from __future__ import annotations

from dataclasses import dataclass
from typing import Literal

Mode = Literal["chat", "work"]
Strength = Literal["light", "medium", "high", "extreme"]
Provider = Literal["k1412", "deepseek"]


@dataclass(frozen=True, slots=True)
class ModelSpec:
    public_id: str
    display_name: str
    mode: Mode
    strength: Strength
    provider: Provider
    provider_model: str
    thinking_enabled: bool
    reasoning_effort: str | None
    max_output_tokens: int
    max_iterations: int
    context_char_budget: int


_TIERS = {
    "light": ("轻度", "k1412", "ChatGPT-5.6:Luna", False, None, 4_096, 8, 120_000),
    "medium": ("中", "k1412", "ChatGPT-5.6:Terra", False, None, 4_096, 16, 240_000),
    "high": ("高", "k1412", "ChatGPT-5.6:Sol", False, None, 4_096, 24, 400_000),
    "extreme": ("极高", "deepseek", "deepseek-v4-pro", True, "max", 16_384, 32, 800_000),
}

MODEL_SPECS: dict[str, ModelSpec] = {
    f"{mode}-{strength}": ModelSpec(
        public_id=f"{mode}-{strength}",
        display_name=f"{'Chat' if mode == 'chat' else 'Work'} · {label}",
        mode=mode,
        strength=strength,
        provider=provider,
        provider_model=provider_model,
        thinking_enabled=thinking_enabled,
        reasoning_effort=reasoning_effort,
        max_output_tokens=max_output_tokens,
        max_iterations=max_iterations,
        context_char_budget=context_budget,
    )
    for mode in ("chat", "work")
    for strength, (
        label,
        provider,
        provider_model,
        thinking_enabled,
        reasoning_effort,
        max_output_tokens,
        max_iterations,
        context_budget,
    ) in _TIERS.items()
}


def get_model_spec(model_id: str) -> ModelSpec:
    try:
        return MODEL_SPECS[model_id]
    except KeyError as exc:
        raise ValueError(f"Unsupported model: {model_id}") from exc


def openai_model_list() -> dict:
    return {
        "object": "list",
        "data": [
            {
                "id": spec.public_id,
                "object": "model",
                "owned_by": "k1412-agent",
                "name": spec.display_name,
            }
            for spec in MODEL_SPECS.values()
        ],
    }