Rufen Sie Anthropic Claude auf Amazon Bedrock mit Bedrocks Converse auf API - Amazon Bedrock

Die vorliegende Übersetzung wurde maschinell erstellt. Im Falle eines Konflikts oder eines Widerspruchs zwischen dieser übersetzten Fassung und der englischen Fassung (einschließlich infolge von Verzögerungen bei der Übersetzung) ist die englische Fassung maßgeblich.

Rufen Sie Anthropic Claude auf Amazon Bedrock mit Bedrocks Converse auf API

Die folgenden Codebeispiele zeigen, wie Sie mithilfe von Bedrocks Converse eine Textnachricht an Anthropic Claude senden. API

.NET
AWS SDK for .NET
Anmerkung

Es gibt noch mehr dazu GitHub. Das vollständige Beispiel und Informationen zur Einrichtung und Ausführung finden Sie in AWS Repository mit Codebeispielen.

Senden Sie mithilfe von Bedrocks Converse eine Textnachricht an Anthropic Claude. API

// Use the Converse API to send a text message to Anthropic Claude. 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., 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 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; }
Java
SDKfür Java 2.x
Anmerkung

Es gibt noch mehr dazu. GitHub Das vollständige Beispiel und Informationen zur Einrichtung und Ausführung finden Sie in AWS Repository mit Codebeispielen.

Senden Sie mithilfe von Bedrocks Converse eine Textnachricht an Anthropic Claude. API

// Use the Converse API to send a text message to Anthropic Claude. 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.ContentBlock; import software.amazon.awssdk.services.bedrockruntime.model.ConversationRole; import software.amazon.awssdk.services.bedrockruntime.model.ConverseResponse; import software.amazon.awssdk.services.bedrockruntime.model.Message; public class Converse { public static String converse() { // Create a Bedrock Runtime client in the AWS Region you want to use. // Replace the DefaultCredentialsProvider with your preferred credentials provider. var client = BedrockRuntimeClient.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(); try { // Send the message with a basic inference configuration. ConverseResponse response = client.converse(request -> request .modelId(modelId) .messages(message) .inferenceConfig(config -> config .maxTokens(512) .temperature(0.5F) .topP(0.9F))); // Retrieve the generated text from Bedrock's response object. var responseText = response.output().message().content().get(0).text(); System.out.println(responseText); return responseText; } 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) { converse(); } }

Senden Sie mithilfe von Bedrocks Converse API mit dem asynchronen Java-Client eine Textnachricht an Anthropic Claude.

// Use the Converse API to send a text message to Anthropic Claude // with the async Java client. 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.Message; import java.util.concurrent.CompletableFuture; import java.util.concurrent.ExecutionException; public class ConverseAsync { public static String converseAsync() { // 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(); // Send the message with a basic inference configuration. var request = client.converse(params -> params .modelId(modelId) .messages(message) .inferenceConfig(config -> config .maxTokens(512) .temperature(0.5F) .topP(0.9F)) ); // Prepare a future object to handle the asynchronous response. CompletableFuture<String> future = new CompletableFuture<>(); // Handle the response or error using the future object. request.whenComplete((response, error) -> { if (error == null) { // Extract the generated text from Bedrock's response object. String responseText = response.output().message().content().get(0).text(); future.complete(responseText); } else { future.completeExceptionally(error); } }); try { // Wait for the future object to complete and retrieve the generated text. String responseText = future.get(); System.out.println(responseText); return responseText; } catch (ExecutionException | InterruptedException e) { System.err.printf("Can't invoke '%s': %s", modelId, e.getMessage()); throw new RuntimeException(e); } } public static void main(String[] args) { converseAsync(); } }
JavaScript
SDKfür JavaScript (v3)
Anmerkung

Es gibt noch mehr dazu GitHub. Das vollständige Beispiel und Informationen zur Einrichtung und Ausführung finden Sie in AWS Repository mit Codebeispielen.

Senden Sie mithilfe von Bedrocks Converse eine Textnachricht an Anthropic Claude. API

// Use the Conversation API to send a text message to Anthropic Claude. 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., 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 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); }
Python
SDKfür Python (Boto3)
Anmerkung

Es gibt noch mehr dazu. GitHub Das vollständige Beispiel und Informationen zur Einrichtung und Ausführung finden Sie in AWS Repository mit Codebeispielen.

Senden Sie mithilfe von Bedrocks Converse eine Textnachricht an Anthropic Claude. API

# Use the Conversation API to send a text message to Anthropic Claude. 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. 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)
Rust
SDKfür Rust
Anmerkung

Es gibt noch mehr dazu GitHub. Das vollständige Beispiel und Informationen zur Einrichtung und Ausführung finden Sie in AWS Repository mit Codebeispielen.

Senden Sie mithilfe von Bedrocks Converse eine Textnachricht an Anthropic Claude. API

#[tokio::main] async fn main() -> Result<(), BedrockConverseError> { 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() .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; match response { Ok(output) => { let text = get_converse_output_text(output)?; println!("{}", text); Ok(()) } Err(e) => Err(e .as_service_error() .map(BedrockConverseError::from) .unwrap_or_else(|| BedrockConverseError("Unknown service error".into()))), } } fn get_converse_output_text(output: ConverseOutput) -> Result<String, BedrockConverseError> { let text = output .output() .ok_or("no output")? .as_message() .map_err(|_| "output not a message")? .content() .first() .ok_or("no content in message")? .as_text() .map_err(|_| "content is not text")? .to_string(); Ok(text) }

Verwenden Sie Anweisungen, das Error-Hilfsprogramm und Konstanten.

use aws_config::BehaviorVersion; use aws_sdk_bedrockruntime::{ operation::converse::{ConverseError, ConverseOutput}, types::{ContentBlock, ConversationRole, 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 BedrockConverseError(String); impl std::fmt::Display for BedrockConverseError { 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 BedrockConverseError {} impl From<&str> for BedrockConverseError { fn from(value: &str) -> Self { BedrockConverseError(value.to_string()) } } impl From<&ConverseError> for BedrockConverseError { fn from(value: &ConverseError) -> Self { BedrockConverseError::from(match value { ConverseError::ModelTimeoutException(_) => "Model took too long", ConverseError::ModelNotReadyException(_) => "Model is not ready", _ => "Unknown", }) } }
  • APIEinzelheiten finden Sie unter Converse in AWS SDKals API Referenz auf Rust.

Für eine vollständige Liste von AWS SDKEntwicklerhandbücher und Codebeispiele finden Sie unterNutzung dieses Dienstes mit einem AWS SDK. Dieses Thema enthält auch Informationen zu den ersten Schritten und Details zu früheren SDK Versionen.