Amazon Bedrock Runtime

{'guardrailIdentifier': 'string',
 'guardrailVersion': 'string',
 'trace': 'ENABLED | DISABLED'}

Invokes the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body. You use model inference to generate text, images, and embeddings.

For example code, see Invoke model code examples in the Amazon Bedrock User Guide.

This operation requires permission for the bedrock:InvokeModel action.

See also: AWS API Documentation

Request Syntax

client.invoke_model(
    body=b'bytes'|file,
    contentType='string',
    accept='string',
    modelId='string',
    trace='ENABLED'|'DISABLED',
    guardrailIdentifier='string',
    guardrailVersion='string'
)

type body:

bytes or seekable file-like object

param body:

[REQUIRED]

The prompt and inference parameters in the format specified in the contentType in the header. To see the format and content of the request and response bodies for different models, refer to Inference parameters. For more information, see Run inference in the Bedrock User Guide.

type contentType:

string

param contentType:

The MIME type of the input data in the request. The default value is application/json.

type accept:

string

param accept:

The desired MIME type of the inference body in the response. The default value is application/json.

type modelId:

string

param modelId:

[REQUIRED]

The unique identifier of the model to invoke to run inference.

The modelId to provide depends on the type of model that you use:

• If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see Amazon Bedrock base model IDs (on-demand throughput) in the Amazon Bedrock User Guide.

• If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see Run inference using a Provisioned Throughput in the Amazon Bedrock User Guide.

• If you use a custom model, first purchase Provisioned Throughput for it. Then specify the ARN of the resulting provisioned model. For more information, see Use a custom model in Amazon Bedrock in the Amazon Bedrock User Guide.

type trace:

string

param trace:

Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.

type guardrailIdentifier:

string

param guardrailIdentifier:

The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.

An error will be thrown in the following situations.

• You don't provide a guardrail identifier but you specify the amazon-bedrock-guardrailConfig field in the request body.

• You enable the guardrail but the contentType isn't application/json.

• You provide a guardrail identifier, but guardrailVersion isn't specified.

type guardrailVersion:

string

param guardrailVersion:

The version number for the guardrail. The value can also be DRAFT.

rtype:

dict

returns:

Response Syntax

{
    'body': b'bytes'|file,
    'contentType': 'string'
}

Response Structure

• (dict) --

  • body (bytes or seekable file-like object) --

    Inference response from the model in the format specified in the contentType header. To see the format and content of the request and response bodies for different models, refer to Inference parameters.

  • contentType (string) --

    The MIME type of the inference result.

{'guardrailIdentifier': 'string',
 'guardrailVersion': 'string',
 'trace': 'ENABLED | DISABLED'}

Invoke the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body. The response is returned in a stream.

To see if a model supports streaming, call GetFoundationModel and check the responseStreamingSupported field in the response.

For example code, see Invoke model with streaming code example in the Amazon Bedrock User Guide.

This operation requires permissions to perform the bedrock:InvokeModelWithResponseStream action.

See also: AWS API Documentation

Request Syntax

client.invoke_model_with_response_stream(
    body=b'bytes'|file,
    contentType='string',
    accept='string',
    modelId='string',
    trace='ENABLED'|'DISABLED',
    guardrailIdentifier='string',
    guardrailVersion='string'
)

type body:

bytes or seekable file-like object

param body:

[REQUIRED]

The prompt and inference parameters in the format specified in the contentType in the header. To see the format and content of the request and response bodies for different models, refer to Inference parameters. For more information, see Run inference in the Bedrock User Guide.

type contentType:

string

param contentType:

The MIME type of the input data in the request. The default value is application/json.

type accept:

string

param accept:

The desired MIME type of the inference body in the response. The default value is application/json.

type modelId:

string

param modelId:

[REQUIRED]

The unique identifier of the model to invoke to run inference.

The modelId to provide depends on the type of model that you use:

• If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see Amazon Bedrock base model IDs (on-demand throughput) in the Amazon Bedrock User Guide.

• If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see Run inference using a Provisioned Throughput in the Amazon Bedrock User Guide.

• If you use a custom model, first purchase Provisioned Throughput for it. Then specify the ARN of the resulting provisioned model. For more information, see Use a custom model in Amazon Bedrock in the Amazon Bedrock User Guide.

type trace:

string

param trace:

Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.

type guardrailIdentifier:

string

param guardrailIdentifier:

The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.

An error is thrown in the following situations.

• You don't provide a guardrail identifier but you specify the amazon-bedrock-guardrailConfig field in the request body.

• You enable the guardrail but the contentType isn't application/json.

• You provide a guardrail identifier, but guardrailVersion isn't specified.

type guardrailVersion:

string

param guardrailVersion:

The version number for the guardrail. The value can also be DRAFT.

rtype:

dict

returns:

The response of this operation contains an :class:`.EventStream` member. When iterated the :class:`.EventStream` will yield events based on the structure below, where only one of the top level keys will be present for any given event.

Response Syntax

{
    'body': EventStream({
        'chunk': {
            'bytes': b'bytes'
        },
        'internalServerException': {
            'message': 'string'
        },
        'modelStreamErrorException': {
            'message': 'string',
            'originalStatusCode': 123,
            'originalMessage': 'string'
        },
        'validationException': {
            'message': 'string'
        },
        'throttlingException': {
            'message': 'string'
        },
        'modelTimeoutException': {
            'message': 'string'
        }
    }),
    'contentType': 'string'
}

Response Structure

• (dict) --

  • body (:class:`.EventStream`) --

    Inference response from the model in the format specified by the contentType header. To see the format and content of this field for different models, refer to Inference parameters.

    • chunk (dict) --

      Content included in the response.

      • bytes (bytes) --

        Base64-encoded bytes of payload data.

    • internalServerException (dict) --

      An internal server error occurred. Retry your request.

      • message (string) --

    • modelStreamErrorException (dict) --

      An error occurred while streaming the response. Retry your request.

      • message (string) --

      • originalStatusCode (integer) --

        The original status code.

      • originalMessage (string) --

        The original message.

    • validationException (dict) --

      Input validation failed. Check your request parameters and retry the request.

      • message (string) --

    • throttlingException (dict) --

      The number or frequency of requests exceeds the limit. Resubmit your request later.

      • message (string) --

    • modelTimeoutException (dict) --

      The request took too long to process. Processing time exceeded the model timeout length.

      • message (string) --

  • contentType (string) --

    The MIME type of the inference result.