Added multi-tab layout and warning for summarization time

app.py

@@ -5,48 +5,103 @@ from modules.summarizer import summarize_text
 from modules.classifier import classify_text
 from modules.event_detector import detect_events
 
-# Main function that processes input
-def process_text(input_text):
+# Define individual task functions
+def process_summarization(input_text):
     summary = summarize_text(input_text)
+    return summary
+
+def process_classification(input_text):
     classification = classify_text(input_text)
+    return classification
+
+def process_event_detection(input_text):
     events = detect_events(input_text)
-    
-    # Display events in a comma-separated format
     events_formatted = ', '.join(events) if isinstance(events, list) else events
-    return summary, classification, events_formatted
+    return events_formatted
 
-# Create the Gradio UI
+# Create Gradio UI with Tabs
 with gr.Blocks() as demo:
     gr.Markdown(
         """
         # 🧠 NLP Assistant
-        Enter your text below and get:
-        - 📚 **Summarization**
-        - 🏷️ **Text Classification**
-        - 🗂️ **Event Detection**
+        A simple app for:
+        - 📚 Summarization
+        - 🏷️ News Classification
+        - 🗂️ Event Detection
         """
     )
 
-    with gr.Row():
-        input_text = gr.Textbox(
-            label="Input Text",
-            placeholder="Paste your article, document, or paragraph here...",
-            lines=10
-        )
-
-    with gr.Row():
-        submit_btn = gr.Button("Process")
-
-    with gr.Row():
-        summary_output = gr.Textbox(label="Summary", lines=5)
-        classification_output = gr.Textbox(label="Classification", lines=2)
-        events_output = gr.Textbox(label="Detected Events", lines=5)
-
-    submit_btn.click(
-        fn=process_text,
-        inputs=[input_text],
-        outputs=[summary_output, classification_output, events_output]
-    )
+    with gr.Tabs():
+        # Summarization Tab
+        with gr.Tab("📚 Summarization"):
+            gr.Markdown(
+                """
+                ## 📚 Summarization
+                Enter your text below and get a summarized version.
+
+                ⚠️ **Note:**  
+                - This task can take **~800–1000 seconds (~13–16 minutes)** for about **700–800 words**.  
+                - Longer articles will take **even more time**.  
+                - Please be patient!
+                """
+            )
+            input_text_sum = gr.Textbox(
+                label="Input Text for Summarization",
+                placeholder="Paste your article, document, or paragraph here...",
+                lines=10
+            )
+            summarize_btn = gr.Button("Summarize")
+            summary_output = gr.Textbox(label="Summary", lines=8)
+
+            summarize_btn.click(
+                fn=process_summarization,
+                inputs=[input_text_sum],
+                outputs=[summary_output]
+            )
+
+        # Classification Tab
+        with gr.Tab("🏷️ Classification"):
+            gr.Markdown(
+                """
+                ## 🏷️ News/Text Classification
+                Enter your text below to detect its category.
+                """
+            )
+            input_text_classify = gr.Textbox(
+                label="Input Text for Classification",
+                placeholder="Paste your article or paragraph here...",
+                lines=10
+            )
+            classify_btn = gr.Button("Classify")
+            classification_output = gr.Textbox(label="Classification Result", lines=2)
+
+            classify_btn.click(
+                fn=process_classification,
+                inputs=[input_text_classify],
+                outputs=[classification_output]
+            )
+
+        # Event Detection Tab
+        with gr.Tab("🗂️ Event Detection"):
+            gr.Markdown(
+                """
+                ## 🗂️ Event Detection
+                Extract keywords and named entities from your text.
+                """
+            )
+            input_text_events = gr.Textbox(
+                label="Input Text for Event Detection",
+                placeholder="Paste your article, news, or report here...",
+                lines=10
+            )
+            detect_btn = gr.Button("Detect Events")
+            events_output = gr.Textbox(label="Detected Events", lines=8)
+
+            detect_btn.click(
+                fn=process_event_detection,
+                inputs=[input_text_events],
+                outputs=[events_output]
+            )
 
 # Launch Gradio app
 if __name__ == "__main__":