Membuat prompt untuk membuat pengujian unit (AI Generatif)
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Simpan dan kategorikan konten berdasarkan preferensi Anda.
Membuat perintah yang dapat digunakan dengan model chat penayang untuk membuat pengujian unit.
Contoh kode
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],[],[],[],null,["# Create prompts to generate unit tests (Generative AI)\n\nCreate prompts that work with a publisher chat model to generate unit tests.\n\nCode sample\n-----------\n\n### Java\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/protobuf/latest/com.google.protobuf.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 PredictCodeGenerationUnitTestSample {\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 generate code:\n // https://cloud.google.com/vertex-ai/docs/generative-ai/code/code-generation-prompts\n String instance =\n \"{ \\\"prefix\\\": \\\"Write a unit test for this function:\\n\"\n + \" def is_leap_year(year):\\n\"\n + \" if year % 4 == 0:\\n\"\n + \" if year % 100 == 0:\\n\"\n + \" if year % 400 == 0:\\n\"\n + \" return True\\n\"\n + \" else:\\n\"\n + \" return False\\n\"\n + \" else:\\n\"\n + \" return True\\n\"\n + \" else:\\n\"\n + \" return False\\n\"\n + \"\\\"}\";\n String parameters = \"{\\n\" + \" \\\"temperature\\\": 0.5,\\n\" + \" \\\"maxOutputTokens\\\": 256\\n\" + \"}\";\n String location = \"us-central1\";\n String publisher = \"google\";\n String model = \"code-bison@001\";\n\n predictUnitTest(instance, parameters, project, location, publisher, model);\n }\n\n // Use Codey for Code Generation to generate a unit test\n public static void predictUnitTest(\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/protobuf/latest/com.google.protobuf.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/protobuf/latest/com.google.protobuf.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/protobuf/latest/com.google.protobuf.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/protobuf/latest/com.google.protobuf.Value.html.Builder builder = https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.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\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=aiplatform)."]]