sheet upload fix

app/intelligence/discount_model.py

@@ -17,7 +17,7 @@ business-rule signal.
 from __future__ import annotations
 
 from dataclasses import dataclass
-from typing import Dict, List
+from typing import Dict
 
 import numpy as np
 import pandas as pd

app/intelligence/features.py

@@ -9,10 +9,9 @@ ML feature logic without a live Postgres instance.
 from __future__ import annotations
 
 import math
-from datetime import date, datetime
-from typing import Dict, Iterable, List, Optional
+from datetime import date
+from typing import Dict, Iterable, Optional
 
-import numpy as np
 import pandas as pd
 
 # ---------------------------------------------------------------------------

app/intelligence/forecasting.py

@@ -26,7 +26,7 @@ individually; only the training data is pooled).
 """
 from __future__ import annotations
 
-from datetime import date, timedelta
+from datetime import date
 from typing import List
 
 import numpy as np

app/intelligence/nutrition_clustering.py

@@ -20,7 +20,6 @@ from __future__ import annotations
 import logging
 from typing import Any, Dict, List, Tuple
 
-import numpy as np
 import pandas as pd
 
 from app.intelligence.model_utils import ModelBundle, load_bundle, save_bundle

app/intelligence/nutrition_similarity.py

@@ -22,7 +22,6 @@ from __future__ import annotations
 import logging
 from typing import Any, Dict, List
 
-import numpy as np
 import pandas as pd
 
 from app.intelligence.model_utils import ModelBundle, load_bundle, save_bundle

app/intelligence/order_simulation.py

@@ -22,9 +22,9 @@ repeatable ML training and for demos.
 """
 from __future__ import annotations
 
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from datetime import date, timedelta
-from typing import Dict, List, Optional, Sequence
+from typing import Dict, List, Sequence
 
 import hashlib
 import numpy as np

app/intelligence/purchase_propensity_model.py

@@ -18,10 +18,9 @@ propensity score in the analytics UI).
 """
 from __future__ import annotations
 
-from datetime import date, timedelta
+from datetime import date
 from typing import List
 
-import numpy as np
 import pandas as pd
 
 from app.intelligence import features as F

app/intelligence/store_performance_model.py

@@ -15,7 +15,6 @@ heavy tuning.
 """
 from __future__ import annotations
 
-from typing import List
 
 import numpy as np
 import pandas as pd

app/intelligence/trending_model.py

@@ -17,8 +17,8 @@ is `predicted_score.sort_values(ascending=False)` on live order data.
 """
 from __future__ import annotations
 
-from datetime import date, timedelta
-from typing import Dict, List, Literal, Optional
+from datetime import date
+from typing import Dict, List, Literal
 
 import numpy as np
 import pandas as pd