Eingabeaufforderungen für den Abschluss von Codekommentaren erstellen (Generative AI)
Mit Sammlungen den Überblick behalten
Sie können Inhalte basierend auf Ihren Einstellungen speichern und kategorisieren.
Erstellen Sie Eingabeaufforderungen, die mit einem Publisher-Code-Modell funktionieren, um Vorschläge zur Vervollständigung von Code-Kommentaren zu erstellen.
Codebeispiel
Nächste Schritte
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[[["Leicht verständlich","easyToUnderstand","thumb-up"],["Mein Problem wurde gelöst","solvedMyProblem","thumb-up"],["Sonstiges","otherUp","thumb-up"]],[["Schwer verständlich","hardToUnderstand","thumb-down"],["Informationen oder Beispielcode falsch","incorrectInformationOrSampleCode","thumb-down"],["Benötigte Informationen/Beispiele nicht gefunden","missingTheInformationSamplesINeed","thumb-down"],["Problem mit der Übersetzung","translationIssue","thumb-down"],["Sonstiges","otherDown","thumb-down"]],[],[],[],null,["Create prompts to work with a publisher code model to create code comment completion suggestions.\n\nCode sample \n\nJava\n\n\nBefore trying this sample, follow the Java setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Java API\nreference documentation](/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n\n import com.google.cloud.aiplatform.v1.https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.EndpointName.html;\n import com.google.cloud.aiplatform.v1.https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictResponse.html;\n import com.google.cloud.aiplatform.v1.https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictionServiceClient.html;\n import com.google.cloud.aiplatform.v1.https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictionServiceSettings.html;\n import com.google.protobuf.https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.InvalidProtocolBufferException.html;\n import com.google.protobuf.https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.Value.html;\n import com.google.protobuf.util.https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.util.JsonFormat.html;\n import java.io.IOException;\n import java.util.ArrayList;\n import java.util.List;\n\n public class PredictCodeCompletionCommentSample {\n\n public static void main(String[] args) throws IOException {\n // TODO(developer): Replace this variable before running the sample.\n String project = \"YOUR_PROJECT_ID\";\n\n // Learn how to create prompts to work with a code model to create code completion suggestions:\n // https://cloud.google.com/vertex-ai/docs/generative-ai/code/code-completion-prompts\n String instance =\n \"{ \\\"prefix\\\": \\\"\"\n + \"def reverse_string(s):\\n\"\n + \" return s[::-1]\\n\"\n + \"#This function\"\n + \"\\\"}\";\n String parameters = \"{\\n\" + \" \\\"temperature\\\": 0.2,\\n\" + \" \\\"maxOutputTokens\\\": 64,\\n\" + \"}\";\n String location = \"us-central1\";\n String publisher = \"google\";\n String model = \"code-gecko@001\";\n\n predictComment(instance, parameters, project, location, publisher, model);\n }\n\n // Use Codey for Code Completion to complete a code comment\n public static void predictComment(\n String instance,\n String parameters,\n String project,\n String location,\n String publisher,\n String model)\n throws IOException {\n final String endpoint = String.format(\"%s-aiplatform.googleapis.com:443\", location);\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictionServiceSettings.html predictionServiceSettings =\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictionServiceSettings.html.newBuilder().setEndpoint(endpoint).build();\n\n // Initialize client that will be used to send requests. This client only needs to be created\n // once, and can be reused for multiple requests.\n try (https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictionServiceClient.html predictionServiceClient =\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictionServiceClient.html.create(predictionServiceSettings)) {\n final https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.EndpointName.html endpointName =\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.EndpointName.html.https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.EndpointName.html#com_google_cloud_aiplatform_v1_EndpointName_ofProjectLocationPublisherModelName_java_lang_String_java_lang_String_java_lang_String_java_lang_String_(project, location, publisher, model);\n\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.Value.html instanceValue = stringToValue(instance);\n https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.ListValue.html instances = new ArrayList\u003c\u003e();\n instances.add(instanceValue);\n\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.Value.html parameterValue = stringToValue(parameters);\n\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.PredictResponse.html predictResponse =\n predictionServiceClient.predict(endpointName, instances, parameterValue);\n System.out.println(\"Predict Response\");\n System.out.println(predictResponse);\n }\n }\n\n // Convert a Json string to a protobuf.Value\n static https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.Value.html stringToValue(String value) throws https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.InvalidProtocolBufferException.html {\n https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.Value.html.Builder builder = https://cloud.google.com/java/docs/reference/google-cloud-aiplatform/latest/com.google.cloud.aiplatform.v1.Value.html.newBuilder();\n https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.util.JsonFormat.html.parser().merge(value, builder);\n return https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.TextFormatParseInfoTree.html#com_google_protobuf_TextFormatParseInfoTree_builder__.build();\n }\n }\n\nWhat's next\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=aiplatform)."]]