Spaces:
Running
Running
# analyze_sentiment.py | |
# This script analyzes the sentiment of the summarized content using the Hugging Face Transformers library. | |
from transformers import pipeline | |
# Load sentiment analysis pipeline | |
sentiment_analyzer = pipeline("sentiment-analysis", model = "distilbert-base-uncased-finetuned-sst-2-english") | |
def analyze_summary(summary): | |
""" | |
Analyze the sentiment of the given summary. | |
Returns a tuple of (sentiment, score). | |
""" | |
try: | |
if not summary.strip(): | |
return "No input provided.", 0.0 | |
result = sentiment_analyzer(summary)[0] | |
sentiment = result['label'] | |
score = result['score'] | |
return sentiment, score | |
except Exception as e: | |
return f"Error analyzing sentiment: {str(e)}", 0.0 | |
# Example usage |