Update app.py

app.py

@@ -1,12 +1,15 @@
 import gradio as gr
 from transformers import pipeline
 
+# Load sentiment analysis model from Hugging Face
 sentiment_analyzer = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
 
+# Function to analyze sentiment and convert it to star rating (1-5)
 def analyze_sentiment(text):
     result = sentiment_analyzer(text)[0]
     sentiment_score = result['label']
     
+    # Convert sentiment score to numeric star rating (1-5 stars)
     if sentiment_score == '1 star':
         return 1
     elif sentiment_score == '2 stars':
@@ -18,6 +21,7 @@ def analyze_sentiment(text):
     else:
         return 5
 
+# Define example sentences for easy testing
 examples = [
     "I love this product! It's amazing!",
     "This was the worst experience I've ever had.",
@@ -25,6 +29,7 @@ examples = [
     "Absolutely fantastic! I would recommend it to everyone."
 ]
 
+# Build the Gradio interface
 iface = gr.Interface(
     fn=analyze_sentiment,  # Function to call for sentiment analysis
     inputs=[
@@ -37,4 +42,5 @@ iface = gr.Interface(
     description="Sentiment analysis using BERT-based model for multilingual sentiment prediction."
 )
 
+# Launch the Gradio interface
 iface.launch()