"""OpenAI-backed order parser.

Wraps the OpenAI Chat Completions API. Returns a validated
:class:`OrderTicket`. If the API key is missing OR the API call fails,
``parse_order`` falls back to a deterministic heuristic parser so that the
Gradio demo never crashes (this is documented in the README).
"""

from __future__ import annotations

import json
import os
import re
import sys
from pathlib import Path
from typing import Optional

sys.path.insert(0, str(Path(__file__).resolve().parents[2]))

from src.config import DISH_TO_STATION, OPENAI_MODEL  # noqa: E402
from src.nlp.prompts import PROMPTS  # noqa: E402
from src.nlp.schema import ORDER_JSON_SCHEMA, OrderItem, OrderTicket, route_to_station  # noqa: E402


def _maybe_load_dotenv() -> None:
    try:
        from dotenv import load_dotenv  # type: ignore
    except ImportError:
        return
    env_path = Path(__file__).resolve().parents[2] / ".env"
    if env_path.exists():
        load_dotenv(env_path)


_maybe_load_dotenv()


def _openai_client():
    api_key = os.getenv("OPENAI_API_KEY")
    if not api_key:
        return None
    try:
        from openai import OpenAI  # type: ignore
    except ImportError:
        return None
    return OpenAI(api_key=api_key)


def call_llm(text: str, prompt_version: str = "v3_constrained") -> Optional[dict]:
    """Call the LLM. Returns the parsed JSON dict, or None on failure."""
    client = _openai_client()
    if client is None:
        return None

    system = PROMPTS.get(prompt_version, PROMPTS["v3_constrained"])
    try:
        response = client.chat.completions.create(
            model=OPENAI_MODEL,
            messages=[
                {"role": "system", "content": system},
                {"role": "user", "content": text},
            ],
            response_format={"type": "json_object"},
            temperature=0.0,
        )
        content = response.choices[0].message.content or "{}"
        return json.loads(content)
    except Exception as exc:  # noqa: BLE001  - we degrade to fallback
        print(f"[nlp.parser] OpenAI call failed: {exc}")
        return None


_NUMBER_WORDS = {
    "one": 1, "ein": 1, "eine": 1, "einen": 1, "a": 1,
    "two": 2, "zwei": 2,
    "three": 3, "drei": 3,
    "four": 4, "vier": 4,
    "five": 5, "fuenf": 5, "fünf": 5,
    "six": 6, "sechs": 6,
    "seven": 7, "sieben": 7,
    "eight": 8, "acht": 8,
}


def heuristic_parse(text: str) -> OrderTicket:
    """Very small fallback parser used when OpenAI is unavailable."""
    text_low = text.lower()
    items: list[OrderItem] = []

    for keyword, station in DISH_TO_STATION.items():
        if keyword in text_low:
            qty = 1
            # try to find a count immediately before the keyword
            match = re.search(rf"(\d+)\s+\w*\s*{re.escape(keyword)}", text_low)
            if match:
                qty = int(match.group(1))
            else:
                for word, value in _NUMBER_WORDS.items():
                    if re.search(rf"\b{word}\b\s+\w*\s*{re.escape(keyword)}", text_low):
                        qty = value
                        break
            items.append(
                OrderItem(
                    dish=keyword,
                    quantity=qty,
                    modifiers=[],
                    station=station,
                )
            )

    if not items:
        items.append(
            OrderItem(dish="unknown_dish", quantity=1, modifiers=[], station=None)
        )

    return OrderTicket(items=items, raw_text=text).finalize()


def parse_order(text: str, prompt_version: str = "v3_constrained") -> OrderTicket:
    """Public entry point. Returns a finalized :class:`OrderTicket`."""
    data = call_llm(text, prompt_version=prompt_version)
    if data is None:
        return heuristic_parse(text)

    try:
        ticket = OrderTicket.model_validate({**data, "raw_text": text})
        return ticket.finalize()
    except Exception as exc:  # noqa: BLE001
        print(f"[nlp.parser] schema validation failed: {exc}. Using heuristic.")
        return heuristic_parse(text)