Use azure to detect sentiments

This commit is contained in:
Werner
2021-11-15 11:29:09 -03:00
parent bd7549ca47
commit 417a837bcd

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@ -1,7 +1,54 @@
package app.azure;
import com.azure.core.credential.AzureKeyCredential;
import com.azure.ai.textanalytics.models.*;
import com.azure.ai.textanalytics.TextAnalyticsClientBuilder;
import com.azure.ai.textanalytics.TextAnalyticsClient;
import com.azure.core.credential.AzureKeyCredential;
import com.azure.ai.textanalytics.models.*;
import com.azure.ai.textanalytics.TextAnalyticsClientBuilder;
import com.azure.ai.textanalytics.TextAnalyticsClient;
public class JavaAzure {
private static String KEY = "CHAVE_ULTRA_SECRETA";
private static String ENDPOINT = "URL_ULTRA_SECRETA";
public static void main(String[] args) {
System.out.println( "Hello World");
TextAnalyticsClient client = authenticateClient(KEY, ENDPOINT);
analyseSentiments(client, "I had the best day of my life. I wish you were there with me.");
analyseSentiments(client, "That game was a shame, the surrender in the first round!");
analyseSentiments(client, "To capture pirate empress Boa Hancock, we're heading to Amazon Lily.");
analyseSentiments(client, "Will justice be done? But of course it will, because it's the winner who dictates justice.");
}
static TextAnalyticsClient authenticateClient(String key, String endpoint) {
return new TextAnalyticsClientBuilder()
.credential(new AzureKeyCredential(key))
.endpoint(endpoint)
.buildClient();
}
static void analyseSentiments(TextAnalyticsClient client, String text)
{
System.out.println("Frase: " + text);
DocumentSentiment documentSentiment = client.analyzeSentiment(text);
System.out.printf(
"Semtimento do documento: %s (positivo: %s, neutro: %s, negativo: %s) %n",
documentSentiment.getSentiment(),
documentSentiment.getConfidenceScores().getPositive(),
documentSentiment.getConfidenceScores().getNeutral(),
documentSentiment.getConfidenceScores().getNegative());
for (SentenceSentiment sentenceSentiment : documentSentiment.getSentences()) {
System.out.printf(
"Semtimento da frase: %s (positivo: %s, neutro: %s, negativo: %s) %n",
sentenceSentiment.getSentiment(),
sentenceSentiment.getConfidenceScores().getPositive(),
sentenceSentiment.getConfidenceScores().getNeutral(),
sentenceSentiment.getConfidenceScores().getNegative());
}
}
}