Update app.py

app.py

@@ -3,33 +3,34 @@ import torch
 import gradio as gr
 import time
 from ccd import ccd_eval, run_eval
-from libra.eval.run_libra import load_model
 
 # =========================================
-# Safe Libra Hook: fallback to CPU if no CUDA
+# Safe Libra Hook (CPU fallback for no-GPU environments)
 # =========================================
 import torch
 import libra.model.builder as builder
+import libra.eval.run_libra as run_libra
 
+# --- Patch 1: replace load_pretrained_model ---
 _original_load_pretrained_model = builder.load_pretrained_model
 
 def safe_load_pretrained_model(model_path, model_base=None, model_name=None, **kwargs):
-    print("[INFO] Applying safe device fallback hook for Libra...")
+    print("[INFO] Hook activated: safe_load_pretrained_model()")
+
     tokenizer, model, image_processor, context_len = _original_load_pretrained_model(
         model_path, model_base, model_name, **kwargs
     )
 
     if torch.cuda.is_available():
         device, dtype = "cuda", torch.float16
-        print("[INFO] GPU detected: using float16 precision.")
+        print("[INFO] GPU detected — using CUDA + float16.")
     else:
         device, dtype = "cpu", torch.float32
-        print("[WARN] No GPU detected. Running Libra on CPU with float32.")
+        print("[WARN] No GPU found — forcing model to CPU (float32).")
 
     try:
-        vision_tower = model.get_vision_tower()
-        vision_tower.to(device=device, dtype=dtype)
-        print(f"[INFO] Vision tower moved to {device} ({dtype})")
+        model.get_vision_tower().to(device=device, dtype=dtype)
+        print(f"[INFO] Vision tower moved to {device} ({dtype}).")
     except Exception as e:
         print(f"[WARN] Could not move vision tower: {e}")
 
@@ -38,6 +39,14 @@ def safe_load_pretrained_model(model_path, model_base=None, model_name=None, **k
 builder.load_pretrained_model = safe_load_pretrained_model
 
 
+# --- Patch 2: replace run_libra.load_model to force using our patched builder ---
+def safe_load_model(model_path, model_base=None, model_name=None):
+    print("[INFO] Hook activated: safe_load_model()")
+    return safe_load_pretrained_model(model_path, model_base, model_name)
+
+run_libra.load_model = safe_load_model
+
+
 # =========================================
 # Global Configuration
 # =========================================