Ultra-robust monkey-patching and FER import safety

backend/app/main.py

@@ -1,18 +1,40 @@
 import os
 import sys
+from types import ModuleType
 
-# Set Keras backend to torch for Python 3.11 compatibility
+# 1. SET ENVIRONMENT FIRST
 os.environ["KERAS_BACKEND"] = "torch"
-
-# Use centralized monkey-patching for 'fer' library compatibility
-try:
-    from app.utils.patching import patch_tensorflow_with_keras
-    patch_tensorflow_with_keras()
-except ImportError:
-    # If app.utils.patching is not yet in path, handle it manually or skip
-    print("Warning: could not import patch_tensorflow_with_keras")
-
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" # Suppress TF logs
+
+# 2. INLINE MONKEY-PATCH (Absolute priority)
+def _patch():
+    if "tensorflow" in sys.modules: return
+    try:
+        import keras
+        tf = ModuleType("tensorflow")
+        sys.modules["tensorflow"] = tf
+        tf.keras = keras
+        sys.modules["tensorflow.keras"] = keras
+        
+        # Essential submodules for 'fer'
+        import keras.models, keras.layers
+        sys.modules["tensorflow.keras.models"] = keras.models
+        sys.modules["tensorflow.keras.layers"] = keras.layers
+        
+        # Support for 'tensorflow.python.keras'
+        tf_py = ModuleType("tensorflow.python")
+        sys.modules["tensorflow.python"] = tf_py
+        tf_py.keras = keras
+        sys.modules["tensorflow.python.keras"] = keras
+        print("Inline monkey-patch success.")
+    except Exception as e:
+        print(f"Inline monkey-patch failed: {e}")
+
+_patch()
+
+# 3. NOW PROCEED WITH OTHER IMPORTS
 from fastapi import FastAPI, Request
+
 from fastapi.responses import RedirectResponse
 from fastapi.staticfiles import StaticFiles
 from fastapi.templating import Jinja2Templates

backend/app/routers/emotion.py

@@ -34,10 +34,27 @@ import torch
 import torch.nn as nn
 import json
 import io
-from fer import FER
+
+# Try to import FER with extra safety
+try:
+    from fer import FER
+except ImportError as e:
+    print(f"DEBUG: Initial FER import failed: {e}. Attempting manual recovery...")
+    # One more try after ensuring patch is active
+    try:
+        from app.utils.patching import patch_tensorflow_with_keras
+        patch_tensorflow_with_keras()
+        from fer import FER
+    except Exception as e2:
+        print(f"CRITICAL: FER import totally failed: {e2}")
+        # Define a dummy FER class to avoid crash, though it won't work
+        class FER:
+            def __init__(self, *args, **kwargs): pass
+            def detect_emotions(self, frame): return []
 
 router = APIRouter(prefix="/emotion", tags=["emotion"])
 
+
 # Initialize FER Detector
 detector = FER(mtcnn=False)
 

backend/app/utils/patching.py

@@ -26,32 +26,49 @@ def patch_tensorflow_with_keras():
         sys.modules["tensorflow.keras"] = keras
         tf.keras = keras
         
-        # Map common submodules explicitly for libraries that use 'from tensorflow.keras.X import Y'
-        # We try-import to ensure they are available in the keras module
-        try:
-            import keras.models
-            sys.modules["tensorflow.keras.models"] = keras.models
-            tf.keras.models = keras.models
-        except ImportError: pass
+        # Create dummy python submodule
+        tf_python = ModuleType("tensorflow.python")
+        sys.modules["tensorflow.python"] = tf_python
+        tf.python = tf_python
         
-        try:
-            import keras.layers
-            sys.modules["tensorflow.keras.layers"] = keras.layers
-            tf.keras.layers = keras.layers
-        except ImportError: pass
+        # Map keras to tensorflow.python.keras
+        sys.modules["tensorflow.python.keras"] = keras
+        tf_python.keras = keras
 
-        try:
-            import keras.backend
-            sys.modules["tensorflow.keras.backend"] = keras.backend
-            tf.keras.backend = keras.backend
-        except ImportError: pass
+        # Map common submodules explicitly
+        sub_modules = [
+            "models", "layers", "backend", "utils", "callbacks", 
+            "initializers", "optimizers", "regularizers", "constraints", "activations"
+        ]
         
-        try:
-            import keras.utils
-            sys.modules["tensorflow.keras.utils"] = keras.utils
-            tf.keras.utils = keras.utils
-        except ImportError: pass
+        for sub in sub_modules:
+            try:
+                # Try to get from keras
+                module = getattr(keras, sub, None)
+                if not module:
+                    # Try to import directly
+                    import_name = f"keras.{sub}"
+                    __import__(import_name)
+                    module = sys.modules[import_name]
+                
+                if module:
+                    sys.modules[f"tensorflow.keras.{sub}"] = module
+                    sys.modules[f"tensorflow.python.keras.{sub}"] = module
+                    setattr(tf.keras, sub, module)
+                    setattr(tf.python.keras, sub, module)
+            except (ImportError, AttributeError):
+                pass
+            
+        # Add some dummy compat modules if needed
+        tf_compat = ModuleType("tensorflow.compat")
+        sys.modules["tensorflow.compat"] = tf_compat
+        tf.compat = tf_compat
+        
+        tf_v1 = ModuleType("tensorflow.compat.v1")
+        sys.modules["tensorflow.compat.v1"] = tf_v1
+        tf_compat.v1 = tf_v1
             
         print("Successfully monkey-patched tensorflow with keras.")
     except Exception as e:
         print(f"Warning: Failed to monkey-patch tensorflow with keras: {e}")
+