61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
import os
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from dataclasses import dataclass, field
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from pathlib import Path
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from dotenv import load_dotenv
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load_dotenv(Path(__file__).resolve().parent.parent / ".env")
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@dataclass(frozen=True)
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class Settings:
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# LLM 配置
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llm_api_key: str = field(
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default_factory=lambda: os.getenv("LLM_API_KEY", ""),
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repr=False,
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)
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llm_model: str = field(default_factory=lambda: os.getenv("LLM_MODEL", ""))
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llm_base_url: str | None = field(
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default_factory=lambda: os.getenv("LLM_BASE_URL") or None
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)
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llm_timeout: float = 60.0
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llm_max_retries: int = 2
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# Jev
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typesafe_api_key: str = field(
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default_factory=lambda: os.getenv("TYPESAFE_API_KEY", ""), repr=False
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)
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typesafe_model: str = field(
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default_factory=lambda: os.getenv("TYPESAFE_DEFAULT_MODEL") or "jev-latest"
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)
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typesafe_base_url: str = field(
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default_factory=lambda: (
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os.getenv("TYPESAFE_BASE_URL") or "https://api.typesafe.ai"
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)
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)
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typesafe_timeout: float = field(
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default_factory=lambda: float(os.getenv("TYPESAFE_TIMEOUT", "30"))
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)
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typesafe_max_retries: int = field(
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default_factory=lambda: int(os.getenv("TYPESAFE_MAX_RETRIES", "2"))
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)
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# 意图门控使用 Jev confidence，阈值需按真实语料校准
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intent_min_confidence: float = field(
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default_factory=lambda: float(os.getenv("INTENT_MIN_CONFIDENCE", "0.7"))
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)
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# 动作自动修正次数，不含首次生成，0 表示不重试，与用户澄清轮数无关
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max_action_retries: int = field(
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default_factory=lambda: int(os.getenv("MAX_ACTION_RETRIES", "2"))
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)
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def __post_init__(self):
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if type(self.max_action_retries) is not int or self.max_action_retries < 0:
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raise ValueError("MAX_ACTION_RETRIES 必须是非负整数")
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if not 0 <= self.intent_min_confidence <= 1:
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raise ValueError("INTENT_MIN_CONFIDENCE 必须在 0 到 1 之间")
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settings = Settings()
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