Invoke Amazon Titan Image on Amazon Bedrock to generate an image - Amazon Bedrock

Invoke Amazon Titan Image on Amazon Bedrock to generate an image

The following code examples show how to invoke Amazon Titan Image on Amazon Bedrock to generate an image.

Go
SDK for Go V2
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

Create an image with the Amazon Titan Image Generator.

type TitanImageRequest struct { TaskType string `json:"taskType"` TextToImageParams TextToImageParams `json:"textToImageParams"` ImageGenerationConfig ImageGenerationConfig `json:"imageGenerationConfig"` } type TextToImageParams struct { Text string `json:"text"` } type ImageGenerationConfig struct { NumberOfImages int `json:"numberOfImages"` Quality string `json:"quality"` CfgScale float64 `json:"cfgScale"` Height int `json:"height"` Width int `json:"width"` Seed int64 `json:"seed"` } type TitanImageResponse struct { Images []string `json:"images"` } // Invokes the Titan Image model to create an image using the input provided // in the request body. func (wrapper InvokeModelWrapper) InvokeTitanImage(ctx context.Context, prompt string, seed int64) (string, error) { modelId := "amazon.titan-image-generator-v1" body, err := json.Marshal(TitanImageRequest{ TaskType: "TEXT_IMAGE", TextToImageParams: TextToImageParams{ Text: prompt, }, ImageGenerationConfig: ImageGenerationConfig{ NumberOfImages: 1, Quality: "standard", CfgScale: 8.0, Height: 512, Width: 512, Seed: seed, }, }) if err != nil { log.Fatal("failed to marshal", err) } output, err := wrapper.BedrockRuntimeClient.InvokeModel(ctx, &bedrockruntime.InvokeModelInput{ ModelId: aws.String(modelId), ContentType: aws.String("application/json"), Body: body, }) if err != nil { ProcessError(err, modelId) } var response TitanImageResponse if err := json.Unmarshal(output.Body, &response); err != nil { log.Fatal("failed to unmarshal", err) } base64ImageData := response.Images[0] return base64ImageData, nil }
  • For API details, see InvokeModel in AWS SDK for Go API Reference.

Java
SDK for Java 2.x
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

Create an image with the Amazon Titan Image Generator.

// Create an image with the Amazon Titan Image Generator. 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.core.exception.SdkClientException; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeClient; import java.math.BigInteger; import java.security.SecureRandom; import static com.example.bedrockruntime.libs.ImageTools.displayImage; public class InvokeModel { public static String invokeModel() { // 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., Titan Image G1. var modelId = "amazon.titan-image-generator-v1"; // The InvokeModel 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-image.html var nativeRequestTemplate = """ { "taskType": "TEXT_IMAGE", "textToImageParams": { "text": "{{prompt}}" }, "imageGenerationConfig": { "seed": {{seed}} } }"""; // Define the prompt for the image generation. var prompt = "A stylized picture of a cute old steampunk robot"; // Get a random 31-bit seed for the image generation (max. 2,147,483,647). var seed = new BigInteger(31, new SecureRandom()); // Embed the prompt and seed in the model's native request payload. var nativeRequest = nativeRequestTemplate .replace("{{prompt}}", prompt) .replace("{{seed}}", seed.toString()); try { // Encode and send the request to the Bedrock Runtime. var response = client.invokeModel(request -> request .body(SdkBytes.fromUtf8String(nativeRequest)) .modelId(modelId) ); // Decode the response body. var responseBody = new JSONObject(response.body().asUtf8String()); // Retrieve the generated image data from the model's response. var base64ImageData = new JSONPointer("/images/0").queryFrom(responseBody).toString(); return base64ImageData; } 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) { System.out.println("Generating image. This may take a few seconds..."); String base64ImageData = invokeModel(); displayImage(base64ImageData); } }
  • For API details, see InvokeModel in AWS SDK for Java 2.x API Reference.

PHP
SDK for PHP
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

Create an image with the Amazon Titan Image Generator.

public function invokeTitanImage(string $prompt, int $seed) { # The different model providers have individual request and response formats. # For the format, ranges, and default values for Titan Image models refer to: # https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-titan-image.html $base64_image_data = ""; try { $modelId = 'amazon.titan-image-generator-v1'; $request = json_encode([ 'taskType' => 'TEXT_IMAGE', 'textToImageParams' => [ 'text' => $prompt ], 'imageGenerationConfig' => [ 'numberOfImages' => 1, 'quality' => 'standard', 'cfgScale' => 8.0, 'height' => 512, 'width' => 512, 'seed' => $seed ] ]); $result = $this->bedrockRuntimeClient->invokeModel([ 'contentType' => 'application/json', 'body' => $request, 'modelId' => $modelId, ]); $response_body = json_decode($result['body']); $base64_image_data = $response_body->images[0]; } catch (Exception $e) { echo "Error: ({$e->getCode()}) - {$e->getMessage()}\n"; } return $base64_image_data; }
  • For API details, see InvokeModel in AWS SDK for PHP API Reference.

Python
SDK for Python (Boto3)
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

Create an image with the Amazon Titan Image Generator.

# Use the native inference API to create an image with Amazon Titan Image Generator import base64 import boto3 import json import os import random # 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 Image Generator G1. model_id = "amazon.titan-image-generator-v1" # Define the image generation prompt for the model. prompt = "A stylized picture of a cute old steampunk robot." # Generate a random seed. seed = random.randint(0, 2147483647) # Format the request payload using the model's native structure. native_request = { "taskType": "TEXT_IMAGE", "textToImageParams": {"text": prompt}, "imageGenerationConfig": { "numberOfImages": 1, "quality": "standard", "cfgScale": 8.0, "height": 512, "width": 512, "seed": seed, }, } # Convert the native request to JSON. request = json.dumps(native_request) # Invoke the model with the request. response = client.invoke_model(modelId=model_id, body=request) # Decode the response body. model_response = json.loads(response["body"].read()) # Extract the image data. base64_image_data = model_response["images"][0] # Save the generated image to a local folder. i, output_dir = 1, "output" if not os.path.exists(output_dir): os.makedirs(output_dir) while os.path.exists(os.path.join(output_dir, f"titan_{i}.png")): i += 1 image_data = base64.b64decode(base64_image_data) image_path = os.path.join(output_dir, f"titan_{i}.png") with open(image_path, "wb") as file: file.write(image_data) print(f"The generated image has been saved to {image_path}")
  • For API details, see InvokeModel in AWS SDK for Python (Boto3) API Reference.

For a complete list of AWS SDK developer guides and code examples, see Using Amazon Bedrock with an AWS SDK. This topic also includes information about getting started and details about previous SDK versions.