Update app.py

app.py

@@ -2,10 +2,26 @@ import os
 import numpy as np
 import torch
 
-# --- PYTORCH 2.6+ SECURITY & COMPATIBILITY PATCHES ---
-# 1. Allow WhisperX/Pyannote globals for model loading
+# --- CRITICAL ENVIRONMENT FIXES ---
+# 1. Fix for Hugging Face millicore OMP_NUM_THREADS error (e.g., "7500m")
+# This prevents the underlying math libraries from crashing on startup.
+if os.environ.get("OMP_NUM_THREADS", "").endswith("m"):
+    os.environ["OMP_NUM_THREADS"] = "1"
+
+# 2. Monkeypatch torch.load to default weights_only=False
+# PyTorch 2.6 changed the default to True for security, which breaks 
+# WhisperX/Pyannote checkpoints. Monkeypatching is the only way to fix 
+# internal library calls that we don't control.
+import torch.serialization
+original_load = torch.load
+def patched_load(*args, **kwargs):
+    if 'weights_only' not in kwargs:
+        kwargs['weights_only'] = False
+    return original_load(*args, **kwargs)
+torch.load = patched_load
+
+# --- PYTORCH 2.6+ COMPATIBILITY PATCHES ---
 try:
-    # We import these specifically to add them to the safe list
     from omegaconf.listconfig import ListConfig
     from omegaconf.dictconfig import DictConfig
     try:
@@ -14,7 +30,6 @@ try:
         ContainerMetadata = None
         Metadata = None
 
-    # Exhaustive list of classes required by Pyannote/WhisperX checkpoints
     safe_list = [
         ListConfig, 
         DictConfig,
@@ -24,7 +39,6 @@ try:
     if ContainerMetadata: safe_list.append(ContainerMetadata)
     if Metadata: safe_list.append(Metadata)
     
-    # Handle numpy scalar differences across versions
     if hasattr(np, '_core') and hasattr(np._core, 'multiarray'):
         safe_list.append(np._core.multiarray.scalar)
     elif hasattr(np, 'core') and hasattr(np.core, 'multiarray'):
@@ -34,7 +48,7 @@ try:
 except Exception as e:
     print(f"Safe Globals Warning: {e}")
 
-# 2. Fix NumPy 2.0+ attribute removal (required for older pyannote internals)
+# Fix NumPy 2.0+ attribute removal (required for older pyannote internals)
 if not hasattr(np, 'NaN'):
     np.NaN = np.nan
 
@@ -189,19 +203,7 @@ if uploaded_file:
                         
                         # 3. Diarize
                         st.write("🗣️ **Diarizing Speakers...**")
-                        # Pass token for gated diarization models
-                        # Try to bypass the torch security default if necessary
-                        try:
-                            # We wrap this in a safe_globals context to be absolutely sure
-                            diarize_model = whisperx.DiarizationPipeline(use_auth_token=ACTIVE_HF_TOKEN, device=device)
-                        except Exception as e:
-                            if "Weights only load failed" in str(e) or "Unsupported global" in str(e):
-                                st.warning("⚠️ Security restriction encountered. Re-attempting load with legacy weights_only=False.")
-                                # Note: WhisperX doesn't expose the weights_only flag, so we rely on 
-                                # the Safe Globals established at the top of the file.
-                                diarize_model = whisperx.DiarizationPipeline(use_auth_token=ACTIVE_HF_TOKEN, device=device)
-                            else:
-                                raise e
+                        diarize_model = whisperx.DiarizationPipeline(use_auth_token=ACTIVE_HF_TOKEN, device=device)
                         
                         diarize_kwargs = {}
                         if num_speakers > 0: