Predict for text classification single label
Stay organized with collections
Save and categorize content based on your preferences.
Gets prediction for text classification single label using the predict method.
Code sample
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],[],[],[],null,["# Predict for text classification single label\n\nGets prediction for text classification single label using the predict method.\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python 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 Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\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 from google.cloud import aiplatform\n from google.cloud.aiplatform.gapic.schema import predict\n from google.protobuf import json_format\n from google.protobuf.struct_pb2 import Value\n\n\n def predict_text_classification_single_label_sample(\n project: str,\n endpoint_id: str,\n content: str,\n location: str = \"us-central1\",\n api_endpoint: str = \"us-central1-aiplatform.googleapis.com\",\n ):\n # The AI Platform services require regional API endpoints.\n client_options = {\"api_endpoint\": api_endpoint}\n # Initialize client that will be used to create and send requests.\n # This client only needs to be created once, and can be reused for multiple requests.\n client = aiplatform.gapic.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.prediction_service.PredictionServiceClient.html(client_options=client_options)\n instance = predict.instance.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform.v1.schema.predict.instance_v1.types.TextClassificationPredictionInstance.html(\n content=content,\n ).to_value()\n instances = [instance]\n parameters_dict = {}\n parameters = json_format.ParseDict(parameters_dict, Value())\n endpoint = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.prediction_service.PredictionServiceClient.html#google_cloud_aiplatform_v1_services_prediction_service_PredictionServiceClient_endpoint_path(\n project=project, location=location, endpoint=endpoint_id\n )\n response = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.prediction_service.PredictionServiceClient.html(\n endpoint=endpoint, instances=instances, parameters=parameters\n )\n print(\"response\")\n print(\" deployed_model_id:\", response.deployed_model_id)\n\n predictions = response.predictions\n for prediction in predictions:\n print(\" prediction:\", dict(prediction))\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)."]]