Update app.py

app.py

@@ -1,3 +1,30 @@
+[file name]: image.png
+[file content begin]
+Enter Text
+
+Type in English, Urdu, or Roman Urdu...
+
+Language Selection
+Auto Detect
+
+Analyze Sentiment
+Show Logs
+
+Clear Logs
+
+Sentiment
+Confidence Score
+Detailed Explanation
+Strong Words
+
+Download Logs
+
+Analysis History
+Sent_ Lang_Sent_ Conf_ Stro_Tima_
+
+
+[file content end]
+
 import gradio as gr
 from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
 import pandas as pd
@@ -466,8 +493,11 @@ with gr.Blocks(title="Multilingual Sentiment Analysis") as demo:
     - Language detection: papluca/xlm-roberta-base-language-detection
     """)
     
+    # Top row with two columns
     with gr.Row():
-        with gr.Column():
+        # Left column - Input section
+        with gr.Column(scale=1):
+            gr.Markdown("### 📥 Input Section")
             user_text = gr.Textbox(
                 label="✍️ Enter Text",
                 placeholder="Type in English, Urdu, or Roman Urdu...",
@@ -484,21 +514,47 @@ with gr.Blocks(title="Multilingual Sentiment Analysis") as demo:
                 btn_show = gr.Button("📂 Show Logs")
                 btn_clear = gr.Button("🗑️ Clear Logs")
         
-        with gr.Column():
-            out_sent = gr.Textbox(label="🎭 Sentiment")
-            out_conf = gr.Textbox(label="📊 Confidence Score")
-            out_exp = gr.Textbox(label="💡 Detailed Explanation")
-            out_strong = gr.Textbox(label="💪 Strong Words")
-            out_file = gr.File(label="⬇️ Download Logs")
-    
-        logs_df = gr.Dataframe(
-        headers=["Sentence", "Language", "Sentiment", "Confidence", "Strong_Words", "Timestamp"],
-        label="📋 Analysis History",
-        interactive=False,
-        wrap=True
-    )
+        # Right column - Results section
+        with gr.Column(scale=1):
+            gr.Markdown("### 📊 Results")
+            with gr.Row():
+                with gr.Column():
+                    out_sent = gr.Textbox(label="🎭 Sentiment")
+                    out_conf = gr.Textbox(label="📊 Confidence Score")
+                with gr.Column():
+                    out_strong = gr.Textbox(label="💪 Strong Words")
+                    out_file = gr.File(label="⬇️ Download Logs")
+            
+            out_exp = gr.Textbox(label="💡 Detailed Explanation", lines=3)
+    
+    # Bottom row with analysis history taking 75% width
+    with gr.Row():
+        with gr.Column(scale=3):  # 75% width (3/4)
+            logs_df = gr.Dataframe(
+                headers=["Sentence", "Language", "Sentiment", "Confidence", "Strong_Words", "Timestamp"],
+                label="📋 Analysis History",
+                interactive=False,
+                wrap=True,
+                height=400
+            )
+        with gr.Column(scale=1):  # 25% width (1/4)
+            gr.Markdown("### ℹ️ Information")
+            gr.Markdown("""
+            **How to use:**
+            1. Enter text in any supported language
+            2. Select language or use Auto Detect
+            3. Click Analyze Sentiment
+            4. View results and history
+            
+            **Supported Languages:**
+            - English
+            - Urdu (Script)
+            - Roman Urdu (Latin script)
+            
+            **Note:** Auto Detect works best with clear text samples.
+            """)
     
-    # Event handlers - FIXED: Added missing closing parenthesis
+    # Event handlers
     btn_analyze.click(
         analyze_sentiment_complete,
         inputs=[user_text, lang_dropdown],