chore: better test consistency before agnet

experiments/procesing/pricers/session_aware.py

@@ -107,6 +107,36 @@ class SessionAwarePricer(PricingFunction):
 
         return prices
 
+    def _get_features(self, state_space=None) -> np.ndarray:
+        """Extract elasticity, demand, and session features"""
+        if state_space is None or self.elasticity is None:
+            n = len(self.elasticity) if self.elasticity is not None else 0
+            return np.zeros((n, 5))
+
+        demand = np.asarray(state_space.demand)
+        n_products = len(demand)
+
+        # extract session features
+        velocity = 0.0
+        view_depth = 0.0
+        cart_to_view = 0.0
+
+        if not state_space.session_features.empty:
+            sf = state_space.session_features.iloc[0]
+            velocity = sf.get('interaction_velocity', 0.0)
+            view_depth = sf.get('product_view_depth', 0.0)
+            cart_to_view = sf.get('cart_to_view_ratio', 0.0)
+
+        # broadcast session features to all products
+        features = np.column_stack([
+            self.elasticity,
+            demand,
+            np.full(n_products, velocity),
+            np.full(n_products, view_depth),
+            np.full(n_products, cart_to_view)
+        ])
+        return features
+
 
 class ProductSpecificSessionPricer(PricingFunction):
     """
@@ -170,3 +200,12 @@ class ProductSpecificSessionPricer(PricingFunction):
 
         prices = np.clip(base_prices, self.price_floor, self.price_ceil)
         return prices
+
+    def _get_features(self, state_space=None) -> np.ndarray:
+        """Extract elasticity and demand features for product-specific pricing"""
+        if state_space is None or self.elasticity is None:
+            n = len(self.elasticity) if self.elasticity is not None else 0
+            return np.zeros((n, 2))
+
+        demand = np.asarray(state_space.demand)
+        return np.column_stack([self.elasticity, demand])