Class: AWS.BedrockRuntime

// In Node.js, events are streamed and can be read as they arrive.
bedrockruntime.converseStream({/** params **/}, function(err, data) {
  if (err) {
    // handle error
    return console.error(err);
  }

  var eventStream = data.stream;

  eventStream.on('data', function(event) {
    // Check the top-level field to determine which event this is.
    if (event.messageStart) {
      // handle messageStart event
    } else if (event.contentBlockStart) {
      // handle contentBlockStart event
    } else if (event.contentBlockDelta) {
      // handle contentBlockDelta event
    } else if (event.contentBlockStop) {
      // handle contentBlockStop event
    } else if (event.messageStop) {
      // handle messageStop event
    } else if (event.metadata) {
      // handle metadata event
    } else if (event.internalServerException) {
      // handle internalServerException event
    } else if (event.modelStreamErrorException) {
      // handle modelStreamErrorException event
    } else if (event.validationException) {
      // handle validationException event
    } else if (event.throttlingException) {
      // handle throttlingException event
    }
  });
  eventStream.on('error', function(err) { /** Handle error events **/});
  eventStream.on('end', function() { /** Finished reading all events **/});
});

// In browsers, events aren't processed until the response is fully buffered.
// Events will be accessible as an array.
bedrockruntime.converseStream({/** params **/}, function(err, data) {
  if (err) {
    // handle error
    return console.error(err);
  }

  var events = data.stream;

  for (var event of events) {
    // Check the top-level field to determine which event this is.
    if (event.messageStart) {
      // handle messageStart event
    } else if (event.contentBlockStart) {
      // handle contentBlockStart event
    } else if (event.contentBlockDelta) {
      // handle contentBlockDelta event
    } else if (event.contentBlockStop) {
      // handle contentBlockStop event
    } else if (event.messageStop) {
      // handle messageStop event
    } else if (event.metadata) {
      // handle metadata event
    } else if (event.internalServerException) {
      // handle internalServerException event
    } else if (event.modelStreamErrorException) {
      // handle modelStreamErrorException event
    } else if (event.validationException) {
      // handle validationException event
    } else if (event.throttlingException) {
      // handle throttlingException event
    }
  }
});

// In Node.js v10.x, Readable streams have experimental support for async iteration.
// Instead of listening to the event stream's 'data' event, you can use a for...await loop.
async function example() {
  try {
    const result = await bedrockruntime.converseStream({/** params **/}).promise();

    const events = result.stream;

    for await (const event of events) {
      // Check the top-level field to determine which event this is.
      if (event.messageStart) {
        // handle messageStart event
      } else if (event.contentBlockStart) {
        // handle contentBlockStart event
      } else if (event.contentBlockDelta) {
        // handle contentBlockDelta event
      } else if (event.contentBlockStop) {
        // handle contentBlockStop event
      } else if (event.messageStop) {
        // handle messageStop event
      } else if (event.metadata) {
        // handle metadata event
      } else if (event.internalServerException) {
        // handle internalServerException event
      } else if (event.modelStreamErrorException) {
        // handle modelStreamErrorException event
      } else if (event.validationException) {
        // handle validationException event
      } else if (event.throttlingException) {
        // handle throttlingException event
      }
    }
  } catch (err) {
    // handle error
  }
}

var params = {
  messages: [ /* required */
    {
      content: [ /* required */
        {
          image: {
            format: png | jpeg | gif | webp, /* required */
            source: { /* required */
              bytes: Buffer.from('...') || 'STRING_VALUE' /* Strings will be Base-64 encoded on your behalf */
            }
          },
          text: 'STRING_VALUE',
          toolResult: {
            content: [ /* required */
              {
                image: {
                  format: png | jpeg | gif | webp, /* required */
                  source: { /* required */
                    bytes: Buffer.from('...') || 'STRING_VALUE' /* Strings will be Base-64 encoded on your behalf */
                  }
                },
                json: {
                },
                text: 'STRING_VALUE'
              },
              /* more items */
            ],
            toolUseId: 'STRING_VALUE', /* required */
            status: success | error
          },
          toolUse: {
            input: { /* required */
            },
            name: 'STRING_VALUE', /* required */
            toolUseId: 'STRING_VALUE' /* required */
          }
        },
        /* more items */
      ],
      role: user | assistant /* required */
    },
    /* more items */
  ],
  modelId: 'STRING_VALUE', /* required */
  additionalModelRequestFields: {
  },
  additionalModelResponseFieldPaths: [
    'STRING_VALUE',
    /* more items */
  ],
  inferenceConfig: {
    maxTokens: 'NUMBER_VALUE',
    stopSequences: [
      'STRING_VALUE',
      /* more items */
    ],
    temperature: 'NUMBER_VALUE',
    topP: 'NUMBER_VALUE'
  },
  system: [
    {
      text: 'STRING_VALUE'
    },
    /* more items */
  ],
  toolConfig: {
    tools: [ /* required */
      {
        toolSpec: {
          inputSchema: { /* required */
            json: {
            }
          },
          name: 'STRING_VALUE', /* required */
          description: 'STRING_VALUE'
        }
      },
      /* more items */
    ],
    toolChoice: {
      any: {
      },
      auto: {
      },
      tool: {
        name: 'STRING_VALUE' /* required */
      }
    }
  }
};
bedrockruntime.converseStream(params, function(err, data) {
  if (err) console.log(err, err.stack); // an error occurred
  else     console.log(data);           // successful response
});

Parameters:

• params (Object) (defaults to: {}) —
  • modelId — (String)

    The ID for the model.

    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.

  • messages — (Array<map>)

    The messages that you want to send to the model.

    • role — required — (String)

      The role that the message plays in the message.

      Possible values include:
      • "user"
      • "assistant"
    • content — required — (Array<map>)

      The message content.

      • text — (String)

        Text to include in the message.

      • image — (map)

        Image to include in the message.

        Note: This field is only supported by Anthropic Claude 3 models.
        • format — required — (String)

          The format of the image.

          Possible values include:
          • "png"
          • "jpeg"
          • "gif"
          • "webp"
        • source — required — (map)

          The source for the image.

          • bytes — (Buffer, Typed Array, Blob, String)

            The raw image bytes for the image. If you use an AWS SDK, you don't need to base64 encode the image bytes.

      • toolUse — (map)

        Information about a tool use request from a model.

        • toolUseId — required — (String)

          The ID for the tool request.

        • name — required — (String)

          The name of the tool that the model wants to use.

        • input — required — (map)

          The input to pass to the tool.

      • toolResult — (map)

        The result for a tool request that a model makes.

        • toolUseId — required — (String)

          The ID of the tool request that this is the result for.

        • content — required — (Array<map>)

          The content for tool result content block.

          • json — (map)

            A tool result that is JSON format data.

          • text — (String)

            A tool result that is text.

          • image — (map)

            A tool result that is an image.

            Note: This field is only supported by Anthropic Claude 3 models.
            • format — required — (String)

              The format of the image.

              Possible values include:
              • "png"
              • "jpeg"
              • "gif"
              • "webp"
            • source — required — (map)

              The source for the image.

              • bytes — (Buffer, Typed Array, Blob, String)

                The raw image bytes for the image. If you use an AWS SDK, you don't need to base64 encode the image bytes.

        • status — (String)

          The status for the tool result content block.

          Note: This field is only supported Anthropic Claude 3 models.
          Possible values include:
          • "success"
          • "error"
  • system — (Array<map>)

    A system prompt to send to the model.

    • text — (String)

      A system prompt for the model.

  • inferenceConfig — (map)

    Inference parameters to pass to the model. ConverseStream supports a base set of inference parameters. If you need to pass additional parameters that the model supports, use the additionalModelRequestFields request field.

    • maxTokens — (Integer)

      The maximum number of tokens to allow in the generated response. The default value is the maximum allowed value for the model that you are using. For more information, see Inference parameters for foundatio{ "messages": [ { "role": "user", "content": [ { "text": "what's the weather in Queens, NY and Austin, TX?" } ] }, { "role": "assistant", "content": [ { "toolUse": { "toolUseId": "1", "name": "get_weather", "input": { "city": "Queens", "state": "NY" } } }, { "toolUse": { "toolUseId": "2", "name": "get_weather", "input": { "city": "Austin", "state": "TX" } } } ] }, { "role": "user", "content": [ { "toolResult": { "toolUseId": "2", "content": [ { "json": { "weather": "40" } } ] } }, { "text": "..." }, { "toolResult": { "toolUseId": "1", "content": [ { "text": "result text" } ] } } ] } ], "toolConfig": { "tools": [ { "name": "get_weather", "description": "Get weather", "inputSchema": { "type": "object", "properties": { "city": { "type": "string", "description": "City of location" }, "state": { "type": "string", "description": "State of location" } }, "required": ["city", "state"] } } ] } } n models.

    • temperature — (Float)

      The likelihood of the model selecting higher-probability options while generating a response. A lower value makes the model more likely to choose higher-probability options, while a higher value makes the model more likely to choose lower-probability options.

      The default value is the default value for the model that you are using. For more information, see Inference parameters for foundation models.

    • topP — (Float)

      The percentage of most-likely candidates that the model considers for the next token. For example, if you choose a value of 0.8 for topP, the model selects from the top 80% of the probability distribution of tokens that could be next in the sequence.

      The default value is the default value for the model that you are using. For more information, see Inference parameters for foundation models.

    • stopSequences — (Array<String>)

      A list of stop sequences. A stop sequence is a sequence of characters that causes the model to stop generating the response.

  • toolConfig — (map)

    Configuration information for the tools that the model can use when generating a response.

    Note: This field is only supported by Anthropic Claude 3 models.
    • tools — required — (Array<map>)

      An array of tools that you want to pass to a model.

      • toolSpec — (map)

        The specfication for the tool.

        • name — required — (String)

          The name for the tool.

        • description — (String)

          The description for the tool.

        • inputSchema — required — (map)

          The input schema for the tool in JSON format.

          • json — (map)

            The JSON schema for the tool. For more information, see JSON Schema Reference.

    • toolChoice — (map)

      If supported by model, forces the model to request a tool.

      • auto — (map)

        The Model automatically decides if a tool should be called or to whether to generate text instead.

      • any — (map)

        The model must request at least one tool (no text is generated).

      • tool — (map)

        The Model must request the specified tool.

        • name — required — (String)

          The name of the tool that the model must request.

  • additionalModelRequestFields — (map)

    Additional inference parameters that the model supports, beyond the base set of inference parameters that ConverseStream supports in the inferenceConfig field.

  • additionalModelResponseFieldPaths — (Array<String>)

    Additional model parameters field paths to return in the response. ConverseStream returns the requested fields as a JSON Pointer object in the additionalModelResultFields field. The following is example JSON for additionalModelResponseFieldPaths.

    [ "/stop_sequence" ]

    For information about the JSON Pointer syntax, see the Internet Engineering Task Force (IETF) documentation.

    ConverseStream rejects an empty JSON Pointer or incorrectly structured JSON Pointer with a 400 error code. if the JSON Pointer is valid, but the requested field is not in the model response, it is ignored by ConverseStream.

Callback (callback):

• function(err, data) { ... }

  Called when a response from the service is returned. If a callback is not supplied, you must call AWS.Request.send() on the returned request object to initiate the request.

  Context (this):

  • (AWS.Response) —

    the response object containing error, data properties, and the original request object.

  Parameters:

  • err (Error) —

    the error object returned from the request. Set to null if the request is successful.

  • data (Object) —

    the de-serialized data returned from the request. Set to null if a request error occurs. The data object has the following properties:

    • stream — (ReadableStream<Events> | Array<Events>)

      The output stream that the model generated.

      stream is an object-mode Readable stream in Node.js v0.10.x and higher. Attach a listener to the data event to receive events. stream is an array of events in browsers. The possible events that may be returned are listed below. Note that the top-level field in each event matches the event name.
      • messageStart — (map)

        Message start information.

        • role — required — (String)

          The role for the message.

          Possible values include:
          • "user"
          • "assistant"
      • contentBlockStart — (map)

        Start information for a content block.

        • start — required — (map)

          Start information about a content block start event.

          • toolUse — (map)

            Information about a tool that the model is requesting to use.

            • toolUseId — required — (String)

              The ID for the tool request.

            • name — required — (String)

              The name of the tool that the model is requesting to use.

        • contentBlockIndex — required — (Integer)

          The index for a content block start event.

      • contentBlockDelta — (map)

        The messages output content block delta.

        • delta — required — (map)

          The delta for a content block delta event.

          • text — (String)

            The content text.

          • toolUse — (map)

            Information about a tool that the model is requesting to use.

            • input — required — (String)

              The input for a requested tool.

        • contentBlockIndex — required — (Integer)

          The block index for a content block delta event.

      • contentBlockStop — (map)

        Stop information for a content block.

        • contentBlockIndex — required — (Integer)

          The index for a content block.

      • messageStop — (map)

        Message stop information.

        • stopReason — required — (String)

          The reason why the model stopped generating output.

          Possible values include:
          • "end_turn"
          • "tool_use"
          • "max_tokens"
          • "stop_sequence"
          • "content_filtered"
        • additionalModelResponseFields — (map)

          The additional model response fields.

      • metadata — (map)

        Metadata for the converse output stream.

        • usage — required — (map)

          Usage information for the conversation stream event.

          • inputTokens — required — (Integer)

            The number of tokens sent in the request to the model.

          • outputTokens — required — (Integer)

            The number of tokens that the model generated for the request.

          • totalTokens — required — (Integer)

            The total of input tokens and tokens generated by the model.

        • metrics — required — (map)

          The metrics for the conversation stream metadata event.

          • latencyMs — required — (Integer)

            The latency for the streaming request, in milliseconds.

      • internalServerException — (map)

        An internal server error occurred. Retry your request.

        • message — (String)
      • modelStreamErrorException — (map)

        A streaming error occurred. Retry your request.

        • message — (String)
        • originalStatusCode — (Integer)

          The original status code.

        • originalMessage — (String)

          The original message.

      • validationException — (map)

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

        • message — (String)
      • throttlingException — (map)

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

        • message — (String)

Returns:

• (AWS.Request) —

  a handle to the operation request for subsequent event callback registration.

var params = {
  body: Buffer.from('...') || 'STRING_VALUE' /* Strings will be Base-64 encoded on your behalf */, /* required */
  modelId: 'STRING_VALUE', /* required */
  accept: 'STRING_VALUE',
  contentType: 'STRING_VALUE',
  guardrailIdentifier: 'STRING_VALUE',
  guardrailVersion: 'STRING_VALUE',
  trace: ENABLED | DISABLED
};
bedrockruntime.invokeModel(params, function(err, data) {
  if (err) console.log(err, err.stack); // an error occurred
  else     console.log(data);           // successful response
});

Parameters:

• params (Object) (defaults to: {}) —
  • body — (Buffer, Typed Array, Blob, String)

    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.

  • contentType — (String)

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

  • accept — (String)

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

  • modelId — (String)

    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.

  • trace — (String)

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

    Possible values include:
    • "ENABLED"
    • "DISABLED"
  • 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't application/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.

Callback (callback):

• function(err, data) { ... }

  Called when a response from the service is returned. If a callback is not supplied, you must call AWS.Request.send() on the returned request object to initiate the request.

  Context (this):

  • (AWS.Response) —

    the response object containing error, data properties, and the original request object.

  Parameters:

  • err (Error) —

    the error object returned from the request. Set to null if the request is successful.

  • data (Object) —

    the de-serialized data returned from the request. Set to null if a request error occurs. The data object has the following properties:

    • body — (Buffer(Node.js), Typed Array(Browser))

      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.

Returns:

• (AWS.Request) —

  a handle to the operation request for subsequent event callback registration.

// In Node.js, events are streamed and can be read as they arrive.
bedrockruntime.invokeModelWithResponseStream({/** params **/}, function(err, data) {
  if (err) {
    // handle error
    return console.error(err);
  }

  var eventStream = data.body;

  eventStream.on('data', function(event) {
    // Check the top-level field to determine which event this is.
    if (event.chunk) {
      // handle chunk event
    } else if (event.internalServerException) {
      // handle internalServerException event
    } else if (event.modelStreamErrorException) {
      // handle modelStreamErrorException event
    } else if (event.validationException) {
      // handle validationException event
    } else if (event.throttlingException) {
      // handle throttlingException event
    } else if (event.modelTimeoutException) {
      // handle modelTimeoutException event
    }
  });
  eventStream.on('error', function(err) { /** Handle error events **/});
  eventStream.on('end', function() { /** Finished reading all events **/});
});

// In browsers, events aren't processed until the response is fully buffered.
// Events will be accessible as an array.
bedrockruntime.invokeModelWithResponseStream({/** params **/}, function(err, data) {
  if (err) {
    // handle error
    return console.error(err);
  }

  var events = data.body;

  for (var event of events) {
    // Check the top-level field to determine which event this is.
    if (event.chunk) {
      // handle chunk event
    } else if (event.internalServerException) {
      // handle internalServerException event
    } else if (event.modelStreamErrorException) {
      // handle modelStreamErrorException event
    } else if (event.validationException) {
      // handle validationException event
    } else if (event.throttlingException) {
      // handle throttlingException event
    } else if (event.modelTimeoutException) {
      // handle modelTimeoutException event
    }
  }
});

// In Node.js v10.x, Readable streams have experimental support for async iteration.
// Instead of listening to the event stream's 'data' event, you can use a for...await loop.
async function example() {
  try {
    const result = await bedrockruntime.invokeModelWithResponseStream({/** params **/}).promise();

    const events = result.body;

    for await (const event of events) {
      // Check the top-level field to determine which event this is.
      if (event.chunk) {
        // handle chunk event
      } else if (event.internalServerException) {
        // handle internalServerException event
      } else if (event.modelStreamErrorException) {
        // handle modelStreamErrorException event
      } else if (event.validationException) {
        // handle validationException event
      } else if (event.throttlingException) {
        // handle throttlingException event
      } else if (event.modelTimeoutException) {
        // handle modelTimeoutException event
      }
    }
  } catch (err) {
    // handle error
  }
}

var params = {
  body: Buffer.from('...') || 'STRING_VALUE' /* Strings will be Base-64 encoded on your behalf */, /* required */
  modelId: 'STRING_VALUE', /* required */
  accept: 'STRING_VALUE',
  contentType: 'STRING_VALUE',
  guardrailIdentifier: 'STRING_VALUE',
  guardrailVersion: 'STRING_VALUE',
  trace: ENABLED | DISABLED
};
bedrockruntime.invokeModelWithResponseStream(params, function(err, data) {
  if (err) console.log(err, err.stack); // an error occurred
  else     console.log(data);           // successful response
});

Parameters:

• params (Object) (defaults to: {}) —
  • body — (Buffer, Typed Array, Blob, String)

    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.

  • contentType — (String)

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

  • accept — (String)

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

  • modelId — (String)

    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.

  • trace — (String)

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

    Possible values include:
    • "ENABLED"
    • "DISABLED"
  • 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 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.

  • guardrailVersion — (String)

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

Callback (callback):

• function(err, data) { ... }

  Called when a response from the service is returned. If a callback is not supplied, you must call AWS.Request.send() on the returned request object to initiate the request.

  Context (this):

  • (AWS.Response) —

    the response object containing error, data properties, and the original request object.

  Parameters:

  • err (Error) —

    the error object returned from the request. Set to null if the request is successful.

  • data (Object) —

    the de-serialized data returned from the request. Set to null if a request error occurs. The data object has the following properties:

    • body — (ReadableStream<Events> | Array<Events>)

      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.

      body is an object-mode Readable stream in Node.js v0.10.x and higher. Attach a listener to the data event to receive events. body is an array of events in browsers. The possible events that may be returned are listed below. Note that the top-level field in each event matches the event name.
      • chunk — (map)

        Content included in the response.

        • bytes — (Buffer, Typed Array, Blob, String)

          Base64-encoded bytes of payload data.

      • internalServerException — (map)

        An internal server error occurred. Retry your request.

        • message — (String)
      • modelStreamErrorException — (map)

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

        • message — (String)
        • originalStatusCode — (Integer)

          The original status code.

        • originalMessage — (String)

          The original message.

      • validationException — (map)

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

        • message — (String)
      • throttlingException — (map)

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

        • message — (String)
      • modelTimeoutException — (map)

        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.

Returns:

• (AWS.Request) —

  a handle to the operation request for subsequent event callback registration.

Parameters:

• state (String) —

  the resource state to wait for. Available states for this service are listed in "Waiter Resource States" below.

• params (map) (defaults to: {}) —

  a list of parameters for the given state. See each waiter resource state for required parameters.

Callback (callback):

• function(err, data) { ... }

  Callback containing error and data information. See the respective resource state for the expected error or data information.

  If the waiter times out its requests, it will return a ResourceNotReady error.

Returns:

• (AWS.Request) —

  a handle to the operation request for subsequent event callback registration.