource must be specified.
:vartype azure_blob_file_list_source:
~azure.ai.documentintelligence.models.AzureBlobFileListContentSource
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar max_training_hours: Max number of V100-equivalent GPU hours to use for model training.
Default=0.5.
:vartype max_training_hours: float
:ivar allow_overwrite: Allow overwriting an existing model with the same name.
:vartype allow_overwrite: bool
"""
model_id: str = rest_field(name="modelId")
"""Unique document model name. Required."""
description: Optional[str] = rest_field()
"""Document model description."""
build_mode: Union[str, "_models.DocumentBuildMode"] = rest_field(name="buildMode")
"""Custom document model build mode. Required. Known values are: \"template\", \"neural\", and
\"generative\"."""
azure_blob_source: Optional["_models.AzureBlobContentSource"] = rest_field(name="azureBlobSource")
"""Azure Blob Storage location containing the training data. Either
azureBlobSource or azureBlobFileListSource must be specified."""
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = rest_field(
name="azureBlobFileListSource"
)
"""Azure Blob Storage file list specifying the training data. Either
azureBlobSource or azureBlobFileListSource must be specified."""
tags: Optional[Dict[str, str]] = rest_field()
"""List of key-value tag attributes associated with the document model."""
max_training_hours: Optional[float] = rest_field(name="maxTrainingHours")
"""Max number of V100-equivalent GPU hours to use for model training. Default=0.5."""
allow_overwrite: Optional[bool] = rest_field(name="allowOverwrite")
"""Allow overwriting an existing model with the same name."""
@overload
def __init__(
self,
*,
model_id: str,
build_mode: Union[str, "_models.DocumentBuildMode"],
description: Optional[str] = None,
azure_blob_source: Optional["_models.AzureBlobContentSource"] = None,
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = None,
tags: Optional[Dict[str, str]] = None,
max_training_hours: Optional[float] = None,
allow_overwrite: Optional[bool] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class ClassifierCopyAuthorization(_model_base.Model):
"""Authorization to copy a document classifier to the specified target resource and
classifierId.
:ivar target_resource_id: ID of the target Azure resource where the document classifier should
be copied to. Required.
:vartype target_resource_id: str
:ivar target_resource_region: Location of the target Azure resource where the document
classifier should be copied
to. Required.
:vartype target_resource_region: str
:ivar target_classifier_id: Identifier of the target document classifier. Required.
:vartype target_classifier_id: str
:ivar target_classifier_location: URL of the copied document classifier in the target account.
Required.
:vartype target_classifier_location: str
:ivar access_token: Token used to authorize the request. Required.
:vartype access_token: str
:ivar expiration_date_time: Date/time when the access token expires. Required.
:vartype expiration_date_time: ~datetime.datetime
"""
target_resource_id: str = rest_field(name="targetResourceId")
"""ID of the target Azure resource where the document classifier should be copied to. Required."""
target_resource_region: str = rest_field(name="targetResourceRegion")
"""Location of the target Azure resource where the document classifier should be copied
to. Required."""
target_classifier_id: str = rest_field(name="targetClassifierId")
"""Identifier of the target document classifier. Required."""
target_classifier_location: str = rest_field(name="targetClassifierLocation")
"""URL of the copied document classifier in the target account. Required."""
access_token: str = rest_field(name="accessToken")
"""Token used to authorize the request. Required."""
expiration_date_time: datetime.datetime = rest_field(name="expirationDateTime", format="rfc3339")
"""Date/time when the access token expires. Required."""
@overload
def __init__(
self,
*,
target_resource_id: str,
target_resource_region: str,
target_classifier_id: str,
target_classifier_location: str,
access_token: str,
expiration_date_time: datetime.datetime,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class ClassifierDocumentTypeDetails(_model_base.Model):
"""Classifier document type info.
:ivar source_kind: Type of training data source. Known values are: "url", "base64",
"azureBlob", and "azureBlobFileList".
:vartype source_kind: str or ~azure.ai.documentintelligence.models.ContentSourceKind
:ivar azure_blob_source: Azure Blob Storage location containing the training data for a
classifier
document type. Either azureBlobSource or azureBlobFileListSource must be
specified.
:vartype azure_blob_source: ~azure.ai.documentintelligence.models.AzureBlobContentSource
:ivar azure_blob_file_list_source: Azure Blob Storage file list specifying the training data
for a classifier
document type. Either azureBlobSource or azureBlobFileListSource must be
specified.
:vartype azure_blob_file_list_source:
~azure.ai.documentintelligence.models.AzureBlobFileListContentSource
"""
source_kind: Optional[Union[str, "_models.ContentSourceKind"]] = rest_field(name="sourceKind")
"""Type of training data source. Known values are: \"url\", \"base64\", \"azureBlob\", and
\"azureBlobFileList\"."""
azure_blob_source: Optional["_models.AzureBlobContentSource"] = rest_field(name="azureBlobSource")
"""Azure Blob Storage location containing the training data for a classifier
document type. Either azureBlobSource or azureBlobFileListSource must be
specified."""
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = rest_field(
name="azureBlobFileListSource"
)
"""Azure Blob Storage file list specifying the training data for a classifier
document type. Either azureBlobSource or azureBlobFileListSource must be
specified."""
@overload
def __init__(
self,
*,
source_kind: Optional[Union[str, "_models.ContentSourceKind"]] = None,
azure_blob_source: Optional["_models.AzureBlobContentSource"] = None,
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
class ClassifyDocumentRequest(_model_base.Model):
"""Document classification parameters.
:ivar url_source: Document URL to classify. Either urlSource or base64Source must be
specified.
:vartype url_source: str
:ivar bytes_source: Base64 encoding of the document to classify. Either urlSource or
base64Source
must be specified.
:vartype bytes_source: bytes
"""
url_source: Optional[str] = rest_field(name="urlSource")
"""Document URL to classify. Either urlSource or base64Source must be specified."""
bytes_source: Optional[bytes] = rest_field(name="base64Source", format="base64")
"""Base64 encoding of the document to classify. Either urlSource or base64Source
must be specified."""
@overload
def __init__(
self,
*,
url_source: Optional[str] = None,
bytes_source: Optional[bytes] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class ComposeDocumentModelRequest(_model_base.Model):
"""Request body to create a composed document model from component document models.
All required parameters must be populated in order to send to server.
:ivar model_id: Unique document model name. Required.
:vartype model_id: str
:ivar description: Document model description.
:vartype description: str
:ivar classifier_id: Custom classifier to split and classify the input file. Required.
:vartype classifier_id: str
:ivar split: File splitting behavior. Known values are: "auto", "none", and "perPage".
:vartype split: str or ~azure.ai.documentintelligence.models.SplitMode
:ivar doc_types: Dictionary mapping supported docTypes to the corresponding document models.
Required.
:vartype doc_types: dict[str, ~azure.ai.documentintelligence.models.DocumentTypeDetails]
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
"""
model_id: str = rest_field(name="modelId")
"""Unique document model name. Required."""
description: Optional[str] = rest_field()
"""Document model description."""
classifier_id: str = rest_field(name="classifierId")
"""Custom classifier to split and classify the input file. Required."""
split: Optional[Union[str, "_models.SplitMode"]] = rest_field()
"""File splitting behavior. Known values are: \"auto\", \"none\", and \"perPage\"."""
doc_types: Dict[str, "_models.DocumentTypeDetails"] = rest_field(name="docTypes")
"""Dictionary mapping supported docTypes to the corresponding document models. Required."""
tags: Optional[Dict[str, str]] = rest_field()
"""List of key-value tag attributes associated with the document model."""
@overload
def __init__(
self,
*,
model_id: str,
classifier_id: str,
doc_types: Dict[str, "_models.DocumentTypeDetails"],
description: Optional[str] = None,
split: Optional[Union[str, "_models.SplitMode"]] = None,
tags: Optional[Dict[str, str]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class CopyAuthorization(_model_base.Model):
"""Authorization to copy a document model to the specified target resource and
modelId.
:ivar target_resource_id: ID of the target Azure resource where the document model should be
copied to. Required.
:vartype target_resource_id: str
:ivar target_resource_region: Location of the target Azure resource where the document model
should be copied
to. Required.
:vartype target_resource_region: str
:ivar target_model_id: Identifier of the target document model. Required.
:vartype target_model_id: str
:ivar target_model_location: URL of the copied document model in the target account. Required.
:vartype target_model_location: str
:ivar access_token: Token used to authorize the request. Required.
:vartype access_token: str
:ivar expiration_date_time: Date/time when the access token expires. Required.
:vartype expiration_date_time: ~datetime.datetime
"""
target_resource_id: str = rest_field(name="targetResourceId")
"""ID of the target Azure resource where the document model should be copied to. Required."""
target_resource_region: str = rest_field(name="targetResourceRegion")
"""Location of the target Azure resource where the document model should be copied
to. Required."""
target_model_id: str = rest_field(name="targetModelId")
"""Identifier of the target document model. Required."""
target_model_location: str = rest_field(name="targetModelLocation")
"""URL of the copied document model in the target account. Required."""
access_token: str = rest_field(name="accessToken")
"""Token used to authorize the request. Required."""
expiration_date_time: datetime.datetime = rest_field(name="expirationDateTime", format="rfc3339")
"""Date/time when the access token expires. Required."""
@overload
def __init__(
self,
*,
target_resource_id: str,
target_resource_region: str,
target_model_id: str,
target_model_location: str,
access_token: str,
expiration_date_time: datetime.datetime,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class CurrencyValue(_model_base.Model):
"""Currency field value.
:ivar amount: Currency amount. Required.
:vartype amount: float
:ivar currency_symbol: Currency symbol label, if any.
:vartype currency_symbol: str
:ivar currency_code: Resolved currency code (ISO 4217), if any.
:vartype currency_code: str
"""
amount: float = rest_field()
"""Currency amount. Required."""
currency_symbol: Optional[str] = rest_field(name="currencySymbol")
"""Currency symbol label, if any."""
currency_code: Optional[str] = rest_field(name="currencyCode")
"""Resolved currency code (ISO 4217), if any."""
@overload
def __init__(
self,
*,
amount: float,
currency_symbol: Optional[str] = None,
currency_code: Optional[str] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class CustomDocumentModelsDetails(_model_base.Model):
"""Details regarding custom document models.
:ivar count: Number of custom document models in the current resource. Required.
:vartype count: int
:ivar limit: Maximum number of custom document models supported in the current resource.
Required.
:vartype limit: int
"""
count: int = rest_field()
"""Number of custom document models in the current resource. Required."""
limit: int = rest_field()
"""Maximum number of custom document models supported in the current resource. Required."""
@overload
def __init__(
self,
*,
count: int,
limit: int,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class Document(_model_base.Model):
"""An object describing the location and semantic content of a document.
:ivar doc_type: Document type. Required.
:vartype doc_type: str
:ivar bounding_regions: Bounding regions covering the document.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the document in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar fields: Dictionary of named field values.
:vartype fields: dict[str, ~azure.ai.documentintelligence.models.DocumentField]
:ivar confidence: Confidence of correctly extracting the document. Required.
:vartype confidence: float
"""
doc_type: str = rest_field(name="docType")
"""Document type. Required."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the document."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the document in the reading order concatenated content. Required."""
fields: Optional[Dict[str, "_models.DocumentField"]] = rest_field()
"""Dictionary of named field values."""
confidence: float = rest_field()
"""Confidence of correctly extracting the document. Required."""
@overload
def __init__(
self,
*,
doc_type: str,
spans: List["_models.DocumentSpan"],
confidence: float,
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
fields: Optional[Dict[str, "_models.DocumentField"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentBarcode(_model_base.Model):
"""A barcode object.
:ivar kind: Barcode kind. Required. Known values are: "QRCode", "PDF417", "UPCA", "UPCE",
"Code39", "Code128", "EAN8", "EAN13", "DataBar", "Code93", "Codabar", "DataBarExpanded", "ITF",
"MicroQRCode", "Aztec", "DataMatrix", and "MaxiCode".
:vartype kind: str or ~azure.ai.documentintelligence.models.DocumentBarcodeKind
:ivar value: Barcode value. Required.
:vartype value: str
:ivar polygon: Bounding polygon of the barcode, with coordinates specified relative to the
top-left of the page. The numbers represent the x, y values of the polygon
vertices, clockwise from the left (-180 degrees inclusive) relative to the
element orientation.
:vartype polygon: list[float]
:ivar span: Location of the barcode in the reading order concatenated content. Required.
:vartype span: ~azure.ai.documentintelligence.models.DocumentSpan
:ivar confidence: Confidence of correctly extracting the barcode. Required.
:vartype confidence: float
"""
kind: Union[str, "_models.DocumentBarcodeKind"] = rest_field()
"""Barcode kind. Required. Known values are: \"QRCode\", \"PDF417\", \"UPCA\", \"UPCE\",
\"Code39\", \"Code128\", \"EAN8\", \"EAN13\", \"DataBar\", \"Code93\", \"Codabar\",
\"DataBarExpanded\", \"ITF\", \"MicroQRCode\", \"Aztec\", \"DataMatrix\", and \"MaxiCode\"."""
value: str = rest_field()
"""Barcode value. Required."""
polygon: Optional[List[float]] = rest_field()
"""Bounding polygon of the barcode, with coordinates specified relative to the
top-left of the page. The numbers represent the x, y values of the polygon
vertices, clockwise from the left (-180 degrees inclusive) relative to the
element orientation."""
span: "_models.DocumentSpan" = rest_field()
"""Location of the barcode in the reading order concatenated content. Required."""
confidence: float = rest_field()
"""Confidence of correctly extracting the barcode. Required."""
@overload
def __init__(
self,
*,
kind: Union[str, "_models.DocumentBarcodeKind"],
value: str,
span: "_models.DocumentSpan",
confidence: float,
polygon: Optional[List[float]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentCaption(_model_base.Model):
"""A caption object describing a table or figure.
:ivar content: Content of the caption. Required.
:vartype content: str
:ivar bounding_regions: Bounding regions covering the caption.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the caption in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar elements: Child elements of the caption.
:vartype elements: list[str]
"""
content: str = rest_field()
"""Content of the caption. Required."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the caption."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the caption in the reading order concatenated content. Required."""
elements: Optional[List[str]] = rest_field()
"""Child elements of the caption."""
@overload
def __init__(
self,
*,
content: str,
spans: List["_models.DocumentSpan"],
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
elements: Optional[List[str]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class OperationDetails(_model_base.Model):
"""Operation info.
You probably want to use the sub-classes and not this class directly. Known sub-classes are:
DocumentClassifierBuildOperationDetails, DocumentClassifierCopyToOperationDetails,
DocumentModelBuildOperationDetails, DocumentModelComposeOperationDetails,
DocumentModelCopyToOperationDetails
:ivar operation_id: Operation ID. Required.
:vartype operation_id: str
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar created_date_time: Date and time (UTC) when the operation was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar kind: Type of operation. Required. Known values are: "documentModelBuild",
"documentModelCompose", "documentModelCopyTo", "documentClassifierCopyTo", and
"documentClassifierBuild".
:vartype kind: str or ~azure.ai.documentintelligence.models.OperationKind
:ivar resource_location: URL of the resource targeted by this operation. Required.
:vartype resource_location: str
:ivar api_version: API version used to create this operation.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
"""
__mapping__: Dict[str, _model_base.Model] = {}
operation_id: str = rest_field(name="operationId", visibility=["read", "create"])
"""Operation ID. Required."""
status: Union[str, "_models.OperationStatus"] = rest_field()
"""Operation status. notStarted, running, completed, or failed. Required. Known values are:
\"notStarted\", \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
percent_completed: Optional[int] = rest_field(name="percentCompleted")
"""Operation progress (0-100)."""
created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
"""Date and time (UTC) when the operation was created. Required."""
last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
"""Date and time (UTC) when the status was last updated. Required."""
kind: str = rest_discriminator(name="kind")
"""Type of operation. Required. Known values are: \"documentModelBuild\",
\"documentModelCompose\", \"documentModelCopyTo\", \"documentClassifierCopyTo\", and
\"documentClassifierBuild\"."""
resource_location: str = rest_field(name="resourceLocation")
"""URL of the resource targeted by this operation. Required."""
api_version: Optional[str] = rest_field(name="apiVersion")
"""API version used to create this operation."""
tags: Optional[Dict[str, str]] = rest_field()
"""List of key-value tag attributes associated with the document model."""
error: Optional["_models.Error"] = rest_field()
"""Encountered error."""
@overload
def __init__(
self,
*,
operation_id: str,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
kind: str,
resource_location: str,
percent_completed: Optional[int] = None,
api_version: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
error: Optional["_models.Error"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentClassifierBuildOperationDetails(
OperationDetails, discriminator="documentClassifierBuild"
): # pylint: disable=too-many-instance-attributes
"""Get Operation response object.
:ivar operation_id: Operation ID. Required.
:vartype operation_id: str
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar created_date_time: Date and time (UTC) when the operation was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar resource_location: URL of the resource targeted by this operation. Required.
:vartype resource_location: str
:ivar api_version: API version used to create this operation.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar result: Operation result upon success.
:vartype result: ~azure.ai.documentintelligence.models.DocumentClassifierDetails
:ivar kind: Type of operation. Required. Build a new custom classifier model.
:vartype kind: str or ~azure.ai.documentintelligence.models.DOCUMENT_CLASSIFIER_BUILD
"""
result: Optional["_models.DocumentClassifierDetails"] = rest_field()
"""Operation result upon success."""
kind: Literal[OperationKind.DOCUMENT_CLASSIFIER_BUILD] = rest_discriminator(name="kind") # type: ignore
"""Type of operation. Required. Build a new custom classifier model."""
@overload
def __init__(
self,
*,
operation_id: str,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
resource_location: str,
percent_completed: Optional[int] = None,
api_version: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
error: Optional["_models.Error"] = None,
result: Optional["_models.DocumentClassifierDetails"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, kind=OperationKind.DOCUMENT_CLASSIFIER_BUILD, **kwargs)
[docs]
class DocumentClassifierCopyToOperationDetails(
OperationDetails, discriminator="documentClassifierCopyTo"
): # pylint: disable=too-many-instance-attributes
"""Get Operation response object.
:ivar operation_id: Operation ID. Required.
:vartype operation_id: str
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar created_date_time: Date and time (UTC) when the operation was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar resource_location: URL of the resource targeted by this operation. Required.
:vartype resource_location: str
:ivar api_version: API version used to create this operation.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar result: Operation result upon success.
:vartype result: ~azure.ai.documentintelligence.models.DocumentClassifierDetails
:ivar kind: Type of operation. Required. Copy an existing document classifier to potentially a
different resource, region, or
subscription.
:vartype kind: str or ~azure.ai.documentintelligence.models.DOCUMENT_CLASSIFIER_COPY_TO
"""
result: Optional["_models.DocumentClassifierDetails"] = rest_field()
"""Operation result upon success."""
kind: Literal[OperationKind.DOCUMENT_CLASSIFIER_COPY_TO] = rest_discriminator(name="kind") # type: ignore
"""Type of operation. Required. Copy an existing document classifier to potentially a different
resource, region, or
subscription."""
@overload
def __init__(
self,
*,
operation_id: str,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
resource_location: str,
percent_completed: Optional[int] = None,
api_version: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
error: Optional["_models.Error"] = None,
result: Optional["_models.DocumentClassifierDetails"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, kind=OperationKind.DOCUMENT_CLASSIFIER_COPY_TO, **kwargs)
[docs]
class DocumentClassifierDetails(_model_base.Model):
"""Document classifier info.
:ivar classifier_id: Unique document classifier name. Required.
:vartype classifier_id: str
:ivar description: Document classifier description.
:vartype description: str
:ivar created_date_time: Date and time (UTC) when the document classifier was created.
Required.
:vartype created_date_time: ~datetime.datetime
:ivar expiration_date_time: Date and time (UTC) when the document classifier will expire.
:vartype expiration_date_time: ~datetime.datetime
:ivar api_version: API version used to create this document classifier. Required.
:vartype api_version: str
:ivar base_classifier_id: Base classifierId on top of which the classifier was trained.
:vartype base_classifier_id: str
:ivar doc_types: List of document types to classify against. Required.
:vartype doc_types: dict[str,
~azure.ai.documentintelligence.models.ClassifierDocumentTypeDetails]
:ivar warnings: List of warnings encountered while building the classifier.
:vartype warnings: list[~azure.ai.documentintelligence.models.Warning]
"""
classifier_id: str = rest_field(name="classifierId", visibility=["read", "create"])
"""Unique document classifier name. Required."""
description: Optional[str] = rest_field()
"""Document classifier description."""
created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
"""Date and time (UTC) when the document classifier was created. Required."""
expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
"""Date and time (UTC) when the document classifier will expire."""
api_version: str = rest_field(name="apiVersion")
"""API version used to create this document classifier. Required."""
base_classifier_id: Optional[str] = rest_field(name="baseClassifierId")
"""Base classifierId on top of which the classifier was trained."""
doc_types: Dict[str, "_models.ClassifierDocumentTypeDetails"] = rest_field(name="docTypes")
"""List of document types to classify against. Required."""
warnings: Optional[List["_models.Warning"]] = rest_field()
"""List of warnings encountered while building the classifier."""
@overload
def __init__(
self,
*,
classifier_id: str,
created_date_time: datetime.datetime,
api_version: str,
doc_types: Dict[str, "_models.ClassifierDocumentTypeDetails"],
description: Optional[str] = None,
expiration_date_time: Optional[datetime.datetime] = None,
base_classifier_id: Optional[str] = None,
warnings: Optional[List["_models.Warning"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentField(_model_base.Model): # pylint: disable=too-many-instance-attributes
"""An object representing the content and location of a field value.
:ivar type: Data type of the field value. Required. Known values are: "string", "date", "time",
"phoneNumber", "number", "integer", "selectionMark", "countryRegion", "signature", "array",
"object", "currency", "address", "boolean", and "selectionGroup".
:vartype type: str or ~azure.ai.documentintelligence.models.DocumentFieldType
:ivar value_string: String value.
:vartype value_string: str
:ivar value_date: Date value in YYYY-MM-DD format (ISO 8601).
:vartype value_date: ~datetime.date
:ivar value_time: Time value in hh:mm:ss format (ISO 8601).
:vartype value_time: ~datetime.time
:ivar value_phone_number: Phone number value in E.164 format (ex. +19876543210).
:vartype value_phone_number: str
:ivar value_number: Floating point value.
:vartype value_number: float
:ivar value_integer: Integer value.
:vartype value_integer: int
:ivar value_selection_mark: Selection mark value. Known values are: "selected" and
"unselected".
:vartype value_selection_mark: str or
~azure.ai.documentintelligence.models.DocumentSelectionMarkState
:ivar value_signature: Presence of signature. Known values are: "signed" and "unsigned".
:vartype value_signature: str or ~azure.ai.documentintelligence.models.DocumentSignatureType
:ivar value_country_region: 3-letter country code value (ISO 3166-1 alpha-3).
:vartype value_country_region: str
:ivar value_array: Array of field values.
:vartype value_array: list[~azure.ai.documentintelligence.models.DocumentField]
:ivar value_object: Dictionary of named field values.
:vartype value_object: dict[str, ~azure.ai.documentintelligence.models.DocumentField]
:ivar value_currency: Currency value.
:vartype value_currency: ~azure.ai.documentintelligence.models.CurrencyValue
:ivar value_address: Address value.
:vartype value_address: ~azure.ai.documentintelligence.models.AddressValue
:ivar value_boolean: Boolean value.
:vartype value_boolean: bool
:ivar value_selection_group: Selection group value.
:vartype value_selection_group: list[str]
:ivar content: Field content.
:vartype content: str
:ivar bounding_regions: Bounding regions covering the field.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the field in the reading order concatenated content.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar confidence: Confidence of correctly extracting the field.
:vartype confidence: float
"""
type: Union[str, "_models.DocumentFieldType"] = rest_field()
"""Data type of the field value. Required. Known values are: \"string\", \"date\", \"time\",
\"phoneNumber\", \"number\", \"integer\", \"selectionMark\", \"countryRegion\", \"signature\",
\"array\", \"object\", \"currency\", \"address\", \"boolean\", and \"selectionGroup\"."""
value_string: Optional[str] = rest_field(name="valueString")
"""String value."""
value_date: Optional[datetime.date] = rest_field(name="valueDate")
"""Date value in YYYY-MM-DD format (ISO 8601)."""
value_time: Optional[datetime.time] = rest_field(name="valueTime")
"""Time value in hh:mm:ss format (ISO 8601)."""
value_phone_number: Optional[str] = rest_field(name="valuePhoneNumber")
"""Phone number value in E.164 format (ex. +19876543210)."""
value_number: Optional[float] = rest_field(name="valueNumber")
"""Floating point value."""
value_integer: Optional[int] = rest_field(name="valueInteger")
"""Integer value."""
value_selection_mark: Optional[Union[str, "_models.DocumentSelectionMarkState"]] = rest_field(
name="valueSelectionMark"
)
"""Selection mark value. Known values are: \"selected\" and \"unselected\"."""
value_signature: Optional[Union[str, "_models.DocumentSignatureType"]] = rest_field(name="valueSignature")
"""Presence of signature. Known values are: \"signed\" and \"unsigned\"."""
value_country_region: Optional[str] = rest_field(name="valueCountryRegion")
"""3-letter country code value (ISO 3166-1 alpha-3)."""
value_array: Optional[List["_models.DocumentField"]] = rest_field(name="valueArray")
"""Array of field values."""
value_object: Optional[Dict[str, "_models.DocumentField"]] = rest_field(name="valueObject")
"""Dictionary of named field values."""
value_currency: Optional["_models.CurrencyValue"] = rest_field(name="valueCurrency")
"""Currency value."""
value_address: Optional["_models.AddressValue"] = rest_field(name="valueAddress")
"""Address value."""
value_boolean: Optional[bool] = rest_field(name="valueBoolean")
"""Boolean value."""
value_selection_group: Optional[List[str]] = rest_field(name="valueSelectionGroup")
"""Selection group value."""
content: Optional[str] = rest_field()
"""Field content."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the field."""
spans: Optional[List["_models.DocumentSpan"]] = rest_field()
"""Location of the field in the reading order concatenated content."""
confidence: Optional[float] = rest_field()
"""Confidence of correctly extracting the field."""
@overload
def __init__(
self,
*,
type: Union[str, "_models.DocumentFieldType"],
value_string: Optional[str] = None,
value_date: Optional[datetime.date] = None,
value_time: Optional[datetime.time] = None,
value_phone_number: Optional[str] = None,
value_number: Optional[float] = None,
value_integer: Optional[int] = None,
value_selection_mark: Optional[Union[str, "_models.DocumentSelectionMarkState"]] = None,
value_signature: Optional[Union[str, "_models.DocumentSignatureType"]] = None,
value_country_region: Optional[str] = None,
value_array: Optional[List["_models.DocumentField"]] = None,
value_object: Optional[Dict[str, "_models.DocumentField"]] = None,
value_currency: Optional["_models.CurrencyValue"] = None,
value_address: Optional["_models.AddressValue"] = None,
value_boolean: Optional[bool] = None,
value_selection_group: Optional[List[str]] = None,
content: Optional[str] = None,
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
spans: Optional[List["_models.DocumentSpan"]] = None,
confidence: Optional[float] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentFieldSchema(_model_base.Model):
"""Description of the field semantic schema using a JSON Schema style syntax.
:ivar type: Semantic data type of the field value. Required. Known values are: "string",
"date", "time", "phoneNumber", "number", "integer", "selectionMark", "countryRegion",
"signature", "array", "object", "currency", "address", "boolean", and "selectionGroup".
:vartype type: str or ~azure.ai.documentintelligence.models.DocumentFieldType
:ivar description: Field description.
:vartype description: str
:ivar example: Example field content.
:vartype example: str
:ivar items_property: Field type schema of each array element.
:vartype items_property: ~azure.ai.documentintelligence.models.DocumentFieldSchema
:ivar properties: Named sub-fields of the object field.
:vartype properties: dict[str, ~azure.ai.documentintelligence.models.DocumentFieldSchema]
"""
type: Union[str, "_models.DocumentFieldType"] = rest_field()
"""Semantic data type of the field value. Required. Known values are: \"string\", \"date\",
\"time\", \"phoneNumber\", \"number\", \"integer\", \"selectionMark\", \"countryRegion\",
\"signature\", \"array\", \"object\", \"currency\", \"address\", \"boolean\", and
\"selectionGroup\"."""
description: Optional[str] = rest_field()
"""Field description."""
example: Optional[str] = rest_field()
"""Example field content."""
items_property: Optional["_models.DocumentFieldSchema"] = rest_field(name="items")
"""Field type schema of each array element."""
properties: Optional[Dict[str, "_models.DocumentFieldSchema"]] = rest_field()
"""Named sub-fields of the object field."""
@overload
def __init__(
self,
*,
type: Union[str, "_models.DocumentFieldType"],
description: Optional[str] = None,
example: Optional[str] = None,
items_property: Optional["_models.DocumentFieldSchema"] = None,
properties: Optional[Dict[str, "_models.DocumentFieldSchema"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentKeyValueElement(_model_base.Model):
"""An object representing the field key or value in a key-value pair.
:ivar content: Concatenated content of the key-value element in reading order. Required.
:vartype content: str
:ivar bounding_regions: Bounding regions covering the key-value element.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the key-value element in the reading order concatenated content.
Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
"""
content: str = rest_field()
"""Concatenated content of the key-value element in reading order. Required."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the key-value element."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the key-value element in the reading order concatenated content. Required."""
@overload
def __init__(
self,
*,
content: str,
spans: List["_models.DocumentSpan"],
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentKeyValuePair(_model_base.Model):
"""An object representing a form field with distinct field label (key) and field
value (may be empty).
:ivar key: Field label of the key-value pair. Required.
:vartype key: ~azure.ai.documentintelligence.models.DocumentKeyValueElement
:ivar value: Field value of the key-value pair.
:vartype value: ~azure.ai.documentintelligence.models.DocumentKeyValueElement
:ivar confidence: Confidence of correctly extracting the key-value pair. Required.
:vartype confidence: float
"""
key: "_models.DocumentKeyValueElement" = rest_field()
"""Field label of the key-value pair. Required."""
value: Optional["_models.DocumentKeyValueElement"] = rest_field()
"""Field value of the key-value pair."""
confidence: float = rest_field()
"""Confidence of correctly extracting the key-value pair. Required."""
@overload
def __init__(
self,
*,
key: "_models.DocumentKeyValueElement",
confidence: float,
value: Optional["_models.DocumentKeyValueElement"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentLanguage(_model_base.Model):
"""An object representing the detected language for a given text span.
:ivar locale: Detected language. Value may an ISO 639-1 language code (ex. "en", "fr")
or BCP 47 language tag (ex. "zh-Hans"). Required.
:vartype locale: str
:ivar spans: Location of the text elements in the concatenated content the language applies
to. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar confidence: Confidence of correctly identifying the language. Required.
:vartype confidence: float
"""
locale: str = rest_field()
"""Detected language. Value may an ISO 639-1 language code (ex. \"en\", \"fr\")
or BCP 47 language tag (ex. \"zh-Hans\"). Required."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the text elements in the concatenated content the language applies
to. Required."""
confidence: float = rest_field()
"""Confidence of correctly identifying the language. Required."""
@overload
def __init__(
self,
*,
locale: str,
spans: List["_models.DocumentSpan"],
confidence: float,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentLine(_model_base.Model):
"""A content line object consisting of an adjacent sequence of content elements,
such as words and selection marks.
:ivar content: Concatenated content of the contained elements in reading order. Required.
:vartype content: str
:ivar polygon: Bounding polygon of the line, with coordinates specified relative to the
top-left of the page. The numbers represent the x, y values of the polygon
vertices, clockwise from the left (-180 degrees inclusive) relative to the
element orientation.
:vartype polygon: list[float]
:ivar spans: Location of the line in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
"""
content: str = rest_field()
"""Concatenated content of the contained elements in reading order. Required."""
polygon: Optional[List[float]] = rest_field()
"""Bounding polygon of the line, with coordinates specified relative to the
top-left of the page. The numbers represent the x, y values of the polygon
vertices, clockwise from the left (-180 degrees inclusive) relative to the
element orientation."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the line in the reading order concatenated content. Required."""
@overload
def __init__(
self,
*,
content: str,
spans: List["_models.DocumentSpan"],
polygon: Optional[List[float]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentModelBuildOperationDetails(
OperationDetails, discriminator="documentModelBuild"
): # pylint: disable=too-many-instance-attributes
"""Get Operation response object.
:ivar operation_id: Operation ID. Required.
:vartype operation_id: str
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar created_date_time: Date and time (UTC) when the operation was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar resource_location: URL of the resource targeted by this operation. Required.
:vartype resource_location: str
:ivar api_version: API version used to create this operation.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar result: Operation result upon success.
:vartype result: ~azure.ai.documentintelligence.models.DocumentModelDetails
:ivar kind: Type of operation. Required. Build a new custom document model.
:vartype kind: str or ~azure.ai.documentintelligence.models.DOCUMENT_MODEL_BUILD
"""
result: Optional["_models.DocumentModelDetails"] = rest_field()
"""Operation result upon success."""
kind: Literal[OperationKind.DOCUMENT_MODEL_BUILD] = rest_discriminator(name="kind") # type: ignore
"""Type of operation. Required. Build a new custom document model."""
@overload
def __init__(
self,
*,
operation_id: str,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
resource_location: str,
percent_completed: Optional[int] = None,
api_version: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
error: Optional["_models.Error"] = None,
result: Optional["_models.DocumentModelDetails"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, kind=OperationKind.DOCUMENT_MODEL_BUILD, **kwargs)
[docs]
class DocumentModelComposeOperationDetails(
OperationDetails, discriminator="documentModelCompose"
): # pylint: disable=too-many-instance-attributes
"""Get Operation response object.
:ivar operation_id: Operation ID. Required.
:vartype operation_id: str
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar created_date_time: Date and time (UTC) when the operation was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar resource_location: URL of the resource targeted by this operation. Required.
:vartype resource_location: str
:ivar api_version: API version used to create this operation.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar result: Operation result upon success.
:vartype result: ~azure.ai.documentintelligence.models.DocumentModelDetails
:ivar kind: Type of operation. Required. Compose a new custom document model from existing
models.
:vartype kind: str or ~azure.ai.documentintelligence.models.DOCUMENT_MODEL_COMPOSE
"""
result: Optional["_models.DocumentModelDetails"] = rest_field()
"""Operation result upon success."""
kind: Literal[OperationKind.DOCUMENT_MODEL_COMPOSE] = rest_discriminator(name="kind") # type: ignore
"""Type of operation. Required. Compose a new custom document model from existing models."""
@overload
def __init__(
self,
*,
operation_id: str,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
resource_location: str,
percent_completed: Optional[int] = None,
api_version: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
error: Optional["_models.Error"] = None,
result: Optional["_models.DocumentModelDetails"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, kind=OperationKind.DOCUMENT_MODEL_COMPOSE, **kwargs)
[docs]
class DocumentModelCopyToOperationDetails(
OperationDetails, discriminator="documentModelCopyTo"
): # pylint: disable=too-many-instance-attributes
"""Get Operation response object.
:ivar operation_id: Operation ID. Required.
:vartype operation_id: str
:ivar status: Operation status. notStarted, running, completed, or failed. Required. Known
values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
:vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
:ivar percent_completed: Operation progress (0-100).
:vartype percent_completed: int
:ivar created_date_time: Date and time (UTC) when the operation was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
:vartype last_updated_date_time: ~datetime.datetime
:ivar resource_location: URL of the resource targeted by this operation. Required.
:vartype resource_location: str
:ivar api_version: API version used to create this operation.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar error: Encountered error.
:vartype error: ~azure.ai.documentintelligence.models.Error
:ivar result: Operation result upon success.
:vartype result: ~azure.ai.documentintelligence.models.DocumentModelDetails
:ivar kind: Type of operation. Required. Copy an existing document model to potentially a
different resource, region, or
subscription.
:vartype kind: str or ~azure.ai.documentintelligence.models.DOCUMENT_MODEL_COPY_TO
"""
result: Optional["_models.DocumentModelDetails"] = rest_field()
"""Operation result upon success."""
kind: Literal[OperationKind.DOCUMENT_MODEL_COPY_TO] = rest_discriminator(name="kind") # type: ignore
"""Type of operation. Required. Copy an existing document model to potentially a different
resource, region, or
subscription."""
@overload
def __init__(
self,
*,
operation_id: str,
status: Union[str, "_models.OperationStatus"],
created_date_time: datetime.datetime,
last_updated_date_time: datetime.datetime,
resource_location: str,
percent_completed: Optional[int] = None,
api_version: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
error: Optional["_models.Error"] = None,
result: Optional["_models.DocumentModelDetails"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, kind=OperationKind.DOCUMENT_MODEL_COPY_TO, **kwargs)
[docs]
class DocumentModelDetails(_model_base.Model): # pylint: disable=too-many-instance-attributes
"""Document model info.
Readonly variables are only populated by the server, and will be ignored when sending a request.
:ivar model_id: Unique document model name. Required.
:vartype model_id: str
:ivar description: Document model description.
:vartype description: str
:ivar created_date_time: Date and time (UTC) when the document model was created. Required.
:vartype created_date_time: ~datetime.datetime
:ivar expiration_date_time: Date and time (UTC) when the document model will expire.
:vartype expiration_date_time: ~datetime.datetime
:ivar api_version: API version used to create this document model.
:vartype api_version: str
:ivar tags: List of key-value tag attributes associated with the document model.
:vartype tags: dict[str, str]
:ivar build_mode: Custom document model build mode. Known values are: "template", "neural", and
"generative".
:vartype build_mode: str or ~azure.ai.documentintelligence.models.DocumentBuildMode
:ivar azure_blob_source: Azure Blob Storage location containing the training data. Either
azureBlobSource or azureBlobFileListSource must be specified.
:vartype azure_blob_source: ~azure.ai.documentintelligence.models.AzureBlobContentSource
:ivar azure_blob_file_list_source: Azure Blob Storage file list specifying the training data.
Either
azureBlobSource or azureBlobFileListSource must be specified.
:vartype azure_blob_file_list_source:
~azure.ai.documentintelligence.models.AzureBlobFileListContentSource
:ivar classifier_id: For composed models, the custom classifier to split and classify the input
file.
:vartype classifier_id: str
:ivar split: For composed models, the file splitting behavior. Known values are: "auto",
"none", and "perPage".
:vartype split: str or ~azure.ai.documentintelligence.models.SplitMode
:ivar doc_types: Supported document types.
:vartype doc_types: dict[str, ~azure.ai.documentintelligence.models.DocumentTypeDetails]
:ivar warnings: List of warnings encountered while building the model.
:vartype warnings: list[~azure.ai.documentintelligence.models.Warning]
:ivar training_hours: Number of V100-equivalent GPU hours consumed for model training.
:vartype training_hours: float
"""
model_id: str = rest_field(name="modelId", visibility=["read", "create"])
"""Unique document model name. Required."""
description: Optional[str] = rest_field()
"""Document model description."""
created_date_time: datetime.datetime = rest_field(name="createdDateTime", visibility=["read"], format="rfc3339")
"""Date and time (UTC) when the document model was created. Required."""
expiration_date_time: Optional[datetime.datetime] = rest_field(
name="expirationDateTime", visibility=["read"], format="rfc3339"
)
"""Date and time (UTC) when the document model will expire."""
api_version: Optional[str] = rest_field(name="apiVersion", visibility=["read"])
"""API version used to create this document model."""
tags: Optional[Dict[str, str]] = rest_field()
"""List of key-value tag attributes associated with the document model."""
build_mode: Optional[Union[str, "_models.DocumentBuildMode"]] = rest_field(name="buildMode", visibility=["read"])
"""Custom document model build mode. Known values are: \"template\", \"neural\", and
\"generative\"."""
azure_blob_source: Optional["_models.AzureBlobContentSource"] = rest_field(
name="azureBlobSource", visibility=["read"]
)
"""Azure Blob Storage location containing the training data. Either
azureBlobSource or azureBlobFileListSource must be specified."""
azure_blob_file_list_source: Optional["_models.AzureBlobFileListContentSource"] = rest_field(
name="azureBlobFileListSource", visibility=["read"]
)
"""Azure Blob Storage file list specifying the training data. Either
azureBlobSource or azureBlobFileListSource must be specified."""
classifier_id: Optional[str] = rest_field(name="classifierId")
"""For composed models, the custom classifier to split and classify the input file."""
split: Optional[Union[str, "_models.SplitMode"]] = rest_field()
"""For composed models, the file splitting behavior. Known values are: \"auto\", \"none\", and
\"perPage\"."""
doc_types: Optional[Dict[str, "_models.DocumentTypeDetails"]] = rest_field(name="docTypes", visibility=["read"])
"""Supported document types."""
warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read"])
"""List of warnings encountered while building the model."""
training_hours: Optional[float] = rest_field(name="trainingHours", visibility=["read"])
"""Number of V100-equivalent GPU hours consumed for model training."""
@overload
def __init__(
self,
*,
model_id: str,
description: Optional[str] = None,
tags: Optional[Dict[str, str]] = None,
classifier_id: Optional[str] = None,
split: Optional[Union[str, "_models.SplitMode"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentPage(_model_base.Model): # pylint: disable=too-many-instance-attributes
"""Content and layout elements extracted from a page from the input.
:ivar page_number: 1-based page number in the input document. Required.
:vartype page_number: int
:ivar angle: The general orientation of the content in clockwise direction, measured in
degrees between (-180, 180].
:vartype angle: float
:ivar width: The width of the image/PDF in pixels/inches, respectively.
:vartype width: float
:ivar height: The height of the image/PDF in pixels/inches, respectively.
:vartype height: float
:ivar unit: The unit used by the width, height, and polygon properties. For images, the
unit is "pixel". For PDF, the unit is "inch". Known values are: "pixel" and "inch".
:vartype unit: str or ~azure.ai.documentintelligence.models.LengthUnit
:ivar spans: Location of the page in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar words: Extracted words from the page.
:vartype words: list[~azure.ai.documentintelligence.models.DocumentWord]
:ivar selection_marks: Extracted selection marks from the page.
:vartype selection_marks: list[~azure.ai.documentintelligence.models.DocumentSelectionMark]
:ivar lines: Extracted lines from the page, potentially containing both textual and visual
elements.
:vartype lines: list[~azure.ai.documentintelligence.models.DocumentLine]
:ivar barcodes: Extracted barcodes from the page.
:vartype barcodes: list[~azure.ai.documentintelligence.models.DocumentBarcode]
:ivar formulas: Extracted formulas from the page.
:vartype formulas: list[~azure.ai.documentintelligence.models.DocumentFormula]
"""
page_number: int = rest_field(name="pageNumber")
"""1-based page number in the input document. Required."""
angle: Optional[float] = rest_field()
"""The general orientation of the content in clockwise direction, measured in
degrees between (-180, 180]."""
width: Optional[float] = rest_field()
"""The width of the image/PDF in pixels/inches, respectively."""
height: Optional[float] = rest_field()
"""The height of the image/PDF in pixels/inches, respectively."""
unit: Optional[Union[str, "_models.LengthUnit"]] = rest_field()
"""The unit used by the width, height, and polygon properties. For images, the
unit is \"pixel\". For PDF, the unit is \"inch\". Known values are: \"pixel\" and \"inch\"."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the page in the reading order concatenated content. Required."""
words: Optional[List["_models.DocumentWord"]] = rest_field()
"""Extracted words from the page."""
selection_marks: Optional[List["_models.DocumentSelectionMark"]] = rest_field(name="selectionMarks")
"""Extracted selection marks from the page."""
lines: Optional[List["_models.DocumentLine"]] = rest_field()
"""Extracted lines from the page, potentially containing both textual and visual
elements."""
barcodes: Optional[List["_models.DocumentBarcode"]] = rest_field()
"""Extracted barcodes from the page."""
formulas: Optional[List["_models.DocumentFormula"]] = rest_field()
"""Extracted formulas from the page."""
@overload
def __init__(
self,
*,
page_number: int,
spans: List["_models.DocumentSpan"],
angle: Optional[float] = None,
width: Optional[float] = None,
height: Optional[float] = None,
unit: Optional[Union[str, "_models.LengthUnit"]] = None,
words: Optional[List["_models.DocumentWord"]] = None,
selection_marks: Optional[List["_models.DocumentSelectionMark"]] = None,
lines: Optional[List["_models.DocumentLine"]] = None,
barcodes: Optional[List["_models.DocumentBarcode"]] = None,
formulas: Optional[List["_models.DocumentFormula"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentParagraph(_model_base.Model):
"""A paragraph object consisting with contiguous lines generally with common
alignment and spacing.
:ivar role: Semantic role of the paragraph. Known values are: "pageHeader", "pageFooter",
"pageNumber", "title", "sectionHeading", "footnote", and "formulaBlock".
:vartype role: str or ~azure.ai.documentintelligence.models.ParagraphRole
:ivar content: Concatenated content of the paragraph in reading order. Required.
:vartype content: str
:ivar bounding_regions: Bounding regions covering the paragraph.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the paragraph in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
"""
role: Optional[Union[str, "_models.ParagraphRole"]] = rest_field()
"""Semantic role of the paragraph. Known values are: \"pageHeader\", \"pageFooter\",
\"pageNumber\", \"title\", \"sectionHeading\", \"footnote\", and \"formulaBlock\"."""
content: str = rest_field()
"""Concatenated content of the paragraph in reading order. Required."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the paragraph."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the paragraph in the reading order concatenated content. Required."""
@overload
def __init__(
self,
*,
content: str,
spans: List["_models.DocumentSpan"],
role: Optional[Union[str, "_models.ParagraphRole"]] = None,
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentSection(_model_base.Model):
"""An object representing a section in the document.
:ivar spans: Location of the section in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar elements: Child elements of the section.
:vartype elements: list[str]
"""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the section in the reading order concatenated content. Required."""
elements: Optional[List[str]] = rest_field()
"""Child elements of the section."""
@overload
def __init__(
self,
*,
spans: List["_models.DocumentSpan"],
elements: Optional[List[str]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentSelectionMark(_model_base.Model):
"""A selection mark object representing check boxes, radio buttons, and other
elements indicating a selection.
:ivar state: State of the selection mark. Required. Known values are: "selected" and
"unselected".
:vartype state: str or ~azure.ai.documentintelligence.models.DocumentSelectionMarkState
:ivar polygon: Bounding polygon of the selection mark, with coordinates specified relative
to the top-left of the page. The numbers represent the x, y values of the
polygon vertices, clockwise from the left (-180 degrees inclusive) relative
to the element orientation.
:vartype polygon: list[float]
:ivar span: Location of the selection mark in the reading order concatenated content. Required.
:vartype span: ~azure.ai.documentintelligence.models.DocumentSpan
:ivar confidence: Confidence of correctly extracting the selection mark. Required.
:vartype confidence: float
"""
state: Union[str, "_models.DocumentSelectionMarkState"] = rest_field()
"""State of the selection mark. Required. Known values are: \"selected\" and \"unselected\"."""
polygon: Optional[List[float]] = rest_field()
"""Bounding polygon of the selection mark, with coordinates specified relative
to the top-left of the page. The numbers represent the x, y values of the
polygon vertices, clockwise from the left (-180 degrees inclusive) relative
to the element orientation."""
span: "_models.DocumentSpan" = rest_field()
"""Location of the selection mark in the reading order concatenated content. Required."""
confidence: float = rest_field()
"""Confidence of correctly extracting the selection mark. Required."""
@overload
def __init__(
self,
*,
state: Union[str, "_models.DocumentSelectionMarkState"],
span: "_models.DocumentSpan",
confidence: float,
polygon: Optional[List[float]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentSpan(_model_base.Model):
"""Contiguous region of the concatenated content property, specified as an offset
and length.
:ivar offset: Zero-based index of the content represented by the span. Required.
:vartype offset: int
:ivar length: Number of characters in the content represented by the span. Required.
:vartype length: int
"""
offset: int = rest_field()
"""Zero-based index of the content represented by the span. Required."""
length: int = rest_field()
"""Number of characters in the content represented by the span. Required."""
@overload
def __init__(
self,
*,
offset: int,
length: int,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentStyle(_model_base.Model):
"""An object representing observed text styles.
:ivar is_handwritten: Is content handwritten?.
:vartype is_handwritten: bool
:ivar similar_font_family: Visually most similar font from among the set of supported font
families, with
fallback fonts following CSS convention (ex. 'Arial, sans-serif').
:vartype similar_font_family: str
:ivar font_style: Font style. Known values are: "normal" and "italic".
:vartype font_style: str or ~azure.ai.documentintelligence.models.FontStyle
:ivar font_weight: Font weight. Known values are: "normal" and "bold".
:vartype font_weight: str or ~azure.ai.documentintelligence.models.FontWeight
:ivar color: Foreground color in #rrggbb hexadecimal format.
:vartype color: str
:ivar background_color: Background color in #rrggbb hexadecimal format..
:vartype background_color: str
:ivar spans: Location of the text elements in the concatenated content the style applies to.
Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar confidence: Confidence of correctly identifying the style. Required.
:vartype confidence: float
"""
is_handwritten: Optional[bool] = rest_field(name="isHandwritten")
"""Is content handwritten?."""
similar_font_family: Optional[str] = rest_field(name="similarFontFamily")
"""Visually most similar font from among the set of supported font families, with
fallback fonts following CSS convention (ex. 'Arial, sans-serif')."""
font_style: Optional[Union[str, "_models.FontStyle"]] = rest_field(name="fontStyle")
"""Font style. Known values are: \"normal\" and \"italic\"."""
font_weight: Optional[Union[str, "_models.FontWeight"]] = rest_field(name="fontWeight")
"""Font weight. Known values are: \"normal\" and \"bold\"."""
color: Optional[str] = rest_field()
"""Foreground color in #rrggbb hexadecimal format."""
background_color: Optional[str] = rest_field(name="backgroundColor")
"""Background color in #rrggbb hexadecimal format.."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the text elements in the concatenated content the style applies to. Required."""
confidence: float = rest_field()
"""Confidence of correctly identifying the style. Required."""
@overload
def __init__(
self,
*,
spans: List["_models.DocumentSpan"],
confidence: float,
is_handwritten: Optional[bool] = None,
similar_font_family: Optional[str] = None,
font_style: Optional[Union[str, "_models.FontStyle"]] = None,
font_weight: Optional[Union[str, "_models.FontWeight"]] = None,
color: Optional[str] = None,
background_color: Optional[str] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentTable(_model_base.Model):
"""A table object consisting table cells arranged in a rectangular layout.
:ivar row_count: Number of rows in the table. Required.
:vartype row_count: int
:ivar column_count: Number of columns in the table. Required.
:vartype column_count: int
:ivar cells: Cells contained within the table. Required.
:vartype cells: list[~azure.ai.documentintelligence.models.DocumentTableCell]
:ivar bounding_regions: Bounding regions covering the table.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the table in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar caption: Caption associated with the table.
:vartype caption: ~azure.ai.documentintelligence.models.DocumentCaption
:ivar footnotes: List of footnotes associated with the table.
:vartype footnotes: list[~azure.ai.documentintelligence.models.DocumentFootnote]
"""
row_count: int = rest_field(name="rowCount")
"""Number of rows in the table. Required."""
column_count: int = rest_field(name="columnCount")
"""Number of columns in the table. Required."""
cells: List["_models.DocumentTableCell"] = rest_field()
"""Cells contained within the table. Required."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the table."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the table in the reading order concatenated content. Required."""
caption: Optional["_models.DocumentCaption"] = rest_field()
"""Caption associated with the table."""
footnotes: Optional[List["_models.DocumentFootnote"]] = rest_field()
"""List of footnotes associated with the table."""
@overload
def __init__(
self,
*,
row_count: int,
column_count: int,
cells: List["_models.DocumentTableCell"],
spans: List["_models.DocumentSpan"],
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
caption: Optional["_models.DocumentCaption"] = None,
footnotes: Optional[List["_models.DocumentFootnote"]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentTableCell(_model_base.Model):
"""An object representing the location and content of a table cell.
:ivar kind: Table cell kind. Known values are: "content", "rowHeader", "columnHeader",
"stubHead", and "description".
:vartype kind: str or ~azure.ai.documentintelligence.models.DocumentTableCellKind
:ivar row_index: Row index of the cell. Required.
:vartype row_index: int
:ivar column_index: Column index of the cell. Required.
:vartype column_index: int
:ivar row_span: Number of rows spanned by this cell.
:vartype row_span: int
:ivar column_span: Number of columns spanned by this cell.
:vartype column_span: int
:ivar content: Concatenated content of the table cell in reading order. Required.
:vartype content: str
:ivar bounding_regions: Bounding regions covering the table cell.
:vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
:ivar spans: Location of the table cell in the reading order concatenated content. Required.
:vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
:ivar elements: Child elements of the table cell.
:vartype elements: list[str]
"""
kind: Optional[Union[str, "_models.DocumentTableCellKind"]] = rest_field()
"""Table cell kind. Known values are: \"content\", \"rowHeader\", \"columnHeader\", \"stubHead\",
and \"description\"."""
row_index: int = rest_field(name="rowIndex")
"""Row index of the cell. Required."""
column_index: int = rest_field(name="columnIndex")
"""Column index of the cell. Required."""
row_span: Optional[int] = rest_field(name="rowSpan")
"""Number of rows spanned by this cell."""
column_span: Optional[int] = rest_field(name="columnSpan")
"""Number of columns spanned by this cell."""
content: str = rest_field()
"""Concatenated content of the table cell in reading order. Required."""
bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
"""Bounding regions covering the table cell."""
spans: List["_models.DocumentSpan"] = rest_field()
"""Location of the table cell in the reading order concatenated content. Required."""
elements: Optional[List[str]] = rest_field()
"""Child elements of the table cell."""
@overload
def __init__(
self,
*,
row_index: int,
column_index: int,
content: str,
spans: List["_models.DocumentSpan"],
kind: Optional[Union[str, "_models.DocumentTableCellKind"]] = None,
row_span: Optional[int] = None,
column_span: Optional[int] = None,
bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
elements: Optional[List[str]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentTypeDetails(_model_base.Model):
"""Document type info.
:ivar description: Document model description.
:vartype description: str
:ivar build_mode: Custom document model build mode. Known values are: "template", "neural", and
"generative".
:vartype build_mode: str or ~azure.ai.documentintelligence.models.DocumentBuildMode
:ivar field_schema: Description of the document semantic schema using a JSON Schema style
syntax.
:vartype field_schema: dict[str, ~azure.ai.documentintelligence.models.DocumentFieldSchema]
:ivar field_confidence: Estimated confidence for each field.
:vartype field_confidence: dict[str, float]
:ivar model_id: Document model to use for analyzing documents with specified type.
:vartype model_id: str
:ivar confidence_threshold: Only perform analysis if docType confidence is above threshold.
:vartype confidence_threshold: float
:ivar features: List of optional analysis features.
:vartype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
:ivar query_fields: List of additional fields to extract. Ex. "NumberOfGuests,StoreNumber".
:vartype query_fields: list[str]
:ivar max_documents_to_analyze: Maximum number of documents of specified type to analyze.
Default=all.
:vartype max_documents_to_analyze: int
"""
description: Optional[str] = rest_field()
"""Document model description."""
build_mode: Optional[Union[str, "_models.DocumentBuildMode"]] = rest_field(name="buildMode")
"""Custom document model build mode. Known values are: \"template\", \"neural\", and
\"generative\"."""
field_schema: Optional[Dict[str, "_models.DocumentFieldSchema"]] = rest_field(name="fieldSchema")
"""Description of the document semantic schema using a JSON Schema style syntax."""
field_confidence: Optional[Dict[str, float]] = rest_field(name="fieldConfidence")
"""Estimated confidence for each field."""
model_id: Optional[str] = rest_field(name="modelId")
"""Document model to use for analyzing documents with specified type."""
confidence_threshold: Optional[float] = rest_field(name="confidenceThreshold")
"""Only perform analysis if docType confidence is above threshold."""
features: Optional[List[Union[str, "_models.DocumentAnalysisFeature"]]] = rest_field()
"""List of optional analysis features."""
query_fields: Optional[List[str]] = rest_field(name="queryFields")
"""List of additional fields to extract. Ex. \"NumberOfGuests,StoreNumber\"."""
max_documents_to_analyze: Optional[int] = rest_field(name="maxDocumentsToAnalyze")
"""Maximum number of documents of specified type to analyze. Default=all."""
@overload
def __init__(
self,
*,
description: Optional[str] = None,
build_mode: Optional[Union[str, "_models.DocumentBuildMode"]] = None,
field_schema: Optional[Dict[str, "_models.DocumentFieldSchema"]] = None,
field_confidence: Optional[Dict[str, float]] = None,
model_id: Optional[str] = None,
confidence_threshold: Optional[float] = None,
features: Optional[List[Union[str, "_models.DocumentAnalysisFeature"]]] = None,
query_fields: Optional[List[str]] = None,
max_documents_to_analyze: Optional[int] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class DocumentWord(_model_base.Model):
"""A word object consisting of a contiguous sequence of characters. For non-space
delimited languages, such as Chinese, Japanese, and Korean, each character is
represented as its own word.
:ivar content: Text content of the word. Required.
:vartype content: str
:ivar polygon: Bounding polygon of the word, with coordinates specified relative to the
top-left of the page. The numbers represent the x, y values of the polygon
vertices, clockwise from the left (-180 degrees inclusive) relative to the
element orientation.
:vartype polygon: list[float]
:ivar span: Location of the word in the reading order concatenated content. Required.
:vartype span: ~azure.ai.documentintelligence.models.DocumentSpan
:ivar confidence: Confidence of correctly extracting the word. Required.
:vartype confidence: float
"""
content: str = rest_field()
"""Text content of the word. Required."""
polygon: Optional[List[float]] = rest_field()
"""Bounding polygon of the word, with coordinates specified relative to the
top-left of the page. The numbers represent the x, y values of the polygon
vertices, clockwise from the left (-180 degrees inclusive) relative to the
element orientation."""
span: "_models.DocumentSpan" = rest_field()
"""Location of the word in the reading order concatenated content. Required."""
confidence: float = rest_field()
"""Confidence of correctly extracting the word. Required."""
@overload
def __init__(
self,
*,
content: str,
span: "_models.DocumentSpan",
confidence: float,
polygon: Optional[List[float]] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class Error(_model_base.Model):
"""The error object.
:ivar code: One of a server-defined set of error codes. Required.
:vartype code: str
:ivar message: A human-readable representation of the error. Required.
:vartype message: str
:ivar target: The target of the error.
:vartype target: str
:ivar details: An array of details about specific errors that led to this reported error.
:vartype details: list[~azure.ai.documentintelligence.models.Error]
:ivar innererror: An object containing more specific information than the current object about
the error.
:vartype innererror: ~azure.ai.documentintelligence.models.InnerError
"""
code: str = rest_field()
"""One of a server-defined set of error codes. Required."""
message: str = rest_field()
"""A human-readable representation of the error. Required."""
target: Optional[str] = rest_field()
"""The target of the error."""
details: Optional[List["_models.Error"]] = rest_field()
"""An array of details about specific errors that led to this reported error."""
innererror: Optional["_models.InnerError"] = rest_field()
"""An object containing more specific information than the current object about the error."""
@overload
def __init__(
self,
*,
code: str,
message: str,
target: Optional[str] = None,
details: Optional[List["_models.Error"]] = None,
innererror: Optional["_models.InnerError"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class ErrorResponse(_model_base.Model):
"""Error response object.
:ivar error: Error info. Required.
:vartype error: ~azure.ai.documentintelligence.models.Error
"""
error: "_models.Error" = rest_field()
"""Error info. Required."""
@overload
def __init__(
self,
*,
error: "_models.Error",
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class InnerError(_model_base.Model):
"""An object containing more specific information about the error.
:ivar code: One of a server-defined set of error codes.
:vartype code: str
:ivar message: A human-readable representation of the error.
:vartype message: str
:ivar innererror: Inner error.
:vartype innererror: ~azure.ai.documentintelligence.models.InnerError
"""
code: Optional[str] = rest_field()
"""One of a server-defined set of error codes."""
message: Optional[str] = rest_field()
"""A human-readable representation of the error."""
innererror: Optional["_models.InnerError"] = rest_field()
"""Inner error."""
@overload
def __init__(
self,
*,
code: Optional[str] = None,
message: Optional[str] = None,
innererror: Optional["_models.InnerError"] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class ResourceDetails(_model_base.Model):
"""General information regarding the current resource.
:ivar custom_document_models: Details regarding custom document models. Required.
:vartype custom_document_models:
~azure.ai.documentintelligence.models.CustomDocumentModelsDetails
"""
custom_document_models: "_models.CustomDocumentModelsDetails" = rest_field(name="customDocumentModels")
"""Details regarding custom document models. Required."""
@overload
def __init__(
self,
*,
custom_document_models: "_models.CustomDocumentModelsDetails",
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)
[docs]
class Warning(_model_base.Model):
"""The error object.
:ivar code: One of a server-defined set of warning codes. Required.
:vartype code: str
:ivar message: A human-readable representation of the warning. Required.
:vartype message: str
:ivar target: The target of the error.
:vartype target: str
"""
code: str = rest_field()
"""One of a server-defined set of warning codes. Required."""
message: str = rest_field()
"""A human-readable representation of the warning. Required."""
target: Optional[str] = rest_field()
"""The target of the error."""
@overload
def __init__(
self,
*,
code: str,
message: str,
target: Optional[str] = None,
): ...
@overload
def __init__(self, mapping: Mapping[str, Any]):
"""
:param mapping: raw JSON to initialize the model.
:type mapping: Mapping[str, Any]
"""
def __init__(self, *args: Any, **kwargs: Any) -> None: # pylint: disable=useless-super-delegation
super().__init__(*args, **kwargs)