models.py•37.9 kB
# generated by fastapi-codegen:
# filename: openapi.yaml
# timestamp: 2025-06-29T03:04:11+00:00
from __future__ import annotations
from enum import Enum
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field
class CancelOperationRequest(BaseModel):
pass
class DetectLanguageRequest(BaseModel):
content: Optional[str] = Field(
None, description='The content of the input stored as a string.'
)
labels: Optional[Dict[str, str]] = Field(
None,
description='Optional. The labels with user-defined metadata for the request. Label keys and values can be no longer than 63 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. See https://cloud.google.com/translate/docs/labels for more information.',
)
mimeType: Optional[str] = Field(
None,
description='Optional. The format of the source text, for example, "text/html", "text/plain". If left blank, the MIME type defaults to "text/html".',
)
model: Optional[str] = Field(
None,
description='Optional. The language detection model to be used. Format: `projects/{project-number-or-id}/locations/{location-id}/models/language-detection/{model-id}` Only one language detection model is currently supported: `projects/{project-number-or-id}/locations/{location-id}/models/language-detection/default`. If not specified, the default model is used.',
)
class DetectedLanguage(BaseModel):
confidence: Optional[float] = Field(
None, description='The confidence of the detection result for this language.'
)
languageCode: Optional[str] = Field(
None,
description='The BCP-47 language code of source content in the request, detected automatically.',
)
class DocumentTranslation(BaseModel):
byteStreamOutputs: Optional[List[str]] = Field(
None,
description='The array of translated documents. It is expected to be size 1 for now. We may produce multiple translated documents in the future for other type of file formats.',
)
detectedLanguageCode: Optional[str] = Field(
None,
description='The detected language for the input document. If the user did not provide the source language for the input document, this field will have the language code automatically detected. If the source language was passed, auto-detection of the language does not occur and this field is empty.',
)
mimeType: Optional[str] = Field(
None, description="The translated document's mime type."
)
class Empty(BaseModel):
pass
class GcsDestination(BaseModel):
outputUriPrefix: Optional[str] = Field(
None,
description='Required. There must be no files under \'output_uri_prefix\'. \'output_uri_prefix\' must end with "/" and start with "gs://", otherwise an INVALID_ARGUMENT (400) error is returned.',
)
class GcsSource(BaseModel):
inputUri: Optional[str] = Field(
None,
description='Required. Source data URI. For example, `gs://my_bucket/my_object`.',
)
class GlossaryInputConfig(BaseModel):
gcsSource: Optional[GcsSource] = Field(
None,
description='Required. Google Cloud Storage location of glossary data. File format is determined based on the filename extension. API returns [google.rpc.Code.INVALID_ARGUMENT] for unsupported URI-s and file formats. Wildcards are not allowed. This must be a single file in one of the following formats: For unidirectional glossaries: - TSV/CSV (`.tsv`/`.csv`): 2 column file, tab- or comma-separated. The first column is source text. The second column is target text. The file must not contain headers. That is, the first row is data, not column names. - TMX (`.tmx`): TMX file with parallel data defining source/target term pairs. For equivalent term sets glossaries: - CSV (`.csv`): Multi-column CSV file defining equivalent glossary terms in multiple languages. See documentation for more information - [glossaries](https://cloud.google.com/translate/docs/advanced/glossary).',
)
class InputConfig(BaseModel):
gcsSource: Optional[GcsSource] = Field(
None,
description="Required. Google Cloud Storage location for the source input. This can be a single file (for example, `gs://translation-test/input.tsv`) or a wildcard (for example, `gs://translation-test/*`). If a file extension is `.tsv`, it can contain either one or two columns. The first column (optional) is the id of the text request. If the first column is missing, we use the row number (0-based) from the input file as the ID in the output file. The second column is the actual text to be translated. We recommend each row be <= 10K Unicode codepoints, otherwise an error might be returned. Note that the input tsv must be RFC 4180 compliant. You could use https://github.com/Clever/csvlint to check potential formatting errors in your tsv file. csvlint --delimiter='\\t' your_input_file.tsv The other supported file extensions are `.txt` or `.html`, which is treated as a single large chunk of text.",
)
mimeType: Optional[str] = Field(
None,
description='Optional. Can be "text/plain" or "text/html". For `.tsv`, "text/html" is used if mime_type is missing. For `.html`, this field must be "text/html" or empty. For `.txt`, this field must be "text/plain" or empty.',
)
class LanguageCodePair(BaseModel):
sourceLanguageCode: Optional[str] = Field(
None,
description='Required. The BCP-47 language code of the input text, for example, "en-US". Expected to be an exact match for GlossaryTerm.language_code.',
)
targetLanguageCode: Optional[str] = Field(
None,
description='Required. The BCP-47 language code for translation output, for example, "zh-CN". Expected to be an exact match for GlossaryTerm.language_code.',
)
class LanguageCodesSet(BaseModel):
languageCodes: Optional[List[str]] = Field(
None,
description='The BCP-47 language code(s) for terms defined in the glossary. All entries are unique. The list contains at least two entries. Expected to be an exact match for GlossaryTerm.language_code.',
)
class Location(BaseModel):
displayName: Optional[str] = Field(
None,
description='The friendly name for this location, typically a nearby city name. For example, "Tokyo".',
)
labels: Optional[Dict[str, str]] = Field(
None,
description='Cross-service attributes for the location. For example {"cloud.googleapis.com/region": "us-east1"}',
)
locationId: Optional[str] = Field(
None,
description='The canonical id for this location. For example: `"us-east1"`.',
)
metadata: Optional[Dict[str, Any]] = Field(
None,
description='Service-specific metadata. For example the available capacity at the given location.',
)
name: Optional[str] = Field(
None,
description='Resource name for the location, which may vary between implementations. For example: `"projects/example-project/locations/us-east1"`',
)
class OutputConfig(BaseModel):
gcsDestination: Optional[GcsDestination] = Field(
None,
description="Google Cloud Storage destination for output content. For every single input file (for example, gs://a/b/c.[extension]), we generate at most 2 * n output files. (n is the # of target_language_codes in the BatchTranslateTextRequest). Output files (tsv) generated are compliant with RFC 4180 except that record delimiters are '\\n' instead of '\\r\\n'. We don't provide any way to change record delimiters. While the input files are being processed, we write/update an index file 'index.csv' under 'output_uri_prefix' (for example, gs://translation-test/index.csv) The index file is generated/updated as new files are being translated. The format is: input_file,target_language_code,translations_file,errors_file, glossary_translations_file,glossary_errors_file input_file is one file we matched using gcs_source.input_uri. target_language_code is provided in the request. translations_file contains the translations. (details provided below) errors_file contains the errors during processing of the file. (details below). Both translations_file and errors_file could be empty strings if we have no content to output. glossary_translations_file and glossary_errors_file are always empty strings if the input_file is tsv. They could also be empty if we have no content to output. Once a row is present in index.csv, the input/output matching never changes. Callers should also expect all the content in input_file are processed and ready to be consumed (that is, no partial output file is written). Since index.csv will be keeping updated during the process, please make sure there is no custom retention policy applied on the output bucket that may avoid file updating. (https://cloud.google.com/storage/docs/bucket-lock#retention-policy) The format of translations_file (for target language code 'trg') is: `gs://translation_test/a_b_c_'trg'_translations.[extension]` If the input file extension is tsv, the output has the following columns: Column 1: ID of the request provided in the input, if it's not provided in the input, then the input row number is used (0-based). Column 2: source sentence. Column 3: translation without applying a glossary. Empty string if there is an error. Column 4 (only present if a glossary is provided in the request): translation after applying the glossary. Empty string if there is an error applying the glossary. Could be same string as column 3 if there is no glossary applied. If input file extension is a txt or html, the translation is directly written to the output file. If glossary is requested, a separate glossary_translations_file has format of gs://translation_test/a_b_c_'trg'_glossary_translations.[extension] The format of errors file (for target language code 'trg') is: gs://translation_test/a_b_c_'trg'_errors.[extension] If the input file extension is tsv, errors_file contains the following: Column 1: ID of the request provided in the input, if it's not provided in the input, then the input row number is used (0-based). Column 2: source sentence. Column 3: Error detail for the translation. Could be empty. Column 4 (only present if a glossary is provided in the request): Error when applying the glossary. If the input file extension is txt or html, glossary_error_file will be generated that contains error details. glossary_error_file has format of gs://translation_test/a_b_c_'trg'_glossary_errors.[extension]",
)
class Status(BaseModel):
code: Optional[int] = Field(
None,
description='The status code, which should be an enum value of google.rpc.Code.',
)
details: Optional[List[Dict[str, Any]]] = Field(
None,
description='A list of messages that carry the error details. There is a common set of message types for APIs to use.',
)
message: Optional[str] = Field(
None,
description='A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.',
)
class SupportedLanguage(BaseModel):
displayName: Optional[str] = Field(
None,
description='Human readable name of the language localized in the display language specified in the request.',
)
languageCode: Optional[str] = Field(
None,
description="Supported language code, generally consisting of its ISO 639-1 identifier, for example, 'en', 'ja'. In certain cases, BCP-47 codes including language and region identifiers are returned (for example, 'zh-TW' and 'zh-CN')",
)
supportSource: Optional[bool] = Field(
None, description='Can be used as source language.'
)
supportTarget: Optional[bool] = Field(
None, description='Can be used as target language.'
)
class SupportedLanguages(BaseModel):
languages: Optional[List[SupportedLanguage]] = Field(
None,
description='A list of supported language responses. This list contains an entry for each language the Translation API supports.',
)
class TranslateTextGlossaryConfig(BaseModel):
glossary: Optional[str] = Field(
None,
description='Required. Specifies the glossary used for this translation. Use this format: projects/*/locations/*/glossaries/*',
)
ignoreCase: Optional[bool] = Field(
None,
description='Optional. Indicates match is case-insensitive. Default value is false if missing.',
)
class TranslateTextRequest(BaseModel):
contents: Optional[List[str]] = Field(
None,
description='Required. The content of the input in string format. We recommend the total content be less than 30k codepoints. The max length of this field is 1024. Use BatchTranslateText for larger text.',
)
glossaryConfig: Optional[TranslateTextGlossaryConfig] = Field(
None,
description='Optional. Glossary to be applied. The glossary must be within the same region (have the same location-id) as the model, otherwise an INVALID_ARGUMENT (400) error is returned.',
)
labels: Optional[Dict[str, str]] = Field(
None,
description='Optional. The labels with user-defined metadata for the request. Label keys and values can be no longer than 63 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. See https://cloud.google.com/translate/docs/labels for more information.',
)
mimeType: Optional[str] = Field(
None,
description='Optional. The format of the source text, for example, "text/html", "text/plain". If left blank, the MIME type defaults to "text/html".',
)
model: Optional[str] = Field(
None,
description='Optional. The `model` type requested for this translation. The format depends on model type: - AutoML Translation models: `projects/{project-number-or-id}/locations/{location-id}/models/{model-id}` - General (built-in) models: `projects/{project-number-or-id}/locations/{location-id}/models/general/nmt`, For global (non-regionalized) requests, use `location-id` `global`. For example, `projects/{project-number-or-id}/locations/global/models/general/nmt`. If not provided, the default Google model (NMT) will be used',
)
sourceLanguageCode: Optional[str] = Field(
None,
description='Optional. The BCP-47 language code of the input text if known, for example, "en-US" or "sr-Latn". Supported language codes are listed in Language Support. If the source language isn\'t specified, the API attempts to identify the source language automatically and returns the source language within the response.',
)
targetLanguageCode: Optional[str] = Field(
None,
description='Required. The BCP-47 language code to use for translation of the input text, set to one of the language codes listed in Language Support.',
)
class Translation(BaseModel):
detectedLanguageCode: Optional[str] = Field(
None,
description='The BCP-47 language code of source text in the initial request, detected automatically, if no source language was passed within the initial request. If the source language was passed, auto-detection of the language does not occur and this field is empty.',
)
glossaryConfig: Optional[TranslateTextGlossaryConfig] = Field(
None, description='The `glossary_config` used for this translation.'
)
model: Optional[str] = Field(
None,
description='Only present when `model` is present in the request. `model` here is normalized to have project number. For example: If the `model` requested in TranslationTextRequest is `projects/{project-id}/locations/{location-id}/models/general/nmt` then `model` here would be normalized to `projects/{project-number}/locations/{location-id}/models/general/nmt`.',
)
translatedText: Optional[str] = Field(
None,
description='Text translated into the target language. If an error occurs during translation, this field might be excluded from the response.',
)
class WaitOperationRequest(BaseModel):
timeout: Optional[str] = Field(
None,
description='The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.',
)
class FieldXgafv(Enum):
field_1 = '1'
field_2 = '2'
class Alt(Enum):
json = 'json'
media = 'media'
proto = 'proto'
class BatchDocumentInputConfig(BaseModel):
gcsSource: Optional[GcsSource] = Field(
None,
description='Google Cloud Storage location for the source input. This can be a single file (for example, `gs://translation-test/input.docx`) or a wildcard (for example, `gs://translation-test/*`). File mime type is determined based on extension. Supported mime type includes: - `pdf`, application/pdf - `docx`, application/vnd.openxmlformats-officedocument.wordprocessingml.document - `pptx`, application/vnd.openxmlformats-officedocument.presentationml.presentation - `xlsx`, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet The max file size to support for `.docx`, `.pptx` and `.xlsx` is 100MB. The max file size to support for `.pdf` is 1GB and the max page limit is 1000 pages. The max file size to support for all input documents is 1GB.',
)
class BatchDocumentOutputConfig(BaseModel):
gcsDestination: Optional[GcsDestination] = Field(
None,
description='Google Cloud Storage destination for output content. For every single input document (for example, gs://a/b/c.[extension]), we generate at most 2 * n output files. (n is the # of target_language_codes in the BatchTranslateDocumentRequest). While the input documents are being processed, we write/update an index file `index.csv` under `gcs_destination.output_uri_prefix` (for example, gs://translation_output/index.csv) The index file is generated/updated as new files are being translated. The format is: input_document,target_language_code,translation_output,error_output, glossary_translation_output,glossary_error_output `input_document` is one file we matched using gcs_source.input_uri. `target_language_code` is provided in the request. `translation_output` contains the translations. (details provided below) `error_output` contains the error message during processing of the file. Both translations_file and errors_file could be empty strings if we have no content to output. `glossary_translation_output` and `glossary_error_output` are the translated output/error when we apply glossaries. They could also be empty if we have no content to output. Once a row is present in index.csv, the input/output matching never changes. Callers should also expect all the content in input_file are processed and ready to be consumed (that is, no partial output file is written). Since index.csv will be keeping updated during the process, please make sure there is no custom retention policy applied on the output bucket that may avoid file updating. (https://cloud.google.com/storage/docs/bucket-lock#retention-policy) The naming format of translation output files follows (for target language code [trg]): `translation_output`: gs://translation_output/a_b_c_[trg]_translation.[extension] `glossary_translation_output`: gs://translation_test/a_b_c_[trg]_glossary_translation.[extension] The output document will maintain the same file format as the input document. The naming format of error output files follows (for target language code [trg]): `error_output`: gs://translation_test/a_b_c_[trg]_errors.txt `glossary_error_output`: gs://translation_test/a_b_c_[trg]_glossary_translation.txt The error output is a txt file containing error details.',
)
class BatchTranslateDocumentRequest(BaseModel):
customizedAttribution: Optional[str] = Field(
None,
description='Optional. This flag is to support user customized attribution. If not provided, the default is `Machine Translated by Google`. Customized attribution should follow rules in https://cloud.google.com/translate/attribution#attribution_and_logos',
)
enableShadowRemovalNativePdf: Optional[bool] = Field(
None,
description='Optional. If true, use the text removal server to remove the shadow text on background image for native pdf translation. Shadow removal feature can only be enabled when is_translate_native_pdf_only: false && pdf_native_only: false',
)
formatConversions: Optional[Dict[str, str]] = Field(None, description='Optional.')
glossaries: Optional[Dict[str, TranslateTextGlossaryConfig]] = Field(
None,
description="Optional. Glossaries to be applied. It's keyed by target language code.",
)
inputConfigs: Optional[List[BatchDocumentInputConfig]] = Field(
None,
description='Required. Input configurations. The total number of files matched should be <= 100. The total content size to translate should be <= 100M Unicode codepoints. The files must use UTF-8 encoding.',
)
models: Optional[Dict[str, str]] = Field(
None,
description="Optional. The models to use for translation. Map's key is target language code. Map's value is the model name. Value can be a built-in general model, or an AutoML Translation model. The value format depends on model type: - AutoML Translation models: `projects/{project-number-or-id}/locations/{location-id}/models/{model-id}` - General (built-in) models: `projects/{project-number-or-id}/locations/{location-id}/models/general/nmt`, If the map is empty or a specific model is not requested for a language pair, then default google model (nmt) is used.",
)
outputConfig: Optional[BatchDocumentOutputConfig] = Field(
None,
description="Required. Output configuration. If 2 input configs match to the same file (that is, same input path), we don't generate output for duplicate inputs.",
)
sourceLanguageCode: Optional[str] = Field(
None,
description='Required. The BCP-47 language code of the input document if known, for example, "en-US" or "sr-Latn". Supported language codes are listed in [Language Support](https://cloud.google.com/translate/docs/languages).',
)
targetLanguageCodes: Optional[List[str]] = Field(
None,
description='Required. The BCP-47 language code to use for translation of the input document. Specify up to 10 language codes here.',
)
class BatchTranslateTextRequest(BaseModel):
glossaries: Optional[Dict[str, TranslateTextGlossaryConfig]] = Field(
None,
description="Optional. Glossaries to be applied for translation. It's keyed by target language code.",
)
inputConfigs: Optional[List[InputConfig]] = Field(
None,
description='Required. Input configurations. The total number of files matched should be <= 100. The total content size should be <= 100M Unicode codepoints. The files must use UTF-8 encoding.',
)
labels: Optional[Dict[str, str]] = Field(
None,
description='Optional. The labels with user-defined metadata for the request. Label keys and values can be no longer than 63 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. See https://cloud.google.com/translate/docs/labels for more information.',
)
models: Optional[Dict[str, str]] = Field(
None,
description="Optional. The models to use for translation. Map's key is target language code. Map's value is model name. Value can be a built-in general model, or an AutoML Translation model. The value format depends on model type: - AutoML Translation models: `projects/{project-number-or-id}/locations/{location-id}/models/{model-id}` - General (built-in) models: `projects/{project-number-or-id}/locations/{location-id}/models/general/nmt`, If the map is empty or a specific model is not requested for a language pair, then default google model (nmt) is used.",
)
outputConfig: Optional[OutputConfig] = Field(
None,
description="Required. Output configuration. If 2 input configs match to the same file (that is, same input path), we don't generate output for duplicate inputs.",
)
sourceLanguageCode: Optional[str] = Field(
None, description='Required. Source language code.'
)
targetLanguageCodes: Optional[List[str]] = Field(
None, description='Required. Specify up to 10 language codes here.'
)
class DetectLanguageResponse(BaseModel):
languages: Optional[List[DetectedLanguage]] = Field(
None,
description='A list of detected languages sorted by detection confidence in descending order. The most probable language first.',
)
class DocumentInputConfig(BaseModel):
content: Optional[str] = Field(
None, description="Document's content represented as a stream of bytes."
)
gcsSource: Optional[GcsSource] = Field(
None,
description='Google Cloud Storage location. This must be a single file. For example: gs://example_bucket/example_file.pdf',
)
mimeType: Optional[str] = Field(
None,
description="Specifies the input document's mime_type. If not specified it will be determined using the file extension for gcs_source provided files. For a file provided through bytes content the mime_type must be provided. Currently supported mime types are: - application/pdf - application/vnd.openxmlformats-officedocument.wordprocessingml.document - application/vnd.openxmlformats-officedocument.presentationml.presentation - application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
)
class DocumentOutputConfig(BaseModel):
gcsDestination: Optional[GcsDestination] = Field(
None,
description='Optional. Google Cloud Storage destination for the translation output, e.g., `gs://my_bucket/my_directory/`. The destination directory provided does not have to be empty, but the bucket must exist. If a file with the same name as the output file already exists in the destination an error will be returned. For a DocumentInputConfig.contents provided document, the output file will have the name "output_[trg]_translations.[ext]", where - [trg] corresponds to the translated file\'s language code, - [ext] corresponds to the translated file\'s extension according to its mime type. For a DocumentInputConfig.gcs_uri provided document, the output file will have a name according to its URI. For example: an input file with URI: "gs://a/b/c.[extension]" stored in a gcs_destination bucket with name "my_bucket" will have an output URI: "gs://my_bucket/a_b_c_[trg]_translations.[ext]", where - [trg] corresponds to the translated file\'s language code, - [ext] corresponds to the translated file\'s extension according to its mime type. If the document was directly provided through the request, then the output document will have the format: "gs://my_bucket/translated_document_[trg]_translations.[ext], where - [trg] corresponds to the translated file\'s language code, - [ext] corresponds to the translated file\'s extension according to its mime type. If a glossary was provided, then the output URI for the glossary translation will be equal to the default output URI but have `glossary_translations` instead of `translations`. For the previous example, its glossary URI would be: "gs://my_bucket/a_b_c_[trg]_glossary_translations.[ext]". Thus the max number of output files will be 2 (Translated document, Glossary translated document). Callers should expect no partial outputs. If there is any error during document translation, no output will be stored in the Cloud Storage bucket.',
)
mimeType: Optional[str] = Field(
None,
description="Optional. Specifies the translated document's mime_type. If not specified, the translated file's mime type will be the same as the input file's mime type. Currently only support the output mime type to be the same as input mime type. - application/pdf - application/vnd.openxmlformats-officedocument.wordprocessingml.document - application/vnd.openxmlformats-officedocument.presentationml.presentation - application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
)
class Glossary(BaseModel):
endTime: Optional[str] = Field(
None, description='Output only. When the glossary creation was finished.'
)
entryCount: Optional[int] = Field(
None, description='Output only. The number of entries defined in the glossary.'
)
inputConfig: Optional[GlossaryInputConfig] = Field(
None,
description='Required. Provides examples to build the glossary from. Total glossary must not exceed 10M Unicode codepoints.',
)
languageCodesSet: Optional[LanguageCodesSet] = Field(
None, description='Used with equivalent term set glossaries.'
)
languagePair: Optional[LanguageCodePair] = Field(
None, description='Used with unidirectional glossaries.'
)
name: Optional[str] = Field(
None,
description='Required. The resource name of the glossary. Glossary names have the form `projects/{project-number-or-id}/locations/{location-id}/glossaries/{glossary-id}`.',
)
submitTime: Optional[str] = Field(
None, description='Output only. When CreateGlossary was called.'
)
class ListGlossariesResponse(BaseModel):
glossaries: Optional[List[Glossary]] = Field(
None, description='The list of glossaries for a project.'
)
nextPageToken: Optional[str] = Field(
None,
description='A token to retrieve a page of results. Pass this value in the [ListGlossariesRequest.page_token] field in the subsequent call to `ListGlossaries` method to retrieve the next page of results.',
)
class ListLocationsResponse(BaseModel):
locations: Optional[List[Location]] = Field(
None,
description='A list of locations that matches the specified filter in the request.',
)
nextPageToken: Optional[str] = Field(
None, description='The standard List next-page token.'
)
class Operation(BaseModel):
done: Optional[bool] = Field(
None,
description='If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.',
)
error: Optional[Status] = Field(
None,
description='The error result of the operation in case of failure or cancellation.',
)
metadata: Optional[Dict[str, Any]] = Field(
None,
description='Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.',
)
name: Optional[str] = Field(
None,
description='The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.',
)
response: Optional[Dict[str, Any]] = Field(
None,
description='The normal response of the operation in case of success. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.',
)
class TranslateDocumentRequest(BaseModel):
customizedAttribution: Optional[str] = Field(
None,
description='Optional. This flag is to support user customized attribution. If not provided, the default is `Machine Translated by Google`. Customized attribution should follow rules in https://cloud.google.com/translate/attribution#attribution_and_logos',
)
documentInputConfig: Optional[DocumentInputConfig] = Field(
None, description='Required. Input configurations.'
)
documentOutputConfig: Optional[DocumentOutputConfig] = Field(
None,
description="Optional. Output configurations. Defines if the output file should be stored within Cloud Storage as well as the desired output format. If not provided the translated file will only be returned through a byte-stream and its output mime type will be the same as the input file's mime type.",
)
enableRotationCorrection: Optional[bool] = Field(
None, description='Optional. If true, enable auto rotation correction in DVS.'
)
enableShadowRemovalNativePdf: Optional[bool] = Field(
None,
description='Optional. If true, use the text removal server to remove the shadow text on background image for native pdf translation. Shadow removal feature can only be enabled when is_translate_native_pdf_only: false && pdf_native_only: false',
)
glossaryConfig: Optional[TranslateTextGlossaryConfig] = Field(
None,
description='Optional. Glossary to be applied. The glossary must be within the same region (have the same location-id) as the model, otherwise an INVALID_ARGUMENT (400) error is returned.',
)
isTranslateNativePdfOnly: Optional[bool] = Field(
None,
description='Optional. is_translate_native_pdf_only field for external customers. If true, the page limit of online native pdf translation is 300 and only native pdf pages will be translated.',
)
labels: Optional[Dict[str, str]] = Field(
None,
description='Optional. The labels with user-defined metadata for the request. Label keys and values can be no longer than 63 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. See https://cloud.google.com/translate/docs/advanced/labels for more information.',
)
model: Optional[str] = Field(
None,
description='Optional. The `model` type requested for this translation. The format depends on model type: - AutoML Translation models: `projects/{project-number-or-id}/locations/{location-id}/models/{model-id}` - General (built-in) models: `projects/{project-number-or-id}/locations/{location-id}/models/general/nmt`, If not provided, the default Google model (NMT) will be used for translation.',
)
sourceLanguageCode: Optional[str] = Field(
None,
description='Optional. The BCP-47 language code of the input document if known, for example, "en-US" or "sr-Latn". Supported language codes are listed in Language Support. If the source language isn\'t specified, the API attempts to identify the source language automatically and returns the source language within the response. Source language must be specified if the request contains a glossary or a custom model.',
)
targetLanguageCode: Optional[str] = Field(
None,
description='Required. The BCP-47 language code to use for translation of the input document, set to one of the language codes listed in Language Support.',
)
class TranslateDocumentResponse(BaseModel):
documentTranslation: Optional[DocumentTranslation] = Field(
None, description='Translated document.'
)
glossaryConfig: Optional[TranslateTextGlossaryConfig] = Field(
None, description='The `glossary_config` used for this translation.'
)
glossaryDocumentTranslation: Optional[DocumentTranslation] = Field(
None,
description="The document's translation output if a glossary is provided in the request. This can be the same as [TranslateDocumentResponse.document_translation] if no glossary terms apply.",
)
model: Optional[str] = Field(
None,
description="Only present when 'model' is present in the request. 'model' is normalized to have a project number. For example: If the 'model' field in TranslateDocumentRequest is: `projects/{project-id}/locations/{location-id}/models/general/nmt` then `model` here would be normalized to `projects/{project-number}/locations/{location-id}/models/general/nmt`.",
)
class TranslateTextResponse(BaseModel):
glossaryTranslations: Optional[List[Translation]] = Field(
None,
description='Text translation responses if a glossary is provided in the request. This can be the same as `translations` if no terms apply. This field has the same length as `contents`.',
)
translations: Optional[List[Translation]] = Field(
None,
description='Text translation responses with no glossary applied. This field has the same length as `contents`.',
)
class ListOperationsResponse(BaseModel):
nextPageToken: Optional[str] = Field(
None, description='The standard List next-page token.'
)
operations: Optional[List[Operation]] = Field(
None,
description='A list of operations that matches the specified filter in the request.',
)