Create start.sh

start.sh

@@ -0,0 +1,52 @@
+#!/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