// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_entity_recognizer::_create_entity_recognizer_output::CreateEntityRecognizerOutputBuilder;

pub use crate::operation::create_entity_recognizer::_create_entity_recognizer_input::CreateEntityRecognizerInputBuilder;

/// Fluent builder constructing a request to `CreateEntityRecognizer`.
///
/// <p>Creates an entity recognizer using submitted files. After your <code>CreateEntityRecognizer</code> request is submitted, you can check job status using the <code>DescribeEntityRecognizer</code> API. </p>
#[derive(std::clone::Clone, std::fmt::Debug)]
pub struct CreateEntityRecognizerFluentBuilder {
    handle: std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_entity_recognizer::builders::CreateEntityRecognizerInputBuilder,
}
impl CreateEntityRecognizerFluentBuilder {
    /// Creates a new `CreateEntityRecognizer`.
    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::create_entity_recognizer::CreateEntityRecognizer,
            aws_http::retry::AwsResponseRetryClassifier,
        >,
        aws_smithy_http::result::SdkError<
            crate::operation::create_entity_recognizer::CreateEntityRecognizerError,
        >,
    > {
        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::create_entity_recognizer::CreateEntityRecognizerOutput,
        aws_smithy_http::result::SdkError<
            crate::operation::create_entity_recognizer::CreateEntityRecognizerError,
        >,
    > {
        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>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.</p>
    pub fn recognizer_name(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.recognizer_name(input.into());
        self
    }
    /// <p>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.</p>
    pub fn set_recognizer_name(mut self, input: std::option::Option<std::string::String>) -> Self {
        self.inner = self.inner.set_recognizer_name(input);
        self
    }
    /// <p>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/Region.</p>
    pub fn version_name(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.version_name(input.into());
        self
    }
    /// <p>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/Region.</p>
    pub fn set_version_name(mut self, input: std::option::Option<std::string::String>) -> Self {
        self.inner = self.inner.set_version_name(input);
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.</p>
    pub fn data_access_role_arn(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.data_access_role_arn(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.</p>
    pub fn set_data_access_role_arn(
        mut self,
        input: std::option::Option<std::string::String>,
    ) -> Self {
        self.inner = self.inner.set_data_access_role_arn(input);
        self
    }
    /// Appends an item to `Tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>Tags to associate with the entity recognizer. 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. </p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>Tags to associate with the entity recognizer. 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. </p>
    pub fn set_tags(
        mut self,
        input: std::option::Option<std::vec::Vec<crate::types::Tag>>,
    ) -> Self {
        self.inner = self.inner.set_tags(input);
        self
    }
    /// <p>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. </p>
    pub fn input_data_config(
        mut self,
        input: crate::types::EntityRecognizerInputDataConfig,
    ) -> Self {
        self.inner = self.inner.input_data_config(input);
        self
    }
    /// <p>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. </p>
    pub fn set_input_data_config(
        mut self,
        input: std::option::Option<crate::types::EntityRecognizerInputDataConfig>,
    ) -> Self {
        self.inner = self.inner.set_input_data_config(input);
        self
    }
    /// <p> A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.</p>
    pub fn client_request_token(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.client_request_token(input.into());
        self
    }
    /// <p> A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.</p>
    pub fn set_client_request_token(
        mut self,
        input: std::option::Option<std::string::String>,
    ) -> Self {
        self.inner = self.inner.set_client_request_token(input);
        self
    }
    /// <p> You can specify any of the following languages: English ("en"), Spanish ("es"), French ("fr"), Italian ("it"), German ("de"), or Portuguese ("pt"). If you plan to use this entity recognizer with PDF, Word, or image input files, you must specify English as the language. All training 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> You can specify any of the following languages: English ("en"), Spanish ("es"), French ("fr"), Italian ("it"), German ("de"), or Portuguese ("pt"). If you plan to use this entity recognizer with PDF, Word, or image input files, you must specify English as the language. All training 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>ID for the Amazon Web Services 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:</p>
    /// <ul>
    /// <li> <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// <li> <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// </ul>
    pub fn volume_kms_key_id(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.volume_kms_key_id(input.into());
        self
    }
    /// <p>ID for the Amazon Web Services 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:</p>
    /// <ul>
    /// <li> <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// <li> <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// </ul>
    pub fn set_volume_kms_key_id(
        mut self,
        input: std::option::Option<std::string::String>,
    ) -> Self {
        self.inner = self.inner.set_volume_kms_key_id(input);
        self
    }
    /// <p>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 <a href="https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html">Amazon VPC</a>. </p>
    pub fn vpc_config(mut self, input: crate::types::VpcConfig) -> Self {
        self.inner = self.inner.vpc_config(input);
        self
    }
    /// <p>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 <a href="https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html">Amazon VPC</a>. </p>
    pub fn set_vpc_config(mut self, input: std::option::Option<crate::types::VpcConfig>) -> Self {
        self.inner = self.inner.set_vpc_config(input);
        self
    }
    /// <p>ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li> <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// <li> <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// </ul>
    pub fn model_kms_key_id(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.model_kms_key_id(input.into());
        self
    }
    /// <p>ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li> <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// <li> <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code> </p> </li>
    /// </ul>
    pub fn set_model_kms_key_id(mut self, input: std::option::Option<std::string::String>) -> Self {
        self.inner = self.inner.set_model_kms_key_id(input);
        self
    }
    /// <p>The JSON resource-based policy to attach to your custom entity recognizer model. You can use this policy to allow another Amazon Web Services account to import your custom model.</p>
    /// <p>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:</p>
    /// <p> <code>"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"</code> </p>
    /// <p>To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:</p>
    /// <p> <code>'{"attribute": "value", "attribute": ["value"]}'</code> </p>
    pub fn model_policy(mut self, input: impl Into<std::string::String>) -> Self {
        self.inner = self.inner.model_policy(input.into());
        self
    }
    /// <p>The JSON resource-based policy to attach to your custom entity recognizer model. You can use this policy to allow another Amazon Web Services account to import your custom model.</p>
    /// <p>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:</p>
    /// <p> <code>"{\"attribute\": \"value\", \"attribute\": [\"value\"]}"</code> </p>
    /// <p>To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:</p>
    /// <p> <code>'{"attribute": "value", "attribute": ["value"]}'</code> </p>
    pub fn set_model_policy(mut self, input: std::option::Option<std::string::String>) -> Self {
        self.inner = self.inner.set_model_policy(input);
        self
    }
}