static price reading

backend/provider/app.py

@@ -24,6 +24,7 @@ from procesing.steps import (
 )
 from procesing import PipelineContext
 sys.path.append(os.path.dirname(os.path.abspath(__file__))+ "/../../lib/")
+print(os.path.dirname(os.path.abspath(__file__))+ "/../../lib/")
 from lib.model_registry import ModelRegistry
 
 # Config
@@ -53,20 +54,12 @@ def get_price(mode: Literal['hotel', 'airline'], productId: str, sessionId: Opti
     metadata = product['metadata']
     base_price = metadata.get('base_price', 100.0)
 
-    class Provider(SupabaseProvider, BackendAPIProvider):
-        def __init__(self, backend_url: str):
-            SupabaseProvider.__init__(self)
-            BackendAPIProvider.__init__(self, backend_url=backend_url)
-
-    context = PipelineContext(
-        provider=Provider(backend_url=os.getenv("BACKEND_URL")),
-        store_mode=mode
-    )
-
-    pricing_model = registry.get_pricing_model('latest')
+    # fetch pre-computed prices from registry
+    prices_df = registry.get_prices('latest')
     elasticity_df = registry.get_elasticity('latest')
 
-    if pricing_model is None or elasticity_df is None:
+    if prices_df is None:
+        # fallback: no pre-computed prices available
         return PriceResponse(
             productId=productId,
             price=base_price,
@@ -75,87 +68,26 @@ def get_price(mode: Literal['hotel', 'airline'], productId: str, sessionId: Opti
             elasticity=None
         )
 
-    products = context.products
-    if products.empty:
-        raise HTTPException(500, "No products available in catalog")
-
-    # merge elasticity with product base prices
-    products_with_meta = products.copy()
-    products_with_meta['base_price'] = products_with_meta['metadata'].apply(
-        lambda m: m.get('base_price', 100.0) if isinstance(m, dict) else 100.0
-    )
-
-    merged = products_with_meta[['id', 'base_price']].rename(
-        columns={'id': 'productId'}
-    ).merge(
-        elasticity_df[['productId', 'elasticity']],
-        on='productId',
-        how='left'
-    ).fillna({'elasticity': 0.0})
-
-    # compute demand: use pricer's mean_demand if available, else default
-    demand_values = (pricing_model.mean_demand
-                    if hasattr(pricing_model, 'mean_demand') and pricing_model.mean_demand is not None
-                    else np.ones(len(merged)) * 10.0)
-
-    # build state space with session features if sessionId provided
-    session_features = pd.DataFrame()
-    if sessionId:
-        try:
-            # fetch recent session interactions from backend
-            from procesing.steps.session import ExtractSessionFeaturesStep
-            import requests
-            from datetime import datetime, timedelta
-
-            t_end = datetime.utcnow()
-            t_start = t_end - timedelta(hours=1)
-            backend_url = os.getenv("BACKEND_URL")
-            print(backend_url)
-
-            resp = requests.get(
-                f"{os.getenv('BACKEND_URL')}/api/kafka/dump", # TODO: THIS IS SHIT, must fix this
-                params={'topic': 'user-interactions', 't_start': t_start.isoformat(), 't_end': t_end.isoformat()},
-                timeout=2
-            )
-
-            if resp.ok:
-                msgs = resp.json().get('messages', [])
-                interactions_df = pd.DataFrame(msgs)
-
-                if not interactions_df.empty and 'sessionId' in interactions_df.columns:
-                    session_interactions = interactions_df[interactions_df['sessionId'] == sessionId]
-
-                    if not session_interactions.empty:
-                        extractor = ExtractSessionFeaturesStep(context=context)
-                        session_features_df = extractor.transform(session_interactions)
-
-                        if not session_features_df.empty:
-                            session_features = session_features_df.drop(columns=['sessionId'])
-        except Exception as e:
-            print(f"[session-features-error] {e}")
-            # continue without session features
-
-    state = StateSpace(
-        demand=demand_values,
-        prices=merged['base_price'].values,
-        session_features=session_features,
-        product_ids=merged['productId'].values,
-        elasticity=merged['elasticity'].values,
-        metadata={'sessionId': sessionId, 'experimentId': experimentId}
-    )
-
-    oracle = PredictPricesStep(context=context)
-    prices_df = oracle.transform((pricing_model, state))
-
+    # lookup pre-computed price for this product
     product_price_row = prices_df[prices_df['productId'] == productId]
     if product_price_row.empty:
-        raise HTTPException(404, f"No pricing available for product {productId}")
+        # product not in pre-computed prices, fallback to base
+        return PriceResponse(
+            productId=productId,
+            price=base_price,
+            base_price=base_price,
+            markup=1.0,
+            elasticity=None
+        )
 
     optimal_price = float(product_price_row['predicted_price'].iloc[0])
 
-    product_elasticity_row = elasticity_df[elasticity_df['productId'] == productId]
-    product_elasticity = (float(product_elasticity_row['elasticity'].iloc[0])
-                         if not product_elasticity_row.empty else None)
+    # get elasticity if available
+    product_elasticity = None
+    if elasticity_df is not None:
+        product_elasticity_row = elasticity_df[elasticity_df['productId'] == productId]
+        if not product_elasticity_row.empty:
+            product_elasticity = float(product_elasticity_row['elasticity'].iloc[0])
 
     return PriceResponse(
         productId=productId,