Examples with SentimentType com.amplifyframework.predictions.models.SentimentType used on opensource projects

Example 1 with SentimentType

use of com.amplifyframework.predictions.models.SentimentType in project amplify-android by aws-amplify.

the class AWSComprehendService method fetchSentiment.

private Sentiment fetchSentiment(String text, LanguageType language) throws PredictionsException {
    // Skip if configuration specifies NOT sentiment
    if (!isResourceConfigured(InterpretTextConfiguration.InterpretType.SENTIMENT)) {
        return null;
    }
    DetectSentimentRequest request = new DetectSentimentRequest().withText(text).withLanguageCode(language.getLanguageCode());
    // Detect sentiment from given text via AWS Comprehend
    final DetectSentimentResult result;
    try {
        result = comprehend.detectSentiment(request);
    } catch (AmazonClientException serviceException) {
        throw new PredictionsException("AWS Comprehend encountered an error while detecting sentiment.", serviceException, "See attached service exception for more details.");
    }
    // Convert AWS Comprehend's detection result to Amplify-compatible format
    String comprehendSentiment = result.getSentiment();
    SentimentScore sentimentScore = result.getSentimentScore();
    SentimentType predominantSentiment = SentimentTypeAdapter.fromComprehend(comprehendSentiment);
    final float score;
    switch(predominantSentiment) {
        case POSITIVE:
            score = sentimentScore.getPositive();
            break;
        case NEGATIVE:
            score = sentimentScore.getNegative();
            break;
        case NEUTRAL:
            score = sentimentScore.getNeutral();
            break;
        case MIXED:
            score = sentimentScore.getMixed();
            break;
        default:
            score = 0f;
    }
    return Sentiment.builder().value(predominantSentiment).confidence(score * PERCENT).build();
}

Example 2 with SentimentType

use of com.amplifyframework.predictions.models.SentimentType in project amplify-android by aws-amplify.

the class TensorFlowTextClassificationService method fetchSentiment.

@VisibleForTesting
Sentiment fetchSentiment(String text) throws PredictionsException {
    float[][] input;
    float[][] output;
    try {
        // Pre-process input text
        input = dictionary.tokenizeInputText(text);
        output = new float[1][labels.size()];
        // Run inference.
        interpreter.run(input, output);
    } catch (IllegalArgumentException exception) {
        throw new PredictionsException("TensorFlow Lite failed to make an inference.", exception, "Verify that the label size matches the output size of the model.");
    }
    // Find the predominant sentiment
    Sentiment sentiment = null;
    for (int i = 0; i < labels.size(); i++) {
        SentimentType sentimentType = SentimentTypeAdapter.fromTensorFlow(labels.get(i));
        float confidenceScore = output[0][i] * PERCENT;
        if (sentiment == null || sentiment.getConfidence() < confidenceScore) {
            sentiment = Sentiment.builder().value(sentimentType).confidence(confidenceScore).build();
        }
    }
    return sentiment;
}