Update app.py

app.py

@@ -1,24 +1,65 @@
 import gradio as gr
 from transformers import pipeline
+import matplotlib.pyplot as plt
+import torch
+from pydub import AudioSegment
+import numpy as np
 
-# Load the sentiment analysis pipeline
+# Load sentiment analysis model
 sentiment_pipeline = pipeline("sentiment-analysis")
 
 # Function to analyze sentiment
 def analyze_sentiment(text):
     result = sentiment_pipeline(text)[0]
-    sentiment = result['label']
-    confidence = result['score']
-    return f"Sentiment: {sentiment} (Confidence: {confidence:.2f})"
-
-# Create a Gradio interface
-iface = gr.Interface(
-    fn=analyze_sentiment, 
-    inputs=gr.Textbox(lines=2, placeholder="Enter a sentence..."), 
-    outputs=gr.Textbox(label="Sentiment Analysis Result"),
-    title="Text Sentiment Analyzer",
-    description="Enter a sentence to analyze its sentiment (Positive, Negative, Neutral)."
-)
+    sentiment, confidence = result['label'], result['score']
+
+    # Sentiment Mapping for UI Display
+    sentiment_map = {
+        "POSITIVE": ("🟢 Positive 😊", "green"),
+        "NEGATIVE": ("🔴 Negative 😠", "red"),
+        "NEUTRAL": ("🟡 Neutral 😐", "orange")
+    }
+    
+    sentiment_label, color = sentiment_map.get(sentiment.upper(), ("⚪ Unknown ❓", "gray"))
+
+    # Generate Confidence Score Bar Chart
+    fig, ax = plt.subplots(figsize=(4, 2))
+    ax.bar(sentiment, confidence, color=color)
+    ax.set_ylim([0, 1])
+    ax.set_ylabel("Confidence Score")
+    ax.set_title("Sentiment Confidence")
+
+    return sentiment_label, f"Confidence: {confidence:.2f}", fig
+
+# Function to process audio input
+def process_audio(audio_path):
+    try:
+        audio = AudioSegment.from_file(audio_path)
+        audio = audio.set_channels(1).set_frame_rate(16000)
+        audio_array = np.array(audio.get_array_of_samples(), dtype=np.float32) / 32768.0
+        return analyze_sentiment("Speech-to-text processing not available in this version.")
+    except Exception as e:
+        return "Error processing audio", str(e), None
+
+# Gradio UI
+with gr.Blocks(theme=gr.themes.Soft()) as iface:
+    gr.Markdown("# 📢 Text Sentiment Analyzer")
+    gr.Markdown("Analyze the sentiment of your text input and visualize the confidence score.")
+
+    with gr.Row():
+        text_input = gr.Textbox(lines=2, placeholder="Enter text here...", label="Your Input")
+        audio_input = gr.Audio(source="microphone", type="filepath", label="Or Speak")
+
+    analyze_button = gr.Button("Analyze Sentiment ✨")
+
+    with gr.Row():
+        sentiment_output = gr.Textbox(label="Sentiment Result", interactive=False)
+        confidence_output = gr.Textbox(label="Confidence Score", interactive=False)
+    
+    chart_output = gr.Plot(label="Confidence Score Chart")
+
+    analyze_button.click(analyze_sentiment, inputs=text_input, outputs=[sentiment_output, confidence_output, chart_output])
+    analyze_button.click(process_audio, inputs=audio_input, outputs=[sentiment_output, confidence_output, chart_output])
 
 # Launch the app
 if __name__ == "__main__":