app.py

import os
import subprocess
import sys
from pathlib import Path

# --- 0. Hardcoded Toggle for Execution Environment ---
# Set this to True to use Hugging Face ZeroGPU (recommended)
# Set this to False to use the slower, pure CPU environment
USE_ZEROGPU = True

# --- 1. Clone the VibeVoice Repository ---
repo_dir = "VibeVoice"
if not os.path.exists(repo_dir):
    print("Cloning the VibeVoice repository...")
    try:
        subprocess.run(
            ["git", "clone", "https://github.com/microsoft/VibeVoice.git"],
            check=True,
            capture_output=True,
            text=True
        )
        print("Repository cloned successfully.")
    except subprocess.CalledProcessError as e:
        print(f"Error cloning repository: {e.stderr}")
        sys.exit(1)
else:
    print("Repository already exists. Skipping clone.")

# --- 2. Install the VibeVoice Package ---
# Note: Other dependencies are installed via requirements.txt
os.chdir(repo_dir)
print(f"Changed directory to: {os.getcwd()}")

print("Installing the VibeVoice package in editable mode...")
try:
    subprocess.run(
        [sys.executable, "-m", "pip", "install", "-e", "."],
        check=True,
        capture_output=True,
        text=True
    )
    print("Package installed successfully.")
except subprocess.CalledProcessError as e:
    print(f"Error installing package: {e.stderr}")
    sys.exit(1)

# --- 3. Modify the demo script to be environment-aware ---
demo_script_path = Path("demo/gradio_demo.py")
print(f"Reading {demo_script_path} to apply environment-specific modifications...")

try:
    file_content = demo_script_path.read_text()

    # Define the original model loading block that we need to replace.
    # This block is problematic because it hardcodes FlashAttention.
    original_block = """        self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
            self.model_path,
            torch_dtype=torch.bfloat16,
            device_map='cuda',
            attn_implementation="flash_attention_2",
        )"""

    if USE_ZEROGPU:
        print("Optimizing for ZeroGPU execution...")
        
        # New block for ZeroGPU: We remove the problematic `attn_implementation` line.
        # `transformers` will automatically use the best available attention mechanism.
        replacement_block_gpu = """        self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
            self.model_path,
            torch_dtype=torch.bfloat16,
            device_map='cuda',
        )"""
        
        # Add 'import spaces' at the beginning of the file for the @spaces.GPU decorator
        modified_content = "import spaces\n" + file_content
        
        # Decorate the main interface class to request a GPU from the Spaces infrastructure
        modified_content = modified_content.replace(
            "class VibeVoiceGradioInterface:",
            "@spaces.GPU(duration=120)\nclass VibeVoiceGradioInterface:"
        )
        
        # Replace the model loading block
        modified_content = modified_content.replace(original_block, replacement_block_gpu)
        print("Script modified for ZeroGPU successfully.")

    else: # Pure CPU execution
        print("Modifying for pure CPU execution...")
        
        # New block for CPU: Use float32 and map directly to the CPU.
        replacement_block_cpu = """        self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
            self.model_path,
            torch_dtype=torch.float32,  # Use float32 for CPU
            device_map="cpu",
        )"""
        
        # Replace the original model loading block with the CPU version
        modified_content = file_content.replace(original_block, replacement_block_cpu)
        print("Script modified for CPU successfully.")

    # Write the dynamically modified content back to the demo file
    demo_script_path.write_text(modified_content)

except Exception as e:
    print(f"An error occurred while modifying the script: {e}")
    sys.exit(1)

# --- 4. Launch the Gradio Demo ---
model_id = "microsoft/VibeVoice-1.5B"

# Construct the command to run the modified demo script
command = [
    "python",
    str(demo_script_path),
    "--model_path",
    model_id,
    "--share"
]

print(f"Launching Gradio demo with command: {' '.join(command)}")
subprocess.run(command)