Mengklasifikasikan konten file Cloud Storage
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Menganalisis file yang disimpan di Google Cloud Storage dan menampilkan daftar kategori konten yang berlaku untuk teks yang ditemukan dalam dokumen
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[[["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,["Analyze a file stored in Google Cloud Storage and return a list of content categories that apply to the text found in the document\n\nExplore further\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [Classifying Content](/natural-language/docs/classifying-text)\n\nCode sample \n\nGo\n\n\nTo learn how to install and use the client library for Natural Language, see\n[Natural Language client libraries](/natural-language/docs/reference/libraries).\n\n\nFor more information, see the\n[Natural Language Go API\nreference documentation](/go/docs/reference/cloud.google.com/go/language/latest/apiv1).\n\n\nTo authenticate to Natural Language, 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 func classifyTextFromGCS(ctx context.Context, gcsURI string) (*languagepb.ClassifyTextResponse, error) {\n \treturn client.ClassifyText(ctx, &languagepb.ClassifyTextRequest{\n \t\tDocument: &languagepb.Document{\n \t\t\tSource: &languagepb.Document_GcsContentUri{\n \t\t\t\tGcsContentUri: gcsURI,\n \t\t\t},\n \t\t\tType: languagepb.Document_PLAIN_TEXT,\n \t\t},\n \t})\n }\n\nJava\n\n\nTo learn how to install and use the client library for Natural Language, see\n[Natural Language client libraries](/natural-language/docs/reference/libraries).\n\n\nFor more information, see the\n[Natural Language Java API\nreference documentation](/java/docs/reference/google-cloud-language/latest/overview).\n\n\nTo authenticate to Natural Language, 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 // Instantiate the Language client com.google.cloud.language.v2.LanguageServiceClient\n try (LanguageServiceClient language = LanguageServiceClient.create()) {\n // Set the GCS content URI path\n Document doc =\n Document.newBuilder().setGcsContentUri(gcsUri).setType(Type.PLAIN_TEXT).build();\n ClassifyTextRequest request = ClassifyTextRequest.newBuilder().setDocument(doc).build();\n // Detect categories in the given file\n ClassifyTextResponse response = language.classifyText(request);\n\n for (ClassificationCategory category : response.getCategoriesList()) {\n System.out.printf(\n \"Category name : %s, Confidence : %.3f\\n\",\n category.getName(), category.getConfidence());\n }\n }\n\nNode.js\n\n\nTo learn how to install and use the client library for Natural Language, see\n[Natural Language client libraries](/natural-language/docs/reference/libraries).\n\n\nFor more information, see the\n[Natural Language Node.js API\nreference documentation](/nodejs/docs/reference/language/latest).\n\n\nTo authenticate to Natural Language, 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 // Imports the Google Cloud client library.\n const language = require(&https://cloud.google.com/nodejs/docs/reference/language/latest/overview.htmluage');\n\n // Creates a client.\n const client = new lhttps://cloud.google.com/nodejs/docs/reference/language/latest/overview.htmlhttps://cloud.google.com/nodejs/docs/reference/language/latest/overview.htmlceClient();\n\n /**\n * TODO(developer): Uncomment the following lines to run this code\n */\n // const bucketName = 'Your bucket name, e.g. my-bucket';\n // const fileName = 'Your file name, e.g. my-file.txt';\n\n // Prepares a document, representing a text file in Cloud Storage\n const document = {\n gcsContentUri: `gs://${bucketName}/${fileName}`,\n type: 'PLAIN_TEXT',\n };\n\n // Classifies text in the document\n const [classification] = await client.classifyText({document});\n\n console.log('Categories:');\n clas\u003esification.categories.forEach(category = {\n console.log(`Name: ${category.name}, Confidence: ${category.confidence}`);\n });\n\nPHP\n\n\nTo learn how to install and use the client library for Natural Language, see\n[Natural Language client libraries](/natural-language/docs/reference/libraries).\n\n\nTo authenticate to Natural Language, 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 use Google\\Cloud\\Language\\V1\\ClassifyTextRequest;\n use Google\\Cloud\\Language\\V1\\Client\\LanguageServiceClient;\n use Google\\Cloud\\Language\\V1\\Document;\n use Google\\Cloud\\Language\\V1\\Document\\Type;\n\n /**\n * @param string $uri The cloud storage object to analyze (gs://your-bucket-name/your-object-name)\n */\n function classify_text_from_file(string $uri): void\n {\n $languageServiceClient = new LanguageServiceClient();\n\n // Create a new Document, pass GCS URI and set type to PLAIN_TEXT\n $document = (new Document())\n -\u003esetGcsContentUri($uri)\n -\u003esetType(Type::PLAIN_TEXT);\n\n // Call the analyzeSentiment function\n $request = (new ClassifyTextRequest())\n -\u003esetDocument($document);\n $response = $languageServiceClient-\u003eclassifyText($request);\n $categories = $response-\u003egetCategories();\n // Print document information\n foreach ($categories as $category) {\n printf('Category Name: %s' . PHP_EOL, $c\u003eategory-getName());\n printf('Confidence: %s' . PHP\u003e_EOL, $category-getConfidence());\n print(PHP_EOL);\n }\n }\n\nPython\n\n\nTo learn how to install and use the client library for Natural Language, see\n[Natural Language client libraries](/natural-language/docs/reference/libraries).\n\n\nFor more information, see the\n[Natural Language Python API\nreference documentation](/python/docs/reference/language/latest).\n\n\nTo authenticate to Natural Language, 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 from google.cloud import language_v1\n\n\n def sample_classify_text(gcs_content_uri):\n \"\"\"\n Classifying Content in text file stored in Cloud Storage\n\n Args:\n gcs_content_uri Google Cloud Storage URI where the file content is located.\n e.g. gs://[Your Bucket]/[Path to File]\n The text file must include at least 20 words.\n \"\"\"\n\n client = language_v1.LanguageServiceClient()\n\n # gcs_content_uri = 'gs://cloud-samples-data/language/classify-entertainment.txt'\n\n # Available types: PLAIN_TEXT, HTML\n type_ = language_v1.Document.Type.PLAIN_TEXT\n\n # Optional. If not specified, the language is automatically detected.\n # For list of supported languages:\n # https://cloud.google.com/natural-language/docs/languages\n language = \"en\"\n document = {\n \"gcs_content_uri\": gcs_content_uri,\n \"type_\": type_,\n \"language\": language,\n }\n\n response = client.https://cloud.google.com/python/docs/reference/language/latest/google.cloud.language_v1.services.language_service.LanguageServiceClient.html#google_cloud_language_v1_services_language_service_LanguageServiceClient_classify_text(request={\"document\": document})\n # Loop through classified categories returned from the API\n for category in response.categories:\n # Get the name of the category representing the document.\n # See the predefined taxonomy of categories:\n # https://cloud.google.com/natural-language/docs/categories\n print(f\"Category name: {category.name}\")\n # Get the confidence. Number representing how certain the classifier\n # is that this category represents the provided text.\n print(f\"Confidence: {category.confidence}\")\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=language)."]]