Fix decorator

app.py

@@ -1,46 +1,51 @@
 import gradio as gr
 import torch
 from transformers import pipeline
+import spaces  # Ensure spaces library is imported if using GPU decorator
 
-@spaces.GPU(duration=60)
+@spaces.GPU(duration=60)  # Decorator to allocate GPU for the app
+def main():
+    # Force GPU if available, fallback to CPU
+    device = 0 if torch.cuda.is_available() else -1
 
-# Check if GPU is available; fallback to CPU if not
-# device = 0 if torch.cuda.is_available() else -1
-
-try:
-    # Load models with error handling
-    transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=cuda)
-    summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
-except Exception as e:
-    print(f"Error loading models: {e}")
-    raise
-
-# Function to process audio
-def process_audio(audio_file):
     try:
-        # Transcribe the audio
-        transcription = transcriber(audio_file)["text"]
-        # Summarize the transcription
-        summary = summarizer(transcription, max_length=50, min_length=10, do_sample=False)[0]["summary_text"]
-        return transcription, summary
+        # Load models with explicit device
+        transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base", device=device)
+        summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
     except Exception as e:
-        return f"Error processing audio: {e}", ""
+        print(f"Error loading models: {e}")
+        raise
+
+    # Function to process audio
+    def process_audio(audio_file):
+        try:
+            # Transcribe the audio
+            transcription = transcriber(audio_file)["text"]
+            # Summarize the transcription
+            summary = summarizer(transcription, max_length=50, min_length=10, do_sample=False)[0]["summary_text"]
+            return transcription, summary
+        except Exception as e:
+            return f"Error processing audio: {e}", ""
+
+    # Gradio Interface with Horizontal Layout
+    with gr.Blocks() as interface:
+        with gr.Row():
+            with gr.Column():
+                audio_input = gr.Audio(type="filepath", label="Upload Audio File")
+                process_button = gr.Button("Process Audio")
+            with gr.Column():
+                transcription_output = gr.Textbox(label="Full Transcription", lines=10)
+                summary_output = gr.Textbox(label="Summary", lines=5)
 
-# Gradio Interface with Horizontal Layout
-with gr.Blocks() as interface:
-    with gr.Row():
-        with gr.Column():
-            audio_input = gr.Audio(type="filepath", label="Upload Audio File")
-            process_button = gr.Button("Process Audio")
-        with gr.Column():
-            transcription_output = gr.Textbox(label="Full Transcription", lines=10)
-            summary_output = gr.Textbox(label="Summary", lines=5)
+        process_button.click(
+            process_audio,
+            inputs=[audio_input],
+            outputs=[transcription_output, summary_output]
+        )
 
-    process_button.click(
-        process_audio,
-        inputs=[audio_input],
-        outputs=[transcription_output, summary_output]
-    )
+    # Launch the interface with optional public sharing
+    interface.launch(share=True)
 
-# Launch the interface with optional public sharing
-interface.launch(share=True)
+# Run the main function
+if __name__ == "__main__":
+    main()