Update app.py

app.py

@@ -1,8 +1,10 @@
 import os
 import json
+import numpy as np
 from flask import Flask, jsonify, request
 from transformers import pipeline
 from pydub import AudioSegment
+from scipy.io import wavfile
 from io import BytesIO
 
 # Create a Flask app
@@ -39,7 +41,14 @@ def preprocess_audio(file):
         # Truncate if longer than target duration
         audio = audio[:target_duration_ms]
 
-    return audio
+    # Convert audio to numpy array
+    audio_np = np.array(audio.get_array_of_samples())
+    
+    # Normalize to [-1, 1] range if needed
+    audio_np = audio_np.astype(np.float32)
+    audio_np /= np.max(np.abs(audio_np))
+    
+    return audio_np
 
 @app.route('/detect', methods=['POST'])
 def detect_deepfake():
@@ -50,15 +59,10 @@ def detect_deepfake():
     if audio_file:
         try:
             # Preprocess the audio file
-            audio = preprocess_audio(audio_file)
-            
-            # Save the processed file temporarily
-            temp_wav = BytesIO()
-            audio.export(temp_wav, format="wav")
-            temp_wav.seek(0)
+            audio_np = preprocess_audio(audio_file)
 
             # Perform detection
-            result = audio_model(temp_wav)
+            result = audio_model(audio_np)
             result_dict = {item['label']: item['score'] for item in result}
 
             return jsonify({"message": "Detection completed", "results": result_dict}), 200