"""Deterministic scripted BUILD/FIX JSON for the MockBackend.

Each petition maps to a category by keyword; each category emits a complete
BUILD JSON string (parsed by mind/validate.py exactly like real backend
output), with names and blurbs varied by a crc32 seed of the petition — same
petition in, same permit out, so demos replay exactly. The category library
exercises every building kind.

fix_script reads the candidate ids and report numbers back out of the
rendered fix prompt (the "- F1: desc (predicted index 41)" lines from
mind/prompts.py — keep the two in lockstep) and picks the best predicted
index, so mock fixes cite real numbers too.
"""

from __future__ import annotations

import json
import random
import re
import zlib

NAME_MAX = 24
BLURB_MAX = 140


def _seed_for(petition: str) -> int:
    return zlib.crc32(" ".join(petition.lower().split()).encode("utf-8")) & 0x7FFFFFFF


def _entry(kind: str, name: str, near=None, floors=None, hue=None) -> dict:
    return {"kind": kind, "name": name[:NAME_MAX], "near": near, "floors": floors, "hue": hue}


def _plan(blurb: str, buildings: list[dict]) -> dict:
    return {
        "intent": "build",
        "blurb": blurb[:BLURB_MAX],
        "buildings": buildings[:3],
        "decline_reason": None,
    }


_STOP_WORDS = {
    "a", "an", "the", "please", "build", "make", "made", "add", "want",
    "wants", "need", "needs", "near", "for", "with", "of", "in", "on", "to",
    "and", "my", "me", "us", "we", "i", "new", "some", "little", "big",
}


def _petition_name(petition: str, suffix: str = "House") -> str:
    words = [w for w in re.findall(r"[A-Za-z]+", petition) if w.lower() not in _STOP_WORDS]
    base = " ".join(w.capitalize() for w in words[:2])
    name = f"{base} {suffix}".strip()
    return (name[:NAME_MAX].rstrip() or f"Petition {suffix}")[:NAME_MAX]


_CAFES = ("Cafe Luna", "The Brass Kettle", "Marigold Coffee", "The Daily Grind", "Cafe Fig")
_HOUSES = ("Wren Cottage", "Maple End", "The Little Blue", "Juniper House", "Quince Cottage")
_APTS = ("Linden Court", "The Beacon Flats", "Harbor House", "The Gables", "Rookery Flats")
_TOWERS = ("Meridian Tower", "The Spindle", "Apex Tower", "Cobalt Point", "The Needle")
_PARKS = ("Dapple Green", "Whistle Park", "Petal Commons", "Old Elm Green")
_STADIUMS = ("The Civic Bowl", "Tin Cup Stadium", "The Roaring Yard")
_CHURCHES = ("The Quiet Spire", "St. Alder's", "Lantern Chapel")
_SCHOOLS = ("Alder Primary", "Hilltop School", "The Brightwork School")
_HOSPITALS = ("Riverside General", "St. Junia Hospital", "Bluebell General")
_FACTORIES = ("The Tin Works", "Cobalt Works", "The Bottling Hall")
_MARKETS = ("Penny Market", "The Mercantile", "Six Crows Market")
_BANKS = ("The Counting House", "First Acorn Bank", "The Strongbox")
_SHOPS = ("The Odd Shelf", "Tortoise & Finch", "The Blue Awning")
_NEARS = ("downtown", "the park", "Main St", "1st Ave")


def _district(petition: str, rng: random.Random) -> dict:
    flats, cafe, shop = rng.choice(_APTS), rng.choice(_CAFES), rng.choice(_SHOPS)
    buildings = [
        _entry("apartments", flats, "downtown", rng.randint(4, 7), rng.choice((25, 35, 200))),
        _entry("cafe", cafe, "downtown", 1, rng.choice((30, 40, 50))),
    ]
    if rng.random() < 0.7:
        buildings.append(_entry("shop", shop, "downtown", 1, rng.choice((10, 180, 320))))
    blurb = rng.choice((
        f"Zoning approved: a new block downtown — {flats} rising with {cafe} on the corner.",
        f"A whole block takes shape: {flats}, {cafe}, and room for more.",
    ))
    return _plan(blurb, buildings)


def _river(petition: str, rng: random.Random) -> dict:
    park, cafe = rng.choice(_PARKS), rng.choice(("The Ferry Light", "Pier Nine Cafe", "The Eddy"))
    blurb = rng.choice((
        f"The waterfront gets its due: {park} on the bank, {cafe} watching the water.",
        f"Permits issued by the river — {park}, and {cafe} for the crossing crowd.",
    ))
    return _plan(blurb, [
        _entry("park", park, "the river"),
        _entry("cafe", cafe, "the river", 1, rng.choice((35, 45))),
    ])


def _cafe(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_CAFES)
    near = rng.choice(_NEARS)
    blurb = rng.choice((
        f"{name} opens near {near} — pastries at dawn, lamplight at dusk.",
        f"Permit granted: {name}, sidewalk tables facing the street.",
    ))
    return _plan(blurb, [_entry("cafe", name, near, 1, rng.choice((30, 40, 50)))])


def _house(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_HOUSES)
    blurb = rng.choice((
        f"{name} gets its lot — a porch, a chimney, a light in the window.",
        f"A home is granted: {name}, keys cut while the paint dries.",
    ))
    return _plan(blurb, [_entry("house", name, rng.choice(_NEARS), rng.randint(1, 2), rng.choice((20, 35, 200, 350)))])


def _apartments(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_APTS)
    blurb = rng.choice((
        f"{name} approved — {rng.randint(4, 7)} floors of new neighbors.",
        f"Housing first: {name} will fill with families by the weekend.",
    ))
    return _plan(blurb, [_entry("apartments", name, rng.choice(_NEARS), rng.randint(4, 7), rng.choice((25, 200, 160)))])


def _tower(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_TOWERS)
    blurb = rng.choice((
        f"{name} cleared for the skyline — cranes by morning.",
        f"Downtown grows up: {name}, {rng.randint(8, 16)} floors against the horizon.",
    ))
    return _plan(blurb, [_entry("tower", name, "downtown", rng.randint(8, 16), rng.choice((210, 220, 35)))])


def _park(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_PARKS)
    blurb = rng.choice((
        f"Green space wins: {name}, benches and old trees included.",
        f"{name} is set aside — the city keeps a place to breathe.",
    ))
    return _plan(blurb, [_entry("park", name, rng.choice(_NEARS))])


def _stadium(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_STADIUMS)
    blurb = rng.choice((
        f"{name} approved — floodlights, roar, and a home team to be named.",
        f"Game on: {name} takes the big lot.",
    ))
    return _plan(blurb, [_entry("stadium", name, "downtown", 1, rng.choice((10, 210)))])


def _church(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_CHURCHES)
    blurb = f"{name} is granted its steeple — bells on the hour."
    return _plan(blurb, [_entry("church", name, rng.choice(_NEARS), 1, rng.choice((40, 350)))])


def _school(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_SCHOOLS)
    blurb = rng.choice((
        f"{name} chartered — chalk dust and a morning bell.",
        f"The city invests in small citizens: {name} opens soon.",
    ))
    return _plan(blurb, [_entry("school", name, rng.choice(_NEARS), rng.randint(1, 2), 200)])


def _hospital(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_HOSPITALS)
    blurb = f"{name} approved — the city will be looked after."
    return _plan(blurb, [_entry("hospital", name, rng.choice(_NEARS), rng.randint(3, 6), 200)])


def _bank(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_BANKS)
    blurb = f"{name} chartered downtown — marble face, careful ledgers."
    return _plan(blurb, [_entry("bank", name, "downtown", rng.randint(2, 4), 210)])


def _factory(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_FACTORIES)
    blurb = rng.choice((
        f"{name} zoned for the edge of town — jobs by the shift.",
        f"Industry arrives: {name}, smokestack and all.",
    ))
    return _plan(blurb, [_entry("factory", name, "the river", rng.randint(1, 2), 30)])


def _market(petition: str, rng: random.Random) -> dict:
    name = rng.choice(_MARKETS)
    blurb = rng.choice((
        f"{name} licensed — stalls up by Saturday.",
        f"Permit granted: {name}, the street will smell of bread.",
    ))
    return _plan(blurb, [_entry("market", name, rng.choice(_NEARS), 1, rng.choice((35, 15)))])


def _default(petition: str, rng: random.Random) -> dict:
    name = _petition_name(petition)
    blurb = f"City hall reads the petition twice, nods, and grants {name}."
    return _plan(blurb, [_entry("house", name, rng.choice(_NEARS), rng.randint(1, 2), rng.choice((20, 200, 320)))])


# Order matters: most specific first; "house" is the safety net before default.
_CATEGORIES: tuple[tuple[re.Pattern[str], object], ...] = (
    (re.compile(r"\b(districts?|downtown|neighbou?rhoods?|blocks?|quarters?|villages?|towns?|suburbs?|expand|grow)\b", re.I), _district),
    (re.compile(r"\b(rivers?|riverside|waterfront|bridges?|docks?|harbou?rs?|piers?|ferry)\b", re.I), _river),
    (re.compile(r"\b(caf[eé]s?|coffee|espresso|diners?|restaurants?|baker(?:y|ies)|bistros?|tea|ramen|pizz\w*|brunch|noodles?)\b", re.I), _cafe),
    (re.compile(r"\b(apartments?|condos?|flats?|hotels?|housing|lofts?)\b", re.I), _apartments),
    (re.compile(r"\b(towers?|offices?|skyscrapers?|high-?rises?|headquarters|startups?)\b", re.I), _tower),
    (re.compile(r"\b(stadiums?|arenas?|sports?|football|soccer|baseball|matches?)\b", re.I), _stadium),
    (re.compile(r"\b(church(?:es)?|temples?|chapels?|mosques?|cathedrals?|shrines?)\b", re.I), _church),
    (re.compile(r"\b(schools?|librar(?:y|ies)|universit(?:y|ies)|colleges?|academ(?:y|ies)|kids|children)\b", re.I), _school),
    (re.compile(r"\b(hospitals?|clinics?|doctors?|medical|health)\b", re.I), _hospital),
    (re.compile(r"\b(banks?|finance|credit|vaults?)\b", re.I), _bank),
    (re.compile(r"\b(factor(?:y|ies)|industr\w*|plants?|warehouses?|mills?|workshops?)\b", re.I), _factory),
    (re.compile(r"\b(markets?|malls?|grocer\w*|supermarkets?|shops?|stores?|boutiques?|bazaars?|pharmac\w*)\b", re.I), _market),
    (re.compile(r"\b(parks?|gardens?|greens?|trees?|playgrounds?|plazas?|squares?|fountains?)\b", re.I), _park),
    (re.compile(r"\b(houses?|homes?|cottages?|bungalows?|cabins?|townhouses?)\b", re.I), _house),
)


def build_script(petition: str) -> str:
    """The full BUILD JSON string for a petition. Deterministic: same
    petition (modulo case/whitespace) always yields the same permit."""
    petition = (petition or "").strip() or "a small building"
    rng = random.Random(_seed_for(petition))
    for pattern, builder in _CATEGORIES:
        if pattern.search(petition):
            return json.dumps(builder(petition, rng), ensure_ascii=False)  # type: ignore[operator]
    return json.dumps(_default(petition, rng), ensure_ascii=False)


_CANDIDATE_LINE_RE = re.compile(r"-\s*(F\d+):\s*([^\n(]*)\(predicted index (\d+)\)")
_TRAFFIC_INDEX_RE = re.compile(r'"traffic_index"\s*:\s*(\d+)')
_WORST_RE = re.compile(r'"worst"\s*:\s*"([^"]{1,48})"')


def fix_script(prompt: str) -> str:
    """The FIX JSON string, built from the candidates/numbers rendered into
    the fix prompt by mind/prompts.py. Picks the lowest predicted index."""
    text = str(prompt or "")
    m = _WORST_RE.search(text)
    worst = m.group(1) if m else "the worst crossing"
    ti = _TRAFFIC_INDEX_RE.search(text)
    pairs = _CANDIDATE_LINE_RE.findall(text)
    if pairs:
        cid, desc, pred = min(pairs, key=lambda p: int(p[2]))
        desc = " ".join(desc.split()).rstrip(" ,") or "the engine's bypass"
        if ti:
            diagnosis = (
                f"Index {ti.group(1)} with {worst} over capacity; "
                f"{cid} ({desc}) brings the predicted index to {pred}."
            )
        else:
            diagnosis = f"{worst} is over capacity; {cid} ({desc}) brings the predicted index to {pred}."
    else:
        m = re.search(r"\b(F\d+)\b", text)
        cid = m.group(1) if m else "F1"
        diagnosis = f"{worst} runs over capacity; applying {cid}."
    blurb = f"CITY ENGINEER: relief ordered for {worst}."
    return json.dumps(
        {"diagnosis": diagnosis[:160], "choice": cid, "blurb": blurb[:120]},
        ensure_ascii=False,
    )