Rufen Sie Amazon Nova auf Amazon Bedrock mithilfe der Converse-API von Bedrock auf

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Amazon Nova.

// Use the Converse API to send a text message to Amazon Nova.

using System;
using System.Collections.Generic;
using Amazon;
using Amazon.BedrockRuntime;
using Amazon.BedrockRuntime.Model;

// Create a Bedrock Runtime client in the AWS Region you want to use.
var client = new AmazonBedrockRuntimeClient(RegionEndpoint.USEast1);

// Set the model ID, e.g., Amazon Nova Lite.
var modelId = "amazon.nova-lite-v1:0";

// Define the user message.
var userMessage = "Describe the purpose of a 'hello world' program in one line.";

// Create a request with the model ID, the user message, and an inference configuration.
var request = new ConverseRequest
{
    ModelId = modelId,
    Messages = new List<Message>
    {
        new Message
        {
            Role = ConversationRole.User,
            Content = new List<ContentBlock> { new ContentBlock { Text = userMessage } }
        }
    },
    InferenceConfig = new InferenceConfiguration()
    {
        MaxTokens = 512,
        Temperature = 0.5F,
        TopP = 0.9F
    }
};

try
{
    // Send the request to the Bedrock Runtime and wait for the result.
    var response = await client.ConverseAsync(request);

    // Extract and print the response text.
    string responseText = response?.Output?.Message?.Content?[0]?.Text ?? "";
    Console.WriteLine(responseText);
}
catch (AmazonBedrockRuntimeException e)
{
    Console.WriteLine($"ERROR: Can't invoke '{modelId}'. Reason: {e.Message}");
    throw;
}

Senden Sie mithilfe der Converse-API von Bedrock mit einer Toolkonfiguration eine Konversation mit Nachrichten an Amazon Nova.

/// <summary>
/// Wrapper class for interacting with the Amazon Bedrock Converse API.
/// </summary>
public class BedrockActionsWrapper
{
    private readonly IAmazonBedrockRuntime _bedrockClient;
    private readonly ILogger<BedrockActionsWrapper> _logger;

    /// <summary>
    /// Initializes a new instance of the <see cref="BedrockActionsWrapper"/> class.
    /// </summary>
    /// <param name="bedrockClient">The Bedrock Converse API client.</param>
    /// <param name="logger">The logger instance.</param>
    public BedrockActionsWrapper(IAmazonBedrockRuntime bedrockClient, ILogger<BedrockActionsWrapper> logger)
    {
        _bedrockClient = bedrockClient;
        _logger = logger;
    }

    /// <summary>
    /// Sends a Converse request to the Amazon Bedrock Converse API.
    /// </summary>
    /// <param name="modelId">The Bedrock Model Id.</param>
    /// <param name="systemPrompt">A system prompt instruction.</param>
    /// <param name="conversation">The array of messages in the conversation.</param>
    /// <param name="toolSpec">The specification for a tool.</param>
    /// <returns>The response of the model.</returns>
    public async Task<ConverseResponse> SendConverseRequestAsync(string modelId, string systemPrompt, List<Message> conversation, ToolSpecification toolSpec)
    {
        try
        {
            var request = new ConverseRequest()
            {
                ModelId = modelId,
                System = new List<SystemContentBlock>()
                {
                    new SystemContentBlock()
                    {
                        Text = systemPrompt
                    }
                },
                Messages = conversation,
                ToolConfig = new ToolConfiguration()
                {
                    Tools = new List<Tool>()
                    {
                        new Tool()
                        {
                            ToolSpec = toolSpec
                        }
                    }
                }
            };

            var response = await _bedrockClient.ConverseAsync(request);

            return response;
        }
        catch (ModelNotReadyException ex)
        {
            _logger.LogError(ex, "Model not ready, please wait and try again.");
            throw;
        }
        catch (AmazonBedrockRuntimeException ex)
        {
            _logger.LogError(ex, "Error occurred while sending Converse request.");
            throw;
        }
    }
}

Senden Sie mithilfe der Converse-API von Bedrock mit dem asynchronen Java-Client eine Textnachricht an Amazon Nova.

import software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeAsyncClient;
import software.amazon.awssdk.services.bedrockruntime.model.*;

import java.util.concurrent.CompletableFuture;

/**
 * This example demonstrates how to use the Amazon Nova foundation models
 * with an asynchronous Amazon Bedrock runtime client to generate text.
 * It shows how to:
 * - Set up the Amazon Bedrock runtime client
 * - Create a message
 * - Configure and send a request
 * - Process the response
 */
public class ConverseAsync {

    public static String converseAsync() {

        // Step 1: Create the Amazon Bedrock runtime client
        // The runtime client handles the communication with AI models on Amazon Bedrock
        BedrockRuntimeAsyncClient client = BedrockRuntimeAsyncClient.builder()
                .credentialsProvider(DefaultCredentialsProvider.create())
                .region(Region.US_EAST_1)
                .build();

        // Step 2: Specify which model to use
        // Available Amazon Nova models and their characteristics:
        // - Amazon Nova Micro: Text-only model optimized for lowest latency and cost
        // - Amazon Nova Lite:  Fast, low-cost multimodal model for image, video, and text
        // - Amazon Nova Pro:   Advanced multimodal model balancing accuracy, speed, and cost
        //
        // For the latest available models, see:
        // https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
        String modelId = "amazon.nova-lite-v1:0";

        // Step 3: Create the message
        // The message includes the text prompt and specifies that it comes from the user
        var inputText = "Describe the purpose of a 'hello world' program in one line.";
        var message = Message.builder()
                .content(ContentBlock.fromText(inputText))
                .role(ConversationRole.USER)
                .build();

        // Step 4: Configure the request
        // Optional parameters to control the model's response:
        // - maxTokens: maximum number of tokens to generate
        // - temperature: randomness (max: 1.0, default: 0.7)
        //   OR
        // - topP: diversity of word choice (max: 1.0, default: 0.9)
        // Note: Use either temperature OR topP, but not both
        ConverseRequest request = ConverseRequest.builder()
                .modelId(modelId)
                .messages(message)
                .inferenceConfig(config -> config
                                .maxTokens(500)     // The maximum response length
                                .temperature(0.5F)  // Using temperature for randomness control
                        //.topP(0.9F)       // Alternative: use topP instead of temperature
                ).build();

        // Step 5: Send and process the request asynchronously
        // - Send the request to the model
        // - Extract and return the generated text from the response
        try {
            CompletableFuture<ConverseResponse> asyncResponse = client.converse(request);
            return asyncResponse.thenApply(
                    response -> response.output().message().content().get(0).text()
            ).get();

        } catch (Exception e) {
            System.err.printf("Can't invoke '%s': %s", modelId, e.getMessage());
            throw new RuntimeException(e);
        }
    }

    public static void main(String[] args) {
        String response = converseAsync();
        System.out.println(response);
    }
}

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Amazon Nova.

import software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider;
import software.amazon.awssdk.core.exception.SdkClientException;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeClient;
import software.amazon.awssdk.services.bedrockruntime.model.*;

/**
 * This example demonstrates how to use the Amazon Nova foundation models
 * with a synchronous Amazon Bedrock runtime client to generate text.
 * It shows how to:
 * - Set up the Amazon Bedrock runtime client
 * - Create a message
 * - Configure and send a request
 * - Process the response
 */
public class Converse {

    public static String converse() {

        // Step 1: Create the Amazon Bedrock runtime client
        // The runtime client handles the communication with AI models on Amazon Bedrock
        BedrockRuntimeClient client = BedrockRuntimeClient.builder()
                .credentialsProvider(DefaultCredentialsProvider.create())
                .region(Region.US_EAST_1)
                .build();

        // Step 2: Specify which model to use
        // Available Amazon Nova models and their characteristics:
        // - Amazon Nova Micro: Text-only model optimized for lowest latency and cost
        // - Amazon Nova Lite:  Fast, low-cost multimodal model for image, video, and text
        // - Amazon Nova Pro:   Advanced multimodal model balancing accuracy, speed, and cost
        //
        // For the latest available models, see:
        // https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
        String modelId = "amazon.nova-lite-v1:0";

        // Step 3: Create the message
        // The message includes the text prompt and specifies that it comes from the user
        var inputText = "Describe the purpose of a 'hello world' program in one line.";
        var message = Message.builder()
                .content(ContentBlock.fromText(inputText))
                .role(ConversationRole.USER)
                .build();

        // Step 4: Configure the request
        // Optional parameters to control the model's response:
        // - maxTokens: maximum number of tokens to generate
        // - temperature: randomness (max: 1.0, default: 0.7)
        //   OR
        // - topP: diversity of word choice (max: 1.0, default: 0.9)
        // Note: Use either temperature OR topP, but not both
        ConverseRequest request = ConverseRequest.builder()
                .modelId(modelId)
                .messages(message)
                .inferenceConfig(config -> config
                                .maxTokens(500)     // The maximum response length
                                .temperature(0.5F)  // Using temperature for randomness control
                        //.topP(0.9F)       // Alternative: use topP instead of temperature
                ).build();

        // Step 5: Send and process the request
        // - Send the request to the model
        // - Extract and return the generated text from the response
        try {
            ConverseResponse response = client.converse(request);
            return response.output().message().content().get(0).text();

        } catch (SdkClientException e) {
            System.err.printf("ERROR: Can't invoke '%s'. Reason: %s", modelId, e.getMessage());
            throw new RuntimeException(e);
        }
    }

    public static void main(String[] args) {
        String response = converse();
        System.out.println(response);
    }
}

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Amazon Nova.

// Use the Conversation API to send a text message to Amazon Titan Text.

import {
  BedrockRuntimeClient,
  ConverseCommand,
} from "@aws-sdk/client-bedrock-runtime";

// Create a Bedrock Runtime client in the AWS Region you want to use.
const client = new BedrockRuntimeClient({ region: "us-east-1" });

// Set the model ID, e.g., Titan Text Premier.
const modelId = "amazon.titan-text-premier-v1:0";

// Start a conversation with the user message.
const userMessage =
  "Describe the purpose of a 'hello world' program in one line.";
const conversation = [
  {
    role: "user",
    content: [{ text: userMessage }],
  },
];

// Create a command with the model ID, the message, and a basic configuration.
const command = new ConverseCommand({
  modelId,
  messages: conversation,
  inferenceConfig: { maxTokens: 512, temperature: 0.5, topP: 0.9 },
});

try {
  // Send the command to the model and wait for the response
  const response = await client.send(command);

  // Extract and print the response text.
  const responseText = response.output.message.content[0].text;
  console.log(responseText);
} catch (err) {
  console.log(`ERROR: Can't invoke '${modelId}'. Reason: ${err}`);
  process.exit(1);
}

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Amazon Nova.

# Use the Conversation API to send a text message to Amazon Nova.

import boto3
from botocore.exceptions import ClientError

# Create a Bedrock Runtime client in the AWS Region you want to use.
client = boto3.client("bedrock-runtime", region_name="us-east-1")

# Set the model ID, e.g., Amazon Nova Lite.
model_id = "amazon.nova-lite-v1:0"

# Start a conversation with the user message.
user_message = "Describe the purpose of a 'hello world' program in one line."
conversation = [
    {
        "role": "user",
        "content": [{"text": user_message}],
    }
]

try:
    # Send the message to the model, using a basic inference configuration.
    response = client.converse(
        modelId=model_id,
        messages=conversation,
        inferenceConfig={"maxTokens": 512, "temperature": 0.5, "topP": 0.9},
    )

    # Extract and print the response text.
    response_text = response["output"]["message"]["content"][0]["text"]
    print(response_text)

except (ClientError, Exception) as e:
    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
    exit(1)