Create app.py

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+import pandas as pd
+import numpy as np
+from nltk.sentiment import SentimentIntensityAnalyzer
+import nltk
+
+# Download VADER lexicon
+nltk.download('vader_lexicon', quiet=True)
+
+def perform_sentiment_analysis(text):
+    sia = SentimentIntensityAnalyzer()
+    return sia.polarity_scores(text)
+
+def categorize_sentiment(compound_score):
+    if compound_score >= 0.05:
+        return 'Positive'
+    elif compound_score <= -0.05:
+        return 'Negative'
+    else:
+        return 'Neutral'
+
+def analyze_sentiment(input_text):
+    scores = perform_sentiment_analysis(input_text)
+    sentiment = categorize_sentiment(scores['compound'])
+    return {"Sentiment": sentiment, "Scores": scores}
+
+demo = gr.Interface(
+    fn=analyze_sentiment,
+    inputs=gr.Textbox(label="Enter text for sentiment analysis"),
+    outputs="json",
+    title="Sentiment Analysis Tool using Reddit Data",
+    description="Analyze sentiment of text using Reddit data."
+)
+
+demo.launch()