Richiama Anthropic Claude su Amazon Bedrock utilizzando Converse di Bedrock API - Amazon Bedrock

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Richiama Anthropic Claude su Amazon Bedrock utilizzando Converse di Bedrock API

I seguenti esempi di codice mostrano come inviare un messaggio di testo a Anthropic Claude utilizzando Converse di Bedrock. API

.NET
AWS SDK for .NET
Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

Invia un messaggio di testo a Anthropic Claude, usando le Converse di Bedrock. 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
SDKper Java 2.x
Nota

C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

Invia un messaggio di testo a Anthropic Claude, usando le Converse di Bedrock. 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(); } }

Invia un messaggio di testo a Anthropic Claude utilizzando Converse di Bedrock con il client Java asincrono. API

// 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
SDKper JavaScript (v3)
Nota

C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

Invia un messaggio di testo a Anthropic Claude, usando le Converse di Bedrock. 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
SDKper Python (Boto3)
Nota

C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

Invia un messaggio di testo a Anthropic Claude, usando le Converse di Bedrock. 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)
  • Per API i dettagli, consulta Converse in AWS SDKfor Python (APIBoto3) Reference.

Rust
SDKper Rust
Nota

c'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel Repository di esempi di codice AWS.

Invia un messaggio di testo a Anthropic Claude, usando le Converse di Bedrock. 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) }

Usa istruzioni, utilità Error e costanti.

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", }) } }
  • Per API i dettagli, consulta Converse in AWS SDKfor Rust API reference.

Per un elenco completo delle guide per AWS SDK gli sviluppatori e degli esempi di codice, consultaUtilizzo di Amazon Bedrock con un AWS SDK. Questo argomento include anche informazioni su come iniziare e dettagli sulle SDK versioni precedenti.