MobilityOps/backend/app/schemas.py

from __future__ import annotations

from datetime import datetime
from typing import Annotated, Any, Literal

from pydantic import BaseModel, Field

Role = Literal["operations_manager", "rental_employee"]


class DemoLoginRequest(BaseModel):
    role: Role


class CurrentUser(BaseModel):
    public_ref: str
    display_name: str
    role: Role


class VehicleOut(BaseModel):
    public_ref: str
    make: str
    model: str
    model_year: int
    registration_number: str
    location: str
    operational_status: str
    odometer_km: int
    next_service_km: int
    active: bool
    attention: bool = False


class BookingSummaryOut(BaseModel):
    public_ref: str
    customer_ref: str
    vehicle_ref: str
    starts_at: datetime
    ends_at: datetime
    status: str


class BookingOut(BookingSummaryOut):
    start_odometer_km: int | None
    end_odometer_km: int | None
    requirements_complete: bool
    customer_name: str


class RegisterReturnRequest(BaseModel):
    end_odometer_km: Annotated[int, Field(ge=0)]
    fuel_level_percent: Annotated[int, Field(ge=0, le=100)]
    cleanliness_ok: bool
    damage_reported: bool
    technical_warning: bool
    notes: str | None = Field(default=None, max_length=2000)


class NextBookingRisk(BaseModel):
    booking_ref: str
    starts_at: datetime
    at_risk: bool


class RegisterReturnResult(BaseModel):
    booking_ref: str
    vehicle_ref: str
    inspection_ref: str
    resulting_vehicle_status: str
    odometer_regression: bool
    quality_issue_ref: str | None
    workflow_event_id: str
    next_booking_risk: NextBookingRisk | None


class ReturnPreviewResult(BaseModel):
    booking_ref: str
    vehicle_ref: str
    canonical_odometer_km: int
    submitted_odometer_km: int
    odometer_regression: bool
    resulting_odometer_km: int
    resulting_vehicle_status: str
    status_reason: str
    would_create_quality_issue: bool
    attention_reasons: list[str]
    next_booking_risk: NextBookingRisk | None


class InspectionOut(BaseModel):
    public_ref: str
    booking_ref: str
    type: str
    fuel_level_percent: int
    cleanliness_ok: bool
    damage_reported: bool
    technical_warning: bool
    odometer_km: int
    completed_at: datetime


class MaintenanceOut(BaseModel):
    public_ref: str
    occurred_at: datetime
    odometer_km: int
    category: str
    summary: str


class DataQualityIssueOut(BaseModel):
    public_ref: str
    rule_type: str
    entity_type: str
    entity_ref: str
    severity: str
    status: str
    evidence: dict[str, Any]
    detected_at: datetime
    resolved_at: datetime | None = None


class DataQualityIssueDetailOut(DataQualityIssueOut):
    entity_snapshot: dict[str, Any] | None = None
    related_snapshots: list[dict[str, Any]] = Field(default_factory=list)


class MergeCustomersRequest(BaseModel):
    survivor_ref: str
    field_overrides: dict[str, str] | None = None


class MergeCustomersResult(BaseModel):
    issue_ref: str
    survivor_ref: str
    loser_ref: str
    rewired_bookings: int


class ScanResultOut(BaseModel):
    created: dict[str, int]


class ProvideFieldsRequest(BaseModel):
    fields: dict[str, str]


class ResolveOdometerRegressionRequest(BaseModel):
    decision: Literal["retain_canonical", "correct_reading"]
    booking_ref: str | None = None
    corrected_odometer_km: Annotated[int, Field(ge=0)] | None = None
    note: str | None = Field(default=None, max_length=500)


class ResolveOverlapRequest(BaseModel):
    booking_ref: str
    note: str | None = Field(default=None, max_length=500)


class ApplyRecommendedStatusResult(BaseModel):
    issue: DataQualityIssueOut
    applied_status: str
    reason: str


class VehicleDetailOut(VehicleOut):
    bookings: list[BookingSummaryOut] = Field(default_factory=list)
    inspections: list[InspectionOut] = Field(default_factory=list)
    maintenance: list[MaintenanceOut] = Field(default_factory=list)
    quality_issues: list[DataQualityIssueOut] = Field(default_factory=list)


class DashboardMetrics(BaseModel):
    available: int
    rented: int
    cleaning: int
    maintenance: int
    blocked: int
    open_quality_issues: int
    pending_or_failed_workflows: int


class AttentionItem(BaseModel):
    kind: Literal["quality_issue", "vehicle"]
    severity: str
    title: str
    detail: str
    link_type: Literal["vehicle", "booking", "customer"]
    link_ref: str
    issue_ref: str | None = None


class TodayItem(BaseModel):
    kind: Literal["departure", "return"]
    booking_ref: str
    vehicle_ref: str
    scheduled_at: datetime


class AutomationRunOut(BaseModel):
    event_id: str
    event_type: str
    aggregate_ref: str
    status: str
    attempts: int
    last_error: str | None
    occurred_at: datetime


class DashboardOut(BaseModel):
    metrics: DashboardMetrics
    attention_items: list[AttentionItem]
    today: list[TodayItem]
    recent_automation: list[AutomationRunOut]


class OperationsSummaryOut(BaseModel):
    tenant: str
    metrics: DashboardMetrics


class AttentionVehicleOut(BaseModel):
    vehicle_ref: str
    severity: Literal["low", "medium", "high"]
    rule_type: str
    summary: str
    detected_at: datetime


class McpVehicleDetailOut(BaseModel):
    public_ref: str
    make: str
    model: str
    model_year: int
    location: str
    operational_status: str
    odometer_km: int
    next_service_km: int
    open_quality_issue_count: int
    current_booking_ref: str | None


class McpKnowledgeSearchRequest(BaseModel):
    question: str = Field(min_length=3, max_length=1000)
    max_sources: int = Field(default=4, ge=1, le=8)


class AuditEventOut(BaseModel):
    id: str
    actor_type: str
    actor_label: str
    action: str
    entity_type: str
    entity_id: str | None
    entity_ref: str | None = None
    entity_link: str | None = None
    correlation_id: str
    occurred_at: datetime
    before: dict[str, Any] | None = None
    after: dict[str, Any] | None = None
    metadata: dict[str, Any] | None = None