317 lines
15 KiB
Python
317 lines
15 KiB
Python
# services/tenant/app/schemas/tenant_settings.py
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"""
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Tenant Settings Schemas
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Pydantic models for API request/response validation
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"""
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from pydantic import BaseModel, Field, validator
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from typing import Optional
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from datetime import datetime
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from uuid import UUID
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# ================================================================
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# SETTING CATEGORY SCHEMAS
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# ================================================================
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class ProcurementSettings(BaseModel):
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"""Procurement and auto-approval settings"""
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auto_approve_enabled: bool = True
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auto_approve_threshold_eur: float = Field(500.0, ge=0, le=10000)
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auto_approve_min_supplier_score: float = Field(0.80, ge=0.0, le=1.0)
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require_approval_new_suppliers: bool = True
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require_approval_critical_items: bool = True
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procurement_lead_time_days: int = Field(3, ge=1, le=30)
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demand_forecast_days: int = Field(14, ge=1, le=90)
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safety_stock_percentage: float = Field(20.0, ge=0.0, le=100.0)
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po_approval_reminder_hours: int = Field(24, ge=1, le=168)
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po_critical_escalation_hours: int = Field(12, ge=1, le=72)
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use_reorder_rules: bool = Field(True, description="Use ingredient reorder point and reorder quantity in procurement calculations")
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economic_rounding: bool = Field(True, description="Round order quantities to economic multiples (reorder_quantity or supplier minimum_order_quantity)")
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respect_storage_limits: bool = Field(True, description="Enforce max_stock_level constraints on orders")
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use_supplier_minimums: bool = Field(True, description="Respect supplier minimum_order_quantity and minimum_order_amount")
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optimize_price_tiers: bool = Field(True, description="Optimize order quantities to capture volume discount price tiers")
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class InventorySettings(BaseModel):
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"""Inventory management settings"""
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low_stock_threshold: int = Field(10, ge=1, le=1000)
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reorder_point: int = Field(20, ge=1, le=1000)
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reorder_quantity: int = Field(50, ge=1, le=1000)
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expiring_soon_days: int = Field(7, ge=1, le=30)
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expiration_warning_days: int = Field(3, ge=1, le=14)
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quality_score_threshold: float = Field(8.0, ge=0.0, le=10.0)
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temperature_monitoring_enabled: bool = True
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refrigeration_temp_min: float = Field(1.0, ge=-5.0, le=10.0)
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refrigeration_temp_max: float = Field(4.0, ge=-5.0, le=10.0)
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freezer_temp_min: float = Field(-20.0, ge=-30.0, le=0.0)
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freezer_temp_max: float = Field(-15.0, ge=-30.0, le=0.0)
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room_temp_min: float = Field(18.0, ge=10.0, le=35.0)
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room_temp_max: float = Field(25.0, ge=10.0, le=35.0)
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temp_deviation_alert_minutes: int = Field(15, ge=1, le=60)
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critical_temp_deviation_minutes: int = Field(5, ge=1, le=30)
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@validator('refrigeration_temp_max')
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def validate_refrigeration_range(cls, v, values):
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if 'refrigeration_temp_min' in values and v <= values['refrigeration_temp_min']:
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raise ValueError('refrigeration_temp_max must be greater than refrigeration_temp_min')
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return v
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@validator('freezer_temp_max')
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def validate_freezer_range(cls, v, values):
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if 'freezer_temp_min' in values and v <= values['freezer_temp_min']:
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raise ValueError('freezer_temp_max must be greater than freezer_temp_min')
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return v
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@validator('room_temp_max')
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def validate_room_range(cls, v, values):
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if 'room_temp_min' in values and v <= values['room_temp_min']:
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raise ValueError('room_temp_max must be greater than room_temp_min')
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return v
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class ProductionSettings(BaseModel):
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"""Production settings"""
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planning_horizon_days: int = Field(7, ge=1, le=30)
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minimum_batch_size: float = Field(1.0, ge=0.1, le=100.0)
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maximum_batch_size: float = Field(100.0, ge=1.0, le=1000.0)
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production_buffer_percentage: float = Field(10.0, ge=0.0, le=50.0)
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working_hours_per_day: int = Field(12, ge=1, le=24)
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max_overtime_hours: int = Field(4, ge=0, le=12)
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capacity_utilization_target: float = Field(0.85, ge=0.5, le=1.0)
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capacity_warning_threshold: float = Field(0.95, ge=0.7, le=1.0)
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quality_check_enabled: bool = True
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minimum_yield_percentage: float = Field(85.0, ge=50.0, le=100.0)
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quality_score_threshold: float = Field(8.0, ge=0.0, le=10.0)
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schedule_optimization_enabled: bool = True
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prep_time_buffer_minutes: int = Field(30, ge=0, le=120)
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cleanup_time_buffer_minutes: int = Field(15, ge=0, le=120)
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labor_cost_per_hour_eur: float = Field(15.0, ge=5.0, le=100.0)
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overhead_cost_percentage: float = Field(20.0, ge=0.0, le=50.0)
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@validator('maximum_batch_size')
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def validate_batch_size_range(cls, v, values):
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if 'minimum_batch_size' in values and v <= values['minimum_batch_size']:
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raise ValueError('maximum_batch_size must be greater than minimum_batch_size')
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return v
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@validator('capacity_warning_threshold')
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def validate_capacity_threshold(cls, v, values):
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if 'capacity_utilization_target' in values and v <= values['capacity_utilization_target']:
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raise ValueError('capacity_warning_threshold must be greater than capacity_utilization_target')
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return v
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class SupplierSettings(BaseModel):
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"""Supplier management settings"""
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default_payment_terms_days: int = Field(30, ge=1, le=90)
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default_delivery_days: int = Field(3, ge=1, le=30)
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excellent_delivery_rate: float = Field(95.0, ge=90.0, le=100.0)
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good_delivery_rate: float = Field(90.0, ge=80.0, le=99.0)
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excellent_quality_rate: float = Field(98.0, ge=90.0, le=100.0)
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good_quality_rate: float = Field(95.0, ge=80.0, le=99.0)
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critical_delivery_delay_hours: int = Field(24, ge=1, le=168)
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critical_quality_rejection_rate: float = Field(10.0, ge=0.0, le=50.0)
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high_cost_variance_percentage: float = Field(15.0, ge=0.0, le=100.0)
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@validator('good_delivery_rate')
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def validate_delivery_rates(cls, v, values):
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if 'excellent_delivery_rate' in values and v >= values['excellent_delivery_rate']:
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raise ValueError('good_delivery_rate must be less than excellent_delivery_rate')
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return v
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@validator('good_quality_rate')
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def validate_quality_rates(cls, v, values):
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if 'excellent_quality_rate' in values and v >= values['excellent_quality_rate']:
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raise ValueError('good_quality_rate must be less than excellent_quality_rate')
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return v
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class POSSettings(BaseModel):
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"""POS integration settings"""
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sync_interval_minutes: int = Field(5, ge=1, le=60)
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auto_sync_products: bool = True
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auto_sync_transactions: bool = True
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class OrderSettings(BaseModel):
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"""Order and business rules settings"""
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max_discount_percentage: float = Field(50.0, ge=0.0, le=100.0)
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default_delivery_window_hours: int = Field(48, ge=1, le=168)
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dynamic_pricing_enabled: bool = False
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discount_enabled: bool = True
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delivery_tracking_enabled: bool = True
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class ReplenishmentSettings(BaseModel):
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"""Replenishment planning settings"""
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projection_horizon_days: int = Field(7, ge=1, le=30)
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service_level: float = Field(0.95, ge=0.0, le=1.0)
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buffer_days: int = Field(1, ge=0, le=14)
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enable_auto_replenishment: bool = True
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min_order_quantity: float = Field(1.0, ge=0.1, le=1000.0)
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max_order_quantity: float = Field(1000.0, ge=1.0, le=10000.0)
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demand_forecast_days: int = Field(14, ge=1, le=90)
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class SafetyStockSettings(BaseModel):
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"""Safety stock settings"""
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service_level: float = Field(0.95, ge=0.0, le=1.0)
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method: str = Field("statistical", description="Method for safety stock calculation")
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min_safety_stock: float = Field(0.0, ge=0.0, le=1000.0)
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max_safety_stock: float = Field(100.0, ge=0.0, le=1000.0)
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reorder_point_calculation: str = Field("safety_stock_plus_lead_time_demand", description="Method for reorder point calculation")
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class MOQSettings(BaseModel):
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"""MOQ aggregation settings"""
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consolidation_window_days: int = Field(7, ge=1, le=30)
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allow_early_ordering: bool = True
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enable_batch_optimization: bool = True
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min_batch_size: float = Field(1.0, ge=0.1, le=1000.0)
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max_batch_size: float = Field(1000.0, ge=1.0, le=10000.0)
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class SupplierSelectionSettings(BaseModel):
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"""Supplier selection settings"""
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price_weight: float = Field(0.40, ge=0.0, le=1.0)
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lead_time_weight: float = Field(0.20, ge=0.0, le=1.0)
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quality_weight: float = Field(0.20, ge=0.0, le=1.0)
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reliability_weight: float = Field(0.20, ge=0.0, le=1.0)
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diversification_threshold: int = Field(1000, ge=0, le=1000)
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max_single_percentage: float = Field(0.70, ge=0.0, le=1.0)
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enable_supplier_score_optimization: bool = True
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@validator('price_weight', 'lead_time_weight', 'quality_weight', 'reliability_weight')
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def validate_weights_sum(cls, v, values):
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weights = [values.get('price_weight', 0.40), values.get('lead_time_weight', 0.20),
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values.get('quality_weight', 0.20), values.get('reliability_weight', 0.20)]
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total = sum(weights)
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if total > 1.0:
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raise ValueError('Weights must sum to 1.0 or less')
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return v
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class MLInsightsSettings(BaseModel):
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"""ML Insights configuration settings"""
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# Inventory ML (Safety Stock Optimization)
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inventory_lookback_days: int = Field(90, ge=30, le=365, description="Days of demand history for safety stock analysis")
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inventory_min_history_days: int = Field(30, ge=7, le=180, description="Minimum days of history required")
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# Production ML (Yield Prediction)
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production_lookback_days: int = Field(90, ge=30, le=365, description="Days of production history for yield analysis")
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production_min_history_runs: int = Field(30, ge=10, le=100, description="Minimum production runs required")
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# Procurement ML (Supplier Analysis & Price Forecasting)
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supplier_analysis_lookback_days: int = Field(180, ge=30, le=730, description="Days of order history for supplier analysis")
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supplier_analysis_min_orders: int = Field(10, ge=5, le=100, description="Minimum orders required for analysis")
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price_forecast_lookback_days: int = Field(180, ge=90, le=730, description="Days of price history for forecasting")
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price_forecast_horizon_days: int = Field(30, ge=7, le=90, description="Days to forecast ahead")
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# Forecasting ML (Dynamic Rules)
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rules_generation_lookback_days: int = Field(90, ge=30, le=365, description="Days of sales history for rule learning")
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rules_generation_min_samples: int = Field(10, ge=5, le=100, description="Minimum samples required for rule generation")
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# Global ML Settings
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enable_ml_insights: bool = Field(True, description="Enable/disable ML insights generation")
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ml_insights_auto_trigger: bool = Field(False, description="Automatically trigger ML insights in daily workflow")
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ml_confidence_threshold: float = Field(0.80, ge=0.0, le=1.0, description="Minimum confidence threshold for ML recommendations")
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class NotificationSettings(BaseModel):
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"""Notification and communication settings"""
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# WhatsApp Configuration (Shared Account Model)
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whatsapp_enabled: bool = Field(False, description="Enable WhatsApp notifications for this tenant")
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whatsapp_phone_number_id: str = Field("", description="Meta WhatsApp Phone Number ID (from shared master account)")
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whatsapp_display_phone_number: str = Field("", description="Display format for UI (e.g., '+34 612 345 678')")
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whatsapp_default_language: str = Field("es", description="Default language for WhatsApp templates")
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# Email Configuration
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email_enabled: bool = Field(True, description="Enable email notifications for this tenant")
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email_from_address: str = Field("", description="Custom from email address (optional)")
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email_from_name: str = Field("", description="Custom from name (optional)")
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email_reply_to: str = Field("", description="Reply-to email address (optional)")
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# Notification Preferences
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enable_po_notifications: bool = Field(True, description="Enable purchase order notifications")
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enable_inventory_alerts: bool = Field(True, description="Enable inventory alerts")
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enable_production_alerts: bool = Field(True, description="Enable production alerts")
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enable_forecast_alerts: bool = Field(True, description="Enable forecast alerts")
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# Notification Channels
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po_notification_channels: list[str] = Field(["email"], description="Channels for PO notifications (email, whatsapp)")
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inventory_alert_channels: list[str] = Field(["email"], description="Channels for inventory alerts")
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production_alert_channels: list[str] = Field(["email"], description="Channels for production alerts")
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forecast_alert_channels: list[str] = Field(["email"], description="Channels for forecast alerts")
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@validator('po_notification_channels', 'inventory_alert_channels', 'production_alert_channels', 'forecast_alert_channels')
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def validate_channels(cls, v):
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"""Validate that channels are valid"""
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valid_channels = ["email", "whatsapp", "sms", "push"]
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for channel in v:
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if channel not in valid_channels:
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raise ValueError(f"Invalid channel: {channel}. Must be one of {valid_channels}")
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return v
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@validator('whatsapp_phone_number_id')
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def validate_phone_number_id(cls, v, values):
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"""Validate phone number ID is provided if WhatsApp is enabled"""
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if values.get('whatsapp_enabled') and not v:
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raise ValueError("whatsapp_phone_number_id is required when WhatsApp is enabled")
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return v
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# ================================================================
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# REQUEST/RESPONSE SCHEMAS
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# ================================================================
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class TenantSettingsResponse(BaseModel):
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"""Response schema for tenant settings"""
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id: UUID
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tenant_id: UUID
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procurement_settings: ProcurementSettings
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inventory_settings: InventorySettings
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production_settings: ProductionSettings
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supplier_settings: SupplierSettings
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pos_settings: POSSettings
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order_settings: OrderSettings
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replenishment_settings: ReplenishmentSettings
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safety_stock_settings: SafetyStockSettings
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moq_settings: MOQSettings
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supplier_selection_settings: SupplierSelectionSettings
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ml_insights_settings: MLInsightsSettings
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notification_settings: NotificationSettings
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created_at: datetime
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updated_at: datetime
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class Config:
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from_attributes = True
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class TenantSettingsUpdate(BaseModel):
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"""Schema for updating tenant settings"""
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procurement_settings: Optional[ProcurementSettings] = None
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inventory_settings: Optional[InventorySettings] = None
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production_settings: Optional[ProductionSettings] = None
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supplier_settings: Optional[SupplierSettings] = None
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pos_settings: Optional[POSSettings] = None
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order_settings: Optional[OrderSettings] = None
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replenishment_settings: Optional[ReplenishmentSettings] = None
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safety_stock_settings: Optional[SafetyStockSettings] = None
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moq_settings: Optional[MOQSettings] = None
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supplier_selection_settings: Optional[SupplierSelectionSettings] = None
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ml_insights_settings: Optional[MLInsightsSettings] = None
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notification_settings: Optional[NotificationSettings] = None
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class CategoryUpdateRequest(BaseModel):
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"""Schema for updating a single category"""
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settings: dict
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class CategoryResetResponse(BaseModel):
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"""Response schema for category reset"""
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category: str
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settings: dict
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message: str
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