src/compliment_forest/schema.py

from __future__ import annotations

from typing import Literal

from pydantic import BaseModel, ConfigDict, Field, field_validator

ForestStyle = Literal[
    "surprise",
    "watercolor",
    "paper_cut",
    "moonlit_gouache",
    "botanical_ink",
]
ArcRole = Literal["arrive", "steady", "widen", "step", "carry"]


class StrictModel(BaseModel):
    model_config = ConfigDict(extra="forbid", str_strip_whitespace=True)


class FactAnchor(StrictModel):
    source_phrase: str = Field(min_length=1, max_length=240)
    meaning: str = Field(min_length=3, max_length=300)


class SituationPlan(StrictModel):
    faithful_summary: str = Field(min_length=12, max_length=500)
    fact_anchors: list[FactAnchor] = Field(min_length=1, max_length=4)
    central_uncertainty: str = Field(min_length=3, max_length=300)
    desired_direction: str = Field(min_length=3, max_length=300)


class Clearing(StrictModel):
    arc_role: ArcRole
    source_phrase: str = Field(min_length=1, max_length=240)
    scene_title: str = Field(min_length=3, max_length=80)
    scene_intro: str = Field(min_length=12, max_length=240)
    narration: str = Field(min_length=80, max_length=720)
    strength: str = Field(min_length=3, max_length=100)
    reflection: str = Field(min_length=12, max_length=260)
    spell: str = Field(min_length=3, max_length=80)
    image_prompt: str = Field(min_length=8, max_length=300)

    @field_validator("spell")
    @classmethod
    def validate_spell(cls, value: str) -> str:
        if not value.lower().startswith(("i ", "i'm ", "i am ")):
            raise ValueError("spell must be a first-person present-tense mantra")
        if len(value.split()) > 12:
            raise ValueError("spell must contain at most 12 words")
        return value


class IntakeTurn(StrictModel):
    question: str = Field(min_length=4, max_length=240)
    answer: str = Field(min_length=1, max_length=240)


class IntakeQuestion(StrictModel):
    question: str = Field(min_length=4, max_length=240)
    options: list[str] = Field(min_length=3, max_length=4)
    rationale: str = Field(default="", max_length=2000)

    @field_validator("options")
    @classmethod
    def validate_unique_options(cls, values: list[str]) -> list[str]:
        normalized = {value.casefold() for value in values}
        if len(normalized) != len(values):
            raise ValueError("options must be unique")
        return values


class ForestDraft(StrictModel):
    forest_title: str = Field(min_length=3, max_length=120)
    proposed_strengths: list[str] = Field(min_length=3, max_length=6)
    clearings: list[Clearing] = Field(min_length=1, max_length=6)

    @field_validator("proposed_strengths")
    @classmethod
    def validate_unique_strengths(cls, values: list[str]) -> list[str]:
        normalized = {value.casefold() for value in values}
        if len(normalized) != len(values):
            raise ValueError("proposed strengths must be unique")
        return values


class CriticScore(StrictModel):
    index: int = Field(ge=0, le=5)
    specificity: int = Field(ge=1, le=5)
    warmth: int = Field(ge=1, le=5)
    non_genericness: int = Field(ge=1, le=5)
    non_toxic_positivity: int = Field(ge=1, le=5)
    reason: str = Field(min_length=3, max_length=240)


class CriticDecision(StrictModel):
    keep_indices: list[int] = Field(min_length=1, max_length=6)
    revise_indices: list[int] = Field(default_factory=list, max_length=6)
    reasons: dict[str, str] = Field(default_factory=dict)
    scores: list[CriticScore] = Field(default_factory=list, max_length=6)

    @field_validator("keep_indices", "revise_indices")
    @classmethod
    def validate_unique_indices(cls, values: list[int]) -> list[int]:
        if len(set(values)) != len(values):
            raise ValueError("indices must be unique")
        if any(index < 0 or index > 5 for index in values):
            raise ValueError("indices must be between zero and five")
        return values


class GuardResult(StrictModel):
    allowed: bool
    category: Literal["ok", "invalid", "crisis", "abuse", "medical"]
    message: str = ""


class StreamEvent(StrictModel):
    type: Literal[
        "status",
        "support",
        "forest",
        "clearing",
        "soundscape",
        "complete",
        "error",
    ]
    message: str = ""
    data: dict[str, object] = Field(default_factory=dict)