feat: updates from tests

apps/recommendation/api/src/huggy/core/model_engine/factory.py

@@ -1,3 +1,4 @@
+from dataclasses import dataclass
 from typing import Optional
 
 import huggy.schemas.offer as o
@@ -9,6 +10,7 @@
 from sqlalchemy.ext.asyncio import AsyncSession
 
 
+@dataclass
 class ModelEngineOut:
     model: ModelEngine
     results: list[str]
@@ -44,7 +46,7 @@ async def handle_prediction(
         results = await model_engine.get_scoring(db)
 
         # Handle fallback scenario if enabled and no results are found
-        if use_fallback and not results:
+        if use_fallback and len(results) == 0:
             model_engine = await ModelEngineFactory._handle_fallback(
                 user, params_in, call_id, input_offers
             )

apps/recommendation/api/src/huggy/core/scorer/offer.py

@@ -217,7 +217,7 @@ async def get_nearest_offers(
         multiple_item_offers = []
 
         offer_latitude, offer_longitude = await self.get_mean_offer_coordinates(
-            db, input_offers
+            input_offers
         )
 
         for v in recommendable_items_ids.values():

apps/recommendation/api/src/huggy/views/home.py

@@ -36,7 +36,7 @@ async def playlist_recommendation(
     model_engine_out: ModelEngineOut = await ModelEngineFactory.handle_prediction(
         db,
         user=user,
-        playlist_params=playlist_params,
+        params_in=playlist_params,
         call_id=call_id,
         context="recommendation",
         input_offers=input_offers,

apps/recommendation/api/src/huggy/views/offer.py

@@ -32,7 +32,7 @@ async def __similar_offers(
     model_engine_out: ModelEngineOut = await ModelEngineFactory.handle_prediction(
         db,
         user=user,
-        playlist_params=playlist_params,
+        params_in=playlist_params,
         call_id=call_id,
         context="similar_offer",
         input_offers=input_offers,