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predict_text_sentiment_analysis_sample.py
54 lines (49 loc) · 2.16 KB
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predict_text_sentiment_analysis_sample.py
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# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# [START aiplatform_predict_text_sentiment_analysis_sample]
from google.cloud import aiplatform
from google.cloud.aiplatform.gapic.schema import predict
from google.protobuf import json_format
from google.protobuf.struct_pb2 import Value
def predict_text_sentiment_analysis_sample(
project: str,
endpoint_id: str,
content: str,
location: str = "us-central1",
api_endpoint: str = "us-central1-aiplatform.googleapis.com",
):
# The AI Platform services require regional API endpoints.
client_options = {"api_endpoint": api_endpoint}
# Initialize client that will be used to create and send requests.
# This client only needs to be created once, and can be reused for multiple requests.
client = aiplatform.gapic.PredictionServiceClient(client_options=client_options)
instance = predict.instance.TextSentimentPredictionInstance(
content=content,
).to_value()
instances = [instance]
parameters_dict = {}
parameters = json_format.ParseDict(parameters_dict, Value())
endpoint = client.endpoint_path(
project=project, location=location, endpoint=endpoint_id
)
response = client.predict(
endpoint=endpoint, instances=instances, parameters=parameters
)
print("response")
print(" deployed_model_id:", response.deployed_model_id)
# See gs://google-cloud-aiplatform/schema/predict/prediction/text_sentiment_1.0.0.yaml for the format of the predictions.
predictions = response.predictions
for prediction in predictions:
print(" prediction:", dict(prediction))
# [END aiplatform_predict_text_sentiment_analysis_sample]