Update app.py

app.py

@@ -106,6 +106,33 @@ st.write("🚀 Detect Fake News, Deepfake Images, and Videos using AI")
 # Load Models
 fake_news_detector = pipeline("text-classification", model="microsoft/deberta-v3-base")
 
+@st.cache_resource
+def load_fake_news_model():
+    return pipeline("text-classification", model="microsoft/deberta-v3-base")
+
+@st.cache_resource
+def load_deepfake_models():
+    base_model_image = Xception(weights="imagenet", include_top=False)
+    base_model_image.trainable = False  
+    x = GlobalAveragePooling2D()(base_model_image.output)
+    x = Dense(1024, activation="relu")(x)
+    x = Dense(1, activation="sigmoid")(x)
+    deepfake_image_model = Model(inputs=base_model_image.input, outputs=x)
+
+    base_model_video = EfficientNetB7(weights="imagenet", include_top=False)
+    base_model_video.trainable = False
+    x = GlobalAveragePooling2D()(base_model_video.output)
+    x = Dense(1024, activation="relu")(x)
+    x = Dense(1, activation="sigmoid")(x)
+    deepfake_video_model = Model(inputs=base_model_video.input, outputs=x)
+
+    return deepfake_image_model, deepfake_video_model
+
+# Load models once in cache
+fake_news_detector = load_fake_news_model()
+deepfake_image_model, deepfake_video_model = load_deepfake_models()
+
+
 # Load Deepfake Detection Models
 base_model_image = Xception(weights="imagenet", include_top=False)
 base_model_image.trainable = False  # Freeze base layers