updated examples

app.py

@@ -2,45 +2,46 @@ import gradio as gr
 import nltk
 from nltk.sentiment import SentimentIntensityAnalyzer
 
-# Download VADER lexicon
+# Download VADER lexicon for sentiment analysis
 nltk.download('vader_lexicon', quiet=True)
 
 def perform_sentiment_analysis(text):
+    """Analyzes the sentiment of the given text using VADER."""
     sia = SentimentIntensityAnalyzer()
     return sia.polarity_scores(text)
 
 def categorize_sentiment(compound_score):
-    # Adjusting thresholds for a more balanced classification
-    if compound_score > 0.1:  # Increased positive threshold
+    """Categorizes sentiment based on the compound score."""
+    if compound_score > 0.1:  # Adjusted threshold for more balanced classification
         return 'Positive'
-    elif compound_score < -0.1:  # Increased negative threshold
+    elif compound_score < -0.1:
         return 'Negative'
     else:
         return 'Neutral'
 
 def analyze_sentiment(input_text):
+    """Performs sentiment analysis and categorizes the sentiment."""
     scores = perform_sentiment_analysis(input_text)
     sentiment = categorize_sentiment(scores['compound'])
     return {"Sentiment": sentiment, "Scores": scores}
 
-# Example Reddit posts for sentiment analysis
+# Improved examples for sentiment analysis
 examples = [
-    "Just got a new job and I'm so excited! The team seems great and the work looks interesting.",  # Positive
-    "I'm really frustrated with how the job market is right now. It's so unfair.",    # Negative
-    "Hey John, did you finish your intro to Machine Learning textbook?",  # Neutral
-    "I hate Data structures.",  # Negative
-    "I really enjoyed the last movie I watched; it was captivating and well-made.",  # Positive
-    "Where are you ?",  # Neutral
+    "Absolutely thrilled about my vacation next week! Can't wait!",  # Positive
+    "The customer service was terrible. I wouldn't recommend this place to anyone.",  # Negative
+    "I'm not sure what to think about the new policy. It has pros and cons.",  # Neutral
+    "This product exceeded my expectations! The quality is fantastic.",  # Positive
+    "I'm feeling overwhelmed with all these assignments due tomorrow.",  # Negative
+    "Did you complete your homework for the AI course?",  # Neutral
 ]
 
+# Create Gradio interface
 demo = gr.Interface(
     fn=analyze_sentiment,
     inputs=gr.Textbox(label="Enter text for sentiment analysis", placeholder="Type your text here..."),
     outputs="json",
     title="Sentiment Analysis Tool",
-    description=(
-        "Enter text to see the sentiment analysis result. You can also use the examples below to test different sentiments."
-    ),
+    description="Analyze the sentiment of any text. Enter your own text or choose an example below.",
     examples=examples
 )