Request Syntax URI Request Parameters Request Body Response Syntax Response Elements Errors Examples See Also

InvokeModel

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.

This operation requires permission for the bedrock:InvokeModel action.

Important

To deny all inference access to resources that you specify in the modelId field, you need to deny access to the bedrock:InvokeModel and bedrock:InvokeModelWithResponseStream actions. Doing this also denies access to the resource through the Converse API actions (Converse and ConverseStream). For more information see Deny access for inference on specific models.

For troubleshooting some of the common errors you might encounter when using the InvokeModel API, see Troubleshooting Amazon Bedrock API Error Codes in the Amazon Bedrock User Guide

Request Syntax


POST /model/modelId/invoke HTTP/1.1
Accept: accept
Content-Type: contentType
X-Amzn-Bedrock-GuardrailIdentifier: guardrailIdentifier
X-Amzn-Bedrock-GuardrailVersion: guardrailVersion
X-Amzn-Bedrock-PerformanceConfig-Latency: performanceConfigLatency
X-Amzn-Bedrock-Trace: trace

body

URI Request Parameters

The request uses the following URI parameters.

accept

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

contentType

The MIME type of the input data in the request. You must specify application/json.

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.

Length Constraints: Minimum length of 0. Maximum length of 2048.

Pattern: ^(([a-z0-9]+)|(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:[0-9]{12}:guardrail/[a-z0-9]+))$

guardrailVersion

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

Pattern: ^(([1-9][0-9]{0,7})|(DRAFT))$

modelId

Specifies the model or throughput with which to run inference, or the prompt resource to use in inference. The value depends on the resource 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 an Amazon Bedrock Marketplace model, specify the ID or ARN of the marketplace endpoint that you created. For more information about Amazon Bedrock Marketplace and setting up an endpoint, see Amazon Bedrock Marketplace in the Amazon Bedrock User Guide.
If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see Supported Regions and models for cross-region inference in the Amazon Bedrock User Guide.
If you use a prompt created through Prompt management, specify the ARN of the prompt version. For more information, see Test a prompt using Prompt management.
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.
If you use an imported model, specify the ARN of the imported model. You can get the model ARN from a successful call to CreateModelImportJob or from the Imported models page in the Amazon Bedrock console.

Length Constraints: Minimum length of 1. Maximum length of 2048.

Pattern: ^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})|([0-9]{12}:(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|([a-zA-Z0-9-:.]+)$|(^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:[0-9]{12}:prompt/[0-9a-zA-Z]{10}(?::[0-9]{1,5})?))$|(^arn:aws:sagemaker:[a-z0-9-]+:[0-9]{12}:endpoint/[a-zA-Z0-9-]+$)|(^arn:aws(-[^:]+)?:bedrock:([0-9a-z-]{1,20}):([0-9]{12}):(default-)?prompt-router/[a-zA-Z0-9-:.]+$)$

Required: Yes

performanceConfigLatency

Model performance settings for the request.

Valid Values: standard | optimized

trace

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

Valid Values: ENABLED | DISABLED | ENABLED_FULL

Request Body

The request accepts the following binary data.

body

The prompt and inference parameters in the format specified in the contentType in the header. You must provide the body in JSON format. 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.

Length Constraints: Minimum length of 0. Maximum length of 25000000.

Response Syntax


HTTP/1.1 200
Content-Type: contentType
X-Amzn-Bedrock-PerformanceConfig-Latency: performanceConfigLatency

body

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The response returns the following HTTP headers.

contentType

The MIME type of the inference result.

performanceConfigLatency

Model performance settings for the request.

Valid Values: standard | optimized

The response returns the following as the HTTP body.

body

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.

Length Constraints: Minimum length of 0. Maximum length of 25000000.

Errors

For information about the errors that are common to all actions, see Common Errors.

AccessDeniedException

The request is denied because you do not have sufficient permissions to perform the requested action. For troubleshooting this error, see AccessDeniedException in the Amazon Bedrock User Guide

HTTP Status Code: 403

InternalServerException

An internal server error occurred. For troubleshooting this error, see InternalFailure in the Amazon Bedrock User Guide

HTTP Status Code: 500

ModelErrorException

The request failed due to an error while processing the model.

HTTP Status Code: 424

ModelNotReadyException

The model specified in the request is not ready to serve inference requests. The AWS SDK will automatically retry the operation up to 5 times. For information about configuring automatic retries, see Retry behavior in the AWS SDKs and Tools reference guide.

HTTP Status Code: 429

ModelTimeoutException

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

HTTP Status Code: 408

ResourceNotFoundException

The specified resource ARN was not found. For troubleshooting this error, see ResourceNotFound in the Amazon Bedrock User Guide

HTTP Status Code: 404

ServiceQuotaExceededException

Your request exceeds the service quota for your account. You can view your quotas at Viewing service quotas. You can resubmit your request later.

HTTP Status Code: 400

ServiceUnavailableException

The service isn't currently available. For troubleshooting this error, see ServiceUnavailable in the Amazon Bedrock User Guide

HTTP Status Code: 503

ThrottlingException

Your request was denied due to exceeding the account quotas for Amazon Bedrock. For troubleshooting this error, see ThrottlingException in the Amazon Bedrock User Guide

HTTP Status Code: 429

ValidationException

The input fails to satisfy the constraints specified by Amazon Bedrock. For troubleshooting this error, see ValidationError in the Amazon Bedrock User Guide

HTTP Status Code: 400

Examples

Run inference on a text model

Send an invoke request to run inference on a Titan Text G1 - Express model. We set the accept parameter to accept any content type in the response.

Sample Request


POST https://bedrock-runtime.us-east-1.amazonaws.com/model/amazon.titan-text-express-v1/invoke

-H accept: */*  
-H content-type: application/json

Payload
{"inputText": "Hello world"}

Run inference on an image model

In the following example, the request sets the accept parameter to image/png.

Sample Request


POST https://bedrock-runtime.us-east-1.amazonaws.com/model/stability.stable-diffusion-xl-v1/invoke

-H accept: image/png
-H content-type: application/json

Payload
{"inputText": "Picture of a bird"}

Use a guardrail

This example shows how to use a guardrail with InvokeModel.

Sample Request


POST /model/modelId/invoke HTTP/1.1
Accept: accept
Content-Type: contentType
X-Amzn-Bedrock-GuardrailIdentifier: guardrailIdentifier
X-Amzn-Bedrock-GuardrailVersion: guardrailVersion
X-Amzn-Bedrock-GuardrailTrace: guardrailTrace
X-Amzn-Bedrock-Trace: trace

body

// body
{
    "amazon-bedrock-guardrailConfig": {
        "tagSuffix": "string"
    }
}

Example response

This is an example response from InvokeModel when using a guardrail.

Sample Request


HTTP/1.1 200
Content-Type: contentType

body

// body
{
  "amazon-bedrock-guardrailAction": "INTERVENED | NONE",
  "amazon-bedrock-trace": {
    "guardrails": {
      //  Detailed guardrail trace    
    }
  }
}

Use an inference profile in model invocation

The following request calls the US Anthropic Claude 3.5 Sonnet inference profile to route traffic to the us-east-1 and us-west-2 regions.

Sample Request


POST /model/us.anthropic.claude-3-5-sonnet-20240620-v1:0/invoke HTTP/1.1

{
    "anthropic_version": "bedrock-2023-05-31",
    "max_tokens": 1024,
    "messages": [
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Hello world"
                }
            ]
        }
    ]
}