Les traductions sont fournies par des outils de traduction automatique. En cas de conflit entre le contenu d'une traduction et celui de la version originale en anglais, la version anglaise prévaudra. # Invoquez Stability.ai Stable Image Core sur Amazon Bedrock pour générer une image Les exemples de code suivants montrent comment invoquer Stability.ai Stable Image Core sur Amazon Bedrock pour générer une image. ------ #### [ .NET ] **SDK pour .NET** Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/dotnetv3/Bedrock-runtime#code-examples). Créez une image avec Stable Image Core. ``` /// /// Asynchronously invokes the Stability.ai Stable Image Core model to run an inference based on the provided input. /// /// The prompt that describes the image Stability.ai Stable Image Core has to generate. /// A base-64 encoded image generated by model /// /// The different model providers have individual request and response formats. /// For the format, ranges, and default values for Stability.ai Stable Image Core, refer to: /// https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-diffusion-stable-image-core-text-image-request-response.html /// public static async Task InvokeStableImageCoreAsync(string prompt, int seed) { string stableImageCoreModelId = "stability.stable-image-core-v1:1"; AmazonBedrockRuntimeClient client = new(RegionEndpoint.USWest2); string payload = new JsonObject() { { "prompt", prompt }, { "aspect_ratio", "1:1" }, { "seed", seed }, { "output_format", "png" } }.ToJsonString(); try { InvokeModelResponse response = await client.InvokeModelAsync(new InvokeModelRequest() { ModelId = stableImageCoreModelId, Body = AWSSDKUtils.GenerateMemoryStreamFromString(payload), ContentType = "application/json", Accept = "application/json" }); if (response.HttpStatusCode == System.Net.HttpStatusCode.OK) { var results = JsonNode.ParseAsync(response.Body).Result?["images"]?.AsArray(); return results?[0]?.GetValue(); } else { Console.WriteLine("InvokeModelAsync failed with status code " + response.HttpStatusCode); } } catch (AmazonBedrockRuntimeException e) { Console.WriteLine(e.Message); } return null; } ``` + Pour plus de détails sur l'API, consultez [ InvokeModel ](https://docs.aws.amazon.com/goto/DotNetSDKV3/bedrock-runtime-2023-09-30/InvokeModel) la section Référence de *AWS SDK pour .NET l'API*. **SDK pour .NET (v4)** Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/dotnetv4/Bedrock-runtime#code-examples). Créez une image avec Stable Image Core. ``` /// /// Asynchronously invokes the Stability.ai Stable Image Core model to run an inference based on the provided input. /// /// The prompt that describes the image Stability.ai Stable Image Core has to generate. /// A base-64 encoded image generated by model /// /// The different model providers have individual request and response formats. /// For the format, ranges, and default values for Stability.ai Stable Image Core, refer to: /// https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-diffusion-stable-image-core-text-image-request-response.html /// public static async Task InvokeStableImageCoreAsync(string prompt, int seed) { string stableImageCoreModelId = "stability.stable-image-core-v1:1"; AmazonBedrockRuntimeClient client = new(RegionEndpoint.USWest2); string payload = new JsonObject() { { "prompt", prompt }, { "aspect_ratio", "1:1" }, { "seed", seed }, { "output_format", "png" } }.ToJsonString(); try { InvokeModelResponse response = await client.InvokeModelAsync(new InvokeModelRequest() { ModelId = stableImageCoreModelId, Body = AWSSDKUtils.GenerateMemoryStreamFromString(payload), ContentType = "application/json", Accept = "application/json" }); if (response.HttpStatusCode == System.Net.HttpStatusCode.OK) { var results = JsonNode.ParseAsync(response.Body).Result?["images"]?.AsArray(); return results?[0]?.GetValue(); } else { Console.WriteLine("InvokeModelAsync failed with status code " + response.HttpStatusCode); } } catch (AmazonBedrockRuntimeException e) { Console.WriteLine(e.Message); } return null; } ``` + Pour plus de détails sur l'API, consultez [ InvokeModel ](https://docs.aws.amazon.com/goto/DotNetSDKV4/bedrock-runtime-2023-09-30/InvokeModel) la section Référence de *AWS SDK pour .NET l'API*. ------ #### [ Java ] **SDK pour Java 2.x** Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/bedrock-runtime#code-examples). Créez une image avec 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); } } ``` + Pour plus de détails sur l'API, consultez [ InvokeModel ](https://docs.aws.amazon.com/goto/SdkForJavaV2/bedrock-runtime-2023-09-30/InvokeModel) la section Référence de *AWS SDK for Java 2.x l'API*. ------ #### [ PHP ] **Kit SDK pour PHP** Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/php/example_code/bedrock-runtime#code-examples). Créez une image avec 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; } ``` + Pour plus de détails sur l'API, consultez [ InvokeModel ](https://docs.aws.amazon.com/goto/SdkForPHPV3/bedrock-runtime-2023-09-30/InvokeModel) la section Référence de *AWS SDK pour PHP l'API*. ------ #### [ Python ] **Kit SDK for Python (Boto3)** Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/bedrock-runtime#code-examples). Créez une image avec 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}") ``` + Pour plus de détails sur l'API, consultez [ InvokeModel ](https://docs.aws.amazon.com/goto/boto3/bedrock-runtime-2023-09-30/InvokeModel) la section Référence de l'API *AWS SDK pour Python (Boto3). * ------ #### [ SAP ABAP ] **Kit SDK pour SAP ABAP** Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le [référentiel d’exemples de code AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/bdr#code-examples). Créez une image avec 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. ``` Invoquez le modèle de base Stability.ai Stable Image Core pour générer des images à l'aide du client de haut niveau L2. ``` 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. ``` + Pour plus de détails sur l'API, consultez [ InvokeModel ](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) le *AWS SDK pour la référence de l'API SAP ABAP. * ------ Pour obtenir la liste complète des guides du développeur du AWS SDK et des exemples de code, consultez[Utilisation d'Amazon Bedrock avec AWS Kit SDK](sdk-general-information-section.md). Cette rubrique comprend également des informations sur le démarrage et sur les versions précédentes du kit SDK.