api_op_CreateLanguageModel.go

// Code generated by smithy-go-codegen DO NOT EDIT.

package transcribe

import (
	"context"
	"fmt"
	awsmiddleware "github.com/aws/aws-sdk-go-v2/aws/middleware"
	"github.com/aws/aws-sdk-go-v2/service/transcribe/types"
	"github.com/aws/smithy-go/middleware"
	smithyhttp "github.com/aws/smithy-go/transport/http"
)

// Creates a new custom language model.
//
// When creating a new custom language model, you must specify:
//
//   - If you want a Wideband (audio sample rates over 16,000 Hz) or Narrowband
//     (audio sample rates under 16,000 Hz) base model
//
//   - The location of your training and tuning files (this must be an Amazon S3
//     URI)
//
//   - The language of your model
//
//   - A unique name for your model
func (c *Client) CreateLanguageModel(ctx context.Context, params *CreateLanguageModelInput, optFns ...func(*Options)) (*CreateLanguageModelOutput, error) {
	if params == nil {
		params = &CreateLanguageModelInput{}
	}

	result, metadata, err := c.invokeOperation(ctx, "CreateLanguageModel", params, optFns, c.addOperationCreateLanguageModelMiddlewares)
	if err != nil {
		return nil, err
	}

	out := result.(*CreateLanguageModelOutput)
	out.ResultMetadata = metadata
	return out, nil
}

type CreateLanguageModelInput struct {

	// The Amazon Transcribe standard language model, or base model, used to create
	// your custom language model. Amazon Transcribe offers two options for base
	// models: Wideband and Narrowband.
	//
	// If the audio you want to transcribe has a sample rate of 16,000 Hz or greater,
	// choose WideBand . To transcribe audio with a sample rate less than 16,000 Hz,
	// choose NarrowBand .
	//
	// This member is required.
	BaseModelName types.BaseModelName

	// Contains the Amazon S3 location of the training data you want to use to create
	// a new custom language model, and permissions to access this location.
	//
	// When using InputDataConfig , you must include these sub-parameters: S3Uri ,
	// which is the Amazon S3 location of your training data, and DataAccessRoleArn ,
	// which is the Amazon Resource Name (ARN) of the role that has permission to
	// access your specified Amazon S3 location. You can optionally include
	// TuningDataS3Uri , which is the Amazon S3 location of your tuning data. If you
	// specify different Amazon S3 locations for training and tuning data, the ARN you
	// use must have permissions to access both locations.
	//
	// This member is required.
	InputDataConfig *types.InputDataConfig

	// The language code that represents the language of your model. Each custom
	// language model must contain terms in only one language, and the language you
	// select for your custom language model must match the language of your training
	// and tuning data.
	//
	// For a list of supported languages and their associated language codes, refer to
	// the [Supported languages]table. Note that US English ( en-US ) is the only language supported with
	// Amazon Transcribe Medical.
	//
	// A custom language model can only be used to transcribe files in the same
	// language as the model. For example, if you create a custom language model using
	// US English ( en-US ), you can only apply this model to files that contain
	// English audio.
	//
	// [Supported languages]: https://docs.aws.amazon.com/transcribe/latest/dg/supported-languages.html
	//
	// This member is required.
	LanguageCode types.CLMLanguageCode

	// A unique name, chosen by you, for your custom language model.
	//
	// This name is case sensitive, cannot contain spaces, and must be unique within
	// an Amazon Web Services account. If you try to create a new custom language model
	// with the same name as an existing custom language model, you get a
	// ConflictException error.
	//
	// This member is required.
	ModelName *string

	// Adds one or more custom tags, each in the form of a key:value pair, to a new
	// custom language model at the time you create this new model.
	//
	// To learn more about using tags with Amazon Transcribe, refer to [Tagging resources].
	//
	// [Tagging resources]: https://docs.aws.amazon.com/transcribe/latest/dg/tagging.html
	Tags []types.Tag

	noSmithyDocumentSerde
}

type CreateLanguageModelOutput struct {

	// The Amazon Transcribe standard language model, or base model, you specified
	// when creating your custom language model.
	BaseModelName types.BaseModelName

	// Lists your data access role ARN (Amazon Resource Name) and the Amazon S3
	// locations you provided for your training ( S3Uri ) and tuning ( TuningDataS3Uri
	// ) data.
	InputDataConfig *types.InputDataConfig

	// The language code you selected for your custom language model.
	LanguageCode types.CLMLanguageCode

	// The name of your custom language model.
	ModelName *string

	// The status of your custom language model. When the status displays as COMPLETED
	// , your model is ready to use.
	ModelStatus types.ModelStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata

	noSmithyDocumentSerde
}

func (c *Client) addOperationCreateLanguageModelMiddlewares(stack *middleware.Stack, options Options) (err error) {
	if err := stack.Serialize.Add(&setOperationInputMiddleware{}, middleware.After); err != nil {
		return err
	}
	err = stack.Serialize.Add(&awsAwsjson11_serializeOpCreateLanguageModel{}, middleware.After)
	if err != nil {
		return err
	}
	err = stack.Deserialize.Add(&awsAwsjson11_deserializeOpCreateLanguageModel{}, middleware.After)
	if err != nil {
		return err
	}
	if err := addProtocolFinalizerMiddlewares(stack, options, "CreateLanguageModel"); err != nil {
		return fmt.Errorf("add protocol finalizers: %v", err)
	}

	if err = addlegacyEndpointContextSetter(stack, options); err != nil {
		return err
	}
	if err = addSetLoggerMiddleware(stack, options); err != nil {
		return err
	}
	if err = addClientRequestID(stack); err != nil {
		return err
	}
	if err = addComputeContentLength(stack); err != nil {
		return err
	}
	if err = addResolveEndpointMiddleware(stack, options); err != nil {
		return err
	}
	if err = addComputePayloadSHA256(stack); err != nil {
		return err
	}
	if err = addRetry(stack, options); err != nil {
		return err
	}
	if err = addRawResponseToMetadata(stack); err != nil {
		return err
	}
	if err = addRecordResponseTiming(stack); err != nil {
		return err
	}
	if err = addClientUserAgent(stack, options); err != nil {
		return err
	}
	if err = smithyhttp.AddErrorCloseResponseBodyMiddleware(stack); err != nil {
		return err
	}
	if err = smithyhttp.AddCloseResponseBodyMiddleware(stack); err != nil {
		return err
	}
	if err = addSetLegacyContextSigningOptionsMiddleware(stack); err != nil {
		return err
	}
	if err = addOpCreateLanguageModelValidationMiddleware(stack); err != nil {
		return err
	}
	if err = stack.Initialize.Add(newServiceMetadataMiddleware_opCreateLanguageModel(options.Region), middleware.Before); err != nil {
		return err
	}
	if err = addRecursionDetection(stack); err != nil {
		return err
	}
	if err = addRequestIDRetrieverMiddleware(stack); err != nil {
		return err
	}
	if err = addResponseErrorMiddleware(stack); err != nil {
		return err
	}
	if err = addRequestResponseLogging(stack, options); err != nil {
		return err
	}
	if err = addDisableHTTPSMiddleware(stack, options); err != nil {
		return err
	}
	return nil
}

func newServiceMetadataMiddleware_opCreateLanguageModel(region string) *awsmiddleware.RegisterServiceMetadata {
	return &awsmiddleware.RegisterServiceMetadata{
		Region:        region,
		ServiceID:     ServiceID,
		OperationName: "CreateLanguageModel",
	}
}