BedrockRuntime / Client / invoke_model
invoke_model#
- BedrockRuntime.Client.invoke_model(**kwargs)#
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.Warning
To deny all inference access to resources that you specify in the modelId field, you need to deny access to the
bedrock:InvokeModel
andbedrock: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 GuideSee also: AWS API Documentation
Request Syntax
response = client.invoke_model( body=b'bytes'|file, contentType='string', accept='string', modelId='string', trace='ENABLED'|'DISABLED', guardrailIdentifier='string', guardrailVersion='string', performanceConfigLatency='standard'|'optimized' )
- Parameters:
body (bytes or seekable file-like object) – 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.contentType (string) – The MIME type of the input data in the request. You must specify
application/json
.accept (string) – The desired MIME type of the inference body in the response. The default value is
application/json
.modelId (string) –
[REQUIRED]
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: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 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 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.
trace (string) – Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.
guardrailIdentifier (string) –
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’tapplication/json
.You provide a guardrail identifier, but
guardrailVersion
isn’t specified.
guardrailVersion (string) – The version number for the guardrail. The value can also be
DRAFT
.performanceConfigLatency (string) – Model performance settings for the request.
- Return type:
dict
- Returns:
Response Syntax
{ 'body': StreamingBody(), 'contentType': 'string', 'performanceConfigLatency': 'standard'|'optimized' }
Response Structure
(dict) –
body (
StreamingBody
) –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.
performanceConfigLatency (string) –
Model performance settings for the request.
Exceptions