"""大模型回退层：Mock 与 OpenAI 兼容 API 两种后端。"""
from __future__ import annotations

import asyncio
from typing import Dict

from .config import get_api_key
from .llm_client import OpenAICompatClient
from .models import ExpertResponse


class FallbackProvider:
    name: str = "fallback"

    async def generate(self, query: str) -> ExpertResponse:
        raise NotImplementedError


class MockFallback(FallbackProvider):
    """确定性 mock 大模型：标识为 fallback，便于测试升级路径。"""

    def __init__(self, model: str = "mock-large"):
        self.model = model
        self.name = f"fallback-{model}"

    async def generate(self, query: str) -> ExpertResponse:
        await asyncio.sleep(0.002)
        body = (
            f"（大模型回退）「{query}」\n\n"
            "这是一条来自大模型回退路径的完整回答。\n"
            "要点：\n"
            "1. 对复杂/跨域任务给出综合推理\n"
            "2. 补充领域专家未覆盖的上下文\n"
            "3. 给出可执行的后续建议\n"
        )
        return ExpertResponse(
            text=body,
            model_used=self.model,
            latency_ms=2.0,
            tokens=120,
            cost_est=2.0 * 120 / 1_000_000,
        )


class APIFallback(FallbackProvider):
    """OpenAI 兼容大模型 API（如 DeepSeek / OpenAI / 本地 vLLM）。"""

    def __init__(self, model: str, base_url: str, api_key: str):
        self.model = model
        self.name = f"fallback-{model}"
        self._client = OpenAICompatClient(base_url, api_key, timeout=90.0)

    async def generate(self, query: str) -> ExpertResponse:
        data = await self._client.chat(
            self.model,
            [{"role": "user", "content": query}],
            temperature=0.3,
            max_tokens=2048,
        )
        body = self._client.completion_text(data)
        tokens = self._client.completion_tokens(data, body)
        return ExpertResponse(
            text=body,
            model_used=self.model,
            latency_ms=0.0,
            tokens=tokens,
            cost_est=2.0 * tokens / 1_000_000,
        )


def build_fallback(cfg: Dict) -> FallbackProvider:
    """cfg 为 fallback 段配置。"""
    ftype = cfg.get("type", "mock")
    model = cfg.get("model", "deepseek-chat")
    if ftype == "mock":
        return MockFallback(model=model)
    if ftype == "api":
        api_key = cfg.get("api_key") or get_api_key(cfg)
        if not api_key:
            raise RuntimeError(
                f"APIFallback 缺少 API Key：请设置环境变量 {cfg.get('api_key_env')} 或配置 api_key"
            )
        return APIFallback(model, cfg.get("base_url", "https://api.deepseek.com/v1"), api_key)
    raise ValueError(f"未知 fallback 类型: {ftype}（支持 mock | api）")