InvokeModel - Amazon Bedrock

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-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

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

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

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-:.]+)$|(^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:[0-9]{12}:prompt/[0-9a-zA-Z]{10}(?::[0-9]{1,5})?))$

Required: Yes

trace

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

Valid Values: ENABLED | DISABLED

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 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.

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" } ] } ] }

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: