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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::detect_entities::_detect_entities_output::DetectEntitiesOutputBuilder;

pub use crate::operation::detect_entities::_detect_entities_input::DetectEntitiesInputBuilder;

/// Fluent builder constructing a request to `DetectEntities`.
///
/// <p>Detects named entities in input text when you use the pre-trained model. Detects custom entities if you have a custom entity recognition model. </p>
/// <p> When detecting named entities using the pre-trained model, use plain text as the input. For more information about named entities, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/how-entities.html">Entities</a> in the Comprehend Developer Guide.</p>
/// <p>When you use a custom entity recognition model, you can input plain text or you can upload a single-page input document (text, PDF, Word, or image). </p>
/// <p>If the system detects errors while processing a page in the input document, the API response includes an entry in <code>Errors</code> for each error. </p>
/// <p>If the system detects a document-level error in your input document, the API returns an <code>InvalidRequestException</code> error response. For details about this exception, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/idp-inputs-sync-err.html"> Errors in semi-structured documents</a> in the Comprehend Developer Guide. </p>
#[derive(std::clone::Clone, std::fmt::Debug)]
pub struct DetectEntitiesFluentBuilder {
    handle: std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::detect_entities::builders::DetectEntitiesInputBuilder,
}
impl DetectEntitiesFluentBuilder {
    /// Creates a new `DetectEntities`.
    pub(crate) fn new(handle: std::sync::Arc<crate::client::Handle>) -> Self {
        Self {
            handle,
            inner: Default::default(),
        }
    }
    /// Consume this builder, creating a customizable operation that can be modified before being
    /// sent. The operation's inner [http::Request] can be modified as well.
    pub async fn customize(
        self,
    ) -> std::result::Result<
        crate::client::customize::CustomizableOperation<
            crate::operation::detect_entities::DetectEntities,
            aws_http::retry::AwsResponseRetryClassifier,
        >,
        aws_smithy_http::result::SdkError<crate::operation::detect_entities::DetectEntitiesError>,
    > {
        let handle = self.handle.clone();
        let operation = self
            .inner
            .build()
            .map_err(aws_smithy_http::result::SdkError::construction_failure)?
            .make_operation(&handle.conf)
            .await
            .map_err(aws_smithy_http::result::SdkError::construction_failure)?;
        Ok(crate::client::customize::CustomizableOperation { handle, operation })
    }

    /// Sends the request and returns the response.
    ///
    /// If an error occurs, an `SdkError` will be returned with additional details that
    /// can be matched against.
    ///
    /// By default, any retryable failures will be retried twice. Retry behavior
    /// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
    /// set when configuring the client.
    pub async fn send(
        self,
    ) -> std::result::Result<
        crate::operation::detect_entities::DetectEntitiesOutput,
        aws_smithy_http::result::SdkError<crate::operation::detect_entities::DetectEntitiesError>,
    > {
        let op = self
            .inner
            .build()
            .map_err(aws_smithy_http::result::SdkError::construction_failure)?
            .make_operation(&self.handle.conf)
            .await
            .map_err(aws_smithy_http::result::SdkError::construction_failure)?;
        self.handle.client.call(op).await
    }
    /// <p>A UTF-8 text string. The maximum string size is 100 KB. If you enter text using this parameter, do not use the <code>Bytes</code> parameter.</p>
    pub fn text(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.text(input.into());
        self
    }
    /// <p>A UTF-8 text string. The maximum string size is 100 KB. If you enter text using this parameter, do not use the <code>Bytes</code> parameter.</p>
    pub fn set_text(mut self, input: std::option::Option<std::string::String>) -> Self {
        self.inner = self.inner.set_text(input);
        self
    }
    /// <p>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.</p>
    /// <p>All input documents must be in the same language.</p>
    pub fn language_code(mut self, input: crate::types::LanguageCode) -> Self {
        self.inner = self.inner.language_code(input);
        self
    }
    /// <p>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.</p>
    /// <p>All input documents must be in the same language.</p>
    pub fn set_language_code(
        mut self,
        input: std::option::Option<crate::types::LanguageCode>,
    ) -> Self {
        self.inner = self.inner.set_language_code(input);
        self
    }
    /// <p>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.</p>
    /// <p>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.</p>
    /// <p>For information about endpoints, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html">Managing endpoints</a>.</p>
    pub fn endpoint_arn(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.endpoint_arn(input.into());
        self
    }
    /// <p>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.</p>
    /// <p>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.</p>
    /// <p>For information about endpoints, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/manage-endpoints.html">Managing endpoints</a>.</p>
    pub fn set_endpoint_arn(mut self, input: std::option::Option<std::string::String>) -> Self {
        self.inner = self.inner.set_endpoint_arn(input);
        self
    }
    /// <p>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 <code>Text</code> field.</p>
    /// <p> Use the <code>Bytes</code> parameter to input a text, PDF, Word or image file. Using a plain-text file in the <code>Bytes</code> parameter is equivelent to using the <code>Text</code> parameter (the <code>Entities</code> field in the response is identical).</p>
    /// <p>You can also use the <code>Bytes</code> parameter to input an Amazon Textract <code>DetectDocumentText</code> or <code>AnalyzeDocument</code> output file.</p>
    /// <p>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. </p>
    /// <p>The maximum length of this field depends on the input document type. For details, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/idp-inputs-sync.html"> Inputs for real-time custom analysis</a> in the Comprehend Developer Guide. </p>
    /// <p>If you use the <code>Bytes</code> parameter, do not use the <code>Text</code> parameter.</p>
    pub fn bytes(mut self, input: aws_smithy_types::Blob) -> Self {
        self.inner = self.inner.bytes(input);
        self
    }
    /// <p>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 <code>Text</code> field.</p>
    /// <p> Use the <code>Bytes</code> parameter to input a text, PDF, Word or image file. Using a plain-text file in the <code>Bytes</code> parameter is equivelent to using the <code>Text</code> parameter (the <code>Entities</code> field in the response is identical).</p>
    /// <p>You can also use the <code>Bytes</code> parameter to input an Amazon Textract <code>DetectDocumentText</code> or <code>AnalyzeDocument</code> output file.</p>
    /// <p>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. </p>
    /// <p>The maximum length of this field depends on the input document type. For details, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/idp-inputs-sync.html"> Inputs for real-time custom analysis</a> in the Comprehend Developer Guide. </p>
    /// <p>If you use the <code>Bytes</code> parameter, do not use the <code>Text</code> parameter.</p>
    pub fn set_bytes(mut self, input: std::option::Option<aws_smithy_types::Blob>) -> Self {
        self.inner = self.inner.set_bytes(input);
        self
    }
    /// <p>Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.</p>
    pub fn document_reader_config(mut self, input: crate::types::DocumentReaderConfig) -> Self {
        self.inner = self.inner.document_reader_config(input);
        self
    }
    /// <p>Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.</p>
    pub fn set_document_reader_config(
        mut self,
        input: std::option::Option<crate::types::DocumentReaderConfig>,
    ) -> Self {
        self.inner = self.inner.set_document_reader_config(input);
        self
    }
}