R/comprehend_service.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 new_handlers new_service set_config merge_config
NULL

#' Amazon Comprehend
#'
#' @description
#' Amazon Comprehend is an Amazon Web Services service for gaining insight
#' into the content of documents. Use these actions to determine the topics
#' contained in your documents, the topics they discuss, the predominant
#' sentiment expressed in them, the predominant language used, and more.
#'
#' @param
#' config
#' Optional configuration of credentials, endpoint, and/or region.
#' \itemize{
#' \item{\strong{credentials}: \itemize{
#' \item{\strong{creds}: \itemize{
#' \item{\strong{access_key_id}: AWS access key ID}
#' \item{\strong{secret_access_key}: AWS secret access key}
#' \item{\strong{session_token}: AWS temporary session token}
#' }}
#' \item{\strong{profile}: The name of a profile to use. If not given, then the default profile is used.}
#' \item{\strong{anonymous}: Set anonymous credentials.}
#' }}
#' \item{\strong{endpoint}: The complete URL to use for the constructed client.}
#' \item{\strong{region}: The AWS Region used in instantiating the client.}
#' \item{\strong{close_connection}: Immediately close all HTTP connections.}
#' \item{\strong{timeout}: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.}
#' \item{\strong{s3_force_path_style}: Set this to `true` to force the request to use path-style addressing, i.e. `http://s3.amazonaws.com/BUCKET/KEY`.}
#' \item{\strong{sts_regional_endpoint}: Set sts regional endpoint resolver to regional or legacy \url{https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html}}
#' }
#' @param
#' credentials
#' Optional credentials shorthand for the config parameter
#' \itemize{
#' \item{\strong{creds}: \itemize{
#' \item{\strong{access_key_id}: AWS access key ID}
#' \item{\strong{secret_access_key}: AWS secret access key}
#' \item{\strong{session_token}: AWS temporary session token}
#' }}
#' \item{\strong{profile}: The name of a profile to use. If not given, then the default profile is used.}
#' \item{\strong{anonymous}: Set anonymous credentials.}
#' }
#' @param
#' endpoint
#' Optional shorthand for complete URL to use for the constructed client.
#' @param
#' region
#' Optional shorthand for AWS Region used in instantiating the client.
#'
#' @section Service syntax:
#' ```
#' svc <- comprehend(
#'   config = list(
#'     credentials = list(
#'       creds = list(
#'         access_key_id = "string",
#'         secret_access_key = "string",
#'         session_token = "string"
#'       ),
#'       profile = "string",
#'       anonymous = "logical"
#'     ),
#'     endpoint = "string",
#'     region = "string",
#'     close_connection = "logical",
#'     timeout = "numeric",
#'     s3_force_path_style = "logical",
#'     sts_regional_endpoint = "string"
#'   ),
#'   credentials = list(
#'     creds = list(
#'       access_key_id = "string",
#'       secret_access_key = "string",
#'       session_token = "string"
#'     ),
#'     profile = "string",
#'     anonymous = "logical"
#'   ),
#'   endpoint = "string",
#'   region = "string"
#' )
#' ```
#'
#' @examples
#' \dontrun{
#' svc <- comprehend()
#' svc$batch_detect_dominant_language(
#'   Foo = 123
#' )
#' }
#'
#' @section Operations:
#' \tabular{ll}{
#'  \link[=comprehend_batch_detect_dominant_language]{batch_detect_dominant_language} \tab Determines the dominant language of the input text for a batch of documents\cr
#'  \link[=comprehend_batch_detect_entities]{batch_detect_entities} \tab Inspects the text of a batch of documents for named entities and returns information about them\cr
#'  \link[=comprehend_batch_detect_key_phrases]{batch_detect_key_phrases} \tab Detects the key noun phrases found in a batch of documents\cr
#'  \link[=comprehend_batch_detect_sentiment]{batch_detect_sentiment} \tab Inspects a batch of documents and returns an inference of the prevailing sentiment, POSITIVE, NEUTRAL, MIXED, or NEGATIVE, in each one\cr
#'  \link[=comprehend_batch_detect_syntax]{batch_detect_syntax} \tab 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\cr
#'  \link[=comprehend_batch_detect_targeted_sentiment]{batch_detect_targeted_sentiment} \tab Inspects a batch of documents and returns a sentiment analysis for each entity identified in the documents\cr
#'  \link[=comprehend_classify_document]{classify_document} \tab Creates a classification request to analyze a single document in real-time\cr
#'  \link[=comprehend_contains_pii_entities]{contains_pii_entities} \tab 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\cr
#'  \link[=comprehend_create_dataset]{create_dataset} \tab Creates a dataset to upload training or test data for a model associated with a flywheel\cr
#'  \link[=comprehend_create_document_classifier]{create_document_classifier} \tab Creates a new document classifier that you can use to categorize documents\cr
#'  \link[=comprehend_create_endpoint]{create_endpoint} \tab Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see Managing endpoints\cr
#'  \link[=comprehend_create_entity_recognizer]{create_entity_recognizer} \tab Creates an entity recognizer using submitted files\cr
#'  \link[=comprehend_create_flywheel]{create_flywheel} \tab A flywheel is an Amazon Web Services resource that orchestrates the ongoing training of a model for custom classification or custom entity recognition\cr
#'  \link[=comprehend_delete_document_classifier]{delete_document_classifier} \tab Deletes a previously created document classifier\cr
#'  \link[=comprehend_delete_endpoint]{delete_endpoint} \tab Deletes a model-specific endpoint for a previously-trained custom model\cr
#'  \link[=comprehend_delete_entity_recognizer]{delete_entity_recognizer} \tab Deletes an entity recognizer\cr
#'  \link[=comprehend_delete_flywheel]{delete_flywheel} \tab Deletes a flywheel\cr
#'  \link[=comprehend_delete_resource_policy]{delete_resource_policy} \tab Deletes a resource-based policy that is attached to a custom model\cr
#'  \link[=comprehend_describe_dataset]{describe_dataset} \tab Returns information about the dataset that you specify\cr
#'  \link[=comprehend_describe_document_classification_job]{describe_document_classification_job} \tab Gets the properties associated with a document classification job\cr
#'  \link[=comprehend_describe_document_classifier]{describe_document_classifier} \tab Gets the properties associated with a document classifier\cr
#'  \link[=comprehend_describe_dominant_language_detection_job]{describe_dominant_language_detection_job} \tab Gets the properties associated with a dominant language detection job\cr
#'  \link[=comprehend_describe_endpoint]{describe_endpoint} \tab Gets the properties associated with a specific endpoint\cr
#'  \link[=comprehend_describe_entities_detection_job]{describe_entities_detection_job} \tab Gets the properties associated with an entities detection job\cr
#'  \link[=comprehend_describe_entity_recognizer]{describe_entity_recognizer} \tab Provides details about an entity recognizer including status, S3 buckets containing training data, recognizer metadata, metrics, and so on\cr
#'  \link[=comprehend_describe_events_detection_job]{describe_events_detection_job} \tab Gets the status and details of an events detection job\cr
#'  \link[=comprehend_describe_flywheel]{describe_flywheel} \tab Provides configuration information about the flywheel\cr
#'  \link[=comprehend_describe_flywheel_iteration]{describe_flywheel_iteration} \tab Retrieve the configuration properties of a flywheel iteration\cr
#'  \link[=comprehend_describe_key_phrases_detection_job]{describe_key_phrases_detection_job} \tab Gets the properties associated with a key phrases detection job\cr
#'  \link[=comprehend_describe_pii_entities_detection_job]{describe_pii_entities_detection_job} \tab Gets the properties associated with a PII entities detection job\cr
#'  \link[=comprehend_describe_resource_policy]{describe_resource_policy} \tab Gets the details of a resource-based policy that is attached to a custom model, including the JSON body of the policy\cr
#'  \link[=comprehend_describe_sentiment_detection_job]{describe_sentiment_detection_job} \tab Gets the properties associated with a sentiment detection job\cr
#'  \link[=comprehend_describe_targeted_sentiment_detection_job]{describe_targeted_sentiment_detection_job} \tab Gets the properties associated with a targeted sentiment detection job\cr
#'  \link[=comprehend_describe_topics_detection_job]{describe_topics_detection_job} \tab Gets the properties associated with a topic detection job\cr
#'  \link[=comprehend_detect_dominant_language]{detect_dominant_language} \tab Determines the dominant language of the input text\cr
#'  \link[=comprehend_detect_entities]{detect_entities} \tab Detects named entities in input text when you use the pre-trained model\cr
#'  \link[=comprehend_detect_key_phrases]{detect_key_phrases} \tab Detects the key noun phrases found in the text\cr
#'  \link[=comprehend_detect_pii_entities]{detect_pii_entities} \tab Inspects the input text for entities that contain personally identifiable information (PII) and returns information about them\cr
#'  \link[=comprehend_detect_sentiment]{detect_sentiment} \tab Inspects text and returns an inference of the prevailing sentiment (POSITIVE, NEUTRAL, MIXED, or NEGATIVE)\cr
#'  \link[=comprehend_detect_syntax]{detect_syntax} \tab Inspects text for syntax and the part of speech of words in the document\cr
#'  \link[=comprehend_detect_targeted_sentiment]{detect_targeted_sentiment} \tab Inspects the input text and returns a sentiment analysis for each entity identified in the text\cr
#'  \link[=comprehend_detect_toxic_content]{detect_toxic_content} \tab Performs toxicity analysis on the list of text strings that you provide as input\cr
#'  \link[=comprehend_import_model]{import_model} \tab Creates a new custom model that replicates a source custom model that you import\cr
#'  \link[=comprehend_list_datasets]{list_datasets} \tab List the datasets that you have configured in this Region\cr
#'  \link[=comprehend_list_document_classification_jobs]{list_document_classification_jobs} \tab Gets a list of the documentation classification jobs that you have submitted\cr
#'  \link[=comprehend_list_document_classifiers]{list_document_classifiers} \tab Gets a list of the document classifiers that you have created\cr
#'  \link[=comprehend_list_document_classifier_summaries]{list_document_classifier_summaries} \tab Gets a list of summaries of the document classifiers that you have created\cr
#'  \link[=comprehend_list_dominant_language_detection_jobs]{list_dominant_language_detection_jobs} \tab Gets a list of the dominant language detection jobs that you have submitted\cr
#'  \link[=comprehend_list_endpoints]{list_endpoints} \tab Gets a list of all existing endpoints that you've created\cr
#'  \link[=comprehend_list_entities_detection_jobs]{list_entities_detection_jobs} \tab Gets a list of the entity detection jobs that you have submitted\cr
#'  \link[=comprehend_list_entity_recognizers]{list_entity_recognizers} \tab Gets a list of the properties of all entity recognizers that you created, including recognizers currently in training\cr
#'  \link[=comprehend_list_entity_recognizer_summaries]{list_entity_recognizer_summaries} \tab Gets a list of summaries for the entity recognizers that you have created\cr
#'  \link[=comprehend_list_events_detection_jobs]{list_events_detection_jobs} \tab Gets a list of the events detection jobs that you have submitted\cr
#'  \link[=comprehend_list_flywheel_iteration_history]{list_flywheel_iteration_history} \tab Information about the history of a flywheel iteration\cr
#'  \link[=comprehend_list_flywheels]{list_flywheels} \tab Gets a list of the flywheels that you have created\cr
#'  \link[=comprehend_list_key_phrases_detection_jobs]{list_key_phrases_detection_jobs} \tab Get a list of key phrase detection jobs that you have submitted\cr
#'  \link[=comprehend_list_pii_entities_detection_jobs]{list_pii_entities_detection_jobs} \tab Gets a list of the PII entity detection jobs that you have submitted\cr
#'  \link[=comprehend_list_sentiment_detection_jobs]{list_sentiment_detection_jobs} \tab Gets a list of sentiment detection jobs that you have submitted\cr
#'  \link[=comprehend_list_tags_for_resource]{list_tags_for_resource} \tab Lists all tags associated with a given Amazon Comprehend resource\cr
#'  \link[=comprehend_list_targeted_sentiment_detection_jobs]{list_targeted_sentiment_detection_jobs} \tab Gets a list of targeted sentiment detection jobs that you have submitted\cr
#'  \link[=comprehend_list_topics_detection_jobs]{list_topics_detection_jobs} \tab Gets a list of the topic detection jobs that you have submitted\cr
#'  \link[=comprehend_put_resource_policy]{put_resource_policy} \tab Attaches a resource-based policy to a custom model\cr
#'  \link[=comprehend_start_document_classification_job]{start_document_classification_job} \tab Starts an asynchronous document classification job using a custom classification model\cr
#'  \link[=comprehend_start_dominant_language_detection_job]{start_dominant_language_detection_job} \tab Starts an asynchronous dominant language detection job for a collection of documents\cr
#'  \link[=comprehend_start_entities_detection_job]{start_entities_detection_job} \tab Starts an asynchronous entity detection job for a collection of documents\cr
#'  \link[=comprehend_start_events_detection_job]{start_events_detection_job} \tab Starts an asynchronous event detection job for a collection of documents\cr
#'  \link[=comprehend_start_flywheel_iteration]{start_flywheel_iteration} \tab Start the flywheel iteration\cr
#'  \link[=comprehend_start_key_phrases_detection_job]{start_key_phrases_detection_job} \tab Starts an asynchronous key phrase detection job for a collection of documents\cr
#'  \link[=comprehend_start_pii_entities_detection_job]{start_pii_entities_detection_job} \tab Starts an asynchronous PII entity detection job for a collection of documents\cr
#'  \link[=comprehend_start_sentiment_detection_job]{start_sentiment_detection_job} \tab Starts an asynchronous sentiment detection job for a collection of documents\cr
#'  \link[=comprehend_start_targeted_sentiment_detection_job]{start_targeted_sentiment_detection_job} \tab Starts an asynchronous targeted sentiment detection job for a collection of documents\cr
#'  \link[=comprehend_start_topics_detection_job]{start_topics_detection_job} \tab Starts an asynchronous topic detection job\cr
#'  \link[=comprehend_stop_dominant_language_detection_job]{stop_dominant_language_detection_job} \tab Stops a dominant language detection job in progress\cr
#'  \link[=comprehend_stop_entities_detection_job]{stop_entities_detection_job} \tab Stops an entities detection job in progress\cr
#'  \link[=comprehend_stop_events_detection_job]{stop_events_detection_job} \tab Stops an events detection job in progress\cr
#'  \link[=comprehend_stop_key_phrases_detection_job]{stop_key_phrases_detection_job} \tab Stops a key phrases detection job in progress\cr
#'  \link[=comprehend_stop_pii_entities_detection_job]{stop_pii_entities_detection_job} \tab Stops a PII entities detection job in progress\cr
#'  \link[=comprehend_stop_sentiment_detection_job]{stop_sentiment_detection_job} \tab Stops a sentiment detection job in progress\cr
#'  \link[=comprehend_stop_targeted_sentiment_detection_job]{stop_targeted_sentiment_detection_job} \tab Stops a targeted sentiment detection job in progress\cr
#'  \link[=comprehend_stop_training_document_classifier]{stop_training_document_classifier} \tab Stops a document classifier training job while in progress\cr
#'  \link[=comprehend_stop_training_entity_recognizer]{stop_training_entity_recognizer} \tab Stops an entity recognizer training job while in progress\cr
#'  \link[=comprehend_tag_resource]{tag_resource} \tab Associates a specific tag with an Amazon Comprehend resource\cr
#'  \link[=comprehend_untag_resource]{untag_resource} \tab Removes a specific tag associated with an Amazon Comprehend resource\cr
#'  \link[=comprehend_update_endpoint]{update_endpoint} \tab Updates information about the specified endpoint\cr
#'  \link[=comprehend_update_flywheel]{update_flywheel} \tab Update the configuration information for an existing flywheel
#' }
#'
#' @return
#' A client for the service. You can call the service's operations using
#' syntax like `svc$operation(...)`, where `svc` is the name you've assigned
#' to the client. The available operations are listed in the
#' Operations section.
#'
#' @rdname comprehend
#' @export
comprehend <- function(config = list(), credentials = list(), endpoint = NULL, region = NULL) {
  config <- merge_config(
    config,
    list(
      credentials = credentials,
      endpoint = endpoint,
      region = region
    )
  )
  svc <- .comprehend$operations
  svc <- set_config(svc, config)
  return(svc)
}

# Private API objects: metadata, handlers, interfaces, etc.
.comprehend <- list()

.comprehend$operations <- list()

.comprehend$metadata <- list(
  service_name = "comprehend",
  endpoints = list("*" = list(endpoint = "comprehend.{region}.amazonaws.com", global = FALSE), "cn-*" = list(endpoint = "comprehend.{region}.amazonaws.com.cn", global = FALSE), "eu-isoe-*" = list(endpoint = "comprehend.{region}.cloud.adc-e.uk", global = FALSE), "us-iso-*" = list(endpoint = "comprehend.{region}.c2s.ic.gov", global = FALSE), "us-isob-*" = list(endpoint = "comprehend.{region}.sc2s.sgov.gov", global = FALSE), "us-isof-*" = list(endpoint = "comprehend.{region}.csp.hci.ic.gov", global = FALSE)),
  service_id = "Comprehend",
  api_version = "2017-11-27",
  signing_name = "comprehend",
  json_version = "1.1",
  target_prefix = "Comprehend_20171127"
)

.comprehend$service <- function(config = list(), op = NULL) {
  handlers <- new_handlers("jsonrpc", "v4")
  new_service(.comprehend$metadata, handlers, config, op)
}