Update start.sh

start.sh

@@ -1,17 +1,15 @@
 #!/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
+# Download model if not already downloaded
 if [ -f "$CHECKPOINT_FILE" ]; then
-    echo "✅ Model checkpoint already exists. Skipping download."
+    echo "✅ Model already exists. Skipping download."
 else
-    echo "⬇️  Model not found. Downloading from Hugging Face..."
+    echo "⬇️  Downloading model from Hugging Face..."
     python3 - <<EOF
 from huggingface_hub import snapshot_download
 import os
@@ -25,16 +23,14 @@ snapshot_download(
     local_dir_use_symlinks=False
 )
 EOF
-
-    # Check again if download succeeded
     if [ ! -f "$CHECKPOINT_FILE" ]; then
-        echo "❌ Failed to download model checkpoint. Exiting."
+        echo "❌ Failed to download model. Exiting."
         exit 1
     fi
-    echo "✅ Model downloaded successfully."
+    echo "✅ Model downloaded."
 fi
 
-# Step 2: Run the Flask audio process in the background
+# Start Flask inference in 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' \
@@ -47,6 +43,6 @@ torchrun --nnodes=1 --nproc_per_node=8 --master_port 29605 hymm_gradio/flask_aud
     --use-deepcache 1 \
     --flow-shift-eval-video 5.0 &
 
-# Step 3: After flask is backgrounded, run Gradio UI
+# Launch Gradio UI
 echo "🟢 Starting gradio_audio.py UI..."
 python3 hymm_gradio/gradio_audio.py