R/comprehend_operations.R

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

# This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common get_config new_operation new_request send_request
#' @include comprehend_service.R
NULL

#' Determines the dominant language of the input text for a batch of
#' documents
#'
#' @description
#' Determines the dominant language of the input text for a batch of documents. For a list of languages that Amazon Comprehend can detect, see [Amazon Comprehend Supported Languages](https://docs.aws.amazon.com/comprehend/latest/dg/how-languages.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/batch_detect_dominant_language.html](https://paws-r.github.io/docs/comprehend/batch_detect_dominant_language.html) for full documentation.
#'
#' @param TextList [required] A list containing the text of the input documents. The list can contain
#' a maximum of 25 documents. Each document should contain at least 20
#' characters and must contain fewer than 5,000 bytes of UTF-8 encoded
#' characters.
#'
#' @keywords internal
#'
#' @rdname comprehend_batch_detect_dominant_language
comprehend_batch_detect_dominant_language <- function(TextList) {
  op <- new_operation(
    name = "BatchDetectDominantLanguage",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$batch_detect_dominant_language_input(TextList = TextList)
  output <- .comprehend$batch_detect_dominant_language_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$batch_detect_dominant_language <- comprehend_batch_detect_dominant_language

#' Inspects the text of a batch of documents for named entities and returns
#' information about them
#'
#' @description
#' Inspects the text of a batch of documents for named entities and returns information about them. For more information about named entities, see how-entities
#'
#' See [https://paws-r.github.io/docs/comprehend/batch_detect_entities.html](https://paws-r.github.io/docs/comprehend/batch_detect_entities.html) for full documentation.
#'
#' @param TextList &#91;required&#93; A list containing the text of the input documents. The list can contain
#' a maximum of 25 documents. Each document must contain fewer than 5,000
#' bytes of UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#'
#' @keywords internal
#'
#' @rdname comprehend_batch_detect_entities
comprehend_batch_detect_entities <- function(TextList, LanguageCode) {
  op <- new_operation(
    name = "BatchDetectEntities",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$batch_detect_entities_input(TextList = TextList, LanguageCode = LanguageCode)
  output <- .comprehend$batch_detect_entities_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$batch_detect_entities <- comprehend_batch_detect_entities

#' Detects the key noun phrases found in a batch of documents
#'
#' @description
#' Detects the key noun phrases found in a batch of documents.
#'
#' See [https://paws-r.github.io/docs/comprehend/batch_detect_key_phrases.html](https://paws-r.github.io/docs/comprehend/batch_detect_key_phrases.html) for full documentation.
#'
#' @param TextList &#91;required&#93; A list containing the text of the input documents. The list can contain
#' a maximum of 25 documents. Each document must contain fewer than 5,000
#' bytes of UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#'
#' @keywords internal
#'
#' @rdname comprehend_batch_detect_key_phrases
comprehend_batch_detect_key_phrases <- function(TextList, LanguageCode) {
  op <- new_operation(
    name = "BatchDetectKeyPhrases",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$batch_detect_key_phrases_input(TextList = TextList, LanguageCode = LanguageCode)
  output <- .comprehend$batch_detect_key_phrases_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$batch_detect_key_phrases <- comprehend_batch_detect_key_phrases

#' Inspects a batch of documents and returns an inference of the prevailing
#' sentiment, POSITIVE, NEUTRAL, MIXED, or NEGATIVE, in each one
#'
#' @description
#' Inspects a batch of documents and returns an inference of the prevailing sentiment, `POSITIVE`, `NEUTRAL`, `MIXED`, or `NEGATIVE`, in each one.
#'
#' See [https://paws-r.github.io/docs/comprehend/batch_detect_sentiment.html](https://paws-r.github.io/docs/comprehend/batch_detect_sentiment.html) for full documentation.
#'
#' @param TextList &#91;required&#93; A list containing the text of the input documents. The list can contain
#' a maximum of 25 documents. Each document must contain fewer that 5,000
#' bytes of UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#'
#' @keywords internal
#'
#' @rdname comprehend_batch_detect_sentiment
comprehend_batch_detect_sentiment <- function(TextList, LanguageCode) {
  op <- new_operation(
    name = "BatchDetectSentiment",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$batch_detect_sentiment_input(TextList = TextList, LanguageCode = LanguageCode)
  output <- .comprehend$batch_detect_sentiment_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$batch_detect_sentiment <- comprehend_batch_detect_sentiment

#' Inspects the text of a batch of documents for the syntax and part of
#' speech of the words in the document and returns information about them
#'
#' @description
#' Inspects the text of a batch of documents for the syntax and part of speech of the words in the document and returns information about them. For more information, see how-syntax.
#'
#' See [https://paws-r.github.io/docs/comprehend/batch_detect_syntax.html](https://paws-r.github.io/docs/comprehend/batch_detect_syntax.html) for full documentation.
#'
#' @param TextList &#91;required&#93; A list containing the text of the input documents. The list can contain
#' a maximum of 25 documents. Each document must contain fewer that 5,000
#' bytes of UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the
#' following languages supported by Amazon Comprehend: German ("de"),
#' English ("en"), Spanish ("es"), French ("fr"), Italian ("it"), or
#' Portuguese ("pt"). All documents must be in the same language.
#'
#' @keywords internal
#'
#' @rdname comprehend_batch_detect_syntax
comprehend_batch_detect_syntax <- function(TextList, LanguageCode) {
  op <- new_operation(
    name = "BatchDetectSyntax",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$batch_detect_syntax_input(TextList = TextList, LanguageCode = LanguageCode)
  output <- .comprehend$batch_detect_syntax_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$batch_detect_syntax <- comprehend_batch_detect_syntax

#' Creates a new document classification request to analyze a single
#' document in real-time, using a previously created and trained custom
#' model and an endpoint
#'
#' @description
#' Creates a new document classification request to analyze a single document in real-time, using a previously created and trained custom model and an endpoint.
#'
#' See [https://paws-r.github.io/docs/comprehend/classify_document.html](https://paws-r.github.io/docs/comprehend/classify_document.html) for full documentation.
#'
#' @param Text &#91;required&#93; The document text to be analyzed.
#' @param EndpointArn &#91;required&#93; The Amazon Resource Number (ARN) of the endpoint. For information about
#' endpoints, see [Managing
#' endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' @keywords internal
#'
#' @rdname comprehend_classify_document
comprehend_classify_document <- function(Text, EndpointArn) {
  op <- new_operation(
    name = "ClassifyDocument",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$classify_document_input(Text = Text, EndpointArn = EndpointArn)
  output <- .comprehend$classify_document_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$classify_document <- comprehend_classify_document

#' Analyzes input text for the presence of personally identifiable
#' information (PII) and returns the labels of identified PII entity types
#' such as name, address, bank account number, or phone number
#'
#' @description
#' Analyzes input text for the presence of personally identifiable information (PII) and returns the labels of identified PII entity types such as name, address, bank account number, or phone number.
#'
#' See [https://paws-r.github.io/docs/comprehend/contains_pii_entities.html](https://paws-r.github.io/docs/comprehend/contains_pii_entities.html) for full documentation.
#'
#' @param Text &#91;required&#93; Creates a new document classification request to analyze a single
#' document in real-time, returning personally identifiable information
#' (PII) entity labels.
#' @param LanguageCode &#91;required&#93; The language of the input documents. Currently, English is the only
#' valid language.
#'
#' @keywords internal
#'
#' @rdname comprehend_contains_pii_entities
comprehend_contains_pii_entities <- function(Text, LanguageCode) {
  op <- new_operation(
    name = "ContainsPiiEntities",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$contains_pii_entities_input(Text = Text, LanguageCode = LanguageCode)
  output <- .comprehend$contains_pii_entities_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$contains_pii_entities <- comprehend_contains_pii_entities

#' Creates a new document classifier that you can use to categorize
#' documents
#'
#' @description
#' Creates a new document classifier that you can use to categorize documents. To create a classifier, you provide a set of training documents that labeled with the categories that you want to use. After the classifier is trained you can use it to categorize a set of labeled documents into the categories. For more information, see how-document-classification.
#'
#' See [https://paws-r.github.io/docs/comprehend/create_document_classifier.html](https://paws-r.github.io/docs/comprehend/create_document_classifier.html) for full documentation.
#'
#' @param DocumentClassifierName &#91;required&#93; The name of the document classifier.
#' @param VersionName The version name given to the newly created classifier. Version names
#' can have a maximum of 256 characters. Alphanumeric characters, hyphens
#' (-) and underscores (_) are allowed. The version name must be unique
#' among all models with the same classifier name in the account/AWS
#' Region.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM)
#' role that grants Amazon Comprehend read access to your input data.
#' @param Tags Tags to be associated with the document classifier being created. A tag
#' is a key-value pair that adds as a metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig Enables the addition of output results configuration parameters for
#' custom classifier jobs.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the
#' following languages supported by Amazon Comprehend: German ("de"),
#' English ("en"), Spanish ("es"), French ("fr"), Italian ("it"), or
#' Portuguese ("pt"). All documents must be in the same language.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your custom classifier.
#' For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Mode Indicates the mode in which the classifier will be trained. The
#' classifier can be trained in multi-class mode, which identifies one and
#' only one class for each document, or multi-label mode, which identifies
#' one or more labels for each document. In multi-label mode, multiple
#' labels for an individual document are separated by a delimiter. The
#' default delimiter between labels is a pipe (|).
#' @param ModelKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt trained custom models. The ModelKmsKeyId can be either
#' of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param ModelPolicy The resource-based policy to attach to your custom document classifier
#' model. You can use this policy to allow another AWS account to import
#' your custom model.
#' 
#' Provide your policy as a JSON body that you enter as a UTF-8 encoded
#' string without line breaks. To provide valid JSON, enclose the attribute
#' names and values in double quotes. If the JSON body is also enclosed in
#' double quotes, then you must escape the double quotes that are inside
#' the policy:
#' 
#' `"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"`
#' 
#' To avoid escaping quotes, you can use single quotes to enclose the
#' policy and double quotes to enclose the JSON names and values:
#' 
#' `'{"attribute": "value", "attribute": ["value"]}'`
#'
#' @keywords internal
#'
#' @rdname comprehend_create_document_classifier
comprehend_create_document_classifier <- function(DocumentClassifierName, VersionName = NULL, DataAccessRoleArn, Tags = NULL, InputDataConfig, OutputDataConfig = NULL, ClientRequestToken = NULL, LanguageCode, VolumeKmsKeyId = NULL, VpcConfig = NULL, Mode = NULL, ModelKmsKeyId = NULL, ModelPolicy = NULL) {
  op <- new_operation(
    name = "CreateDocumentClassifier",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$create_document_classifier_input(DocumentClassifierName = DocumentClassifierName, VersionName = VersionName, DataAccessRoleArn = DataAccessRoleArn, Tags = Tags, InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, ClientRequestToken = ClientRequestToken, LanguageCode = LanguageCode, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Mode = Mode, ModelKmsKeyId = ModelKmsKeyId, ModelPolicy = ModelPolicy)
  output <- .comprehend$create_document_classifier_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$create_document_classifier <- comprehend_create_document_classifier

#' Creates a model-specific endpoint for synchronous inference for a
#' previously trained custom model For information about endpoints, see
#' Managing endpoints
#'
#' @description
#' Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see [Managing endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/create_endpoint.html](https://paws-r.github.io/docs/comprehend/create_endpoint.html) for full documentation.
#'
#' @param EndpointName &#91;required&#93; This is the descriptive suffix that becomes part of the `EndpointArn`
#' used for all subsequent requests to this resource.
#' @param ModelArn &#91;required&#93; The Amazon Resource Number (ARN) of the model to which the endpoint will
#' be attached.
#' @param DesiredInferenceUnits &#91;required&#93; The desired number of inference units to be used by the model using this
#' endpoint. Each inference unit represents of a throughput of 100
#' characters per second.
#' @param ClientRequestToken An idempotency token provided by the customer. If this token matches a
#' previous endpoint creation request, Amazon Comprehend will not return a
#' `ResourceInUseException`.
#' @param Tags Tags associated with the endpoint being created. A tag is a key-value
#' pair that adds metadata to the endpoint. For example, a tag with "Sales"
#' as the key might be added to an endpoint to indicate its use by the
#' sales department.
#' @param DataAccessRoleArn The Amazon Resource Name (ARN) of the AWS identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to trained custom
#' models encrypted with a customer managed key (ModelKmsKeyId).
#'
#' @keywords internal
#'
#' @rdname comprehend_create_endpoint
comprehend_create_endpoint <- function(EndpointName, ModelArn, DesiredInferenceUnits, ClientRequestToken = NULL, Tags = NULL, DataAccessRoleArn = NULL) {
  op <- new_operation(
    name = "CreateEndpoint",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$create_endpoint_input(EndpointName = EndpointName, ModelArn = ModelArn, DesiredInferenceUnits = DesiredInferenceUnits, ClientRequestToken = ClientRequestToken, Tags = Tags, DataAccessRoleArn = DataAccessRoleArn)
  output <- .comprehend$create_endpoint_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$create_endpoint <- comprehend_create_endpoint

#' Creates an entity recognizer using submitted files
#'
#' @description
#' Creates an entity recognizer using submitted files. After your [`create_entity_recognizer`][comprehend_create_entity_recognizer] request is submitted, you can check job status using the API.
#'
#' See [https://paws-r.github.io/docs/comprehend/create_entity_recognizer.html](https://paws-r.github.io/docs/comprehend/create_entity_recognizer.html) for full documentation.
#'
#' @param RecognizerName &#91;required&#93; The name given to the newly created recognizer. Recognizer names can be
#' a maximum of 256 characters. Alphanumeric characters, hyphens (-) and
#' underscores (_) are allowed. The name must be unique in the
#' account/region.
#' @param VersionName The version name given to the newly created recognizer. Version names
#' can be a maximum of 256 characters. Alphanumeric characters, hyphens (-)
#' and underscores (_) are allowed. The version name must be unique among
#' all models with the same recognizer name in the account/ AWS Region.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM)
#' role that grants Amazon Comprehend read access to your input data.
#' @param Tags Tags to be associated with the entity recognizer being created. A tag is
#' a key-value pair that adds as a metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data. The S3 bucket
#' containing the input data must be located in the same region as the
#' entity recognizer being created.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param LanguageCode &#91;required&#93; You can specify any of the following languages supported by Amazon
#' Comprehend: English ("en"), Spanish ("es"), French ("fr"), Italian
#' ("it"), German ("de"), or Portuguese ("pt"). All documents must be in
#' the same language.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your custom entity
#' recognizer. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param ModelKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt trained custom models. The ModelKmsKeyId can be either
#' of the following formats
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param ModelPolicy The JSON resource-based policy to attach to your custom entity
#' recognizer model. You can use this policy to allow another AWS account
#' to import your custom model.
#' 
#' Provide your JSON as a UTF-8 encoded string without line breaks. To
#' provide valid JSON for your policy, enclose the attribute names and
#' values in double quotes. If the JSON body is also enclosed in double
#' quotes, then you must escape the double quotes that are inside the
#' policy:
#' 
#' `"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"`
#' 
#' To avoid escaping quotes, you can use single quotes to enclose the
#' policy and double quotes to enclose the JSON names and values:
#' 
#' `'{"attribute": "value", "attribute": ["value"]}'`
#'
#' @keywords internal
#'
#' @rdname comprehend_create_entity_recognizer
comprehend_create_entity_recognizer <- function(RecognizerName, VersionName = NULL, DataAccessRoleArn, Tags = NULL, InputDataConfig, ClientRequestToken = NULL, LanguageCode, VolumeKmsKeyId = NULL, VpcConfig = NULL, ModelKmsKeyId = NULL, ModelPolicy = NULL) {
  op <- new_operation(
    name = "CreateEntityRecognizer",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$create_entity_recognizer_input(RecognizerName = RecognizerName, VersionName = VersionName, DataAccessRoleArn = DataAccessRoleArn, Tags = Tags, InputDataConfig = InputDataConfig, ClientRequestToken = ClientRequestToken, LanguageCode = LanguageCode, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, ModelKmsKeyId = ModelKmsKeyId, ModelPolicy = ModelPolicy)
  output <- .comprehend$create_entity_recognizer_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$create_entity_recognizer <- comprehend_create_entity_recognizer

#' Deletes a previously created document classifier
#'
#' @description
#' Deletes a previously created document classifier
#'
#' See [https://paws-r.github.io/docs/comprehend/delete_document_classifier.html](https://paws-r.github.io/docs/comprehend/delete_document_classifier.html) for full documentation.
#'
#' @param DocumentClassifierArn &#91;required&#93; The Amazon Resource Name (ARN) that identifies the document classifier.
#'
#' @keywords internal
#'
#' @rdname comprehend_delete_document_classifier
comprehend_delete_document_classifier <- function(DocumentClassifierArn) {
  op <- new_operation(
    name = "DeleteDocumentClassifier",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$delete_document_classifier_input(DocumentClassifierArn = DocumentClassifierArn)
  output <- .comprehend$delete_document_classifier_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$delete_document_classifier <- comprehend_delete_document_classifier

#' Deletes a model-specific endpoint for a previously-trained custom model
#'
#' @description
#' Deletes a model-specific endpoint for a previously-trained custom model. All endpoints must be deleted in order for the model to be deleted. For information about endpoints, see [Managing endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/delete_endpoint.html](https://paws-r.github.io/docs/comprehend/delete_endpoint.html) for full documentation.
#'
#' @param EndpointArn &#91;required&#93; The Amazon Resource Number (ARN) of the endpoint being deleted.
#'
#' @keywords internal
#'
#' @rdname comprehend_delete_endpoint
comprehend_delete_endpoint <- function(EndpointArn) {
  op <- new_operation(
    name = "DeleteEndpoint",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$delete_endpoint_input(EndpointArn = EndpointArn)
  output <- .comprehend$delete_endpoint_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$delete_endpoint <- comprehend_delete_endpoint

#' Deletes an entity recognizer
#'
#' @description
#' Deletes an entity recognizer.
#'
#' See [https://paws-r.github.io/docs/comprehend/delete_entity_recognizer.html](https://paws-r.github.io/docs/comprehend/delete_entity_recognizer.html) for full documentation.
#'
#' @param EntityRecognizerArn &#91;required&#93; The Amazon Resource Name (ARN) that identifies the entity recognizer.
#'
#' @keywords internal
#'
#' @rdname comprehend_delete_entity_recognizer
comprehend_delete_entity_recognizer <- function(EntityRecognizerArn) {
  op <- new_operation(
    name = "DeleteEntityRecognizer",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$delete_entity_recognizer_input(EntityRecognizerArn = EntityRecognizerArn)
  output <- .comprehend$delete_entity_recognizer_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$delete_entity_recognizer <- comprehend_delete_entity_recognizer

#' Deletes a resource-based policy that is attached to a custom model
#'
#' @description
#' Deletes a resource-based policy that is attached to a custom model.
#'
#' See [https://paws-r.github.io/docs/comprehend/delete_resource_policy.html](https://paws-r.github.io/docs/comprehend/delete_resource_policy.html) for full documentation.
#'
#' @param ResourceArn &#91;required&#93; The Amazon Resource Name (ARN) of the custom model version that has the
#' policy to delete.
#' @param PolicyRevisionId The revision ID of the policy to delete.
#'
#' @keywords internal
#'
#' @rdname comprehend_delete_resource_policy
comprehend_delete_resource_policy <- function(ResourceArn, PolicyRevisionId = NULL) {
  op <- new_operation(
    name = "DeleteResourcePolicy",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$delete_resource_policy_input(ResourceArn = ResourceArn, PolicyRevisionId = PolicyRevisionId)
  output <- .comprehend$delete_resource_policy_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$delete_resource_policy <- comprehend_delete_resource_policy

#' Gets the properties associated with a document classification job
#'
#' @description
#' Gets the properties associated with a document classification job. Use this operation to get the status of a classification job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_document_classification_job.html](https://paws-r.github.io/docs/comprehend/describe_document_classification_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_document_classification_job
comprehend_describe_document_classification_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeDocumentClassificationJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_document_classification_job_input(JobId = JobId)
  output <- .comprehend$describe_document_classification_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_document_classification_job <- comprehend_describe_document_classification_job

#' Gets the properties associated with a document classifier
#'
#' @description
#' Gets the properties associated with a document classifier.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_document_classifier.html](https://paws-r.github.io/docs/comprehend/describe_document_classifier.html) for full documentation.
#'
#' @param DocumentClassifierArn &#91;required&#93; The Amazon Resource Name (ARN) that identifies the document classifier.
#' The operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_document_classifier
comprehend_describe_document_classifier <- function(DocumentClassifierArn) {
  op <- new_operation(
    name = "DescribeDocumentClassifier",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_document_classifier_input(DocumentClassifierArn = DocumentClassifierArn)
  output <- .comprehend$describe_document_classifier_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_document_classifier <- comprehend_describe_document_classifier

#' Gets the properties associated with a dominant language detection job
#'
#' @description
#' Gets the properties associated with a dominant language detection job. Use this operation to get the status of a detection job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_dominant_language_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_dominant_language_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_dominant_language_detection_job
comprehend_describe_dominant_language_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeDominantLanguageDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_dominant_language_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_dominant_language_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_dominant_language_detection_job <- comprehend_describe_dominant_language_detection_job

#' Gets the properties associated with a specific endpoint
#'
#' @description
#' Gets the properties associated with a specific endpoint. Use this operation to get the status of an endpoint. For information about endpoints, see [Managing endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_endpoint.html](https://paws-r.github.io/docs/comprehend/describe_endpoint.html) for full documentation.
#'
#' @param EndpointArn &#91;required&#93; The Amazon Resource Number (ARN) of the endpoint being described.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_endpoint
comprehend_describe_endpoint <- function(EndpointArn) {
  op <- new_operation(
    name = "DescribeEndpoint",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_endpoint_input(EndpointArn = EndpointArn)
  output <- .comprehend$describe_endpoint_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_endpoint <- comprehend_describe_endpoint

#' Gets the properties associated with an entities detection job
#'
#' @description
#' Gets the properties associated with an entities detection job. Use this operation to get the status of a detection job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_entities_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_entities_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_entities_detection_job
comprehend_describe_entities_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeEntitiesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_entities_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_entities_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_entities_detection_job <- comprehend_describe_entities_detection_job

#' Provides details about an entity recognizer including status, S3 buckets
#' containing training data, recognizer metadata, metrics, and so on
#'
#' @description
#' Provides details about an entity recognizer including status, S3 buckets containing training data, recognizer metadata, metrics, and so on.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_entity_recognizer.html](https://paws-r.github.io/docs/comprehend/describe_entity_recognizer.html) for full documentation.
#'
#' @param EntityRecognizerArn &#91;required&#93; The Amazon Resource Name (ARN) that identifies the entity recognizer.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_entity_recognizer
comprehend_describe_entity_recognizer <- function(EntityRecognizerArn) {
  op <- new_operation(
    name = "DescribeEntityRecognizer",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_entity_recognizer_input(EntityRecognizerArn = EntityRecognizerArn)
  output <- .comprehend$describe_entity_recognizer_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_entity_recognizer <- comprehend_describe_entity_recognizer

#' Gets the status and details of an events detection job
#'
#' @description
#' Gets the status and details of an events detection job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_events_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_events_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the events detection job.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_events_detection_job
comprehend_describe_events_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeEventsDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_events_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_events_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_events_detection_job <- comprehend_describe_events_detection_job

#' Gets the properties associated with a key phrases detection job
#'
#' @description
#' Gets the properties associated with a key phrases detection job. Use this operation to get the status of a detection job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_key_phrases_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_key_phrases_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_key_phrases_detection_job
comprehend_describe_key_phrases_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeKeyPhrasesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_key_phrases_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_key_phrases_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_key_phrases_detection_job <- comprehend_describe_key_phrases_detection_job

#' Gets the properties associated with a PII entities detection job
#'
#' @description
#' Gets the properties associated with a PII entities detection job. For example, you can use this operation to get the job status.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_pii_entities_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_pii_entities_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_pii_entities_detection_job
comprehend_describe_pii_entities_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribePiiEntitiesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_pii_entities_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_pii_entities_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_pii_entities_detection_job <- comprehend_describe_pii_entities_detection_job

#' Gets the details of a resource-based policy that is attached to a custom
#' model, including the JSON body of the policy
#'
#' @description
#' Gets the details of a resource-based policy that is attached to a custom model, including the JSON body of the policy.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_resource_policy.html](https://paws-r.github.io/docs/comprehend/describe_resource_policy.html) for full documentation.
#'
#' @param ResourceArn &#91;required&#93; The Amazon Resource Name (ARN) of the policy to describe.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_resource_policy
comprehend_describe_resource_policy <- function(ResourceArn) {
  op <- new_operation(
    name = "DescribeResourcePolicy",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_resource_policy_input(ResourceArn = ResourceArn)
  output <- .comprehend$describe_resource_policy_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_resource_policy <- comprehend_describe_resource_policy

#' Gets the properties associated with a sentiment detection job
#'
#' @description
#' Gets the properties associated with a sentiment detection job. Use this operation to get the status of a detection job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_sentiment_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_sentiment_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_sentiment_detection_job
comprehend_describe_sentiment_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeSentimentDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_sentiment_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_sentiment_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_sentiment_detection_job <- comprehend_describe_sentiment_detection_job

#' Gets the properties associated with a targeted sentiment detection job
#'
#' @description
#' Gets the properties associated with a targeted sentiment detection job. Use this operation to get the status of the job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_targeted_sentiment_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_targeted_sentiment_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier that Amazon Comprehend generated for the job. The
#' operation returns this identifier in its response.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_targeted_sentiment_detection_job
comprehend_describe_targeted_sentiment_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeTargetedSentimentDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_targeted_sentiment_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_targeted_sentiment_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_targeted_sentiment_detection_job <- comprehend_describe_targeted_sentiment_detection_job

#' Gets the properties associated with a topic detection job
#'
#' @description
#' Gets the properties associated with a topic detection job. Use this operation to get the status of a detection job.
#'
#' See [https://paws-r.github.io/docs/comprehend/describe_topics_detection_job.html](https://paws-r.github.io/docs/comprehend/describe_topics_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier assigned by the user to the detection job.
#'
#' @keywords internal
#'
#' @rdname comprehend_describe_topics_detection_job
comprehend_describe_topics_detection_job <- function(JobId) {
  op <- new_operation(
    name = "DescribeTopicsDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$describe_topics_detection_job_input(JobId = JobId)
  output <- .comprehend$describe_topics_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$describe_topics_detection_job <- comprehend_describe_topics_detection_job

#' Determines the dominant language of the input text
#'
#' @description
#' Determines the dominant language of the input text. For a list of languages that Amazon Comprehend can detect, see [Amazon Comprehend Supported Languages](https://docs.aws.amazon.com/comprehend/latest/dg/how-languages.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/detect_dominant_language.html](https://paws-r.github.io/docs/comprehend/detect_dominant_language.html) for full documentation.
#'
#' @param Text &#91;required&#93; A UTF-8 text string. Each string should contain at least 20 characters
#' and must contain fewer that 5,000 bytes of UTF-8 encoded characters.
#'
#' @keywords internal
#'
#' @rdname comprehend_detect_dominant_language
comprehend_detect_dominant_language <- function(Text) {
  op <- new_operation(
    name = "DetectDominantLanguage",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$detect_dominant_language_input(Text = Text)
  output <- .comprehend$detect_dominant_language_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$detect_dominant_language <- comprehend_detect_dominant_language

#' Inspects text for named entities, and returns information about them
#'
#' @description
#' Inspects text for named entities, and returns information about them. For more information, about named entities, see how-entities.
#'
#' See [https://paws-r.github.io/docs/comprehend/detect_entities.html](https://paws-r.github.io/docs/comprehend/detect_entities.html) for full documentation.
#'
#' @param Text &#91;required&#93; A UTF-8 text string. Each string must contain fewer that 5,000 bytes of
#' UTF-8 encoded characters.
#' @param LanguageCode The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#' 
#' If your request includes the endpoint for a custom entity recognition
#' model, Amazon Comprehend uses the language of your custom model, and it
#' ignores any language code that you specify here.
#' @param EndpointArn The Amazon Resource Name of an endpoint that is associated with a custom
#' entity recognition model. Provide an endpoint if you want to detect
#' entities by using your own custom model instead of the default model
#' that is used by Amazon Comprehend.
#' 
#' If you specify an endpoint, Amazon Comprehend uses the language of your
#' custom model, and it ignores any language code that you provide in your
#' request.
#' 
#' For information about endpoints, see [Managing
#' endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' @keywords internal
#'
#' @rdname comprehend_detect_entities
comprehend_detect_entities <- function(Text, LanguageCode = NULL, EndpointArn = NULL) {
  op <- new_operation(
    name = "DetectEntities",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$detect_entities_input(Text = Text, LanguageCode = LanguageCode, EndpointArn = EndpointArn)
  output <- .comprehend$detect_entities_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$detect_entities <- comprehend_detect_entities

#' Detects the key noun phrases found in the text
#'
#' @description
#' Detects the key noun phrases found in the text.
#'
#' See [https://paws-r.github.io/docs/comprehend/detect_key_phrases.html](https://paws-r.github.io/docs/comprehend/detect_key_phrases.html) for full documentation.
#'
#' @param Text &#91;required&#93; A UTF-8 text string. Each string must contain fewer that 5,000 bytes of
#' UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#'
#' @keywords internal
#'
#' @rdname comprehend_detect_key_phrases
comprehend_detect_key_phrases <- function(Text, LanguageCode) {
  op <- new_operation(
    name = "DetectKeyPhrases",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$detect_key_phrases_input(Text = Text, LanguageCode = LanguageCode)
  output <- .comprehend$detect_key_phrases_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$detect_key_phrases <- comprehend_detect_key_phrases

#' Inspects the input text for entities that contain personally
#' identifiable information (PII) and returns information about them
#'
#' @description
#' Inspects the input text for entities that contain personally identifiable information (PII) and returns information about them.
#'
#' See [https://paws-r.github.io/docs/comprehend/detect_pii_entities.html](https://paws-r.github.io/docs/comprehend/detect_pii_entities.html) for full documentation.
#'
#' @param Text &#91;required&#93; A UTF-8 text string. Each string must contain fewer that 5,000 bytes of
#' UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. Currently, English is the only
#' valid language.
#'
#' @keywords internal
#'
#' @rdname comprehend_detect_pii_entities
comprehend_detect_pii_entities <- function(Text, LanguageCode) {
  op <- new_operation(
    name = "DetectPiiEntities",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$detect_pii_entities_input(Text = Text, LanguageCode = LanguageCode)
  output <- .comprehend$detect_pii_entities_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$detect_pii_entities <- comprehend_detect_pii_entities

#' Inspects text and returns an inference of the prevailing sentiment
#' (POSITIVE, NEUTRAL, MIXED, or NEGATIVE)
#'
#' @description
#' Inspects text and returns an inference of the prevailing sentiment (`POSITIVE`, `NEUTRAL`, `MIXED`, or `NEGATIVE`).
#'
#' See [https://paws-r.github.io/docs/comprehend/detect_sentiment.html](https://paws-r.github.io/docs/comprehend/detect_sentiment.html) for full documentation.
#'
#' @param Text &#91;required&#93; A UTF-8 text string. Each string must contain fewer that 5,000 bytes of
#' UTF-8 encoded characters.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#'
#' @keywords internal
#'
#' @rdname comprehend_detect_sentiment
comprehend_detect_sentiment <- function(Text, LanguageCode) {
  op <- new_operation(
    name = "DetectSentiment",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$detect_sentiment_input(Text = Text, LanguageCode = LanguageCode)
  output <- .comprehend$detect_sentiment_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$detect_sentiment <- comprehend_detect_sentiment

#' Inspects text for syntax and the part of speech of words in the document
#'
#' @description
#' Inspects text for syntax and the part of speech of words in the document. For more information, how-syntax.
#'
#' See [https://paws-r.github.io/docs/comprehend/detect_syntax.html](https://paws-r.github.io/docs/comprehend/detect_syntax.html) for full documentation.
#'
#' @param Text &#91;required&#93; A UTF-8 string. Each string must contain fewer that 5,000 bytes of UTF
#' encoded characters.
#' @param LanguageCode &#91;required&#93; The language code of the input documents. You can specify any of the
#' following languages supported by Amazon Comprehend: German ("de"),
#' English ("en"), Spanish ("es"), French ("fr"), Italian ("it"), or
#' Portuguese ("pt").
#'
#' @keywords internal
#'
#' @rdname comprehend_detect_syntax
comprehend_detect_syntax <- function(Text, LanguageCode) {
  op <- new_operation(
    name = "DetectSyntax",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$detect_syntax_input(Text = Text, LanguageCode = LanguageCode)
  output <- .comprehend$detect_syntax_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$detect_syntax <- comprehend_detect_syntax

#' Creates a new custom model that replicates a source custom model that
#' you import
#'
#' @description
#' Creates a new custom model that replicates a source custom model that you import. The source model can be in your AWS account or another one.
#'
#' See [https://paws-r.github.io/docs/comprehend/import_model.html](https://paws-r.github.io/docs/comprehend/import_model.html) for full documentation.
#'
#' @param SourceModelArn &#91;required&#93; The Amazon Resource Name (ARN) of the custom model to import.
#' @param ModelName The name to assign to the custom model that is created in Amazon
#' Comprehend by this import.
#' @param VersionName The version name given to the custom model that is created by this
#' import. Version names can have a maximum of 256 characters. Alphanumeric
#' characters, hyphens (-) and underscores (_) are allowed. The version
#' name must be unique among all models with the same classifier name in
#' the account/AWS Region.
#' @param ModelKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt trained custom models. The ModelKmsKeyId can be either
#' of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param DataAccessRoleArn The Amazon Resource Name (ARN) of the AWS Identity and Management (IAM)
#' role that allows Amazon Comprehend to use Amazon Key Management Service
#' (KMS) to encrypt or decrypt the custom model.
#' @param Tags Tags to be associated with the custom model that is created by this
#' import. A tag is a key-value pair that adds as a metadata to a resource
#' used by Amazon Comprehend. For example, a tag with "Sales" as the key
#' might be added to a resource to indicate its use by the sales
#' department.
#'
#' @keywords internal
#'
#' @rdname comprehend_import_model
comprehend_import_model <- function(SourceModelArn, ModelName = NULL, VersionName = NULL, ModelKmsKeyId = NULL, DataAccessRoleArn = NULL, Tags = NULL) {
  op <- new_operation(
    name = "ImportModel",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$import_model_input(SourceModelArn = SourceModelArn, ModelName = ModelName, VersionName = VersionName, ModelKmsKeyId = ModelKmsKeyId, DataAccessRoleArn = DataAccessRoleArn, Tags = Tags)
  output <- .comprehend$import_model_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$import_model <- comprehend_import_model

#' Gets a list of the documentation classification jobs that you have
#' submitted
#'
#' @description
#' Gets a list of the documentation classification jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_document_classification_jobs.html](https://paws-r.github.io/docs/comprehend/list_document_classification_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their names,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_document_classification_jobs
comprehend_list_document_classification_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListDocumentClassificationJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_document_classification_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_document_classification_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_document_classification_jobs <- comprehend_list_document_classification_jobs

#' Gets a list of summaries of the document classifiers that you have
#' created
#'
#' @description
#' Gets a list of summaries of the document classifiers that you have created
#'
#' See [https://paws-r.github.io/docs/comprehend/list_document_classifier_summaries.html](https://paws-r.github.io/docs/comprehend/list_document_classifier_summaries.html) for full documentation.
#'
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return on each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_document_classifier_summaries
comprehend_list_document_classifier_summaries <- function(NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListDocumentClassifierSummaries",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_document_classifier_summaries_input(NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_document_classifier_summaries_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_document_classifier_summaries <- comprehend_list_document_classifier_summaries

#' Gets a list of the document classifiers that you have created
#'
#' @description
#' Gets a list of the document classifiers that you have created.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_document_classifiers.html](https://paws-r.github.io/docs/comprehend/list_document_classifiers.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_document_classifiers
comprehend_list_document_classifiers <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListDocumentClassifiers",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_document_classifiers_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_document_classifiers_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_document_classifiers <- comprehend_list_document_classifiers

#' Gets a list of the dominant language detection jobs that you have
#' submitted
#'
#' @description
#' Gets a list of the dominant language detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_dominant_language_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_dominant_language_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters that jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_dominant_language_detection_jobs
comprehend_list_dominant_language_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListDominantLanguageDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_dominant_language_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_dominant_language_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_dominant_language_detection_jobs <- comprehend_list_dominant_language_detection_jobs

#' Gets a list of all existing endpoints that you've created
#'
#' @description
#' Gets a list of all existing endpoints that you've created. For information about endpoints, see [Managing endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/list_endpoints.html](https://paws-r.github.io/docs/comprehend/list_endpoints.html) for full documentation.
#'
#' @param Filter Filters the endpoints that are returned. You can filter endpoints on
#' their name, model, status, or the date and time that they were created.
#' You can only set one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_endpoints
comprehend_list_endpoints <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListEndpoints",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_endpoints_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_endpoints_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_endpoints <- comprehend_list_endpoints

#' Gets a list of the entity detection jobs that you have submitted
#'
#' @description
#' Gets a list of the entity detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_entities_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_entities_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_entities_detection_jobs
comprehend_list_entities_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListEntitiesDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_entities_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_entities_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_entities_detection_jobs <- comprehend_list_entities_detection_jobs

#' Gets a list of summaries for the entity recognizers that you have
#' created
#'
#' @description
#' Gets a list of summaries for the entity recognizers that you have created.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_entity_recognizer_summaries.html](https://paws-r.github.io/docs/comprehend/list_entity_recognizer_summaries.html) for full documentation.
#'
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return on each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_entity_recognizer_summaries
comprehend_list_entity_recognizer_summaries <- function(NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListEntityRecognizerSummaries",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_entity_recognizer_summaries_input(NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_entity_recognizer_summaries_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_entity_recognizer_summaries <- comprehend_list_entity_recognizer_summaries

#' Gets a list of the properties of all entity recognizers that you
#' created, including recognizers currently in training
#'
#' @description
#' Gets a list of the properties of all entity recognizers that you created, including recognizers currently in training. Allows you to filter the list of recognizers based on criteria such as status and submission time. This call returns up to 500 entity recognizers in the list, with a default number of 100 recognizers in the list.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_entity_recognizers.html](https://paws-r.github.io/docs/comprehend/list_entity_recognizers.html) for full documentation.
#'
#' @param Filter Filters the list of entities returned. You can filter on `Status`,
#' `SubmitTimeBefore`, or `SubmitTimeAfter`. You can only set one filter at
#' a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return on each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_entity_recognizers
comprehend_list_entity_recognizers <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListEntityRecognizers",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_entity_recognizers_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_entity_recognizers_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_entity_recognizers <- comprehend_list_entity_recognizers

#' Gets a list of the events detection jobs that you have submitted
#'
#' @description
#' Gets a list of the events detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_events_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_events_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_events_detection_jobs
comprehend_list_events_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListEventsDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_events_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_events_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_events_detection_jobs <- comprehend_list_events_detection_jobs

#' Get a list of key phrase detection jobs that you have submitted
#'
#' @description
#' Get a list of key phrase detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_key_phrases_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_key_phrases_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_key_phrases_detection_jobs
comprehend_list_key_phrases_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListKeyPhrasesDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_key_phrases_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_key_phrases_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_key_phrases_detection_jobs <- comprehend_list_key_phrases_detection_jobs

#' Gets a list of the PII entity detection jobs that you have submitted
#'
#' @description
#' Gets a list of the PII entity detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_pii_entities_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_pii_entities_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_pii_entities_detection_jobs
comprehend_list_pii_entities_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListPiiEntitiesDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_pii_entities_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_pii_entities_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_pii_entities_detection_jobs <- comprehend_list_pii_entities_detection_jobs

#' Gets a list of sentiment detection jobs that you have submitted
#'
#' @description
#' Gets a list of sentiment detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_sentiment_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_sentiment_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_sentiment_detection_jobs
comprehend_list_sentiment_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListSentimentDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_sentiment_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_sentiment_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_sentiment_detection_jobs <- comprehend_list_sentiment_detection_jobs

#' Lists all tags associated with a given Amazon Comprehend resource
#'
#' @description
#' Lists all tags associated with a given Amazon Comprehend resource.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_tags_for_resource.html](https://paws-r.github.io/docs/comprehend/list_tags_for_resource.html) for full documentation.
#'
#' @param ResourceArn &#91;required&#93; The Amazon Resource Name (ARN) of the given Amazon Comprehend resource
#' you are querying.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_tags_for_resource
comprehend_list_tags_for_resource <- function(ResourceArn) {
  op <- new_operation(
    name = "ListTagsForResource",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_tags_for_resource_input(ResourceArn = ResourceArn)
  output <- .comprehend$list_tags_for_resource_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_tags_for_resource <- comprehend_list_tags_for_resource

#' Gets a list of targeted sentiment detection jobs that you have submitted
#'
#' @description
#' Gets a list of targeted sentiment detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_targeted_sentiment_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_targeted_sentiment_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. You can filter jobs on their name,
#' status, or the date and time that they were submitted. You can only set
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_targeted_sentiment_detection_jobs
comprehend_list_targeted_sentiment_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListTargetedSentimentDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_targeted_sentiment_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_targeted_sentiment_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_targeted_sentiment_detection_jobs <- comprehend_list_targeted_sentiment_detection_jobs

#' Gets a list of the topic detection jobs that you have submitted
#'
#' @description
#' Gets a list of the topic detection jobs that you have submitted.
#'
#' See [https://paws-r.github.io/docs/comprehend/list_topics_detection_jobs.html](https://paws-r.github.io/docs/comprehend/list_topics_detection_jobs.html) for full documentation.
#'
#' @param Filter Filters the jobs that are returned. Jobs can be filtered on their name,
#' status, or the date and time that they were submitted. You can set only
#' one filter at a time.
#' @param NextToken Identifies the next page of results to return.
#' @param MaxResults The maximum number of results to return in each page. The default is
#' 100.
#'
#' @keywords internal
#'
#' @rdname comprehend_list_topics_detection_jobs
comprehend_list_topics_detection_jobs <- function(Filter = NULL, NextToken = NULL, MaxResults = NULL) {
  op <- new_operation(
    name = "ListTopicsDetectionJobs",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$list_topics_detection_jobs_input(Filter = Filter, NextToken = NextToken, MaxResults = MaxResults)
  output <- .comprehend$list_topics_detection_jobs_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$list_topics_detection_jobs <- comprehend_list_topics_detection_jobs

#' Attaches a resource-based policy to a custom model
#'
#' @description
#' Attaches a resource-based policy to a custom model. You can use this policy to authorize an entity in another AWS account to import the custom model, which replicates it in Amazon Comprehend in their account.
#'
#' See [https://paws-r.github.io/docs/comprehend/put_resource_policy.html](https://paws-r.github.io/docs/comprehend/put_resource_policy.html) for full documentation.
#'
#' @param ResourceArn &#91;required&#93; The Amazon Resource Name (ARN) of the custom model to attach the policy
#' to.
#' @param ResourcePolicy &#91;required&#93; The JSON resource-based policy to attach to your custom model. Provide
#' your JSON as a UTF-8 encoded string without line breaks. To provide
#' valid JSON for your policy, enclose the attribute names and values in
#' double quotes. If the JSON body is also enclosed in double quotes, then
#' you must escape the double quotes that are inside the policy:
#' 
#' `"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"`
#' 
#' To avoid escaping quotes, you can use single quotes to enclose the
#' policy and double quotes to enclose the JSON names and values:
#' 
#' `'{"attribute": "value", "attribute": ["value"]}'`
#' @param PolicyRevisionId The revision ID that Amazon Comprehend assigned to the policy that you
#' are updating. If you are creating a new policy that has no prior
#' version, don't use this parameter. Amazon Comprehend creates the
#' revision ID for you.
#'
#' @keywords internal
#'
#' @rdname comprehend_put_resource_policy
comprehend_put_resource_policy <- function(ResourceArn, ResourcePolicy, PolicyRevisionId = NULL) {
  op <- new_operation(
    name = "PutResourcePolicy",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$put_resource_policy_input(ResourceArn = ResourceArn, ResourcePolicy = ResourcePolicy, PolicyRevisionId = PolicyRevisionId)
  output <- .comprehend$put_resource_policy_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$put_resource_policy <- comprehend_put_resource_policy

#' Starts an asynchronous document classification job
#'
#' @description
#' Starts an asynchronous document classification job. Use the operation to track the progress of the job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_document_classification_job.html](https://paws-r.github.io/docs/comprehend/start_document_classification_job.html) for full documentation.
#'
#' @param JobName The identifier of the job.
#' @param DocumentClassifierArn &#91;required&#93; The Amazon Resource Name (ARN) of the document classifier to use to
#' process the job.
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' @param ClientRequestToken A unique identifier for the request. If you do not set the client
#' request token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your document
#' classification job. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Tags Tags to be associated with the document classification job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_document_classification_job
comprehend_start_document_classification_job <- function(JobName = NULL, DocumentClassifierArn, InputDataConfig, OutputDataConfig, DataAccessRoleArn, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartDocumentClassificationJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_document_classification_job_input(JobName = JobName, DocumentClassifierArn = DocumentClassifierArn, InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_document_classification_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_document_classification_job <- comprehend_start_document_classification_job

#' Starts an asynchronous dominant language detection job for a collection
#' of documents
#'
#' @description
#' Starts an asynchronous dominant language detection job for a collection of documents. Use the operation to track the status of a job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_dominant_language_detection_job.html](https://paws-r.github.io/docs/comprehend/start_dominant_language_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' For more information, see
#' https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.
#' @param JobName An identifier for the job.
#' @param ClientRequestToken A unique identifier for the request. If you do not set the client
#' request token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your dominant language
#' detection job. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Tags Tags to be associated with the dominant language detection job. A tag is
#' a key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_dominant_language_detection_job
comprehend_start_dominant_language_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartDominantLanguageDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_dominant_language_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_dominant_language_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_dominant_language_detection_job <- comprehend_start_dominant_language_detection_job

#' Starts an asynchronous entity detection job for a collection of
#' documents
#'
#' @description
#' Starts an asynchronous entity detection job for a collection of documents. Use the operation to track the status of a job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_entities_detection_job.html](https://paws-r.github.io/docs/comprehend/start_entities_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' For more information, see
#' https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.
#' @param JobName The identifier of the job.
#' @param EntityRecognizerArn The Amazon Resource Name (ARN) that identifies the specific entity
#' recognizer to be used by the
#' [`start_entities_detection_job`][comprehend_start_entities_detection_job].
#' This ARN is optional and is only used for a custom entity recognition
#' job.
#' @param LanguageCode &#91;required&#93; The language of the input documents. All documents must be in the same
#' language. You can specify any of the languages supported by Amazon
#' Comprehend. If custom entities recognition is used, this parameter is
#' ignored and the language used for training the model is used instead.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your entity detection
#' job. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Tags Tags to be associated with the entities detection job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_entities_detection_job
comprehend_start_entities_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, EntityRecognizerArn = NULL, LanguageCode, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartEntitiesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_entities_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, EntityRecognizerArn = EntityRecognizerArn, LanguageCode = LanguageCode, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_entities_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_entities_detection_job <- comprehend_start_entities_detection_job

#' Starts an asynchronous event detection job for a collection of documents
#'
#' @description
#' Starts an asynchronous event detection job for a collection of documents.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_events_detection_job.html](https://paws-r.github.io/docs/comprehend/start_events_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' @param JobName The identifier of the events detection job.
#' @param LanguageCode &#91;required&#93; The language code of the input documents.
#' @param ClientRequestToken An unique identifier for the request. If you don't set the client
#' request token, Amazon Comprehend generates one.
#' @param TargetEventTypes &#91;required&#93; The types of events to detect in the input documents.
#' @param Tags Tags to be associated with the events detection job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_events_detection_job
comprehend_start_events_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, LanguageCode, ClientRequestToken = NULL, TargetEventTypes, Tags = NULL) {
  op <- new_operation(
    name = "StartEventsDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_events_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, LanguageCode = LanguageCode, ClientRequestToken = ClientRequestToken, TargetEventTypes = TargetEventTypes, Tags = Tags)
  output <- .comprehend$start_events_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_events_detection_job <- comprehend_start_events_detection_job

#' Starts an asynchronous key phrase detection job for a collection of
#' documents
#'
#' @description
#' Starts an asynchronous key phrase detection job for a collection of documents. Use the operation to track the status of a job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_key_phrases_detection_job.html](https://paws-r.github.io/docs/comprehend/start_key_phrases_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' For more information, see
#' https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.
#' @param JobName The identifier of the job.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your key phrases
#' detection job. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Tags Tags to be associated with the key phrases detection job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_key_phrases_detection_job
comprehend_start_key_phrases_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, LanguageCode, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartKeyPhrasesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_key_phrases_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, LanguageCode = LanguageCode, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_key_phrases_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_key_phrases_detection_job <- comprehend_start_key_phrases_detection_job

#' Starts an asynchronous PII entity detection job for a collection of
#' documents
#'
#' @description
#' Starts an asynchronous PII entity detection job for a collection of documents.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_pii_entities_detection_job.html](https://paws-r.github.io/docs/comprehend/start_pii_entities_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; The input properties for a PII entities detection job.
#' @param OutputDataConfig &#91;required&#93; Provides configuration parameters for the output of PII entity detection
#' jobs.
#' @param Mode &#91;required&#93; Specifies whether the output provides the locations (offsets) of PII
#' entities or a file in which PII entities are redacted.
#' @param RedactionConfig Provides configuration parameters for PII entity redaction.
#' 
#' This parameter is required if you set the `Mode` parameter to
#' `ONLY_REDACTION`. In that case, you must provide a `RedactionConfig`
#' definition that includes the `PiiEntityTypes` parameter.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' @param JobName The identifier of the job.
#' @param LanguageCode &#91;required&#93; The language of the input documents. Currently, English is the only
#' valid language.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param Tags Tags to be associated with the PII entities detection job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_pii_entities_detection_job
comprehend_start_pii_entities_detection_job <- function(InputDataConfig, OutputDataConfig, Mode, RedactionConfig = NULL, DataAccessRoleArn, JobName = NULL, LanguageCode, ClientRequestToken = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartPiiEntitiesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_pii_entities_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, Mode = Mode, RedactionConfig = RedactionConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, LanguageCode = LanguageCode, ClientRequestToken = ClientRequestToken, Tags = Tags)
  output <- .comprehend$start_pii_entities_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_pii_entities_detection_job <- comprehend_start_pii_entities_detection_job

#' Starts an asynchronous sentiment detection job for a collection of
#' documents
#'
#' @description
#' Starts an asynchronous sentiment detection job for a collection of documents. Use the operation to track the status of a job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_sentiment_detection_job.html](https://paws-r.github.io/docs/comprehend/start_sentiment_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' For more information, see
#' https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.
#' @param JobName The identifier of the job.
#' @param LanguageCode &#91;required&#93; The language of the input documents. You can specify any of the primary
#' languages supported by Amazon Comprehend. All documents must be in the
#' same language.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your sentiment
#' detection job. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Tags Tags to be associated with the sentiment detection job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_sentiment_detection_job
comprehend_start_sentiment_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, LanguageCode, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartSentimentDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_sentiment_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, LanguageCode = LanguageCode, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_sentiment_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_sentiment_detection_job <- comprehend_start_sentiment_detection_job

#' Starts an asynchronous targeted sentiment detection job for a collection
#' of documents
#'
#' @description
#' Starts an asynchronous targeted sentiment detection job for a collection of documents. Use the operation to track the status of a job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_targeted_sentiment_detection_job.html](https://paws-r.github.io/docs/comprehend/start_targeted_sentiment_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; 
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files.
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' For more information, see Role-based permissions.
#' @param JobName The identifier of the job.
#' @param LanguageCode &#91;required&#93; The language of the input documents. Currently, English is the only
#' valid language.
#' @param ClientRequestToken A unique identifier for the request. If you don't set the client request
#' token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the KMS key that Amazon Comprehend uses to encrypt data on the
#' storage volume attached to the ML compute instance(s) that process the
#' analysis job. The VolumeKmsKeyId can be either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig 
#' @param Tags Tags to be associated with the targeted sentiment detection job. A tag
#' is a key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_targeted_sentiment_detection_job
comprehend_start_targeted_sentiment_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, LanguageCode, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartTargetedSentimentDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_targeted_sentiment_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, LanguageCode = LanguageCode, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_targeted_sentiment_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_targeted_sentiment_detection_job <- comprehend_start_targeted_sentiment_detection_job

#' Starts an asynchronous topic detection job
#'
#' @description
#' Starts an asynchronous topic detection job. Use the `DescribeTopicDetectionJob` operation to track the status of a job.
#'
#' See [https://paws-r.github.io/docs/comprehend/start_topics_detection_job.html](https://paws-r.github.io/docs/comprehend/start_topics_detection_job.html) for full documentation.
#'
#' @param InputDataConfig &#91;required&#93; Specifies the format and location of the input data for the job.
#' @param OutputDataConfig &#91;required&#93; Specifies where to send the output files. The output is a compressed
#' archive with two files, `topic-terms.csv` that lists the terms
#' associated with each topic, and `doc-topics.csv` that lists the
#' documents associated with each topic
#' @param DataAccessRoleArn &#91;required&#93; The Amazon Resource Name (ARN) of the AWS Identity and Access Management
#' (IAM) role that grants Amazon Comprehend read access to your input data.
#' For more information, see
#' https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.
#' @param JobName The identifier of the job.
#' @param NumberOfTopics The number of topics to detect.
#' @param ClientRequestToken A unique identifier for the request. If you do not set the client
#' request token, Amazon Comprehend generates one.
#' @param VolumeKmsKeyId ID for the AWS Key Management Service (KMS) key that Amazon Comprehend
#' uses to encrypt data on the storage volume attached to the ML compute
#' instance(s) that process the analysis job. The VolumeKmsKeyId can be
#' either of the following formats:
#' 
#' -   KMS Key ID: `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#' 
#' -   Amazon Resource Name (ARN) of a KMS Key:
#'     `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#' @param VpcConfig Configuration parameters for an optional private Virtual Private Cloud
#' (VPC) containing the resources you are using for your topic detection
#' job. For more information, see [Amazon
#' VPC](https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html).
#' @param Tags Tags to be associated with the topics detection job. A tag is a
#' key-value pair that adds metadata to a resource used by Amazon
#' Comprehend. For example, a tag with "Sales" as the key might be added to
#' a resource to indicate its use by the sales department.
#'
#' @keywords internal
#'
#' @rdname comprehend_start_topics_detection_job
comprehend_start_topics_detection_job <- function(InputDataConfig, OutputDataConfig, DataAccessRoleArn, JobName = NULL, NumberOfTopics = NULL, ClientRequestToken = NULL, VolumeKmsKeyId = NULL, VpcConfig = NULL, Tags = NULL) {
  op <- new_operation(
    name = "StartTopicsDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$start_topics_detection_job_input(InputDataConfig = InputDataConfig, OutputDataConfig = OutputDataConfig, DataAccessRoleArn = DataAccessRoleArn, JobName = JobName, NumberOfTopics = NumberOfTopics, ClientRequestToken = ClientRequestToken, VolumeKmsKeyId = VolumeKmsKeyId, VpcConfig = VpcConfig, Tags = Tags)
  output <- .comprehend$start_topics_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$start_topics_detection_job <- comprehend_start_topics_detection_job

#' Stops a dominant language detection job in progress
#'
#' @description
#' Stops a dominant language detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_dominant_language_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_dominant_language_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the dominant language detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_dominant_language_detection_job
comprehend_stop_dominant_language_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopDominantLanguageDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_dominant_language_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_dominant_language_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_dominant_language_detection_job <- comprehend_stop_dominant_language_detection_job

#' Stops an entities detection job in progress
#'
#' @description
#' Stops an entities detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_entities_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_entities_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the entities detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_entities_detection_job
comprehend_stop_entities_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopEntitiesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_entities_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_entities_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_entities_detection_job <- comprehend_stop_entities_detection_job

#' Stops an events detection job in progress
#'
#' @description
#' Stops an events detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_events_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_events_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the events detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_events_detection_job
comprehend_stop_events_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopEventsDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_events_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_events_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_events_detection_job <- comprehend_stop_events_detection_job

#' Stops a key phrases detection job in progress
#'
#' @description
#' Stops a key phrases detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_key_phrases_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_key_phrases_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the key phrases detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_key_phrases_detection_job
comprehend_stop_key_phrases_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopKeyPhrasesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_key_phrases_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_key_phrases_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_key_phrases_detection_job <- comprehend_stop_key_phrases_detection_job

#' Stops a PII entities detection job in progress
#'
#' @description
#' Stops a PII entities detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_pii_entities_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_pii_entities_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the PII entities detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_pii_entities_detection_job
comprehend_stop_pii_entities_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopPiiEntitiesDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_pii_entities_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_pii_entities_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_pii_entities_detection_job <- comprehend_stop_pii_entities_detection_job

#' Stops a sentiment detection job in progress
#'
#' @description
#' Stops a sentiment detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_sentiment_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_sentiment_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the sentiment detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_sentiment_detection_job
comprehend_stop_sentiment_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopSentimentDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_sentiment_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_sentiment_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_sentiment_detection_job <- comprehend_stop_sentiment_detection_job

#' Stops a targeted sentiment detection job in progress
#'
#' @description
#' Stops a targeted sentiment detection job in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_targeted_sentiment_detection_job.html](https://paws-r.github.io/docs/comprehend/stop_targeted_sentiment_detection_job.html) for full documentation.
#'
#' @param JobId &#91;required&#93; The identifier of the targeted sentiment detection job to stop.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_targeted_sentiment_detection_job
comprehend_stop_targeted_sentiment_detection_job <- function(JobId) {
  op <- new_operation(
    name = "StopTargetedSentimentDetectionJob",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_targeted_sentiment_detection_job_input(JobId = JobId)
  output <- .comprehend$stop_targeted_sentiment_detection_job_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_targeted_sentiment_detection_job <- comprehend_stop_targeted_sentiment_detection_job

#' Stops a document classifier training job while in progress
#'
#' @description
#' Stops a document classifier training job while in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_training_document_classifier.html](https://paws-r.github.io/docs/comprehend/stop_training_document_classifier.html) for full documentation.
#'
#' @param DocumentClassifierArn &#91;required&#93; The Amazon Resource Name (ARN) that identifies the document classifier
#' currently being trained.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_training_document_classifier
comprehend_stop_training_document_classifier <- function(DocumentClassifierArn) {
  op <- new_operation(
    name = "StopTrainingDocumentClassifier",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_training_document_classifier_input(DocumentClassifierArn = DocumentClassifierArn)
  output <- .comprehend$stop_training_document_classifier_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_training_document_classifier <- comprehend_stop_training_document_classifier

#' Stops an entity recognizer training job while in progress
#'
#' @description
#' Stops an entity recognizer training job while in progress.
#'
#' See [https://paws-r.github.io/docs/comprehend/stop_training_entity_recognizer.html](https://paws-r.github.io/docs/comprehend/stop_training_entity_recognizer.html) for full documentation.
#'
#' @param EntityRecognizerArn &#91;required&#93; The Amazon Resource Name (ARN) that identifies the entity recognizer
#' currently being trained.
#'
#' @keywords internal
#'
#' @rdname comprehend_stop_training_entity_recognizer
comprehend_stop_training_entity_recognizer <- function(EntityRecognizerArn) {
  op <- new_operation(
    name = "StopTrainingEntityRecognizer",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$stop_training_entity_recognizer_input(EntityRecognizerArn = EntityRecognizerArn)
  output <- .comprehend$stop_training_entity_recognizer_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$stop_training_entity_recognizer <- comprehend_stop_training_entity_recognizer

#' Associates a specific tag with an Amazon Comprehend resource
#'
#' @description
#' Associates a specific tag with an Amazon Comprehend resource. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.
#'
#' See [https://paws-r.github.io/docs/comprehend/tag_resource.html](https://paws-r.github.io/docs/comprehend/tag_resource.html) for full documentation.
#'
#' @param ResourceArn &#91;required&#93; The Amazon Resource Name (ARN) of the given Amazon Comprehend resource
#' to which you want to associate the tags.
#' @param Tags &#91;required&#93; Tags being associated with a specific Amazon Comprehend resource. There
#' can be a maximum of 50 tags (both existing and pending) associated with
#' a specific resource.
#'
#' @keywords internal
#'
#' @rdname comprehend_tag_resource
comprehend_tag_resource <- function(ResourceArn, Tags) {
  op <- new_operation(
    name = "TagResource",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$tag_resource_input(ResourceArn = ResourceArn, Tags = Tags)
  output <- .comprehend$tag_resource_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$tag_resource <- comprehend_tag_resource

#' Removes a specific tag associated with an Amazon Comprehend resource
#'
#' @description
#' Removes a specific tag associated with an Amazon Comprehend resource.
#'
#' See [https://paws-r.github.io/docs/comprehend/untag_resource.html](https://paws-r.github.io/docs/comprehend/untag_resource.html) for full documentation.
#'
#' @param ResourceArn &#91;required&#93; The Amazon Resource Name (ARN) of the given Amazon Comprehend resource
#' from which you want to remove the tags.
#' @param TagKeys &#91;required&#93; The initial part of a key-value pair that forms a tag being removed from
#' a given resource. For example, a tag with "Sales" as the key might be
#' added to a resource to indicate its use by the sales department. Keys
#' must be unique and cannot be duplicated for a particular resource.
#'
#' @keywords internal
#'
#' @rdname comprehend_untag_resource
comprehend_untag_resource <- function(ResourceArn, TagKeys) {
  op <- new_operation(
    name = "UntagResource",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$untag_resource_input(ResourceArn = ResourceArn, TagKeys = TagKeys)
  output <- .comprehend$untag_resource_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$untag_resource <- comprehend_untag_resource

#' Updates information about the specified endpoint
#'
#' @description
#' Updates information about the specified endpoint. For information about endpoints, see [Managing endpoints](https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html).
#'
#' See [https://paws-r.github.io/docs/comprehend/update_endpoint.html](https://paws-r.github.io/docs/comprehend/update_endpoint.html) for full documentation.
#'
#' @param EndpointArn &#91;required&#93; The Amazon Resource Number (ARN) of the endpoint being updated.
#' @param DesiredModelArn The ARN of the new model to use when updating an existing endpoint.
#' @param DesiredInferenceUnits The desired number of inference units to be used by the model using this
#' endpoint. Each inference unit represents of a throughput of 100
#' characters per second.
#' @param DesiredDataAccessRoleArn Data access role ARN to use in case the new model is encrypted with a
#' customer CMK.
#'
#' @keywords internal
#'
#' @rdname comprehend_update_endpoint
comprehend_update_endpoint <- function(EndpointArn, DesiredModelArn = NULL, DesiredInferenceUnits = NULL, DesiredDataAccessRoleArn = NULL) {
  op <- new_operation(
    name = "UpdateEndpoint",
    http_method = "POST",
    http_path = "/",
    paginator = list()
  )
  input <- .comprehend$update_endpoint_input(EndpointArn = EndpointArn, DesiredModelArn = DesiredModelArn, DesiredInferenceUnits = DesiredInferenceUnits, DesiredDataAccessRoleArn = DesiredDataAccessRoleArn)
  output <- .comprehend$update_endpoint_output()
  config <- get_config()
  svc <- .comprehend$service(config)
  request <- new_request(svc, op, input, output)
  response <- send_request(request)
  return(response)
}
.comprehend$operations$update_endpoint <- comprehend_update_endpoint