sentiment_tools.py

from langchain.tools import tool
from transformers import pipeline

class SentimentTools:
    def __init__(self):
        self.sentiment_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

    @tool("Analyze Sentiment")
    def analyze_sentiment(self, text):
        """Analyzes the sentiment of a given text."""
        # Limit the input text to 512 tokens to ensure faster processing
        truncated_text = ' '.join(text.split()[:512])
        result = self.sentiment_pipeline(truncated_text)[0]
        sentiment = result['label']
        score = result['score']

        if sentiment == 'POSITIVE':
            return "Positive" if score > 0.6 else "Neutral"
        elif sentiment == 'NEGATIVE':
            return "Negative" if score > 0.6 else "Neutral"
        else:
            return "Neutral"