Update app.py

app.py

@@ -1,6 +1,9 @@
 import gradio as gr
 import whisper
 from transformers import pipeline
+import torch
+import numpy as np
+import librosa
 
 # Load Whisper model
 whisper_model = whisper.load_model("base")
@@ -18,9 +21,19 @@ def get_summarizer(model_name):
 
 # Function to transcribe audio file using Whisper
 def transcribe_audio(model_size, audio):
+    if audio is None:
+        return "No audio file provided."
+    
+    # Load the selected Whisper model
     model = whisper.load_model(model_size)
-    result = model.transcribe(audio)
+
+    # Load and convert audio using librosa
+    audio_data, sample_rate = librosa.load(audio, sr=16000)
+
+    # Transcribe the audio file
+    result = model.transcribe(audio_data)
     transcription = result['text']
+    
     return transcription
 
 # Function to summarize the transcribed text