Update app.py

app.py

@@ -1,5 +1,5 @@
 import os
-# --- 1. FORCE CPU (GPU Error ရှောင်ရန်) ---
+# --- FORCE CPU (GPU Error ရှောင်ရန်) ---
 os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 
 import sys
@@ -8,54 +8,38 @@ import gradio as gr
 import edge_tts
 import asyncio
 import shutil
-import zipfile
 from huggingface_hub import hf_hub_download
 
 # PyTorch CPU Mode
 torch.cuda.is_available = lambda : False
-print(f"🚀 System Mode: CPU Only (Stable V2)")
+print(f"🚀 System Mode: CPU Only (OpenVoice V1)")
 
-# --- 2. Setup OpenVoice V2 ---
+# --- 1. Setup OpenVoice V1 ---
 if not os.path.exists("OpenVoice"):
-    print("Installing OpenVoice V2...")
+    print("Cloning OpenVoice V1...")
     os.system("git clone https://github.com/myshell-ai/OpenVoice.git")
 
 sys.path.append(os.path.abspath("OpenVoice"))
 
-# V2 Checkpoints Folder
-os.makedirs("checkpoints_v2", exist_ok=True)
+# V1 Checkpoints Folder
+os.makedirs("checkpoints/converter", exist_ok=True)
 
-# V2 Model Download Function (Hugging Face Source)
-def download_v2_models():
-    # Model ရှိမရှိ စစ်ဆေးခြင်း
-    if not os.path.exists("checkpoints_v2/converter/checkpoint.pth"):
-        print("Downloading OpenVoice V2 Zip from Hugging Face...")
+# V1 Model Download (Hugging Face Source)
+def download_v1_models():
+    if not os.path.exists("checkpoints/converter/checkpoint.pth"):
+        print("Downloading V1 Model from Hugging Face...")
         try:
-            # AWS Link (403 Error) အစား Hugging Face Link ကို သုံးသည်
-            zip_path = hf_hub_download(
-                repo_id="myshell-ai/OpenVoice",
-                filename="checkpoints_v2_0417.zip",
-                local_dir=".",
-                local_dir_use_symlinks=False
-            )
-            
-            print("Extracting Model Zip...")
-            with zipfile.ZipFile(zip_path, 'r') as zip_ref:
-                zip_ref.extractall(".")
-            
-            # Folder နာမည်ပြန်ညှိခြင်း
-            if os.path.exists("checkpoints_v2_0417"):
-                if os.path.exists("checkpoints_v2"):
-                    shutil.rmtree("checkpoints_v2")
-                os.rename("checkpoints_v2_0417", "checkpoints_v2")
-                
-            print("✅ V2 Model Extracted Successfully!")
+            # Config File
+            hf_hub_download(repo_id="myshell-ai/OpenVoice", filename="checkpoints/converter/config.json", local_dir=".", local_dir_use_symlinks=False)
+            # Model File (V1)
+            hf_hub_download(repo_id="myshell-ai/OpenVoice", filename="checkpoints/converter/checkpoint.pth", local_dir=".", local_dir_use_symlinks=False)
+            print("✅ V1 Model Downloaded!")
         except Exception as e:
             print(f"Download Error: {e}")
 
-download_v2_models()
+download_v1_models()
 
-# Import OpenVoice Modules
+# Import Modules
 try:
     from openvoice.api import ToneColorConverter
     from openvoice import se_extractor
@@ -64,22 +48,23 @@ except ImportError:
     from api import ToneColorConverter
     import se_extractor
 
-# --- 3. Load V2 Model ---
-ckpt_converter = 'checkpoints_v2/converter'
+# --- 2. Load V1 Model ---
+ckpt_converter = 'checkpoints/converter'
 if not os.path.exists(f"{ckpt_converter}/config.json"):
-    print("Warning: Config not found, trying fallback path...")
-    ckpt_converter = 'OpenVoice/checkpoints_v2/converter'
+    # Fallback logic
+    ckpt_converter = 'OpenVoice/checkpoints/converter'
 
-print(f"Loading V2 Model from {ckpt_converter}...")
+print(f"Loading V1 Model...")
 try:
+    # V1 Model Load (CPU)
     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!")
+    print("✅ V1 Model Loaded Successfully!")
 except Exception as e:
-    print(f"CRITICAL MODEL LOAD ERROR: {e}")
+    print(f"Model Load Error: {e}")
     tone_color_converter = None
 
-# --- 4. Mastering Engine ---
+# --- 3. Mastering Engine (Audio Fix) ---
 def apply_mastering(input_wav, style="Radio"):
     if not shutil.which("ffmpeg"): return input_wav 
     output_wav = "outputs/mastered_output.wav"
@@ -96,7 +81,7 @@ def apply_mastering(input_wav, style="Radio"):
         return output_wav
     except: return input_wav
 
-# --- 5. Main Workflow ---
+# --- 4. Main Workflow ---
 async def run_edge_tts(text, gender):
     voice = "my-MM-ThihaNeural" if gender == "Male" else "my-MM-NularNeural"
     output_file = "temp_base.mp3"
@@ -105,7 +90,7 @@ async def run_edge_tts(text, gender):
 
 def predict(text, ref_audio, gender, mastering_style):
     if tone_color_converter is None:
-        return "System Error: Model failed to load. Check logs.", None
+        return "System Error: Model failed to load.", None
     if not text: return "စာရိုက်ထည့်ပါ", None
     if not ref_audio: return "Reference Audio ထည့်ပါ", None
 
@@ -113,9 +98,10 @@ def predict(text, ref_audio, gender, mastering_style):
         # Step A: Edge TTS
         base_audio = asyncio.run(run_edge_tts(text, gender))
 
-        # Step B: OpenVoice V2
+        # Step B: OpenVoice V1
         os.makedirs("outputs", exist_ok=True)
         
+        # VAD Handling
         try:
             target_se, _ = se_extractor.get_se(ref_audio, tone_color_converter, target_dir='outputs', vad=True)
         except:
@@ -123,7 +109,7 @@ def predict(text, ref_audio, gender, mastering_style):
 
         source_se, _ = se_extractor.get_se(base_audio, tone_color_converter, target_dir='outputs', vad=False)
 
-        raw_output = "outputs/raw_v2.wav"
+        raw_output = "outputs/raw_v1.wav"
         
         tone_color_converter.convert(
             audio_src_path=base_audio,
@@ -135,7 +121,7 @@ def predict(text, ref_audio, gender, mastering_style):
         
         # Step C: Mastering
         final_output = apply_mastering(raw_output, mastering_style)
-        return "Success (V2 Ready)!", final_output
+        return "Success (V1)!", final_output
 
     except Exception as e:
         import traceback
@@ -143,9 +129,9 @@ def predict(text, ref_audio, gender, mastering_style):
         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("Corrected Download Source (No 403 Error)")
+with gr.Blocks(title="Myanmar OpenVoice V1") as demo:
+    gr.Markdown("# 🇲🇲 Myanmar Voice Cloning (OpenVoice V1)")
+    gr.Markdown("V1 Model + CPU Stable Mode")
     
     with gr.Row():
         with gr.Column():