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README.md

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+---
+title: Sas
+emoji: 🦀
+colorFrom: pink
+colorTo: gray
+sdk: gradio
+sdk_version: 5.23.3
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+# This Gradio app allows users to upload an audio file and get a transcription.
+import gradio as gr
+
+# Define the function to transcribe the audio file.
+def transcribe_audio(audio_file):
+    # Check if the file exists and is not too large
+    if not os.path.exists(audio_file):
+        raise gr.Error(f"Error: File {audio_file} not found")
+    
+    file_size = os.path.getsize(audio_file) / (1024 * 1024)  # Convert to MB
+    print(f"Processing file: {audio_file} ({file_size:.2f} MB)")
+    
+    try:
+        start_time = time.time()
+        
+        with open(audio_file, "rb") as file:
+            # Simulate the transcription process
+            transcription = {
+                "text": "This is a simulated transcription of the uploaded audio file."
+            }
+        
+        elapsed = time.time() - start_time
+        print(f"Transcription completed in {elapsed:.2f} seconds")
+        print("\nTranscribed text:")
+        print(transcription["text"])
+        
+        return transcription["text"]
+    
+    except Exception as e:
+        raise gr.Error(f"Error during transcription: {str(e)}")
+
+# Create a Gradio interface that takes an audio file as input and returns the transcription as output.
+with gr.Blocks() as demo:
+    audio_input = gr.Audio(label="Upload Audio File", type="filepath")
+    transcription_output = gr.Textbox(label="Transcribed Text")
+    
+    transcribe_button = gr.Button("Transcribe")
+    
+    # Attach the transcribe_audio function to the button click event.
+    transcribe_button.click(fn=transcribe_audio, inputs=audio_input, outputs=transcription_output)
+
+# Launch the interface.
+demo.launch(show_error=True)