scripts/run_gradio.sh

#!/bin/bash

JOBS_DIR=$(dirname $(dirname "$0"))
export PYTHONPATH=./

export MODEL_BASE=./weights
MODEL_DIR=${MODEL_BASE}/ckpts/hunyuan-video-t2v-720p
CHECKPOINT_FILE=${MODEL_DIR}/transformers/mp_rank_00_model_states.pt

# Step 1: Check if model already exists
if [ -f "$CHECKPOINT_FILE" ]; then
    echo "✅ Model checkpoint already exists. Skipping download."
else
    echo "⬇️  Model not found. Downloading from Hugging Face..."
    python3 - <<EOF
from huggingface_hub import snapshot_download
import os

target_dir = "${MODEL_DIR}"
os.makedirs(target_dir, exist_ok=True)

snapshot_download(
    repo_id="tencent/HunyuanVideo-Avatar",
    local_dir=target_dir,
    local_dir_use_symlinks=False
)
EOF

    # Check again if download succeeded
    if [ ! -f "$CHECKPOINT_FILE" ]; then
        echo "❌ Failed to download model checkpoint. Exiting."
        exit 1
    fi
    echo "✅ Model downloaded successfully."
fi

# Step 2: Run the Flask audio process in the background
echo "🚀 Starting flask_audio.py..."
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 &

# Step 3: After flask is backgrounded, run Gradio UI
echo "🟢 Starting gradio_audio.py UI..."
python3 hymm_gradio/gradio_audio.py