Update analytics/recommendation_engine.py

analytics/recommendation_engine.py

@@ -1,7 +1,5 @@
 from __future__ import annotations
 
-from typing import Any
-
 import pandas as pd
 
 from analytics.confidence import compute_confidence
@@ -10,13 +8,13 @@ from models.live_fair_simulator_v3 import build_upcoming_simulated_rows
 
 
 def build_upcoming_hitter_recommendations(
-    game_row: dict[str, Any],
+    game_row: dict,
     statcast_df: pd.DataFrame,
     odds_df: pd.DataFrame | None = None,
-    weather_row: dict[str, Any] | None = None,
-) -> list[dict[str, Any]]:
+    weather_row: dict | None = None,
+) -> list[dict]:
     """
-    Batch 3 decision-layer wrapper.
+    Decision-layer wrapper.
     Uses simulated fair rows, then adds confidence + recommendation tier.
     """
     rows = build_upcoming_simulated_rows(
@@ -25,7 +23,7 @@ def build_upcoming_hitter_recommendations(
         weather_row=weather_row,
     )
 
-    recommendations: list[dict[str, Any]] = []
+    recommendations: list[dict] = []
 
     for row in rows:
         confidence_block = compute_confidence(row, game_row=game_row)
@@ -36,4 +34,13 @@ def build_upcoming_hitter_recommendations(
 
         recommendations.append(row)
 
+    recommendations = sorted(
+        recommendations,
+        key=lambda x: (
+            float(x.get("priority_score", 0.0) or 0.0),
+            float(x.get("confidence", 0.0) or 0.0),
+        ),
+        reverse=True,
+    )
+
     return recommendations