import com.google.cloud.automl.v1.AnnotationPayload;
import com.google.cloud.automl.v1.ExamplePayload;
import com.google.cloud.automl.v1.ModelName;
import com.google.cloud.automl.v1.PredictRequest;
import com.google.cloud.automl.v1.PredictResponse;
import com.google.cloud.automl.v1.PredictionServiceClient;
import com.google.cloud.automl.v1.TextSnippet;
import java.io.IOException;
class LanguageSentimentAnalysisPredict {
static void predict() throws IOException {
// TODO(developer): Replace these variables before running the sample.
String projectId = "YOUR_PROJECT_ID";
String modelId = "YOUR_MODEL_ID";
String content = "text to predict";
predict(projectId, modelId, content);
}
static void predict(String projectId, String modelId, String content) throws IOException {
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (PredictionServiceClient client = PredictionServiceClient.create()) {
// Get the full path of the model.
ModelName name = ModelName.of(projectId, "us-central1", modelId);
// For available mime types, see:
// https://cloud.google.com/automl/docs/reference/rest/v1/projects.locations.models/predict#textsnippet
TextSnippet textSnippet =
TextSnippet.newBuilder()
.setContent(content)
.setMimeType("text/plain") // Types: text/plain, text/html
.build();
ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
PredictRequest predictRequest =
PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();
PredictResponse response = client.predict(predictRequest);
for (AnnotationPayload annotationPayload : response.getPayloadList()) {
System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
System.out.format(
"Predicted sentiment score: %d\n", annotationPayload.getTextSentiment().getSentiment());
}
}
}
}