Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import whisper
 from transformers import pipeline
 import librosa
+import os
 
 # Load Whisper model
 whisper_model = whisper.load_model("base")
@@ -19,9 +20,12 @@ def get_summarizer(model_name):
 
 # Function to transcribe audio file using Whisper
 def transcribe_audio(model_size, audio_path):
-    if audio_path is None:
-        return "No audio file provided."
-    
+    # Debug: Check if the file path is correctly passed
+    print(f"Audio file path received: {audio_path}")
+
+    if audio_path is None or not os.path.exists(audio_path):
+        return "No audio file provided or file path invalid."
+
     # Load the selected Whisper model
     model = whisper.load_model(model_size)