Update app.py

app.py

@@ -1,11 +1,29 @@
-import os, sys, json, tempfile, subprocess, shutil, uuid, glob
+import os, sys, json, tempfile, subprocess, shutil, uuid, glob, traceback, datetime
 from pathlib import Path
 from typing import Tuple, List
 
+# ================= Crash trap & verbose logs =================
+import faulthandler
+faulthandler.enable()
+
+os.environ.setdefault("GRADIO_ANALYTICS_ENABLED", "false")
+os.environ.setdefault("GRADIO_NUM_PORTS", "1")
+os.environ.setdefault("HF_HUB_VERBOSE", "1")
+os.environ.setdefault("TRANSFORMERS_VERBOSITY", "info")
+os.environ.setdefault("PYTHONUNBUFFERED", "1")
+
+def _crash_trap(exctype, value, tb):
+    ts = datetime.datetime.utcnow().isoformat()
+    print(f"\n===== FATAL ({ts}Z) =====================================")
+    traceback.print_exception(exctype, value, tb)
+    print("=========================================================\n", flush=True)
+
+sys.excepthook = _crash_trap
+# ============================================================
+
 import gradio as gr
 import spaces
 from huggingface_hub import snapshot_download
-
 from loguru import logger
 import torch, torchaudio
 
@@ -114,7 +132,7 @@ os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
 
 def ensure_clap_safetensors():
     """
-    Proactively cache ONLY safetensors for laion/larger_clap_general so
+    Pre-cache ONLY safetensors for laion/larger_clap_general so
     Transformers never selects a stale/corrupt *.bin.
     """
     snapshot_download(
@@ -216,10 +234,20 @@ def auto_load_models() -> str:
     logger.info("✅ Model loaded")
     return "✅ Model loaded"
 
-# Init logger and load model once
+# Init logger and load model once (with explicit crash surface)
 logger.remove()
 logger.add(lambda msg: print(msg, end=''), level="INFO")
-logger.info(auto_load_models())
+
+try:
+    msg = auto_load_models()
+    logger.info(msg)
+except Exception as e:
+    print("\n[BOOT][ERROR] auto_load_models() failed:")
+    traceback.print_exc()
+    with gr.Blocks(title="Foley Studio · Boot Error") as demo:
+        gr.Markdown("### ❌ Boot failure\n```\n" + "".join(traceback.format_exc()) + "\n```")
+    demo.launch(server_name="0.0.0.0")
+    raise
 
 # ========= Preprocessing =========
 def preprocess_video(in_path: str) -> Tuple[str, float]:
@@ -498,4 +526,19 @@ with gr.Blocks(css=THEME_CSS, title=APP_TITLE, analytics_enabled=False) as demo:
 - Enable **Mux** to get a ready MP4 with the generated foley track.
 """)
 
-    demo.queue(max_size=24).launch()
+# ---- Health endpoint & guarded launch ---------------------------------------
+try:
+    from fastapi import FastAPI
+    fastapi_app = demo.app  # Gradio's FastAPI app
+    @fastapi_app.get("/health")
+    def _health():
+        return {"ok": True, "model_loaded": _model_dict is not None, "device": str(_device)}
+except Exception:
+    pass
+
+try:
+    demo.queue(max_size=24).launch(server_name="0.0.0.0")
+except Exception:
+    print("\n[BOOT][ERROR] Gradio launch failed:")
+    traceback.print_exc()
+    raise