Update app.py

app.py

@@ -2,80 +2,55 @@ import gradio as gr
 from transformers import pipeline
 import matplotlib.pyplot as plt
 from wordcloud import WordCloud
-import json
-import os
 
 # Load sentiment analysis model
 sentiment_pipeline = pipeline("sentiment-analysis")
 
-# Store last input/output using localStorage
-STATE_FILE = "state.json"
-
-def save_state(text, sentiment, confidence):
-    with open(STATE_FILE, "w") as f:
-        json.dump({"text": text, "sentiment": sentiment, "confidence": confidence}, f)
-
-def load_state():
-    if os.path.exists(STATE_FILE):
-        with open(STATE_FILE, "r") as f:
-            return json.load(f)
-    return {"text": "", "sentiment": "", "confidence": ""}
-
-# Function to analyze sentiment in real-time
+# Function to analyze sentiment
 def analyze_sentiment(text):
     if not text.strip():
         return "Enter text to analyze.", "", None, ""
-    
+
     result = sentiment_pipeline(text)[0]
     sentiment, confidence = result['label'], result['score']
-    
+
     sentiment_map = {
         "POSITIVE": ("🟢 Positive 😊", "green"),
         "NEGATIVE": ("🔴 Negative 😠", "red"),
         "NEUTRAL": ("🟡 Neutral 😐", "orange")
     }
-    
+
     sentiment_label, color = sentiment_map.get(sentiment.upper(), ("⚪ Unknown ❓", "gray"))
-    
+
     # Generate Word Cloud
     wordcloud = WordCloud(width=400, height=200, background_color="white").generate(text)
     fig, ax = plt.subplots()
     ax.imshow(wordcloud, interpolation='bilinear')
     ax.axis("off")
-    
-    save_state(text, sentiment_label, confidence)
-    
+
     return sentiment_label, f"Confidence: {confidence:.2%}", fig, text
 
 # UI Layout
 with gr.Blocks(theme=gr.themes.Soft()) as iface:
     gr.Markdown("# 🎭 AI Sentiment Analyzer")
     gr.Markdown("Analyze sentiment in real-time with enhanced visualization.")
-    
+
     with gr.Row():
         dark_mode = gr.Checkbox(label="🌙 Dark Mode")
-        
-    with gr.Row():
-        # With this (corrected)
-        text_input = gr.Textbox(lines=3, placeholder="Type your text here...", label="Your Input")
-        
-        # Attach the `.change()` event to enable real-time analysis
-        text_input.change(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, confidence_output, wordcloud_output, text_input])
-        
-            
+
+    text_input = gr.Textbox(lines=3, placeholder="Type your text here...", label="Your Input")
+    
     analyze_button = gr.Button("Analyze Sentiment ✨")
     reset_button = gr.Button("🔄 Reset")
-    
+
     with gr.Row():
         sentiment_output = gr.Label(label="Sentiment Result")
         confidence_output = gr.Label(label="Confidence Score")
-    
+
     wordcloud_output = gr.Plot(label="Word Cloud Visualization")
-    
-    # Load previous session state
-    state = load_state()
-    text_input.value, sentiment_output.value, confidence_output.value = state['text'], state['sentiment'], state['confidence']
-    
+
+    # Attach event handlers AFTER defining components
+    text_input.change(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, confidence_output, wordcloud_output, text_input])
     analyze_button.click(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, confidence_output, wordcloud_output, text_input])
     reset_button.click(lambda: ("", "", None, ""), inputs=[], outputs=[sentiment_output, confidence_output, wordcloud_output, text_input])