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| from transformers import pipeline | |
| class SentimentAnalyzer: | |
| """Class for analyzing the sentiment of sentences | |
| """ | |
| def __init__(self) -> None: | |
| """initializes the class with sentiment analysis pipeline using the distilbert-base-uncased-finetuned-sst-2-english model | |
| """ | |
| self.analyzer = pipeline( | |
| "sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english") | |
| def score_sentiment(self, sentence: str) -> float: | |
| """Uses the analyzer to analyze the sentiment of the provided sentence | |
| Parameters | |
| ---------- | |
| sentence : str | |
| a short sentence to be analyzed | |
| Returns | |
| ------- | |
| float | |
| score of the sentiment from 0 to 1. Below 0.5 is negative, above is positive. 0.5 is neutral | |
| """ | |
| return self.analyzer(sentence)[0] | |
| def get_sentiment(self, sentence: str) -> str: | |
| """returns the label of the sentiment provided | |
| Parameters | |
| ---------- | |
| sentence : str | |
| a short sentence to be analyzed | |
| Returns | |
| ------- | |
| str | |
| label of the sentiment wether it is positive, negative, or neutral | |
| """ | |
| sentiment_score = self.score_sentiment(sentence) | |
| return sentiment_score['label'] | |
| if __name__ == "__main__": | |
| sentence = "I love you" | |
| sentiment_analyzer = SentimentAnalyzer() | |
| print(sentiment_analyzer.get_sentiment(sentence)) |