app.py

import os
import sys
import subprocess
import time
from huggingface_hub import snapshot_download

MODEL_REPO = "tencent/HunyuanVideo-Avatar"
BASE_DIR = os.getcwd()
WEIGHTS_DIR = os.path.join(BASE_DIR, "weights")
OUTPUT_BASEPATH = os.path.join(BASE_DIR, "results-poor")

# Specific checkpoint to use in the poor sampling run
CHECKPOINT_FILE = os.path.join(
    WEIGHTS_DIR,
    "ckpts",
    "hunyuan-video-t2v-720p",
    "transformers",
    "mp_rank_00_model_states.pt"
)
CHECKPOINT_FP8_FILE = os.path.join(
    WEIGHTS_DIR,
    "ckpts",
    "hunyuan-video-t2v-720p",
    "transformers",
    "mp_rank_00_model_states_fp8.pt"
)

def download_model():
    print("⬇️  Model not found. Downloading with snapshot_download into weights directory...")
    os.makedirs(WEIGHTS_DIR, exist_ok=True)

    snapshot_download(
        repo_id=MODEL_REPO,
        local_dir=WEIGHTS_DIR,
        local_dir_use_symlinks=False
    )

    if not os.path.isfile(CHECKPOINT_FILE):
        print(f"❌ Checkpoint file not found at {CHECKPOINT_FILE} after download.")
        sys.exit(1)
    
    if not os.path.isfile(CHECKPOINT_FP8_FILE):
        print(f"❌ FP8 checkpoint file not found at {CHECKPOINT_FP8_FILE}. Cannot proceed with sample_gpu_poor.py.")
        sys.exit(1)

    print("✅ Model downloaded successfully.")

def run_sample_gpu_poor():
    print("🎬 Running sample_gpu_poor.py...")
    cmd = [
        "python3", "hymm_sp/sample_gpu_poor.py",
        "--input", "assets/test.csv",
        "--ckpt", CHECKPOINT_FP8_FILE,
        "--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():
    print("🚀 Starting flask_audio.py...")
    cmd = [
        "torchrun",
        "--nnodes=1",
        "--nproc_per_node=8",
        "--master_port=29605",
        "hymm_gradio/flask_audio.py",
        "--input", "assets/test.csv",
        "--ckpt", CHECKPOINT_FILE,
        "--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():
    if os.path.isfile(CHECKPOINT_FP8_FILE):
        print("✅ Model checkpoint already exists. Skipping download.")
    else:
        download_model()

    run_sample_gpu_poor()

    # Optional: Start Flask and Gradio UIs after poor sample run
    run_flask_audio()
    time.sleep(5)
    run_gradio_ui()

if __name__ == "__main__":
    main()