from datetime import datetime, timezone

from sqlalchemy import (
    JSON, Boolean, Column, DateTime, Float, ForeignKey, Integer, String, Table, Text,
)
from sqlalchemy.orm import Mapped, mapped_column, relationship

from .database import Base


def utcnow() -> datetime:
    return datetime.now(timezone.utc)


class User(Base):
    """Phase 8 — optional accounts.

    Three kinds of rows share this table:
      - the "local user" (email NULL, is_guest False): auto-created in
        single-user/local mode; owns everything a pre-Phase-8 DB had;
      - guests (email NULL, is_guest True): created on first visit in
        multi-user mode, identified only by their session cookie;
      - registered users (email set): a guest upgraded in place, so their
        data survives registration with no re-parenting.
    """

    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    email: Mapped[str | None] = mapped_column(String(320), unique=True, nullable=True)
    password_hash: Mapped[str | None] = mapped_column(String(300), nullable=True)
    is_guest: Mapped[bool] = mapped_column(Boolean, default=True)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow)
    last_seen_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True)
    # Shared demo key usage (resets when the UTC date changes).
    demo_turns_used: Mapped[int] = mapped_column(Integer, default=0)
    demo_turns_date: Mapped[str] = mapped_column(String(10), default="")


scenario_scripts = Table(
    "scenario_scripts",
    Base.metadata,
    Column("scenario_id", ForeignKey("scenarios.id", ondelete="CASCADE"), primary_key=True),
    Column("script_id", ForeignKey("scripts.id", ondelete="CASCADE"), primary_key=True),
)


class Scenario(Base):
    __tablename__ = "scenarios"

    id: Mapped[int] = mapped_column(primary_key=True)
    # NULL owner + is_public = seeded demo content, readable by everyone.
    user_id: Mapped[int | None] = mapped_column(
        ForeignKey("users.id", ondelete="CASCADE"), nullable=True
    )
    is_public: Mapped[bool] = mapped_column(Boolean, default=False)
    title: Mapped[str] = mapped_column(String(200), default="Untitled Scenario")
    description: Mapped[str] = mapped_column(Text, default="")
    prompt: Mapped[str] = mapped_column(Text, default="")
    # Plot components (AI Dungeon terminology; `memory` == Plot Essentials)
    memory: Mapped[str] = mapped_column(Text, default="")
    authors_note: Mapped[str] = mapped_column(Text, default="")
    ai_instructions: Mapped[str] = mapped_column(Text, default="")
    tags: Mapped[str] = mapped_column(String(500), default="")
    # Cover art. Either an external "https://…" URL or an inline
    # "data:image/…;base64,…" URI (the editor downscales uploads before storing
    # one). Empty means the UI falls back to an emoji sigil or generated art.
    # Kept in the row rather than on disk because Render's free tier has no
    # persistent volume, and it makes export bundles self-contained.
    image: Mapped[str] = mapped_column(Text, default="")
    # A single emoji or glyph used when there's no `image` — cheap art for
    # scenarios nobody wants to find a picture for. Separate from `image`
    # because it's a character, not a locator: no fetch, no cache, no bytes.
    icon: Mapped[str] = mapped_column(String(16), default="")
    # Phase 12: RPG world-state template — stat definitions (bands, rules) and
    # milestones. NULL/empty means this scenario has no RPG layer.
    stat_schema: Mapped[dict | None] = mapped_column(JSON, nullable=True)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow, onupdate=utcnow)

    story_cards: Mapped[list["StoryCard"]] = relationship(
        back_populates="scenario", cascade="all, delete-orphan"
    )
    adventures: Mapped[list["Adventure"]] = relationship(back_populates="scenario")
    scripts: Mapped[list["Script"]] = relationship(secondary=scenario_scripts)


class Adventure(Base):
    __tablename__ = "adventures"

    id: Mapped[int] = mapped_column(primary_key=True)
    user_id: Mapped[int | None] = mapped_column(
        ForeignKey("users.id", ondelete="CASCADE"), nullable=True
    )
    scenario_id: Mapped[int | None] = mapped_column(
        ForeignKey("scenarios.id", ondelete="SET NULL"), nullable=True
    )
    title: Mapped[str] = mapped_column(String(200), default="Untitled Adventure")
    memory: Mapped[str] = mapped_column(Text, default="")
    authors_note: Mapped[str] = mapped_column(Text, default="")
    ai_instructions: Mapped[str] = mapped_column(Text, default="")
    story_summary: Mapped[str] = mapped_column(Text, default="")
    script_state: Mapped[dict] = mapped_column(JSON, default=dict)
    # Phase 12: live RPG world state (world/player/npc stats + milestones),
    # instantiated from the scenario's stat_schema. Empty when there's no RPG layer.
    world_state: Mapped[dict] = mapped_column(JSON, default=dict)
    # The ${Placeholder} answers collected when this adventure was started, kept
    # so "Update from scenario" can re-fill freshly copied scenario text with the
    # same values. NULL for adventures created before this column existed.
    placeholders: Mapped[dict | None] = mapped_column(JSON, nullable=True)
    # Phase 6: opt-in per adventure (extra AI calls)
    auto_summarize: Mapped[bool] = mapped_column(Boolean, default=False)
    memory_bank_enabled: Mapped[bool] = mapped_column(Boolean, default=False)
    # How many actions have already been folded into memories / the story summary.
    memory_cursor: Mapped[int] = mapped_column(Integer, default=0)
    summary_cursor: Mapped[int] = mapped_column(Integer, default=0)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow, onupdate=utcnow)

    scenario: Mapped[Scenario | None] = relationship(back_populates="adventures")
    story_cards: Mapped[list["StoryCard"]] = relationship(
        back_populates="adventure", cascade="all, delete-orphan"
    )
    actions: Mapped[list["Action"]] = relationship(
        back_populates="adventure",
        cascade="all, delete-orphan",
        order_by="Action.index",
    )
    scripts: Mapped[list["AdventureScript"]] = relationship(
        back_populates="adventure",
        cascade="all, delete-orphan",
        order_by="AdventureScript.position",
    )
    memories: Mapped[list["Memory"]] = relationship(
        back_populates="adventure",
        cascade="all, delete-orphan",
        order_by="Memory.id",
    )


class Memory(Base):
    """Phase 6: an auto-summarized (or hand-written) fact about the adventure.

    `embedding` is the raw vector as a JSON list (cosine ranking happens in
    Python — fine at bank sizes of a few hundred). NULL until embedded, which
    also marks it for backfill when an embedding model becomes available.
    """

    __tablename__ = "memories"

    id: Mapped[int] = mapped_column(primary_key=True)
    adventure_id: Mapped[int] = mapped_column(ForeignKey("adventures.id", ondelete="CASCADE"))
    text: Mapped[str] = mapped_column(Text, default="")
    embedding: Mapped[list | None] = mapped_column(JSON, nullable=True)
    # Action index range this memory summarizes (null for manual memories).
    source_start: Mapped[int | None] = mapped_column(Integer, nullable=True)
    source_end: Mapped[int | None] = mapped_column(Integer, nullable=True)
    pinned: Mapped[bool] = mapped_column(Boolean, default=False)
    forgotten: Mapped[bool] = mapped_column(Boolean, default=False)  # evicted, kept for UI
    use_count: Mapped[int] = mapped_column(Integer, default=0)
    last_used_at: Mapped[datetime | None] = mapped_column(DateTime, nullable=True)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow)

    adventure: Mapped[Adventure] = relationship(back_populates="memories")

    @property
    def embedded(self) -> bool:
        return self.embedding is not None


class StoryCard(Base):
    """Owned by either a scenario or an adventure (exactly one set)."""

    __tablename__ = "story_cards"

    id: Mapped[int] = mapped_column(primary_key=True)
    scenario_id: Mapped[int | None] = mapped_column(
        ForeignKey("scenarios.id", ondelete="CASCADE"), nullable=True
    )
    adventure_id: Mapped[int | None] = mapped_column(
        ForeignKey("adventures.id", ondelete="CASCADE"), nullable=True
    )
    type: Mapped[str] = mapped_column(String(100), default="")
    name: Mapped[str] = mapped_column(String(200), default="")
    keys: Mapped[str] = mapped_column(Text, default="")  # comma-separated triggers
    entry: Mapped[str] = mapped_column(Text, default="")
    notes: Mapped[str] = mapped_column(Text, default="")
    # Adventure copies only: which piece of the scenario this card came from —
    # "card:<scenario_card_id>" or "npc:<npc_key>". "Update from scenario"
    # refreshes/removes exactly these; NULL means player-authored (left alone),
    # or a copy predating the column (matched by name, then adopted).
    source_ref: Mapped[str | None] = mapped_column(String(64), nullable=True)

    scenario: Mapped[Scenario | None] = relationship(back_populates="story_cards")
    adventure: Mapped[Adventure | None] = relationship(back_populates="story_cards")


class Action(Base):
    __tablename__ = "actions"

    id: Mapped[int] = mapped_column(primary_key=True)
    adventure_id: Mapped[int] = mapped_column(ForeignKey("adventures.id", ondelete="CASCADE"))
    index: Mapped[int] = mapped_column(Integer)
    type: Mapped[str] = mapped_column(String(20))  # start|do|say|story|continue|ai
    text: Mapped[str] = mapped_column(Text, default="")
    # Reasoning-model "thinking" that preceded the text (AI actions only).
    reasoning: Mapped[str | None] = mapped_column(Text, nullable=True)
    # The full assembled prompt for this turn, for the Insights viewer. By far
    # the biggest column in the database (~74 KB/row in production), and needed
    # by exactly one endpoint, one action at a time — so it is deferred: never
    # loaded unless something actually touches the attribute. Bulk readers must
    # NOT touch it; that is what `world_delta` below exists for.
    context_snapshot: Mapped[dict | None] = mapped_column(
        JSON, nullable=True, deferred=True
    )
    # The small slice of the snapshot that IS needed in bulk: this turn's RPG
    # state changes, for the inline chips under an AI message (world_changes)
    # and for re-attaching the emit block when replaying history to the model.
    # Mirrors the active variant, same as text/reasoning/context_snapshot.
    world_delta: Mapped[dict | None] = mapped_column(JSON, nullable=True)
    # Copy of Adventure.script_state as it was immediately BEFORE this action's
    # script hooks ran, so undo/retry can roll the shared scoreboard back.
    # NULL for actions created before this column existed. Deferred: only ever
    # read for the one action being undone or retried.
    state_before: Mapped[dict | None] = mapped_column(
        JSON, nullable=True, deferred=True
    )
    # Phase 12: same idea for the RPG world_state, so undo/retry rolls it back too.
    world_state_before: Mapped[dict | None] = mapped_column(
        JSON, nullable=True, deferred=True
    )
    # Retry history (AI actions): every attempt made for this turn, oldest
    # first, INCLUDING the active one. NULL/empty means never retried — the row
    # is its own only version. `variant_index` says which entry `text`,
    # `reasoning` and `context_snapshot` currently mirror; retry appends and
    # points here instead of deleting the row, so nothing is lost.
    #
    # Deferred for the same reason as context_snapshot: a list response only
    # ever needs the *count* (see variant_count below), but the column holds
    # every discarded attempt's full narration, so loading it in bulk made each
    # retry a permanent tax on every later page load of that adventure.
    variants: Mapped[list | None] = mapped_column(JSON, nullable=True, deferred=True)
    # len(variants), maintained on write by set_variants() so the deferred
    # column above never has to be fetched just to count it. 0 = never retried.
    variant_count: Mapped[int] = mapped_column(Integer, default=0)
    variant_index: Mapped[int] = mapped_column(Integer, default=0)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow)

    adventure: Mapped[Adventure] = relationship(back_populates="actions")

    @property
    def world_changes(self) -> list[dict]:
        """Compact per-turn RPG state changes (Phase 12), for the inline summary
        under an AI message. Labels are path-based (no schema needed):
        `npc.gwen.trust` -> "gwen trust".

        Reads `world_delta`, never `context_snapshot` — this runs for every
        action in a list response, and touching the deferred snapshot here
        would drag the whole prompt archive out of the database."""
        wd = self.world_delta if isinstance(self.world_delta, dict) else None
        if wd is None:
            return []
        applied = wd.get("applied") or []
        out: list[dict] = []
        for entry in applied:
            parts = str(entry.get("path", "")).split(".")
            section, name = parts[0], parts[-1]
            if section == "flags":
                out.append({"kind": "flag", "label": name, "on": bool(entry.get("new"))})
            elif section == "milestones":
                out.append({"kind": "milestone", "label": name})
            else:
                label = f"{parts[1]} {parts[2]}" if section == "npc" and len(parts) == 3 else name
                old, new = entry.get("old"), entry.get("new")
                delta = new - old if isinstance(old, (int, float)) and isinstance(new, (int, float)) else None
                out.append({"kind": "stat", "label": label, "delta": delta, "value": new})
        return out


class Script(Base):
    __tablename__ = "scripts"

    id: Mapped[int] = mapped_column(primary_key=True)
    user_id: Mapped[int | None] = mapped_column(
        ForeignKey("users.id", ondelete="CASCADE"), nullable=True
    )
    name: Mapped[str] = mapped_column(String(200), default="Untitled Script")
    description: Mapped[str] = mapped_column(Text, default="")
    library_js: Mapped[str] = mapped_column(Text, default="")
    input_js: Mapped[str] = mapped_column(Text, default="")
    context_js: Mapped[str] = mapped_column(Text, default="")
    output_js: Mapped[str] = mapped_column(Text, default="")
    created_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime, default=utcnow, onupdate=utcnow)


class AdventureScript(Base):
    """A script copied into an adventure at creation, so library edits don't
    change running adventures unless the player explicitly re-syncs it from
    `source_script_id`. `state` lives on Adventure.script_state (one shared
    state per adventure, as in AI Dungeon)."""

    __tablename__ = "adventure_scripts"

    id: Mapped[int] = mapped_column(primary_key=True)
    adventure_id: Mapped[int] = mapped_column(ForeignKey("adventures.id", ondelete="CASCADE"))
    # The library Script this copy was made from, so it can be re-synced on
    # demand. NULL for legacy copies (predate this column) and demo-derived
    # ones whose source isn't owned by the player — those fall back to a
    # name match, or simply aren't syncable.
    source_script_id: Mapped[int | None] = mapped_column(
        ForeignKey("scripts.id", ondelete="SET NULL"), nullable=True
    )
    position: Mapped[int] = mapped_column(Integer, default=0)
    enabled: Mapped[bool] = mapped_column(Boolean, default=True)
    name: Mapped[str] = mapped_column(String(200), default="Untitled Script")
    description: Mapped[str] = mapped_column(Text, default="")
    library_js: Mapped[str] = mapped_column(Text, default="")
    input_js: Mapped[str] = mapped_column(Text, default="")
    context_js: Mapped[str] = mapped_column(Text, default="")
    output_js: Mapped[str] = mapped_column(Text, default="")

    adventure: Mapped[Adventure] = relationship(back_populates="scripts")


class Settings(Base):
    __tablename__ = "settings"

    id: Mapped[int] = mapped_column(primary_key=True)
    # Phase 8: one row per user (pre-Phase-8 DBs had a single id=1 row, which
    # the migration assigns to the local user).
    user_id: Mapped[int | None] = mapped_column(
        ForeignKey("users.id", ondelete="CASCADE"), nullable=True, unique=True
    )
    endpoint_url: Mapped[str] = mapped_column(String(500), default="http://localhost:11434/v1")
    # Fernet-encrypted at rest ("enc:..." — see security.py); use api_key_plain.
    api_key: Mapped[str] = mapped_column(String(500), default="")
    model: Mapped[str] = mapped_column(String(200), default="")
    api_mode: Mapped[str] = mapped_column(String(20), default="chat")  # chat|completion
    temperature: Mapped[float] = mapped_column(Float, default=0.8)
    # 800 leaves room for a full scene; 400 tended to truncate mid-paragraph
    # and left reasoning models with nothing after their thinking.
    max_output_tokens: Mapped[int] = mapped_column(Integer, default=800)
    # Separate thinking budget for reasoning models (OpenRouter-style
    # `reasoning: {max_tokens}`); 0 = param not sent, -1 = reasoning explicitly
    # off (`reasoning: {effort: none}`). Added on top of
    # max_output_tokens so story output keeps its full budget.
    reasoning_max_tokens: Mapped[int] = mapped_column(Integer, default=0)
    context_token_budget: Mapped[int] = mapped_column(Integer, default=16384)
    narrator_prompt: Mapped[str] = mapped_column(
        Text,
        default=(
            "You are a masterful storyteller continuing an interactive adventure. "
            "Continue the story naturally in second person, staying consistent with "
            "everything established so far. Write vivid prose. Never speak for the "
            "player or break character. Do not conclude the story; always leave room "
            "for the player's next action."
        ),
    )
    stream: Mapped[bool] = mapped_column(Boolean, default=True)
    # Phase 6: auto-summarization + memory bank
    summary_model: Mapped[str] = mapped_column(String(200), default="")  # "" = main model
    embedding_model: Mapped[str] = mapped_column(String(200), default="")  # "" = bank disabled
    memory_bank_capacity: Mapped[int] = mapped_column(Integer, default=200)
    memory_top_k: Mapped[int] = mapped_column(Integer, default=5)

    @property
    def has_api_key(self) -> bool:
        return bool(self.api_key)

    @property
    def api_key_plain(self) -> str:
        from . import security  # local import: models is imported before security

        return security.decrypt_secret(self.api_key)