add repair

app/main.py

@@ -19,6 +19,7 @@ import librosa.display
 import soundfile as sf
 import opensmile
 
+import ffmpeg
 
 load_dotenv()
 
@@ -237,6 +238,24 @@ def extract_features(file_path):
     all_data = pd.DataFrame([features_reshaped])
     return all_data
 
+def repair_mp3_with_ffmpeg_python(input_path, output_path):
+    """Attempt to repair an MP3 file using FFmpeg."""
+    try:
+        # Define the audio stream with the necessary conversion parameters
+        audio = (
+            ffmpeg
+            .input(input_path, nostdin=None, y=None)
+            .output(output_path, vn=None, acodec='libmp3lame', ar='44100', ac='1', b='192k', af='aresample=44100')
+            .global_args('-nostdin', '-y')  # Applying global arguments
+            .overwrite_output()
+        )
+        
+        # Execute the FFmpeg command
+        ffmpeg.run(audio)
+        print(f"File repaired and saved as {output_path}")
+    except ffmpeg.Error as e:
+        print(f"Failed to repair file {input_path}: {str(e.stderr)}")
+
 
 @app.post("/mlp")
 async def handle_audio(file: UploadFile = File(...)):
@@ -259,7 +278,7 @@ async def handle_audio(file: UploadFile = File(...)):
             f.write(contents)
 
         preprocess_audio(temp_filename, 'app')
-        
+        repair_mp3_with_ffmpeg_python(temp_filename, temp_filename)
         # Here you would add the feature extraction logic
         features = extract_features(temp_filename)
         print("Extracted Features:", features)

requirements.txt

@@ -16,4 +16,5 @@ soundfile
 opensmile
 eyeD3
 matplotlib
-python-multipart
+python-multipart
+ffmpeg-python