Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from transformers import pipeline
 
 # Load models
-transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base")
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=0 if torch.cuda.is_available() else -1)
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
 # Function to process audio
@@ -15,17 +15,24 @@ def process_audio(audio_file):
     
     return transcription, summary
 
-# Gradio Interface
-interface = gr.Interface(
-    fn=process_audio,
-    inputs=gr.Audio(type="filepath", label="Upload Audio File"),
-    outputs=[
-        gr.Textbox(label="Full Transcription"),
-        gr.Textbox(label="Summary")
-    ],
-    title="Audio Transcription and Summarization",
-    description="Upload an audio file to get a full transcription and a brief summary of its content."
-)
+# Gradio Interface with Horizontal Layout
+with gr.Blocks() as interface:
+    with gr.Row():
+        # Upload button on the left
+        with gr.Column():
+            audio_input = gr.Audio(type="filepath", label="Upload Audio File")
+            process_button = gr.Button("Process Audio")
+        # Output text box on the right
+        with gr.Column():
+            transcription_output = gr.Textbox(label="Full Transcription", lines=10)
+            summary_output = gr.Textbox(label="Summary", lines=5)
 
-# Launch the interface
-interface.launch()
+    # Link the button to the function
+    process_button.click(
+        process_audio,
+        inputs=[audio_input],
+        outputs=[transcription_output, summary_output]
+    )
+
+# Launch the interface with SSR disabled and optional public sharing
+interface.launch