Struct DetectEntitiesInput

#[non_exhaustive]
pub struct DetectEntitiesInput {
    pub text: Option<String>,
    pub language_code: Option<LanguageCode>,
    pub endpoint_arn: Option<String>,
    pub bytes: Option<Blob>,
    pub document_reader_config: Option<DocumentReaderConfig>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

text: Option<String>

A UTF-8 text string. The maximum string size is 100 KB. If you enter text using this parameter, do not use the Bytes parameter.

language_code: Option<LanguageCode>

The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. 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.

All input documents must be in the same language.

endpoint_arn: Option<String>

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.

bytes: Option<Blob>

This field applies only when you use a custom entity recognition model that was trained with PDF annotations. For other cases, enter your text input in the Text field.

Use the Bytes parameter to input a text, PDF, Word or image file. Using a plain-text file in the Bytes parameter is equivelent to using the Text parameter (the Entities field in the response is identical).

You can also use the Bytes parameter to input an Amazon Textract DetectDocumentText or AnalyzeDocument output file.

Provide the input document as a sequence of base64-encoded bytes. If your code uses an Amazon Web Services SDK to detect entities, 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.

document_reader_config: Option<DocumentReaderConfig>

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

Implementations

impl DetectEntitiesInput

pub fn text(&self) -> Option<&str>

A UTF-8 text string. The maximum string size is 100 KB. If you enter text using this parameter, do not use the Bytes parameter.

pub fn language_code(&self) -> Option<&LanguageCode>

The language of the input documents. You can specify any of the primary languages supported by Amazon Comprehend. 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.

All input documents must be in the same language.

pub fn endpoint_arn(&self) -> Option<&str>

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.

pub fn bytes(&self) -> Option<&Blob>

This field applies only when you use a custom entity recognition model that was trained with PDF annotations. For other cases, enter your text input in the Text field.

Use the Bytes parameter to input a text, PDF, Word or image file. Using a plain-text file in the Bytes parameter is equivelent to using the Text parameter (the Entities field in the response is identical).

You can also use the Bytes parameter to input an Amazon Textract DetectDocumentText or AnalyzeDocument output file.

Provide the input document as a sequence of base64-encoded bytes. If your code uses an Amazon Web Services SDK to detect entities, 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.

pub fn document_reader_config(&self) -> Option<&DocumentReaderConfig>

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

impl DetectEntitiesInput

pub fn builder() -> DetectEntitiesInputBuilder

Creates a new builder-style object to manufacture DetectEntitiesInput.

Trait Implementations

impl Clone for DetectEntitiesInput

fn clone(&self) -> DetectEntitiesInput

Returns a duplicate of the value.

const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DetectEntitiesInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for DetectEntitiesInput

fn eq(&self, other: &DetectEntitiesInput) -> bool

Tests for self and other values to be equal, and is used by ==.

const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for DetectEntitiesInput