Panggil Amazon Nova di Amazon Bedrock menggunakan API Converse Bedrock

Contoh kode berikut menunjukkan cara mengirim pesan teks ke Amazon Nova, menggunakan API Converse Bedrock.

.NET

SDK untuk .NET

catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di Repositori Contoh Kode AWS.

Kirim pesan teks ke Amazon Nova, menggunakan API Converse Bedrock.

// 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;
}

Kirim percakapan pesan ke Amazon Nova menggunakan API Converse Bedrock dengan konfigurasi alat.

/// <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;
        }
    }
}

• Untuk detail API, lihat Converse di Referensi AWS SDK untuk .NET API.

Java

SDK untuk Java 2.x

catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di Repositori Contoh Kode AWS.

Kirim pesan teks ke Amazon Nova menggunakan API Converse Bedrock dengan klien Java async.

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);
    }
}

Kirim pesan teks ke Amazon Nova, menggunakan API Converse Bedrock.

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);
    }
}

• Untuk detail API, lihat Converse di Referensi AWS SDK for Java 2.x API.

JavaScript

SDK untuk JavaScript (v3)

catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di Repositori Contoh Kode AWS.

Kirim pesan teks ke Amazon Nova, menggunakan API Converse Bedrock.

// This example demonstrates how to use the Amazon Nova foundation models 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

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

// Step 1: Create the Amazon Bedrock runtime client
// Credentials will be automatically loaded from the environment
const client = new BedrockRuntimeClient({ region: "us-east-1" });

// 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 most current model IDs, see:
// https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
const 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
const inputText =
  "Describe the purpose of a 'hello world' program in one line.";
const message = {
  content: [{ text: inputText }],
  role: ConversationRole.USER,
};

// 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
const request = {
  modelId,
  messages: [message],
  inferenceConfig: {
    maxTokens: 500, // The maximum response length
    temperature: 0.5, // Using temperature for randomness control
    //topP: 0.9,        // Alternative: use topP instead of temperature
  },
};

// Step 5: Send and process the request
// - Send the request to the model
// - Extract and return the generated text from the response
try {
  const response = await client.send(new ConverseCommand(request));
  console.log(response.output.message.content[0].text);
} catch (error) {
  console.error(`ERROR: Can't invoke '${modelId}'. Reason: ${error.message}`);
  throw error;
}

• Untuk detail API, lihat Converse di Referensi AWS SDK untuk JavaScript API.

Kotlin

SDK untuk Kotlin

catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di Repositori Contoh Kode AWS.

Kirim pesan teks ke Amazon Nova, menggunakan API Converse Bedrock.

import aws.sdk.kotlin.services.bedrockruntime.BedrockRuntimeClient
import aws.sdk.kotlin.services.bedrockruntime.model.ContentBlock
import aws.sdk.kotlin.services.bedrockruntime.model.ConversationRole
import aws.sdk.kotlin.services.bedrockruntime.model.ConverseRequest
import aws.sdk.kotlin.services.bedrockruntime.model.Message

/**
 * This example demonstrates how to use the Amazon Nova foundation models 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
 */
suspend fun main() {
    converse().also { println(it) }
}

suspend fun converse(): String {
    // Create and configure the Bedrock runtime client
    BedrockRuntimeClient { region = "us-east-1" }.use { client ->

        // Specify the model ID. For the latest available models, see:
        // https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
        val modelId = "amazon.nova-lite-v1:0"

        // Create the message with the user's prompt
        val prompt = "Describe the purpose of a 'hello world' program in one line."
        val message = Message {
            role = ConversationRole.User
            content = listOf(ContentBlock.Text(prompt))
        }

        // Configure the request with optional model parameters
        val request = ConverseRequest {
            this.modelId = modelId
            messages = listOf(message)
            inferenceConfig {
                maxTokens = 500 // Maximum response length
                temperature = 0.5F // Lower values: more focused output
                // topP = 0.8F // Alternative to temperature
            }
        }

        // Send the request and process the model's response
        runCatching {
            val response = client.converse(request)
            return response.output!!.asMessage().content.first().asText()
        }.getOrElse { error ->
            error.message?.let { e -> System.err.println("ERROR: Can't invoke '$modelId'. Reason: $e") }
            throw RuntimeException("Failed to generate text with model $modelId", error)
        }
    }
}

• Untuk detail API, lihat Converse in AWS SDK untuk referensi API Kotlin.

Python

SDK untuk Python (Boto3)

catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara mengatur dan menjalankannya di Repositori Contoh Kode AWS.

Kirim pesan teks ke Amazon Nova, menggunakan API Converse Bedrock.

# 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)

• Untuk detail API, lihat Converse in AWS SDK for Python (Boto3) Referensi API.

Untuk daftar lengkap panduan pengembang AWS SDK dan contoh kode, lihatMenggunakan Amazon Bedrock dengan SDK AWS. Topik ini juga mencakup informasi tentang memulai dan detail tentang versi SDK sebelumnya.