Update app.py

app.py

@@ -8,7 +8,7 @@ asr = pipeline(task="automatic-speech-recognition", model="distil-whisper/distil
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad")
 
-# Global variable to store transcript for Q&A
+# Global transcript
 stored_transcript = ""
 
 def transcribe_and_summarize(video_file):
@@ -24,9 +24,8 @@ def transcribe_and_summarize(video_file):
 
         transcription_result = asr(audio_path, return_timestamps=True)
         transcribed_text = " ".join([segment['text'] for segment in transcription_result['chunks']])
-        stored_transcript = transcribed_text  # Save for Q&A
+        stored_transcript = transcribed_text
 
-        # Summarize
         if len(transcribed_text.split()) < 50:
             summarized_text = "Text too short to summarize."
         else:
@@ -45,23 +44,32 @@ def answer_question(question):
     result = qa_pipeline(question=question, context=stored_transcript)
     return result['answer']
 
-# Gradio interface with three parts
-with gr.Blocks() as iface:
-    with gr.Row():
-        video_input = gr.Video(label="Upload Video (.mp4)")
-        transcribed_text = gr.Textbox(label="Transcribed Text", lines=6)
-        summarized_text = gr.Textbox(label="Summarized Text", lines=6)
+# Gradio UI
+with gr.Blocks(theme=gr.themes.Base()) as iface:
+    gr.Markdown("## 🎥 Video Transcriber, Summarizer & Q&A Tool")
+    gr.Markdown("Upload a video to get a transcript, summary, and ask questions about its content.")
 
-    transcribe_btn = gr.Button("Transcribe and Summarize")
-    transcribe_btn.click(fn=transcribe_and_summarize, inputs=video_input, outputs=[transcribed_text, summarized_text])
+    with gr.Tab("1️⃣ Transcription & Summary"):
+        with gr.Row():
+            video_input = gr.Video(label="📂 Upload Video (.mp4)", interactive=True)
+        with gr.Row():
+            transcribe_btn = gr.Button("🚀 Transcribe and Summarize")
+        with gr.Row():
+            transcribed_text = gr.Textbox(label="📝 Transcribed Text", lines=8, interactive=False)
+            summarized_text = gr.Textbox(label="📄 Summarized Text", lines=8, interactive=False)
 
-    with gr.Row():
-        question_input = gr.Textbox(label="Ask a question about the transcript")
-        answer_output = gr.Textbox(label="Answer")
+        transcribe_btn.click(fn=transcribe_and_summarize, inputs=video_input, outputs=[transcribed_text, summarized_text])
 
-    ask_btn = gr.Button("Get Answer")
-    ask_btn.click(fn=answer_question, inputs=question_input, outputs=answer_output)
+    with gr.Tab("2️⃣ Ask Questions"):
+        with gr.Row():
+            question_input = gr.Textbox(label="❓ Ask a question based on the transcript", placeholder="E.g., What is the main topic?")
+        with gr.Row():
+            ask_btn = gr.Button("🔍 Get Answer")
+        with gr.Row():
+            answer_output = gr.Textbox(label="💬 Answer", interactive=False)
 
-# Launch
+        ask_btn.click(fn=answer_question, inputs=question_input, outputs=answer_output)
+
+# Launch app
 port = int(os.environ.get('PORT1', 7860))
 iface.launch(share=True, server_port=port)