Request Syntax Request Parameters Response Syntax Response Elements Errors See Also

ClassifyDocument

Creates a classification request to analyze a single document in real-time. ClassifyDocument supports the following model types:

Custom classifier - a custom model that you have created and trained. For input, you can provide plain text, a single-page document (PDF, Word, or image), or Amazon Textract API output. For more information, see Custom classification in the Amazon Comprehend Developer Guide.
Prompt safety classifier - Amazon Comprehend provides a pre-trained model for classifying input prompts for generative AI applications. For input, you provide English plain text input. For prompt safety classification, the response includes only the Classes field. For more information about prompt safety classifiers, see Prompt safety classification in the Amazon Comprehend Developer Guide.

If the system detects errors while processing a page in the input document, the API response includes an Errors field that describes the errors.

If the system detects a document-level error in your input document, the API returns an InvalidRequestException error response. For details about this exception, see Errors in semi-structured documents in the Comprehend Developer Guide.

Request Syntax


{
   "Bytes": blob,
   "DocumentReaderConfig": { 
      "DocumentReadAction": "string",
      "DocumentReadMode": "string",
      "FeatureTypes": [ "string" ]
   },
   "EndpointArn": "string",
   "Text": "string"
}

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.

Bytes

Use the Bytes parameter to input a text, PDF, Word or image file.

When you classify a document using a custom model, you can also use the Bytes parameter to input an Amazon Textract DetectDocumentText or AnalyzeDocument output file.

To classify a document using the prompt safety classifier, use the Text parameter for input.

Provide the input document as a sequence of base64-encoded bytes. If your code uses an AWS SDK to classify documents, the SDK may encode the document file bytes for you.

The maximum length of this field depends on the input document type. For details, see Inputs for real-time custom analysis in the Comprehend Developer Guide.

If you use the Bytes parameter, do not use the Text parameter.

Type: Base64-encoded binary data object

Length Constraints: Minimum length of 1.

Required: No

DocumentReaderConfig

Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.

Type: DocumentReaderConfig object

Required: No

EndpointArn

The Amazon Resource Number (ARN) of the endpoint.

For prompt safety classification, Amazon Comprehend provides the endpoint ARN. For more information about prompt safety classifiers, see Prompt safety classification in the Amazon Comprehend Developer Guide

For custom classification, you create an endpoint for your custom model. For more information, see Using Amazon Comprehend endpoints.

Type: String

Length Constraints: Maximum length of 256.

Pattern: arn:aws(-[^:]+)?:comprehend:[a-zA-Z0-9-]*:([0-9]{12}|aws):document-classifier-endpoint/[a-zA-Z0-9](-*[a-zA-Z0-9])*

Required: Yes

Text

The document text to be analyzed. If you enter text using this parameter, do not use the Bytes parameter.

Type: String

Length Constraints: Minimum length of 1.

Required: No

Response Syntax


{
   "Classes": [ 
      { 
         "Name": "string",
         "Page": number,
         "Score": number
      }
   ],
   "DocumentMetadata": { 
      "ExtractedCharacters": [ 
         { 
            "Count": number,
            "Page": number
         }
      ],
      "Pages": number
   },
   "DocumentType": [ 
      { 
         "Page": number,
         "Type": "string"
      }
   ],
   "Errors": [ 
      { 
         "ErrorCode": "string",
         "ErrorMessage": "string",
         "Page": number
      }
   ],
   "Labels": [ 
      { 
         "Name": "string",
         "Page": number,
         "Score": number
      }
   ],
   "Warnings": [ 
      { 
         "Page": number,
         "WarnCode": "string",
         "WarnMessage": "string"
      }
   ]
}

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.

Classes

The classes used by the document being analyzed. These are used for models trained in multi-class mode. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

For prompt safety classification, the response includes only two classes (SAFE_PROMPT and UNSAFE_PROMPT), along with a confidence score for each class. The value range of the score is zero to one, where one is the highest confidence.

Type: Array of DocumentClass objects

DocumentMetadata

Extraction information about the document. This field is present in the response only if your request includes the Byte parameter.

Type: DocumentMetadata object

DocumentType

The document type for each page in the input document. This field is present in the response only if your request includes the Byte parameter.

Type: Array of DocumentTypeListItem objects

Errors

Page-level errors that the system detected while processing the input document. The field is empty if the system encountered no errors.

Type: Array of ErrorsListItem objects

Labels

The labels used in the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Type: Array of DocumentLabel objects

Warnings

Warnings detected while processing the input document. The response includes a warning if there is a mismatch between the input document type and the model type associated with the endpoint that you specified. The response can also include warnings for individual pages that have a mismatch.

The field is empty if the system generated no warnings.

Type: Array of WarningsListItem objects

Errors

For information about the errors that are common to all actions, see Common Errors.

InternalServerException

An internal server error occurred. Retry your request.

HTTP Status Code: 500

InvalidRequestException

The request is invalid.

HTTP Status Code: 400

ResourceUnavailableException

The specified resource is not available. Check the resource and try your request again.

HTTP Status Code: 400

TextSizeLimitExceededException

The size of the input text exceeds the limit. Use a smaller document.

HTTP Status Code: 400