Values.ConverseStreamResponseSourceSends messages to the specified Amazon Bedrock model and returns the response in a stream. ConverseStream provides a consistent API that works with all Amazon Bedrock models that support messages. This allows you to write code once and use it with different models. Should a model have unique inference parameters, you can also pass those unique parameters to the model. To find out if a model supports streaming, call GetFoundationModel and check the responseStreamingSupported field in the response. The CLI doesn't support streaming operations in Amazon Bedrock, including ConverseStream. Amazon Bedrock doesn't store any text, images, or documents that you provide as content. The data is only used to generate the response. You can submit a prompt by including it in the messages field, specifying the modelId of a foundation model or inference profile to run inference on it, and including any other fields that are relevant to your use case. You can also submit a prompt from Prompt management by specifying the ARN of the prompt version and including a map of variables to values in the promptVariables field. You can append more messages to the prompt by using the messages field. If you use a prompt from Prompt management, you can't include the following fields in the request: additionalModelRequestFields, inferenceConfig, system, or toolConfig. Instead, these fields must be defined through Prompt management. For more information, see Use a prompt from Prompt management. For information about the Converse API, see Use the Converse API in the Amazon Bedrock User Guide. To use a guardrail, see Use a guardrail with the Converse API in the Amazon Bedrock User Guide. To use a tool with a model, see Tool use (Function calling) in the Amazon Bedrock User Guide For example code, see Conversation streaming example in the Amazon Bedrock User Guide. This operation requires permission for the bedrock:InvokeModelWithResponseStream action. 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 base inference actions (InvokeModel and InvokeModelWithResponseStream). For more information see Deny access for inference on specific models. For troubleshooting some of the common errors you might encounter when using the ConverseStream API, see Troubleshooting Amazon Bedrock API Error Codes in the Amazon Bedrock User Guide
type nonrec t = {stream : ConverseStreamOutput.t option;The output stream that the model generated.
*)}type nonrec error = [ | `AccessDeniedException of AccessDeniedException.t| `InternalServerException of InternalServerException.t| `ModelErrorException of ModelErrorException.t| `ModelNotReadyException of ModelNotReadyException.t| `ModelTimeoutException of ModelTimeoutException.t| `ResourceNotFoundException of ResourceNotFoundException.t| `ThrottlingException of ThrottlingException.t| `ValidationException of ValidationException.t| `Unknown_operation_error of string * string option ]val error_of_json :
string ->
Yojson.Safe.t ->
[> `AccessDeniedException of AccessDeniedException.t
| `InternalServerException of InternalServerException.t
| `ModelErrorException of ModelErrorException.t
| `ModelNotReadyException of ModelNotReadyException.t
| `ModelTimeoutException of ModelTimeoutException.t
| `ResourceNotFoundException of ResourceNotFoundException.t
| `ServiceUnavailableException of ServiceUnavailableException.t
| `ThrottlingException of ThrottlingException.t
| `Unknown_operation_error of string * string option
| `ValidationException of ValidationException.t ]val error_of_xml :
string ->
Awso.Xml.t ->
[> `AccessDeniedException of AccessDeniedException.t
| `InternalServerException of InternalServerException.t
| `ModelErrorException of ModelErrorException.t
| `ModelNotReadyException of ModelNotReadyException.t
| `ModelTimeoutException of ModelTimeoutException.t
| `ResourceNotFoundException of ResourceNotFoundException.t
| `ServiceUnavailableException of ServiceUnavailableException.t
| `ThrottlingException of ThrottlingException.t
| `Unknown_operation_error of string * string option
| `ValidationException of ValidationException.t ]val to_value :
t ->
[> `Structure of
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* [> `Structure of
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* [> `Enum of string
| `Integer of NonNegativeInteger.t
| `String of NonBlankString.t
| `Structure of
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| `Integer of TokenUsageInputTokensInteger.t
| `List of
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CacheDetailInputTokensInteger.t
| `String of String_.t
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list
| `Long of Long.t
| `String of String_.t
| `Structure of
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* [> `Blob of Blob.t
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| `Double of
GuardrailContextualGroundingFilterThresholdDouble.t
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GuardrailAutomatedReasoningTranslationConfidence.t
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GuardrailAutomatedReasoningStatementLogicContent.t ])
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list
| `Structure of
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GuardrailAutomatedReasoningStatementLogicContent.t ])
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list
| `Long of
GuardrailProcessingLatency.t
| `String of
GuardrailId.t
| `Structure of
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* [>
`Integer of
GuardrailTopicPolicyUnitsProcessed.t
| `Structure of
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list
| `Structure of
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Boolean.t
| `Double of
GuardrailContextualGroundingFilterThresholdDouble.t
| `Enum of string
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String_.t
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GuardrailAutomatedReasoningTranslationConfidence.t
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| `Structure of
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| `Long of
GuardrailProcessingLatency.t
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GuardrailId.t
| `Structure of
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| `Structure of
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list
| `String of ToolUseId.t
| `Structure of
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* [> `Blob of ImageSourceBytesBlob.t
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* [> `Integer of
DocumentCharLocationDocumentIndexInteger.t
| `String of String_.t ])
list ])
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list ])
list ]