Add runtime model downloading to avoid storage limits

- Add download_models.py script to download xcodec_mini_infer models at runtime
- Modify app.py to automatically download models on startup
- Add huggingface_hub dependency for model downloads
- Remove large model files from repository to stay under 1GB limit

app.py

@@ -76,6 +76,28 @@ def install_flash_attn():
 # Setup environment first
 setup_spaces_environment()
 
+# Download required models for YuEGP inference
+def download_required_models():
+    """Download required model files at startup"""
+    try:
+        from download_models import ensure_model_availability
+        print("🚀 Checking and downloading required models...")
+        success = ensure_model_availability()
+        if success:
+            print("✅ Model setup completed successfully")
+        else:
+            print("⚠️ Some models may be missing - continuing with available resources")
+        return success
+    except ImportError as e:
+        print(f"⚠️ Model download script not found: {e}")
+        return False
+    except Exception as e:
+        print(f"❌ Error during model download: {e}")
+        return False
+
+# Download models before other setup
+models_ready = download_required_models()
+
 # Install flash-attn if needed
 flash_attn_available = install_flash_attn()
 

download_models.py

@@ -0,0 +1,128 @@
+#!/usr/bin/env python3
+"""
+Model Download Script for MiloMusic
+Downloads required model files from Hugging Face Hub at runtime to avoid storage limits.
+"""
+
+import os
+import shutil
+from pathlib import Path
+from huggingface_hub import hf_hub_download, snapshot_download
+
+
+def download_xcodec_models():
+    """Download xcodec_mini_infer models from Hugging Face Hub"""
+    
+    # Base path for xcodec models
+    xcodec_base = Path("YuEGP/inference/xcodec_mini_infer")
+    
+    print("📥 Downloading xcodec_mini_infer models...")
+    
+    try:
+        # Download the entire xcodec_mini_infer repository
+        cache_dir = snapshot_download(
+            repo_id="m-a-p/xcodec_mini_infer",
+            cache_dir="/tmp/hf_cache",
+            local_dir=str(xcodec_base),
+            local_dir_use_symlinks=False
+        )
+        
+        print("✅ Successfully downloaded xcodec_mini_infer models")
+        return True
+        
+    except Exception as e:
+        print(f"❌ Error downloading xcodec_mini_infer models: {e}")
+        
+        # Try downloading individual essential files if full download fails
+        try:
+            print("🔄 Attempting to download essential files individually...")
+            
+            # Ensure directories exist
+            os.makedirs(xcodec_base / "semantic_ckpts" / "hf_1_325000", exist_ok=True)
+            os.makedirs(xcodec_base / "final_ckpt", exist_ok=True)
+            os.makedirs(xcodec_base / "decoders", exist_ok=True)
+            
+            # Download essential model files
+            essential_files = [
+                "semantic_ckpts/hf_1_325000/pytorch_model.bin",
+                "semantic_ckpts/hf_1_325000/preprocessor_config.json",
+                "final_ckpt/ckpt_00360000.pth",
+                "final_ckpt/config.yaml",
+                "decoders/decoder_131000.pth",
+                "decoders/decoder_151000.pth",
+                "decoders/config.yaml"
+            ]
+            
+            for file_path in essential_files:
+                try:
+                    local_path = xcodec_base / file_path
+                    os.makedirs(local_path.parent, exist_ok=True)
+                    
+                    downloaded_file = hf_hub_download(
+                        repo_id="m-a-p/xcodec_mini_infer",
+                        filename=file_path,
+                        cache_dir="/tmp/hf_cache"
+                    )
+                    
+                    # Copy to local directory
+                    shutil.copy2(downloaded_file, local_path)
+                    print(f"✅ Downloaded: {file_path}")
+                    
+                except Exception as file_error:
+                    print(f"⚠️ Failed to download {file_path}: {file_error}")
+                    
+            return True
+            
+        except Exception as fallback_error:
+            print(f"❌ Fallback download also failed: {fallback_error}")
+            return False
+
+
+def ensure_model_availability():
+    """
+    Ensure all required models are available locally.
+    Download them if they don't exist.
+    """
+    
+    xcodec_base = Path("YuEGP/inference/xcodec_mini_infer")
+    
+    # Check if essential model files exist
+    essential_files = [
+        xcodec_base / "semantic_ckpts" / "hf_1_325000" / "pytorch_model.bin",
+        xcodec_base / "final_ckpt" / "ckpt_00360000.pth",
+        xcodec_base / "decoders" / "decoder_131000.pth"
+    ]
+    
+    missing_files = [f for f in essential_files if not f.exists()]
+    
+    if missing_files:
+        print(f"⚠️ Missing model files: {[str(f) for f in missing_files]}")
+        print("🚀 Starting model download...")
+        
+        success = download_xcodec_models()
+        
+        if success:
+            print("✅ Model download completed successfully!")
+        else:
+            print("❌ Model download failed. Some functionality may be limited.")
+            return False
+    else:
+        print("✅ All required model files are already present")
+    
+    return True
+
+
+if __name__ == "__main__":
+    """
+    Run model download when script is executed directly
+    """
+    print("🎵 MiloMusic Model Download Script")
+    print("=" * 50)
+    
+    success = ensure_model_availability()
+    
+    if success:
+        print("\n🎉 Setup complete! MiloMusic is ready to generate music.")
+    else:
+        print("\n⚠️ Setup completed with warnings. Check the logs above.")
+        exit(1)

requirements.txt

@@ -28,6 +28,7 @@ python-dotenv==1.1.0
 spaces==0.34.2
 xxhash==3.5.0
 soundfile==0.13.1
+huggingface_hub==0.28.0
 
 # Audio processing
 librosa==0.11.0