app.py

import os
import sys
import subprocess
import time
from huggingface_hub import hf_hub_download

BASE_DIR = os.getcwd()
WEIGHTS_DIR = os.path.join(BASE_DIR, "weights")
OUTPUT_BASEPATH = os.path.join(BASE_DIR, "results-poor")

# Download specific files from Hugging Face repo
def download_checkpoints():
    os.makedirs(WEIGHTS_DIR, exist_ok=True)
    print("⬇️  Downloading necessary checkpoint files...")

    try:
        # Download FP8 checkpoint
        checkpoint_fp8 = hf_hub_download(
            repo_id="tencent/HunyuanVideo-Avatar",
            filename="ckpts/hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states_fp8.pt",
            cache_dir=WEIGHTS_DIR,
            local_dir=WEIGHTS_DIR,
            local_dir_use_symlinks=False
        )

        # Download normal checkpoint for Flask/Gradio UI
        checkpoint = hf_hub_download(
            repo_id="tencent/HunyuanVideo-Avatar",
            filename="ckpts/hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states.pt",
            cache_dir=WEIGHTS_DIR,
            local_dir=WEIGHTS_DIR,
            local_dir_use_symlinks=False
        )

        return checkpoint, checkpoint_fp8

    except Exception as e:
        print(f"❌ Error during checkpoint download: {e}")
        sys.exit(1)

def run_sample_gpu_poor(checkpoint_fp8_path):
    print("🎬 Running sample_gpu_poor.py...")

    cmd = [
        "python3", "hymm_sp/sample_gpu_poor.py",
        "--input", "assets/test.csv",
        "--ckpt", checkpoint_fp8_path,
        "--sample-n-frames", "129",
        "--seed", "128",
        "--image-size", "704",
        "--cfg-scale", "7.5",
        "--infer-steps", "50",
        "--use-deepcache", "1",
        "--flow-shift-eval-video", "5.0",
        "--save-path", OUTPUT_BASEPATH,
        "--use-fp8",
        "--cpu-offload",
        "--infer-min"
    ]

    env = os.environ.copy()
    env["PYTHONPATH"] = "./"
    env["MODEL_BASE"] = WEIGHTS_DIR
    env["CPU_OFFLOAD"] = "1"
    env["CUDA_VISIBLE_DEVICES"] = "0"

    proc = subprocess.run(cmd, env=env)
    if proc.returncode != 0:
        print("❌ sample_gpu_poor.py failed.")
        sys.exit(1)

    print("✅ sample_gpu_poor.py completed successfully.")

def run_flask_audio(checkpoint_path):
    print("🚀 Starting flask_audio.py...")
    cmd = [
        "torchrun",
        "--nnodes=1",
        "--nproc_per_node=1",
        "--master_port=29605",
        "hymm_gradio/flask_audio.py",
        "--input", "assets/test.csv",
        "--ckpt", checkpoint_path,
        "--sample-n-frames", "129",
        "--seed", "128",
        "--image-size", "704",
        "--cfg-scale", "7.5",
        "--infer-steps", "50",
        "--use-deepcache", "1",
        "--flow-shift-eval-video", "5.0"
    ]
    subprocess.Popen(cmd)

def run_gradio_ui():
    print("🟢 Starting gradio_audio.py UI...")
    cmd = ["python3", "hymm_gradio/gradio_audio.py"]
    subprocess.Popen(cmd)

def main():
    # Step 1: Download only needed files from Hugging Face repo
    checkpoint, checkpoint_fp8 = download_checkpoints()

    # Step 2: Run poor sample video generation
    run_sample_gpu_poor(checkpoint_fp8)

    # Step 3: Launch Flask + Gradio UIs
    run_flask_audio(checkpoint)
    time.sleep(5)
    run_gradio_ui()

if __name__ == "__main__":
    main()