Invoquez des modèles Amazon Titan Text sur Amazon Bedrock à l'aide du modèle Invoke API avec un flux de réponse - Exemples de code de l'AWS SDK

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Invoquez des modèles Amazon Titan Text sur Amazon Bedrock à l'aide du modèle Invoke API avec un flux de réponse

Les exemples de code suivants montrent comment envoyer un message texte aux modèles Amazon Titan Text, à l'aide du modèle InvokeAPI, et comment imprimer le flux de réponses.

.NET
AWS SDK for .NET
Note

Il y en a plus sur GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.

Utilisez le modèle Invoke API pour envoyer un message texte et traiter le flux de réponses en temps réel.

// Use the native inference API to send a text message to Amazon Titan Text // and print the response stream. using System; using System.IO; using System.Text.Json; using System.Text.Json.Nodes; 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., Titan Text Premier. var modelId = "amazon.titan-text-premier-v1:0"; // Define the user message. var userMessage = "Describe the purpose of a 'hello world' program in one line."; //Format the request payload using the model's native structure. var nativeRequest = JsonSerializer.Serialize(new { inputText = userMessage, textGenerationConfig = new { maxTokenCount = 512, temperature = 0.5 } }); // Create a request with the model ID and the model's native request payload. var request = new InvokeModelWithResponseStreamRequest() { ModelId = modelId, Body = new MemoryStream(System.Text.Encoding.UTF8.GetBytes(nativeRequest)), ContentType = "application/json" }; try { // Send the request to the Bedrock Runtime and wait for the response. var streamingResponse = await client.InvokeModelWithResponseStreamAsync(request); // Extract and print the streamed response text in real-time. foreach (var item in streamingResponse.Body) { var chunk = JsonSerializer.Deserialize<JsonObject>((item as PayloadPart).Bytes); var text = chunk["outputText"] ?? ""; Console.Write(text); } } catch (AmazonBedrockRuntimeException e) { Console.WriteLine($"ERROR: Can't invoke '{modelId}'. Reason: {e.Message}"); throw; }
Java
SDKpour Java 2.x
Note

Il y en a plus sur GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.

Utilisez le modèle Invoke API pour envoyer un message texte et traiter le flux de réponses en temps réel.

// Use the native inference API to send a text message to Amazon Titan Text // and print the response stream. import org.json.JSONObject; import org.json.JSONPointer; import software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider; import software.amazon.awssdk.core.SdkBytes; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeAsyncClient; import software.amazon.awssdk.services.bedrockruntime.model.InvokeModelWithResponseStreamRequest; import software.amazon.awssdk.services.bedrockruntime.model.InvokeModelWithResponseStreamResponseHandler; import java.util.concurrent.ExecutionException; import static software.amazon.awssdk.services.bedrockruntime.model.InvokeModelWithResponseStreamResponseHandler.Visitor; public class InvokeModelWithResponseStream { public static String invokeModelWithResponseStream() throws ExecutionException, InterruptedException { // 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., Titan Text Premier. var modelId = "amazon.titan-text-premier-v1:0"; // The InvokeModelWithResponseStream API uses the model's native payload. // Learn more about the available inference parameters and response fields at: // https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-titan-text.html var nativeRequestTemplate = "{ \"inputText\": \"{{prompt}}\" }"; // Define the prompt for the model. var prompt = "Describe the purpose of a 'hello world' program in one line."; // Embed the prompt in the model's native request payload. String nativeRequest = nativeRequestTemplate.replace("{{prompt}}", prompt); // Create a request with the model ID and the model's native request payload. var request = InvokeModelWithResponseStreamRequest.builder() .body(SdkBytes.fromUtf8String(nativeRequest)) .modelId(modelId) .build(); // Prepare a buffer to accumulate the generated response text. var completeResponseTextBuffer = new StringBuilder(); // Prepare a handler to extract, accumulate, and print the response text in real-time. var responseStreamHandler = InvokeModelWithResponseStreamResponseHandler.builder() .subscriber(Visitor.builder().onChunk(chunk -> { // Extract and print the text from the model's native response. var response = new JSONObject(chunk.bytes().asUtf8String()); var text = new JSONPointer("/outputText").queryFrom(response); System.out.print(text); // Append the text to the response text buffer. completeResponseTextBuffer.append(text); }).build()).build(); try { // Send the request and wait for the handler to process the response. client.invokeModelWithResponseStream(request, responseStreamHandler).get(); // Return the complete response text. return completeResponseTextBuffer.toString(); } catch (ExecutionException | InterruptedException e) { System.err.printf("Can't invoke '%s': %s", modelId, e.getCause().getMessage()); throw new RuntimeException(e); } } public static void main(String[] args) throws ExecutionException, InterruptedException { invokeModelWithResponseStream(); } }
Python
SDKpour Python (Boto3)
Note

Il y en a plus sur GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.

Utilisez le modèle Invoke API pour envoyer un message texte et traiter le flux de réponses en temps réel.

# Use the native inference API to send a text message to Amazon Titan Text # and print the response stream. import boto3 import json # Create a Bedrock Runtime client in the AWS Region of your choice. client = boto3.client("bedrock-runtime", region_name="us-east-1") # Set the model ID, e.g., Titan Text Premier. model_id = "amazon.titan-text-premier-v1:0" # Define the prompt for the model. prompt = "Describe the purpose of a 'hello world' program in one line." # Format the request payload using the model's native structure. native_request = { "inputText": prompt, "textGenerationConfig": { "maxTokenCount": 512, "temperature": 0.5, }, } # Convert the native request to JSON. request = json.dumps(native_request) # Invoke the model with the request. streaming_response = client.invoke_model_with_response_stream( modelId=model_id, body=request ) # Extract and print the response text in real-time. for event in streaming_response["body"]: chunk = json.loads(event["chunk"]["bytes"]) if "outputText" in chunk: print(chunk["outputText"], end="")