"""Core typed models."""

from __future__ import annotations

from datetime import datetime
from typing import Any, Optional

from pydantic import BaseModel, ConfigDict, Field, field_validator

from app.common.enums import ActionType, DecisionMode, Difficulty, DoseBucket, SubEnvironment
from app.common.normalization import clamp_reward


class StrictBase(BaseModel):
    model_config = ConfigDict(extra="forbid")


class Medication(StrictBase):
    drug: str
    dose_bucket: DoseBucket = DoseBucket.MEDIUM
    indication: Optional[str] = None
    class_name: Optional[str] = None
    requires_taper: bool = False


class LabSummary(StrictBase):
    egfr: Optional[float] = None
    ast: Optional[float] = None
    alt: Optional[float] = None
    inr: Optional[float] = None
    glucose: Optional[float] = None


class PatientProfile(StrictBase):
    patient_id: str
    age: int
    sex: str
    comorbidities: list[str] = Field(default_factory=list)
    medications: list[Medication] = Field(default_factory=list)
    labs: LabSummary = Field(default_factory=LabSummary)
    vitals: dict[str, float] = Field(default_factory=dict)
    specialist_conflicts: list[str] = Field(default_factory=list)
    prior_ade_history: list[str] = Field(default_factory=list)
    frailty_score: float = 0.3
    adherence_estimate: float = 0.8
    latent_confounders: dict[str, float] = Field(default_factory=dict)
    monitoring_gaps: list[str] = Field(default_factory=list)


class CandidateAction(StrictBase):
    candidate_id: str
    mode: DecisionMode
    action_type: ActionType
    target_drug: Optional[str] = None
    replacement_drug: Optional[str] = None
    dose_bucket: DoseBucket = DoseBucket.NA
    taper_days: Optional[int] = None
    monitoring_plan: Optional[str] = None
    evidence_query: Optional[str] = None
    new_drug_name: Optional[str] = None
    candidate_components: list[str] = Field(default_factory=list)
    estimated_safety_delta: float = 0.0
    burden_delta: float = 0.0
    disease_stability_estimate: float = 0.0
    uncertainty_score: float = 0.5
    rationale_tags: list[str] = Field(default_factory=list)
    required_monitoring: list[str] = Field(default_factory=list)
    legality_precheck: bool = True


class PolyGuardAction(StrictBase):
    mode: DecisionMode
    action_type: ActionType
    target_drug: Optional[str] = None
    replacement_drug: Optional[str] = None
    dose_bucket: DoseBucket = DoseBucket.NA
    taper_days: Optional[int] = None
    monitoring_plan: Optional[str] = None
    evidence_query: Optional[str] = None
    new_drug_name: Optional[str] = None
    candidate_components: list[str] = Field(default_factory=list)
    candidate_id: str
    confidence: float
    rationale_brief: str

    @field_validator("confidence")
    @classmethod
    def _valid_confidence(cls, value: float) -> float:
        return clamp_reward(value)


class RewardBreakdown(StrictBase):
    format_compliance_score: float
    candidate_alignment_score: float
    legality_score: float
    safety_delta_score: float
    burden_improvement_score: float
    disease_stability_score: float
    dosing_quality_score: float
    abstention_quality_score: float
    efficiency_score: float
    process_fidelity_score: float
    explanation_grounding_score: float
    anti_cheat_score: float
    uncertainty_calibration_score: float
    primary_safety_legality: float = 0.5
    primary_clinical_improvement: float = 0.5
    primary_dosing_quality: float = 0.5
    primary_process_integrity: float = 0.5
    total_reward: float


class SafetyReport(StrictBase):
    legal: bool
    violations: list[str] = Field(default_factory=list)
    severity: str = "none"
    recommended_fallback: Optional[ActionType] = None
    uncertainty_notes: list[str] = Field(default_factory=list)


class UncertaintyReport(StrictBase):
    overall_uncertainty: float = 0.5
    missing_data_flags: list[str] = Field(default_factory=list)
    abstention_recommended: bool = False


class PolyGuardState(StrictBase):
    episode_id: str
    seed: int
    scenario_id: Optional[str] = None
    difficulty: Difficulty
    sub_environment: SubEnvironment = SubEnvironment.REGIMEN_RISK
    step_count: int
    max_steps: int
    patient: PatientProfile
    active_mode: DecisionMode = DecisionMode.REGIMEN_OPT
    cumulative_reward: float = 0.0
    unresolved_conflicts: list[str] = Field(default_factory=list)
    risk_summary: dict[str, float] = Field(default_factory=dict)
    burden_score: float = 0.5
    precision_dosing_flags: list[str] = Field(default_factory=list)
    action_history: list[dict[str, Any]] = Field(default_factory=list)
    done: bool = False
    created_at: datetime = Field(default_factory=datetime.utcnow)


class PolyGuardObservation(StrictBase):
    patient_summary: dict[str, Any]
    medication_table: list[dict[str, Any]]
    comorbidity_summary: list[str]
    organ_function_summary: dict[str, Any]
    labs_vitals_summary: dict[str, Any]
    graph_safety_summary: dict[str, Any]
    burden_score_summary: dict[str, Any]
    precision_dosing_flags: list[str]
    unresolved_conflicts: list[str]
    candidate_action_set: list[CandidateAction]
    step_budget_remaining: int
    action_history: list[dict[str, Any]]
    warning_summary: list[str]
    abstention_indicators: dict[str, Any]
    sub_environment: SubEnvironment
    deterministic_contract: dict[str, Any] = Field(default_factory=dict)


class StepTrace(StrictBase):
    step: int
    observation_snapshot: PolyGuardObservation
    selected_action: Optional[PolyGuardAction] = None
    critic_output: dict[str, Any] = Field(default_factory=dict)
    reward_components: dict[str, float] = Field(default_factory=dict)
    transition_delta: dict[str, Any] = Field(default_factory=dict)
    uncertainty_report: UncertaintyReport = Field(default_factory=UncertaintyReport)
    failure_reasons: list[str] = Field(default_factory=list)
    timeout: bool = False