"""
平台统一配置管理
================

从 config/platform-config.yaml 加载所有配置：
- platforms: 平台信息、模型列表、方法配置、限流参数
- task_defaults: 任务默认模型映射
- runtime: 任务超时、TTL 策略

使用 Pydantic Schema 校验，启动时加载，全环境只读。
"""

from __future__ import annotations

import logging
from pathlib import Path
from typing import Any

from pydantic import BaseModel, ConfigDict, Field

logger = logging.getLogger(__name__)

try:
    import yaml

    YAML_AVAILABLE = True
except ImportError:
    YAML_AVAILABLE = False
    logger.warning("PyYAML 未安装")


# ═══════════════════════════════════════════════════════════════
# Pydantic Schema
# ═══════════════════════════════════════════════════════════════


class RateLimitConfig(BaseModel):
    """限流配置"""

    qps: float = Field(default=10.0, ge=0)
    burst: int = Field(default=20, ge=1)


class ModelConfig(BaseModel):
    """模型配置"""

    model_config = ConfigDict(protected_namespaces=())

    id: str
    platform_id: str = ""  # 加载时自动注入
    model_name: str = ""
    display_name: str = ""
    capabilities: list[str] = []
    default_params: dict[str, Any] = {}
    is_enabled: bool = True
    cost_per_1k_input: float = 0.0
    cost_per_1k_output: float = 0.0
    max_tokens_limit: int = 4096


class MethodConfig(BaseModel):
    """方法级配置"""

    timeout: int = Field(default=30, ge=1)
    max_connections: int = Field(default=20, ge=1)
    rate_limit: RateLimitConfig = Field(default_factory=RateLimitConfig)

    @property
    def rate_limit_qps(self) -> float:
        return self.rate_limit.qps

    @property
    def rate_limit_burst(self) -> int:
        return self.rate_limit.burst


class PlatformConfigData(BaseModel):
    """平台配置数据（对应 yaml 中单个平台）"""

    name: str = ""
    provider: str = ""
    base_url: str = ""
    priority: int = 100
    rate_limit: RateLimitConfig = Field(default_factory=RateLimitConfig)
    models: list[ModelConfig] = []
    methods: dict[str, MethodConfig] = {}

    @property
    def rate_limit_qps(self) -> float:
        return self.rate_limit.qps

    @property
    def rate_limit_burst(self) -> int:
        return self.rate_limit.burst


class RuntimeSection(BaseModel):
    """运行时策略"""

    task_timeouts: dict[str, int] = {}
    task_ttl: dict[str, int] = {}


class PlatformConfigRoot(BaseModel):
    """配置文件根 Schema"""

    platforms: dict[str, PlatformConfigData] = {}
    task_defaults: dict[str, str] = {}
    runtime: RuntimeSection = Field(default_factory=RuntimeSection)
    version: str = ""


# ═══════════════════════════════════════════════════════════════
# 兼容层 PlatformConfig（保持与旧代码接口一致）
# ═══════════════════════════════════════════════════════════════


class PlatformConfig:
    """平台配置（兼容旧接口，供外部代码使用）"""

    def __init__(self, platform_id: str, data: PlatformConfigData):
        self.id = platform_id
        self.name = data.name
        self.provider = data.provider
        self.base_url = data.base_url
        self.priority = data.priority
        self.rate_limit_qps = data.rate_limit_qps
        self.rate_limit_burst = data.rate_limit_burst
        self.models = data.models
        self.methods = data.methods


# ═══════════════════════════════════════════════════════════════
# 统一加载器
# ═══════════════════════════════════════════════════════════════


class PlatformConfigLoader:
    """平台统一配置加载器

    从 platform-config.yaml 一次性加载并校验所有配置，
    提供 platforms / models / methods / runtime 的统一访问。
    启动时加载，全环境只读（不支持热重载）。
    """

    DEFAULT_CONFIG_PATH = Path(__file__).parent.parent.parent / "config" / "platform-config.yaml"

    def __init__(self, config_path: str | None = None):
        self.config_path = Path(config_path) if config_path else self.DEFAULT_CONFIG_PATH
        self._raw: PlatformConfigRoot | None = None
        self._platforms: dict[str, PlatformConfig] = {}
        self._models: dict[str, ModelConfig] = {}
        self._load()

    def _load(self) -> None:
        """加载并校验配置文件"""
        if not self.config_path.exists():
            raise FileNotFoundError(f"平台配置文件不存在: {self.config_path}")

        try:
            with open(self.config_path, encoding="utf-8") as f:
                if YAML_AVAILABLE:
                    raw_dict = yaml.safe_load(f)
                else:
                    import json

                    raw_dict = json.load(f)

            # Pydantic Schema 校验（失败直接抛异常，fail fast）
            self._raw = PlatformConfigRoot.model_validate(raw_dict)

            # 构建平台索引
            self._platforms = {}
            for pid, pdata in self._raw.platforms.items():
                self._platforms[pid] = PlatformConfig(pid, pdata)

            # 构建模型索引（注入 platform_id）
            self._models = {}
            for pid, pdata in self._raw.platforms.items():
                for m in pdata.models:
                    m.platform_id = pid
                    self._models[m.id] = m

            logger.info(
                f"平台配置加载完成: {len(self._platforms)} 平台, "
                f"{len(self._models)} 模型, "
                f"version={self._raw.version or 'none'}"
            )

        except Exception as e:
            logger.error(f"平台配置加载失败: {e}")
            raise RuntimeError(f"平台配置加载失败: {e}") from e

    # ── 平台查询 ──────────────────────────────────────────────

    def get_platform(self, platform_id: str) -> PlatformConfig | None:
        return self._platforms.get(platform_id)

    def get_all_platforms(self) -> list[PlatformConfig]:
        return sorted(self._platforms.values(), key=lambda p: p.priority)

    # ── 模型查询 ──────────────────────────────────────────────

    def get_model(self, model_id: str) -> ModelConfig | None:
        return self._models.get(model_id)

    def get_all_models(self) -> list[ModelConfig]:
        return list(self._models.values())

    def get_enabled_models(self) -> list[ModelConfig]:
        return [m for m in self._models.values() if m.is_enabled]

    def get_models_by_capability(self, capability: str) -> list[ModelConfig]:
        return [m for m in self._models.values() if m.is_enabled and capability in m.capabilities]

    def get_models_by_platform(self, platform_id: str) -> list[ModelConfig]:
        return [m for m in self._models.values() if m.platform_id == platform_id and m.is_enabled]

    def get_default_model_for_task(self, task_type: str) -> str | None:
        if self._raw is None:
            return None
        return self._raw.task_defaults.get(task_type)

    # ── 方法查询 ──────────────────────────────────────────────

    def get_method_config(self, platform_id: str, method: str) -> MethodConfig | None:
        platform = self._raw.platforms.get(platform_id) if self._raw else None
        if platform:
            return platform.methods.get(method)
        return None

    # ── 运行时策略 ────────────────────────────────────────────

    def get_runtime_raw(self) -> dict[str, Any]:
        """获取运行时配置原始数据（用于 Admin API 展示）"""
        if self._raw is None:
            return {}
        return self._raw.runtime.model_dump()

    def get_task_timeout(self, task_type: str) -> int | None:
        if self._raw is None:
            return None
        return self._raw.runtime.task_timeouts.get(task_type)

    def get_task_ttl(self, task_type: str) -> int | None:
        if self._raw is None:
            return None
        return self._raw.runtime.task_ttl.get(task_type)

    @property
    def version(self) -> str:
        return self._raw.version if self._raw else ""


# ═══════════════════════════════════════════════════════════════
# 全局单例
# ═══════════════════════════════════════════════════════════════

_platform_config_loader: PlatformConfigLoader | None = None


def get_platform_config_loader() -> PlatformConfigLoader:
    global _platform_config_loader
    if _platform_config_loader is None:
        _platform_config_loader = PlatformConfigLoader()
    return _platform_config_loader