Update app.py

app.py

@@ -6,8 +6,17 @@ import numpy as np
 from scipy import signal
 import os
 
-processor = WhisperProcessor.from_pretrained("openai/whisper-large-v3")
-model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v3")
+# Set up directories
+home_dir = os.path.expanduser("~")
+cache_dir = os.path.join(home_dir, "cache")
+flagged_dir = os.path.join(home_dir, "flagged")
+
+# Configure cache
+os.environ['TRANSFORMERS_CACHE'] = cache_dir
+os.makedirs(cache_dir, exist_ok=True)
+
+processor = WhisperProcessor.from_pretrained("openai/whisper-large-v3", cache_dir=cache_dir)
+model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-large-v3", cache_dir=cache_dir)
 
 def process_audio(audio_path):
     waveform, sr = sf.read(audio_path)
@@ -21,14 +30,14 @@ def process_audio(audio_path):
     predicted_ids = model.generate(**inputs, language="mk")
     return processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
 
+# Create Gradio interface with custom flagging directory
 demo = gr.Interface(
     fn=process_audio,
     inputs=gr.Audio(sources=["microphone", "upload"], type="filepath"),
     outputs="text",
     title="Македонско препознавање на говор / Macedonian Speech Recognition",
     description="Качете аудио или користете микрофон за транскрипција на македонски говор / Upload audio or use microphone to transcribe Macedonian speech",
-    allow_flagging="manual",
-    flagging_options=["Incorrect Transcription", "Good Transcription"]
+    flagging_dir=flagged_dir
 )
 
 demo.launch(server_name="0.0.0.0", server_port=7860)