Update app.py

app.py

@@ -24,6 +24,7 @@ from threading import Lock
 import scipy.io.wavfile
 import subprocess
 import spaces
+import torchaudio
 
 # Logging setup
 logging.basicConfig(level=logging.INFO)
@@ -635,7 +636,7 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
             extracted_audio_path = os.path.join("/tmp", f"extracted_audio_{os.path.basename(audio)}.wav")
             logger.info(f"Extracting audio from video file: {audio}")
             ffmpeg_command = [
-                "ffmpeg", "-i", audio, "-vn", "-acodec", "pcm_s16le", "-ar", "48000", "-ac", "2",
+                "ffmpeg", "-i", audio, "-vn", "-acodec", "pcm_s16le", "-ar", "44100", "-ac", "2",
                 extracted_audio_path, "-y"
             ]
             try:
@@ -716,25 +717,50 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
                             continue
                         all_stems.extend(stems_dict[stem_type])
 
-            all_stems = [stem for stem in all_stems if os.path.exists(stem)]
-            if not all_stems:
+            # Dosyaların gerçekten var olduğundan emin ol
+            valid_stems = []
+            for stem in all_stems:
+                if os.path.exists(stem):
+                    valid_stems.append(stem)
+                else:
+                    logger.warning(f"Stem file not found: {stem}")
+            
+            if not valid_stems:
                 raise ValueError("No valid stems found for ensemble after excluding specified stems.")
 
-            weights = [float(w.strip()) for w in weights_str.split(',')] if weights_str.strip() else [1.0] * len(all_stems)
-            if len(weights) != len(all_stems):
-                weights = [1.0] * len(all_stems)
+            weights = [float(w.strip()) for w in weights_str.split(',')] if weights_str.strip() else [1.0] * len(valid_stems)
+            if len(weights) != len(valid_stems):
+                weights = [1.0] * len(valid_stems)
                 logger.info("Weights mismatched, defaulting to 1.0")
-            output_file = os.path.join(output_dir, f"{base_name}_ensemble_{ensemble_method}.{out_format}")
+            
+            # Mutlak yol kullanarak çıktı dosyasını belirle
+            output_file = os.path.abspath(os.path.join(output_dir, f"{base_name}_ensemble_{ensemble_method}.{out_format}"))
+            # Çıktı dizinini oluştur
+            os.makedirs(os.path.dirname(output_file), exist_ok=True)
+            
             ensemble_args = [
-                "--files", *all_stems,
+                "--files", *valid_stems,
                 "--type", ensemble_method,
                 "--weights", *[str(w) for w in weights],
                 "--output", output_file
             ]
             logger.info(f"Running ensemble with args: {ensemble_args}")
-            result = ensemble_files(ensemble_args)
-            if result is None or not os.path.exists(output_file):
-                raise RuntimeError(f"Ensemble failed, output file not created: {output_file}")
+            try:
+                # Ensemble işlemini denetimli çalıştır
+                result = ensemble_files(ensemble_args)
+            except Exception as e:
+                logger.error(f"Ensemble processing failed: {str(e)}")
+                raise RuntimeError(f"Ensemble processing failed: {str(e)}")
+            
+            # Çıktı dosyasının oluştuğundan emin ol
+            if not os.path.exists(output_file):
+                # Alternatif yol deneyelim
+                alt_path = os.path.join(output_dir, f"{base_name}_ensemble_{ensemble_method}.{out_format}")
+                if os.path.exists(alt_path):
+                    logger.info(f"Found ensemble output at alternative path: {alt_path}")
+                    output_file = alt_path
+                else:
+                    raise RuntimeError(f"Ensemble output file not created: {output_file}")
 
             state["current_model_idx"] = 0
             state["current_audio"] = None
@@ -745,7 +771,7 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
             logger.info(f"Ensemble completed, output: {output_file}, took {elapsed:.2f}s")
             progress(1.0, desc="Ensemble completed")
             status = f"Ensemble completed with {ensemble_method}, excluded: {exclude_stems if exclude_stems else 'None'}, {len(model_keys)} models in {elapsed:.2f}s<br>Download files:<ul>"
-            file_list = [output_file] + all_stems
+            file_list = [output_file] + valid_stems
             for file in file_list:
                 file_name = os.path.basename(file)
                 status += f"<li><a href='file={file}' download>{file_name}</a></li>"
@@ -848,7 +874,12 @@ def auto_ensemble_process(audio, model_keys, state, seg_size=64, overlap=0.1, ou
 
     except Exception as e:
         logger.error(f"Ensemble error: {e}")
-        error_msg = f"Processing failed: {e}. Try fewer models (max {max_models}) or uploading a local WAV or video file."
+        # Daha açıklayıcı hata mesajı
+        error_msg = f"Processing failed: {e}\n\nPossible solutions:\n"
+        error_msg += "1. Try fewer models (max 6)\n"
+        error_msg += "2. Upload a local WAV/MP4 file instead of YouTube URL\n"
+        error_msg += "3. Reduce segment size or overlap\n"
+        error_msg += "4. Check if output directory has write permissions"
         raise RuntimeError(error_msg)
 
     finally: