Create app.py

app.py

@@ -0,0 +1,116 @@
+import os
+import sys
+import gradio as gr
+import subprocess
+import json
+
+# Set environment variables for HF Spaces
+os.environ["GRADIO_SERVER_NAME"] = "0.0.0.0"
+os.environ["GRADIO_SERVER_PORT"] = "7860"
+
+# Pre-download models cache
+os.environ["HF_HUB_CACHE"] = "/tmp/hf_cache"
+os.environ["HUGGINGFACE_HUB_CACHE"] = "/tmp/hf_cache"
+
+# Fix potential Hunyuan Video Avatar issues
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+def setup_environment():
+    """Setup environment for HF Spaces with WanGP v6.3"""
+    # Install additional dependencies if needed
+    try:
+        import sageattention
+    except ImportError:
+        print("Installing SageAttention...")
+        subprocess.run([sys.executable, "-m", "pip", "install", "sageattention==1.0.6"], check=True)
+    
+    # Ensure face detection libs are available
+    try:
+        import insightface
+        import facexlib
+    except ImportError:
+        print("Installing face processing libraries...")
+        subprocess.run([sys.executable, "-m", "pip", "install", "insightface", "facexlib"], check=True)
+
+def download_essential_models():
+    """Pre-download essential models for faster startup"""
+    from huggingface_hub import snapshot_download
+    
+    print("Downloading Hunyuan Video Avatar models...")
+    try:
+        # Download Hunyuan Video Avatar base models
+        snapshot_download(
+            repo_id="tencent/HunyuanVideo-Avatar", 
+            cache_dir="/tmp/hf_cache",
+            allow_patterns=["*.safetensors", "*.json", "*.txt", "*.bin"],
+            ignore_patterns=["*.mp4", "*.avi", "*.mov"]  # Skip demo videos
+        )
+        
+        # Download base Hunyuan Video model
+        snapshot_download(
+            repo_id="tencent/HunyuanVideo",
+            cache_dir="/tmp/hf_cache", 
+            allow_patterns=["*.safetensors", "*.json", "*.txt"],
+            ignore_patterns=["*.mp4", "*.avi"]
+        )
+        
+    except Exception as e:
+        print(f"Model download warning: {e}")
+        print("Models will be downloaded on-demand during first use.")
+
+def create_hf_config():
+    """Create optimized config for HF Spaces deployment"""
+    config = {
+        "model_settings": {
+            "profile": 3,  # Optimized for A10G Large
+            "quantize_transformer": True,
+            "attention_mode": "sage",
+            "compile": False,  # Disable for stability on HF
+            "teacache": "2.0"
+        },
+        "avatar_settings": {
+            "max_frames": 120,  # ~5 seconds at 24fps
+            "resolution": "512x512",  # Balanced quality/performance
+            "emotion_control": True,
+            "multi_character": True
+        },
+        "memory_optimization": {
+            "enable_vae_tiling": True,
+            "enable_cpu_offload": True,
+            "max_batch_size": 1,
+            "gradient_checkpointing": True
+        },
+        "audio_processing": {
+            "sample_rate": 16000,
+            "max_duration": 15,  # seconds
+            "supported_formats": ["wav", "mp3", "m4a"]
+        }
+    }
+    
+    with open("/tmp/hf_config.json", "w") as f:
+        json.dump(config, f, indent=2)
+    
+    return config
+
+if __name__ == "__main__":
+    print("🚀 Starting WanGP v6.3 with Hunyuan Video Avatar...")
+    
+    setup_environment()
+    config = create_hf_config()
+    download_essential_models()
+    
+    print("✅ Setup complete! Launching application...")
+    
+    # Import and run the main application
+    from wgp import main
+    main(
+        profile=3,  # Higher profile for A10G Large
+        attention="sage",  # Use Sage attention for better performance
+        server_name="0.0.0.0", 
+        server_port=7860,
+        quantize_transformer=True,
+        teacache="2.0",  # Enable TeaCache for Avatar acceleration
+        compile=False,  # Disabled for HF Spaces stability
+        share=False,  # HF Spaces handles sharing
+        config_file="/tmp/hf_config.json"
+    )