Update app.py

app.py

@@ -2,12 +2,10 @@ import gradio as gr
 from transformers import pipeline
 import time
 
-# Load model once at startup
 print("Loading sentiment model...")
 classifier = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
 print("Model ready!")
 
-# ── Single analysis ──────────────────────────────────────────
 def analyze_single(text):
     if not text or not text.strip():
         return "⚠️ Please enter some text.", "", ""
@@ -30,8 +28,6 @@ def analyze_single(text):
 
     return sentiment_out, confidence_out, time_out
 
-
-# ── Batch analysis ───────────────────────────────────────────
 def analyze_batch(texts_input):
     if not texts_input or not texts_input.strip():
         return "⚠️ Please enter at least one sentence."
@@ -55,26 +51,23 @@ def analyze_batch(texts_input):
     summary_neg = len(results) - summary_pos
 
     output_lines.append("")
-    output_lines.append(f"📊 Summary: {summary_pos} Positive  |  {summary_neg} Negative  |  {len(results)} Total")
+    output_lines.append(f" Summary: {summary_pos} Positive  |  {summary_neg} Negative  |  {len(results)} Total")
 
     return "\n".join(output_lines)
 
-
-# ── UI ───────────────────────────────────────────────────────
 with gr.Blocks(
     theme=gr.themes.Soft(primary_hue="blue", secondary_hue="indigo"),
     title="Sentiment Analyzer"
 ) as demo:
 
     gr.Markdown("""
-    # 🎭 Sentiment Analyzer
+    #  Sentiment Analyzer
     Detects **Positive** or **Negative** sentiment using DistilBERT.
     Built with HuggingFace Transformers · Model accuracy ~91% on SST-2 benchmark.
     """)
 
     with gr.Tabs():
 
-        # ── Tab 1: Single ──
         with gr.TabItem("Single Analysis"):
             with gr.Row():
                 with gr.Column(scale=2):
@@ -84,7 +77,7 @@ with gr.Blocks(
                         label="Input Text",
                         max_lines=6
                     )
-                    analyze_btn = gr.Button("Analyze Sentiment 🔍", variant="primary", size="lg")
+                    analyze_btn = gr.Button("Analyze Sentiment ", variant="primary", size="lg")
 
                 with gr.Column(scale=1):
                     sentiment_out = gr.Textbox(label="Sentiment", interactive=False)
@@ -109,7 +102,6 @@ with gr.Blocks(
                 outputs=[sentiment_out, confidence_out, time_out]
             )
 
-        # ── Tab 2: Batch ──
         with gr.TabItem("Batch Analysis"):
             gr.Markdown("Enter **one sentence per line** (max 20 sentences)")