app.py

print(' # ************************Begin***********************************')
import gradio as gr
from huggingface_hub import InferenceClient
# Check for T4 GPU
import torch
import os
print('load  libs')

if torch.cuda.is_available():
    #and "T4" in torch.cuda.get_device_name(0):
    print("✅  GPU detected")
else:
    print("""
    ⚠️ WARNING: T4 GPU not detected 
    The recommended runtime for this Colab notebook is "T4 GPU".
    To change the runtime type:
        1. Click on "Runtime" in the top navigation menu
        2. Click on "Change runtime type"
        3. Select "T4 GPU"
        4. Click "OK" if a "Disconnect and delete runtime" window appears
        5. Click on "Save"
    """)

# Clone the VibeVoice repository
# ![ -d /VibeVoice ] || git clone --quiet --branch main --depth 1 https://github.com/microsoft/VibeVoice.git /VibeVoice
os.system(" [ -d /tmp/VibeVoice ] || git clone  --branch main https://huggingface.co/vibevoice/VibeVoice-7B /tmp/VibeVoice")
print("✅ Cloned VibeVoice repository")

# Install project dependencies
os.system("uv pip --quiet install --system -e /tmp/VibeVoice")
print("✅ Installed dependencies")

# Download model (~3 minutes)
# !HF_XET_HIGH_PERFORMANCE=1 hf download microsoft/VibeVoice-1.5B --quiet  --local-dir /content/models/VibeVoice-1.5B > /dev/null
# print("✅ Downloaded model: microsoft/VibeVoice-1.5B")

def be_happy(happy):
    if happy:
        print('I"am happy')
    return happy

if __name__ == "__main__":
    print('don"t warry')
    be_happy(True)
    LOADED_MODEL = "vibevoice/VibeVoice-7B" # just to break "if LOADED_MODEL is not None:"

    if LOADED_MODEL is not None:
        # Ganti 'interface' menjadi 'app'
        app = gr.Interface(
            fn=be_happy,
            inputs=gr.Image(type="numpy", label="Unggah Gambar Model Rambut"),
            outputs=gr.Markdown(label="# Rekomendasi"),
            title="vibevoice/VibeVoice-7B",
            description="vibevoice/VibeVoice-7B",
            examples=[ # Opsiona
                # Contoh
                # atau 
                # "./example.jpg",
                # "./examplese.jpg"
            ]
        )
        app.queue().launch() # <= Added