# Invoke Stability.ai Stable Diffusion on Amazon Bedrock to generate an image The following code examples show how to invoke Stability.ai Stable Diffusion on Amazon Bedrock to generate an image. ------ #### [ Java ] **SDK for Java 2.x** There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/bedrock-runtime#code-examples). Create an image with Stable Diffusion. ``` // Create an image with Stability AI Stable Image Core. 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_WEST_2) .build(); // Set the model ID, e.g., Stable Image Core. var modelId = "stability.stable-image-core-v1:1"; // 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-diffusion-stable-image-core-text-image-request-response.html var nativeRequestTemplate = """ { "prompt": "{{prompt}}", "aspect_ratio": "1:1", "seed": {{seed}}, "output_format": "png" }"""; // Define the prompt for the image generation. var prompt = "A stylized picture of a cute old steampunk robot"; // Get a random seed for the image generation (max. 4,294,967,294). var seed = new BigInteger(31, new SecureRandom()); // Embed the prompt and seed in the model's native request payload. String 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](https://docs.aws.amazon.com/goto/SdkForJavaV2/bedrock-runtime-2023-09-30/InvokeModel) in *AWS SDK for Java 2.x API Reference*. ------ #### [ PHP ] **SDK for PHP** There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/php/example_code/bedrock-runtime#code-examples). Create an image with Stable Diffusion. ``` public function invokeStableDiffusion(string $prompt, int $seed = 0, string $aspect_ratio = '1:1') { // The different model providers have individual request and response formats. // For the format, ranges, and available parameters of Stable Diffusion models refer to: // https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-stability-diffusion.html $base64_image_data = ""; try { $modelId = 'stability.stable-image-core-v1:1'; $body = [ 'prompt' => $prompt, 'aspect_ratio' => $aspect_ratio, 'seed' => $seed, 'output_format' => 'png', ]; $result = $this->bedrockRuntimeClient->invokeModel([ 'contentType' => 'application/json', 'body' => json_encode($body), '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](https://docs.aws.amazon.com/goto/SdkForPHPV3/bedrock-runtime-2023-09-30/InvokeModel) in *AWS SDK for PHP API Reference*. ------ #### [ Python ] **SDK for Python (Boto3)** There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/bedrock-runtime#code-examples). Create an image with Stable Diffusion. ``` # Use the native inference API to create an image with Stability AI Stable Image Core 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-west-2") # Set the model ID, e.g., Stable Image Core. model_id = "stability.stable-image-core-v1:1" # 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, 4294967295) # Format the request payload using the model's native structure. native_request = { "prompt": prompt, "aspect_ratio": "1:1", "seed": seed, "output_format": "png", } # 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"stability_{i}.png")): i += 1 image_data = base64.b64decode(base64_image_data) image_path = os.path.join(output_dir, f"stability_{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](https://docs.aws.amazon.com/goto/boto3/bedrock-runtime-2023-09-30/InvokeModel) in *AWS SDK for Python (Boto3) API Reference*. ------ #### [ SAP ABAP ] **SDK for SAP ABAP** There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/bdr#code-examples). Create an image with Stable Diffusion. ``` "Stable Image Core Input Parameters should be in a format like this: * { * "prompt": "Draw a dolphin with a mustache, photorealistic", * "aspect_ratio": "1:1", * "seed": 0, * "output_format": "png" * } DATA: BEGIN OF ls_input, prompt TYPE /aws1/rt_shape_string, aspect_ratio TYPE /aws1/rt_shape_string, seed TYPE /aws1/rt_shape_integer, output_format TYPE /aws1/rt_shape_string, END OF ls_input. ls_input-prompt = iv_prompt. ls_input-aspect_ratio = '1:1'. ls_input-seed = 0. "or better, choose a random integer. ls_input-output_format = 'png'. DATA(lv_json) = /ui2/cl_json=>serialize( data = ls_input pretty_name = /ui2/cl_json=>pretty_mode-low_case ). TRY. DATA(lo_response) = lo_bdr->invokemodel( iv_body = /aws1/cl_rt_util=>string_to_xstring( lv_json ) iv_modelid = 'stability.stable-image-core-v1:1' iv_accept = 'application/json' iv_contenttype = 'application/json' ). "Stable Image Core Result Format: * { * "seeds": ["0"], * "finish_reasons": [null], * "images": ["iVBORw0KGgoAAAANSUhEUgAAAgAAA...."] * } DATA: BEGIN OF ls_response, images TYPE STANDARD TABLE OF /aws1/rt_shape_string, END OF ls_response. /ui2/cl_json=>deserialize( EXPORTING jsonx = lo_response->get_body( ) pretty_name = /ui2/cl_json=>pretty_mode-camel_case CHANGING data = ls_response ). IF ls_response-images IS NOT INITIAL. DATA(lv_image) = cl_http_utility=>if_http_utility~decode_x_base64( ls_response-images[ 1 ] ). ENDIF. CATCH /aws1/cx_bdraccessdeniedex INTO DATA(lo_ex). WRITE / lo_ex->get_text( ). WRITE / |Don't forget to enable model access at https://console.aws.amazon.com/bedrock/home?#/modelaccess|. ENDTRY. ``` Invoke the Stability.ai Stable Diffusion XL foundation model to generate images using L2 high level client. ``` TRY. DATA(lo_bdr_l2_sd) = /aws1/cl_bdr_l2_factory=>create_stable_diffusion_xl_1( lo_bdr ). " iv_prompt contains a prompt like 'Show me a picture of a unicorn reading an enterprise financial report'. DATA(lv_image) = lo_bdr_l2_sd->text_to_image( iv_prompt ). CATCH /aws1/cx_bdraccessdeniedex INTO DATA(lo_ex). WRITE / lo_ex->get_text( ). WRITE / |Don't forget to enable model access at https://console.aws.amazon.com/bedrock/home?#/modelaccess|. ENDTRY. ``` + For API details, see [InvokeModel](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. ------ For a complete list of AWS SDK developer guides and code examples, see [Using Amazon Bedrock with an AWS SDK](sdk-general-information-section.md). This topic also includes information about getting started and details about previous SDK versions.