| from typing import Literal
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| from pydantic import BaseModel, Field
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| class HospitalObservation(BaseModel):
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| hospital_id: str
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| distance_km: float = Field(ge=0)
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| icu: Literal["unknown", "available"]
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| specialization: Literal["cardiac", "trauma", "general"]
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| traffic: Literal["low", "medium", "high"]
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| class ArrivalOutcomeObservation(BaseModel):
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| """What happened when ambulance arrived at hospital"""
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| status: Literal["accepted", "partial", "rejected"]
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| reason: str
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| suitability_score: float = Field(ge=0.0, le=1.0)
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| class Observation(BaseModel):
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| episode_id: int
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| seed: int
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| task_id: Literal["acde_easy", "acde_medium", "acde_hard"]
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| task_objective: str
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| scenario_type: Literal["medical", "accident", "fire"]
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| scenario_name: str
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| scenario_difficulty: Literal["easy", "medium", "hard"]
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| patient_condition: str
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| required_specialization: Literal["cardiac", "trauma", "general"]
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| initial_critical_time_limit_minutes: float = Field(gt=0)
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| critical_time_limit_minutes: float = Field(gt=0)
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| remaining_time_minutes: float = Field(ge=0)
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| step: int = Field(ge=1)
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| max_steps: int = 3
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| hospitals: list[HospitalObservation]
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| previous_action: str | None = None
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| ambulance_status: Literal["en_route", "in_transit", "arrived", "admitted", "rerouting"] = "en_route"
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| current_location_context: str = "incident_site"
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| visited_hospitals: list[str] = Field(default_factory=list)
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| failed_hospitals: list[str] = Field(default_factory=list)
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| recent_failed_hospitals: list[str] = Field(default_factory=list)
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| failed_reasons: dict[str, str] = Field(default_factory=dict)
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| total_time_spent_minutes: float = Field(default=0.0, ge=0.0)
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| rerouting_reason: str | None = None
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| last_arrival_outcome: ArrivalOutcomeObservation | None = None
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| explanation: list[str] = Field(default_factory=list)
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| memory_snapshot: dict[str, dict[str, float | int]] = Field(default_factory=dict)
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