remove persistent storage

app.py

@@ -4,14 +4,8 @@ from transformers import pipeline
 import librosa
 import soundfile as sf
 import os
-import uuid
 import spaces  # Ensure spaces is imported
 
-# Directory to save processed audio files
-OUTPUT_DIR = os.getenv("HF_HOME", ".")  # Use dynamic path or default to current directory
-OUTPUT_DIR = os.path.join(OUTPUT_DIR, "processed_audio_files")
-os.makedirs(OUTPUT_DIR, exist_ok=True)
-
 def split_audio(audio_data, sr, chunk_duration=30):
     """Split audio into chunks of chunk_duration seconds."""
     chunks = []
@@ -38,25 +32,6 @@ def transcribe_long_audio(audio_path, transcriber, chunk_duration=30):
         print(f"Error in transcribe_long_audio: {e}")
         return f"Error processing audio: {e}"
 
-def cleanup_output_dir(max_storage_mb=500):
-    """Remove old files if total directory size exceeds max_storage_mb."""
-    try:
-        total_size = sum(
-            os.path.getsize(os.path.join(OUTPUT_DIR, f)) for f in os.listdir(OUTPUT_DIR)
-        )
-        if total_size > max_storage_mb * 1024 * 1024:
-            files = sorted(
-                (os.path.join(OUTPUT_DIR, f) for f in os.listdir(OUTPUT_DIR)),
-                key=os.path.getctime,
-            )
-            for file in files:
-                os.remove(file)
-                total_size -= os.path.getsize(file)
-                if total_size <= max_storage_mb * 1024 * 1024:
-                    break
-    except Exception as e:
-        print(f"Error during cleanup: {e}")
-
 @spaces.GPU(duration=3)
 def main():
     device = 0 if torch.cuda.is_available() else -1
@@ -80,9 +55,6 @@ def main():
             transcription = transcribe_long_audio(audio_input, transcriber, chunk_duration=30)
             summary = summarizer(transcription, max_length=50, min_length=10, do_sample=False)[0]["summary_text"]
 
-            # Cleanup old files
-            cleanup_output_dir()
-
             return transcription, summary, audio_input
         except Exception as e:
             print(f"Error in process_audio: {e}")
@@ -93,9 +65,9 @@ def main():
             with gr.Column():
                 # Only support file uploads
                 audio_input = gr.Audio(type="filepath", label="Upload Audio File")
-                process_button = gr.Button("Process Audio")
+                process_button = gr.Button("Transcribe Audio")
             with gr.Column():
-                transcription_output = gr.Textbox(label="Full Transcription", lines=10)
+                transcription_output = gr.Textbox(label="Transcription", lines=10)
                 summary_output = gr.Textbox(label="Summary", lines=5)
                 audio_output = gr.Audio(label="Playback Processed Audio")