Flair Sentiment Analysis Function

This function uses a pre-trained sentiment analysis model from the Flair library to analyze the sentiment of a given text and returns the sentiment label (positive, negative, or neutral) of the text.

Technology Stack : Flair, TextClassifier, Sentence

Code Type : Function

Code Difficulty : Intermediate

                
                    
def flair_random_sentiment_analysis(text, language='en'):
    """
    Perform sentiment analysis on a given text using Flair's pre-trained model.

    Args:
    text (str): The text to analyze.
    language (str): The language of the text. Default is 'en' for English.

    Returns:
    str: The sentiment of the text ('positive', 'negative', 'neutral').
    """
    from flair.models import TextClassifier
    from flair.data import Sentence

    # Load pre-trained sentiment analysis model
    classifier = TextClassifier.load('en-sentiment')

    # Create a Sentence object
    sentence = Sentence(text)

    # Perform sentiment analysis
    classifier.predict(sentence)

    # Return the sentiment of the text
    return sentence.labels[0].value