Update app.py

app.py

@@ -1,5 +1,5 @@
 import os
-# --- 1. FORCE CPU (GPU Error ကို အပြီးတိုင်ဖြေရှင်းခြင်း) ---
+# --- 1. FORCE CPU (Driver Error ကာကွယ်ရန်) ---
 os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 
 import sys
@@ -9,9 +9,9 @@ import edge_tts
 import asyncio
 import shutil
 import zipfile
-from huggingface_hub import hf_hub_download
+import urllib.request
 
-# PyTorch ကို CPU ပဲသုံးဖို့ အမိန့်ပေးခြင်း
+# PyTorch CPU Mode
 torch.cuda.is_available = lambda : False
 print(f"🚀 System Mode: CPU Only (Stable V2)")
 
@@ -22,19 +22,33 @@ if not os.path.exists("OpenVoice"):
 
 sys.path.append(os.path.abspath("OpenVoice"))
 
-# Checkpoints V2 folder ဆောက်ခြင်း
+# V2 Checkpoints Folder ဖန်တီးခြင်း
 os.makedirs("checkpoints_v2", exist_ok=True)
 
-# V2 Model Download Function
+# V2 Model Download Function (Official S3 Link)
 def download_v2_models():
-    # V2 Converter မရှိသေးရင် Download ဆွဲမယ်
+    # Model ရှိမရှိ စစ်ဆေးခြင်း
     if not os.path.exists("checkpoints_v2/converter/checkpoint.pth"):
-        print("Downloading OpenVoice V2 Model...")
+        print("Downloading OpenVoice V2 Model from AWS...")
         try:
-            # Converter Model (Tone Color)
-            hf_hub_download(repo_id="myshell-ai/OpenVoice", filename="checkpoints_v2/converter/config.json", local_dir=".", local_dir_use_symlinks=False)
-            hf_hub_download(repo_id="myshell-ai/OpenVoice", filename="checkpoints_v2/converter/checkpoint.pth", local_dir=".", local_dir_use_symlinks=False)
-            print("✅ V2 Model Downloaded!")
+            # 1. Zip ဖိုင်ကို ဒေါင်းလုပ်ဆွဲခြင်း
+            url = "https://myshell-public-repo-hosting.s3.amazonaws.com/openvoice/checkpoints_v2_0417.zip"
+            zip_path = "checkpoints_v2.zip"
+            urllib.request.urlretrieve(url, zip_path)
+            
+            # 2. ဖြည်ချခြင်း (Unzip)
+            print("Extracting Model...")
+            with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+                zip_ref.extractall(".")
+            
+            # 3. Folder နာမည်ပြန်ညှိခြင်း (လိုအပ်လျှင်)
+            if os.path.exists("checkpoints_v2_0417"):
+                # အဟောင်းဖျက်ပြီး အသစ်နေရာချ
+                if os.path.exists("checkpoints_v2"):
+                    shutil.rmtree("checkpoints_v2")
+                os.rename("checkpoints_v2_0417", "checkpoints_v2")
+                
+            print("✅ V2 Model Ready!")
         except Exception as e:
             print(f"Download Error: {e}")
 
@@ -51,18 +65,17 @@ except ImportError:
 
 # --- 3. Load V2 Model ---
 ckpt_converter = 'checkpoints_v2/converter'
-if not os.path.exists(f"{ckpt_converter}/config.json"):
-    # Fallback path logic
-    ckpt_converter = 'OpenVoice/checkpoints_v2/converter'
 
-print("Initializing V2 Model on CPU...")
+print(f"Loading V2 Model from {ckpt_converter}...")
 try:
-    # V2 မှာ device='cpu' လို့ အတိအကျပေးရပါတယ်
+    # V2 requires 'device' argument
     tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device='cpu')
     tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
     print("✅ V2 Model Loaded Successfully!")
 except Exception as e:
     print(f"Model Load Error: {e}")
+    # Error တက်ရင် Variable ကို None ပေးထားမည် (UI မှာ Crash မဖြစ်အောင်)
+    tone_color_converter = None
 
 # --- 4. Mastering Engine ---
 def apply_mastering(input_wav, style="Radio"):
@@ -89,6 +102,8 @@ async def run_edge_tts(text, gender):
     return output_file
 
 def predict(text, ref_audio, gender, mastering_style):
+    if tone_color_converter is None:
+        return "Critical Error: Model not loaded. Check logs.", None
     if not text: return "စာရိုက်ထည့်ပါ", None
     if not ref_audio: return "Reference Audio ထည့်ပါ", None
 
@@ -99,7 +114,7 @@ def predict(text, ref_audio, gender, mastering_style):
         # Step B: OpenVoice V2 Conversion
         os.makedirs("outputs", exist_ok=True)
         
-        # VAD Handling (Try/Except blocks for safety)
+        # VAD Handling
         try:
             target_se, _ = se_extractor.get_se(ref_audio, tone_color_converter, target_dir='outputs', vad=True)
         except:
@@ -109,7 +124,6 @@ def predict(text, ref_audio, gender, mastering_style):
 
         raw_output = "outputs/raw_v2.wav"
         
-        # Actual Conversion
         tone_color_converter.convert(
             audio_src_path=base_audio,
             src_se=source_se,
@@ -123,12 +137,14 @@ def predict(text, ref_audio, gender, mastering_style):
         return "Success (V2 Ready)!", final_output
 
     except Exception as e:
+        import traceback
+        traceback.print_exc()
         return f"Error: {str(e)}", None
 
 # UI
 with gr.Blocks(title="Myanmar OpenVoice V2") as demo:
     gr.Markdown("# 🇲🇲 Myanmar Voice Cloning (OpenVoice V2)")
-    gr.Markdown("V2 Model + CPU Stable Version")
+    gr.Markdown("V2 Model (AWS Source) + CPU Stable")
     
     with gr.Row():
         with gr.Column():