REFACTOR ALL APIs fix 1
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Urtzi Alfaro
@@ -107,3 +107,166 @@ class MultiDayForecastResponse(BaseModel):
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processing_time_ms: int = Field(..., description="Total processing time")
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# ================================================================
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# SCENARIO SIMULATION SCHEMAS - PROFESSIONAL/ENTERPRISE ONLY
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# ================================================================
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class ScenarioType(str, Enum):
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"""Types of scenarios available for simulation"""
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WEATHER = "weather" # Weather impact (heatwave, cold snap, rain, etc.)
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COMPETITION = "competition" # New competitor opening nearby
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EVENT = "event" # Local event (festival, sports, concert, etc.)
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PRICING = "pricing" # Price changes
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PROMOTION = "promotion" # Promotional campaigns
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HOLIDAY = "holiday" # Holiday periods
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SUPPLY_DISRUPTION = "supply_disruption" # Supply chain issues
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CUSTOM = "custom" # Custom user-defined scenario
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class WeatherScenario(BaseModel):
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"""Weather scenario parameters"""
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temperature_change: Optional[float] = Field(None, ge=-30, le=30, description="Temperature change in °C")
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precipitation_change: Optional[float] = Field(None, ge=0, le=100, description="Precipitation change in mm")
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weather_type: Optional[str] = Field(None, description="Weather type (heatwave, cold_snap, rainy, etc.)")
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class CompetitionScenario(BaseModel):
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"""Competition scenario parameters"""
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new_competitors: int = Field(1, ge=1, le=10, description="Number of new competitors")
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distance_km: float = Field(0.5, ge=0.1, le=10, description="Distance from location in km")
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estimated_market_share_loss: float = Field(0.1, ge=0, le=0.5, description="Estimated market share loss (0-50%)")
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class EventScenario(BaseModel):
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"""Event scenario parameters"""
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event_type: str = Field(..., description="Type of event (festival, sports, concert, etc.)")
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expected_attendance: int = Field(..., ge=0, description="Expected attendance")
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distance_km: float = Field(0.5, ge=0, le=50, description="Distance from location in km")
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duration_days: int = Field(1, ge=1, le=30, description="Duration in days")
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class PricingScenario(BaseModel):
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"""Pricing scenario parameters"""
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price_change_percent: float = Field(..., ge=-50, le=100, description="Price change percentage")
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affected_products: Optional[List[str]] = Field(None, description="List of affected product IDs")
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class PromotionScenario(BaseModel):
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"""Promotion scenario parameters"""
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discount_percent: float = Field(..., ge=0, le=75, description="Discount percentage")
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promotion_type: str = Field(..., description="Type of promotion (bogo, discount, bundle, etc.)")
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expected_traffic_increase: float = Field(0.2, ge=0, le=2, description="Expected traffic increase (0-200%)")
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class ScenarioSimulationRequest(BaseModel):
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"""Request schema for scenario simulation - PROFESSIONAL/ENTERPRISE ONLY"""
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scenario_name: str = Field(..., min_length=3, max_length=200, description="Name for this scenario")
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scenario_type: ScenarioType = Field(..., description="Type of scenario to simulate")
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inventory_product_ids: List[str] = Field(..., min_items=1, description="Products to simulate")
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start_date: date = Field(..., description="Simulation start date")
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duration_days: int = Field(7, ge=1, le=30, description="Simulation duration in days")
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# Scenario-specific parameters (one should be provided based on scenario_type)
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weather_params: Optional[WeatherScenario] = None
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competition_params: Optional[CompetitionScenario] = None
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event_params: Optional[EventScenario] = None
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pricing_params: Optional[PricingScenario] = None
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promotion_params: Optional[PromotionScenario] = None
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# Custom scenario parameters
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custom_multipliers: Optional[Dict[str, float]] = Field(
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None,
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description="Custom multipliers for baseline forecast (e.g., {'demand': 1.2, 'traffic': 0.8})"
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)
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# Comparison settings
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include_baseline: bool = Field(True, description="Include baseline forecast for comparison")
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@validator('start_date')
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def validate_start_date(cls, v):
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if v < date.today():
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raise ValueError("Simulation start date cannot be in the past")
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return v
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class ScenarioImpact(BaseModel):
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"""Impact of scenario on a specific product"""
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inventory_product_id: str
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baseline_demand: float
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simulated_demand: float
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demand_change_percent: float
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confidence_range: tuple[float, float]
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impact_factors: Dict[str, Any] # Breakdown of what drove the change
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class ScenarioSimulationResponse(BaseModel):
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"""Response schema for scenario simulation"""
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id: str = Field(..., description="Simulation ID")
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tenant_id: str
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scenario_name: str
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scenario_type: ScenarioType
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# Simulation parameters
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start_date: date
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end_date: date
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duration_days: int
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# Results
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baseline_forecasts: Optional[List[ForecastResponse]] = Field(
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None,
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description="Baseline forecasts (if requested)"
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)
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scenario_forecasts: List[ForecastResponse] = Field(..., description="Forecasts with scenario applied")
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# Impact summary
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total_baseline_demand: float
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total_scenario_demand: float
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overall_impact_percent: float
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product_impacts: List[ScenarioImpact]
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# Insights and recommendations
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insights: List[str] = Field(..., description="AI-generated insights about the scenario")
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recommendations: List[str] = Field(..., description="Actionable recommendations")
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risk_level: str = Field(..., description="Risk level: low, medium, high")
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# Metadata
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created_at: datetime
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processing_time_ms: int
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class Config:
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json_schema_extra = {
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"example": {
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"id": "scenario_123",
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"tenant_id": "tenant_456",
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"scenario_name": "Summer Heatwave Impact",
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"scenario_type": "weather",
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"overall_impact_percent": 15.5,
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"insights": [
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"Cold beverages expected to increase by 45%",
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"Bread products may decrease by 8% due to reduced appetite",
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"Ice cream demand projected to surge by 120%"
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],
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"recommendations": [
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"Increase cold beverage inventory by 40%",
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"Reduce bread production by 10%",
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"Stock additional ice cream varieties"
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],
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"risk_level": "medium"
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}
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}
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class ScenarioComparisonRequest(BaseModel):
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"""Request to compare multiple scenarios"""
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scenario_ids: List[str] = Field(..., min_items=2, max_items=5, description="Scenario IDs to compare")
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class ScenarioComparisonResponse(BaseModel):
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"""Response comparing multiple scenarios"""
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scenarios: List[ScenarioSimulationResponse]
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comparison_matrix: Dict[str, Dict[str, Any]]
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best_case_scenario_id: str
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worst_case_scenario_id: str
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recommended_action: str
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