Update app.py

app.py

@@ -2,6 +2,7 @@ import os
 import json
 from flask import Flask, jsonify, request
 from transformers import pipeline
+from pydub import AudioSegment
 
 # Create a Flask app
 app = Flask(__name__)
@@ -19,6 +20,11 @@ def download_models():
 # Download model when the server starts
 download_models()
 
+def convert_audio_to_wav(input_path, output_path):
+    # Convert any audio format to WAV using pydub
+    audio = AudioSegment.from_file(input_path)
+    audio.export(output_path, format="wav")
+
 @app.route('/detect', methods=['POST'])
 def detect_deepfake():
     # Expect an audio file in the request
@@ -28,15 +34,20 @@ def detect_deepfake():
     if audio_file:
         try:
             # Save the uploaded file temporarily
-            file_path = os.path.join("/tmp", audio_file.filename)
-            audio_file.save(file_path)
+            input_path = os.path.join("/tmp", audio_file.filename)
+            audio_file.save(input_path)
+
+            # Convert the file to WAV format
+            output_path = os.path.splitext(input_path)[0] + '.wav'
+            convert_audio_to_wav(input_path, output_path)
 
             # Perform detection
-            result = audio_model(file_path)
+            result = audio_model(output_path)
             result_dict = {item['label']: item['score'] for item in result}
 
-            # Remove the temporary file
-            os.remove(file_path)
+            # Remove the temporary files
+            os.remove(input_path)
+            os.remove(output_path)
 
             return jsonify({"message": "Detection completed", "results": result_dict}), 200