小鱼开发
755ecc9abe
- 删除 .gitlab-ci.yml - 删除 runtime_config.py 兼容层 - Pydantic Settings + YAML 三层配置分离 - 统一 PlatformConfigLoader 加载器 - docker-compose 移除重复 environment 覆盖 - volcengine base_url 从 YAML 读取 - 微信支付/SMS 空值启动时拦截 - 日志仅输出控制台，不写文件 - 更新 model_router 注释
279 lines
9.8 KiB
Python
279 lines
9.8 KiB
Python
"""
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平台统一配置管理
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================
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从 config/platform-config.yaml 加载所有配置：
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- platforms: 平台信息、模型列表、方法配置、限流参数
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- task_defaults: 任务默认模型映射
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- runtime: 任务超时、TTL 策略
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使用 Pydantic Schema 校验，启动时加载，全环境只读。
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"""
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from __future__ import annotations
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import logging
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from pathlib import Path
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from typing import Any
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from pydantic import BaseModel, ConfigDict, Field
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logger = logging.getLogger(__name__)
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try:
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import yaml
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YAML_AVAILABLE = True
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except ImportError:
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YAML_AVAILABLE = False
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logger.warning("PyYAML 未安装")
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# ═══════════════════════════════════════════════════════════════
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# Pydantic Schema
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# ═══════════════════════════════════════════════════════════════
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class RateLimitConfig(BaseModel):
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"""限流配置"""
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qps: float = Field(default=10.0, ge=0)
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burst: int = Field(default=20, ge=1)
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class ModelConfig(BaseModel):
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"""模型配置"""
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model_config = ConfigDict(protected_namespaces=())
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id: str
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platform_id: str = "" # 加载时自动注入
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model_name: str = ""
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display_name: str = ""
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capabilities: list[str] = []
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default_params: dict[str, Any] = {}
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is_enabled: bool = True
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cost_per_1k_input: float = 0.0
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cost_per_1k_output: float = 0.0
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max_tokens_limit: int = 4096
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class MethodConfig(BaseModel):
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"""方法级配置"""
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timeout: int = Field(default=30, ge=1)
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max_connections: int = Field(default=20, ge=1)
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rate_limit: RateLimitConfig = Field(default_factory=RateLimitConfig)
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@property
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def rate_limit_qps(self) -> float:
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return self.rate_limit.qps
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@property
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def rate_limit_burst(self) -> int:
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return self.rate_limit.burst
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class PlatformConfigData(BaseModel):
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"""平台配置数据（对应 yaml 中单个平台）"""
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name: str = ""
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provider: str = ""
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base_url: str = ""
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priority: int = 100
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rate_limit: RateLimitConfig = Field(default_factory=RateLimitConfig)
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models: list[ModelConfig] = []
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methods: dict[str, MethodConfig] = {}
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@property
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def rate_limit_qps(self) -> float:
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return self.rate_limit.qps
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@property
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def rate_limit_burst(self) -> int:
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return self.rate_limit.burst
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class RuntimeSection(BaseModel):
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"""运行时策略"""
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task_timeouts: dict[str, int] = {}
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task_ttl: dict[str, int] = {}
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class PlatformConfigRoot(BaseModel):
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"""配置文件根 Schema"""
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platforms: dict[str, PlatformConfigData] = {}
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task_defaults: dict[str, str] = {}
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runtime: RuntimeSection = Field(default_factory=RuntimeSection)
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version: str = ""
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# ═══════════════════════════════════════════════════════════════
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# 兼容层 PlatformConfig（保持与旧代码接口一致）
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# ═══════════════════════════════════════════════════════════════
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class PlatformConfig:
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"""平台配置（兼容旧接口，供外部代码使用）"""
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def __init__(self, platform_id: str, data: PlatformConfigData):
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self.id = platform_id
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self.name = data.name
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self.provider = data.provider
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self.base_url = data.base_url
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self.priority = data.priority
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self.rate_limit_qps = data.rate_limit_qps
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self.rate_limit_burst = data.rate_limit_burst
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self.models = data.models
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self.methods = data.methods
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# ═══════════════════════════════════════════════════════════════
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# 统一加载器
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# ═══════════════════════════════════════════════════════════════
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class PlatformConfigLoader:
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"""平台统一配置加载器
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从 platform-config.yaml 一次性加载并校验所有配置，
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提供 platforms / models / methods / runtime 的统一访问。
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启动时加载，全环境只读（不支持热重载）。
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"""
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DEFAULT_CONFIG_PATH = (
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Path(__file__).parent.parent.parent / "config" / "platform-config.yaml"
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)
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def __init__(self, config_path: str | None = None):
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self.config_path = Path(config_path) if config_path else self.DEFAULT_CONFIG_PATH
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self._raw: PlatformConfigRoot | None = None
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self._platforms: dict[str, PlatformConfig] = {}
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self._models: dict[str, ModelConfig] = {}
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self._load()
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def _load(self) -> None:
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"""加载并校验配置文件"""
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if not self.config_path.exists():
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raise FileNotFoundError(
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f"平台配置文件不存在: {self.config_path}"
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)
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try:
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with open(self.config_path, encoding="utf-8") as f:
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if YAML_AVAILABLE:
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raw_dict = yaml.safe_load(f)
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else:
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import json
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raw_dict = json.load(f)
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# Pydantic Schema 校验（失败直接抛异常，fail fast）
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self._raw = PlatformConfigRoot.model_validate(raw_dict)
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# 构建平台索引
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self._platforms = {}
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for pid, pdata in self._raw.platforms.items():
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self._platforms[pid] = PlatformConfig(pid, pdata)
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# 构建模型索引（注入 platform_id）
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self._models = {}
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for pid, pdata in self._raw.platforms.items():
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for m in pdata.models:
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m.platform_id = pid
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self._models[m.id] = m
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logger.info(
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f"平台配置加载完成: {len(self._platforms)} 平台, "
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f"{len(self._models)} 模型, "
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f"version={self._raw.version or 'none'}"
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)
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except Exception as e:
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logger.error(f"平台配置加载失败: {e}")
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raise RuntimeError(f"平台配置加载失败: {e}") from e
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# ── 平台查询 ──────────────────────────────────────────────
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def get_platform(self, platform_id: str) -> PlatformConfig | None:
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return self._platforms.get(platform_id)
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def get_all_platforms(self) -> list[PlatformConfig]:
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return sorted(self._platforms.values(), key=lambda p: p.priority)
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# ── 模型查询 ──────────────────────────────────────────────
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def get_model(self, model_id: str) -> ModelConfig | None:
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return self._models.get(model_id)
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def get_all_models(self) -> list[ModelConfig]:
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return list(self._models.values())
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def get_enabled_models(self) -> list[ModelConfig]:
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return [m for m in self._models.values() if m.is_enabled]
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def get_models_by_capability(self, capability: str) -> list[ModelConfig]:
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return [
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m
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for m in self._models.values()
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if m.is_enabled and capability in m.capabilities
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]
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def get_models_by_platform(self, platform_id: str) -> list[ModelConfig]:
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return [
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m
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for m in self._models.values()
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if m.platform_id == platform_id and m.is_enabled
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]
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def get_default_model_for_task(self, task_type: str) -> str | None:
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if self._raw is None:
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return None
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return self._raw.task_defaults.get(task_type)
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# ── 方法查询 ──────────────────────────────────────────────
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def get_method_config(self, platform_id: str, method: str) -> MethodConfig | None:
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platform = self._raw.platforms.get(platform_id) if self._raw else None
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if platform:
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return platform.methods.get(method)
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return None
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# ── 运行时策略 ────────────────────────────────────────────
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def get_runtime_raw(self) -> dict[str, Any]:
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"""获取运行时配置原始数据（用于 Admin API 展示）"""
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if self._raw is None:
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return {}
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return self._raw.runtime.model_dump()
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def get_task_timeout(self, task_type: str) -> int | None:
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if self._raw is None:
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return None
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return self._raw.runtime.task_timeouts.get(task_type)
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def get_task_ttl(self, task_type: str) -> int | None:
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if self._raw is None:
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return None
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return self._raw.runtime.task_ttl.get(task_type)
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@property
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def version(self) -> str:
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return self._raw.version if self._raw else ""
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# ═══════════════════════════════════════════════════════════════
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# 全局单例
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# ═══════════════════════════════════════════════════════════════
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_platform_config_loader: PlatformConfigLoader | None = None
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def get_platform_config_loader() -> PlatformConfigLoader:
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global _platform_config_loader
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if _platform_config_loader is None:
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_platform_config_loader = PlatformConfigLoader()
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return _platform_config_loader
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