Rufen Sie Anthropic Claude auf Amazon Bedrock mithilfe der Converse-API von Bedrock mit einem Antwortstream auf

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Die folgenden Codebeispiele zeigen, wie Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Anthropic Claude senden und den Antwortstream in Echtzeit verarbeiten.

.NET

AWS SDK for .NET

Anmerkung

Es gibt noch mehr dazu. GitHub Sie sehen das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel-Repository einrichten und ausführen.

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Anthropic Claude und verarbeiten Sie den Antwortstream in Echtzeit.

// Use the Converse API to send a text message to Anthropic Claude
// and print the response stream.

using System;
using System.Collections.Generic;
using System.Linq;
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., Claude 3 Haiku.
var modelId = "anthropic.claude-3-haiku-20240307-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 ConverseStreamRequest
{
    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.ConverseStreamAsync(request);

    // Extract and print the streamed response text in real-time.
    foreach (var chunk in response.Stream.AsEnumerable())
    {
        if (chunk is ContentBlockDeltaEvent)
        {
            Console.Write((chunk as ContentBlockDeltaEvent).Delta.Text);
        }
    }
}
catch (AmazonBedrockRuntimeException e)
{
    Console.WriteLine($"ERROR: Can't invoke '{modelId}'. Reason: {e.Message}");
    throw;
}

• Einzelheiten zur API finden Sie ConverseStreamin AWS SDK for .NET der API-Referenz.

Java

SDK für Java 2.x

Anmerkung

Es gibt noch mehr dazu GitHub. Sie sehen das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel-Repository einrichten und ausführen.

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Anthropic Claude und verarbeiten Sie den Antwortstream in Echtzeit.

// Use the Converse API to send a text message to Anthropic Claude
// and print the response stream.

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.ContentBlock;
import software.amazon.awssdk.services.bedrockruntime.model.ConversationRole;
import software.amazon.awssdk.services.bedrockruntime.model.ConverseStreamResponseHandler;
import software.amazon.awssdk.services.bedrockruntime.model.Message;

import java.util.concurrent.ExecutionException;

public class ConverseStream {

    public static void main(String[] args) {

        // Create a Bedrock Runtime client in the AWS Region you want to use.
        // Replace the DefaultCredentialsProvider with your preferred credentials provider.
        var client = BedrockRuntimeAsyncClient.builder()
                .credentialsProvider(DefaultCredentialsProvider.create())
                .region(Region.US_EAST_1)
                .build();

        // Set the model ID, e.g., Claude 3 Haiku.
        var modelId = "anthropic.claude-3-haiku-20240307-v1:0";

        // Create the input text and embed it in a message object with the user role.
        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();

        // Create a handler to extract and print the response text in real-time.
        var responseStreamHandler = ConverseStreamResponseHandler.builder()
                .subscriber(ConverseStreamResponseHandler.Visitor.builder()
                        .onContentBlockDelta(chunk -> {
                            String responseText = chunk.delta().text();
                            System.out.print(responseText);
                        }).build()
                ).onError(err ->
                        System.err.printf("Can't invoke '%s': %s", modelId, err.getMessage())
                ).build();

        try {
            // Send the message with a basic inference configuration and attach the handler.
            client.converseStream(request -> request.modelId(modelId)
                    .messages(message)
                    .inferenceConfig(config -> config
                            .maxTokens(512)
                            .temperature(0.5F)
                            .topP(0.9F)
                    ), responseStreamHandler).get();

        } catch (ExecutionException | InterruptedException e) {
            System.err.printf("Can't invoke '%s': %s", modelId, e.getCause().getMessage());
        }
    }
}

• Einzelheiten zur API finden Sie ConverseStreamin AWS SDK for Java 2.x der API-Referenz.

JavaScript

SDK für JavaScript (v3)

Anmerkung

Es gibt noch mehr dazu GitHub. Sie sehen das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel-Repository einrichten und ausführen.

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Anthropic Claude und verarbeiten Sie den Antwortstream in Echtzeit.

// Use the Conversation API to send a text message to Anthropic Claude.

import {
  BedrockRuntimeClient,
  ConverseStreamCommand,
} 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., Claude 3 Haiku.
const modelId = "anthropic.claude-3-haiku-20240307-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 ConverseStreamCommand({
  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 streamed response text in real-time.
  for await (const item of response.stream) {
    if (item.contentBlockDelta) {
      process.stdout.write(item.contentBlockDelta.delta?.text);
    }
  }
} catch (err) {
  console.log(`ERROR: Can't invoke '${modelId}'. Reason: ${err}`);
  process.exit(1);
}

• Einzelheiten zur API finden Sie ConverseStreamin AWS SDK for JavaScript der API-Referenz.

Python

SDK für Python (Boto3)

Anmerkung

Es gibt noch mehr dazu GitHub. Sie sehen das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel-Repository einrichten und ausführen.

Senden Sie mithilfe der Converse-API von Bedrock eine Textnachricht an Anthropic Claude und verarbeiten Sie den Antwortstream in Echtzeit.

# Use the Conversation API to send a text message to Anthropic Claude
# and print the response stream.

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., Claude 3 Haiku.
model_id = "anthropic.claude-3-haiku-20240307-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.
    streaming_response = client.converse_stream(
        modelId=model_id,
        messages=conversation,
        inferenceConfig={"maxTokens": 512, "temperature": 0.5, "topP": 0.9},
    )

    # Extract and print the streamed response text in real-time.
    for chunk in streaming_response["stream"]:
        if "contentBlockDelta" in chunk:
            text = chunk["contentBlockDelta"]["delta"]["text"]
            print(text, end="")

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

• Einzelheiten zur API finden Sie ConverseStreamin AWS SDK for Python (Boto3) API Reference.

Rust

SDK für Rust

Anmerkung

Es gibt noch mehr dazu. GitHub Sie sehen das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel-Repository einrichten und ausführen.

Senden Sie mithilfe der Bedrock-API eine Textnachricht an Anthropic Claude und streamen Sie Antwort-Token. ConverseStream

#[tokio::main]
async fn main() -> Result<(), BedrockConverseStreamError> {
    tracing_subscriber::fmt::init();
    let sdk_config = aws_config::defaults(BehaviorVersion::latest())
        .region(CLAUDE_REGION)
        .load()
        .await;
    let client = Client::new(&sdk_config);

    let response = client
        .converse_stream()
        .model_id(MODEL_ID)
        .messages(
            Message::builder()
                .role(ConversationRole::User)
                .content(ContentBlock::Text(USER_MESSAGE.to_string()))
                .build()
                .map_err(|_| "failed to build message")?,
        )
        .send()
        .await;

    let mut stream = match response {
        Ok(output) => Ok(output.stream),
        Err(e) => Err(BedrockConverseStreamError::from(
            e.as_service_error().unwrap(),
        )),
    }?;

    loop {
        let token = stream.recv().await;
        match token {
            Ok(Some(text)) => {
                let next = get_converse_output_text(text)?;
                print!("{}", next);
                Ok(())
            }
            Ok(None) => break,
            Err(e) => Err(e
                .as_service_error()
                .map(BedrockConverseStreamError::from)
                .unwrap_or(BedrockConverseStreamError(
                    "Unknown error receiving stream".into(),
                ))),
        }?
    }

    println!();

    Ok(())
}

fn get_converse_output_text(
    output: ConverseStreamOutputType,
) -> Result<String, BedrockConverseStreamError> {
    Ok(match output {
        ConverseStreamOutputType::ContentBlockDelta(event) => match event.delta() {
            Some(delta) => delta.as_text().cloned().unwrap_or_else(|_| "".into()),
            None => "".into(),
        },
        _ => "".into(),
    })
}

Verwenden Sie Anweisungen, das Error-Hilfsprogramm und Konstanten.

use aws_config::BehaviorVersion;
use aws_sdk_bedrockruntime::{
    error::ProvideErrorMetadata,
    operation::converse_stream::ConverseStreamError,
    types::{
        error::ConverseStreamOutputError, ContentBlock, ConversationRole,
        ConverseStreamOutput as ConverseStreamOutputType, Message,
    },
    Client,
};

// Set the model ID, e.g., Claude 3 Haiku.
const MODEL_ID: &str = "anthropic.claude-3-haiku-20240307-v1:0";
const CLAUDE_REGION: &str = "us-east-1";

// Start a conversation with the user message.
const USER_MESSAGE: &str = "Describe the purpose of a 'hello world' program in one line.";

#[derive(Debug)]
struct BedrockConverseStreamError(String);
impl std::fmt::Display for BedrockConverseStreamError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        write!(f, "Can't invoke '{}'. Reason: {}", MODEL_ID, self.0)
    }
}
impl std::error::Error for BedrockConverseStreamError {}
impl From<&str> for BedrockConverseStreamError {
    fn from(value: &str) -> Self {
        BedrockConverseStreamError(value.into())
    }
}

impl From<&ConverseStreamError> for BedrockConverseStreamError {
    fn from(value: &ConverseStreamError) -> Self {
        BedrockConverseStreamError(
            match value {
                ConverseStreamError::ModelTimeoutException(_) => "Model took too long",
                ConverseStreamError::ModelNotReadyException(_) => "Model is not ready",
                _ => "Unknown",
            }
            .into(),
        )
    }
}

impl From<&ConverseStreamOutputError> for BedrockConverseStreamError {
    fn from(value: &ConverseStreamOutputError) -> Self {
        match value {
            ConverseStreamOutputError::ValidationException(ve) => BedrockConverseStreamError(
                ve.message().unwrap_or("Unknown ValidationException").into(),
            ),
            ConverseStreamOutputError::ThrottlingException(te) => BedrockConverseStreamError(
                te.message().unwrap_or("Unknown ThrottlingException").into(),
            ),
            value => BedrockConverseStreamError(
                value
                    .message()
                    .unwrap_or("Unknown StreamOutput exception")
                    .into(),
            ),
        }
    }
}

• Einzelheiten zur API finden Sie ConverseStreamin der API-Referenz zum AWS SDK für Rust.