82 lines
2.8 KiB
Python
82 lines
2.8 KiB
Python
"""
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Agent 配置模块
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支持从环境变量、构造函数参数加载配置。
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"""
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import os
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Optional
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def _load_env_file():
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"""加载项目根目录的 .env 文件"""
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# 尝试多个可能的位置
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possible_paths = [
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Path.cwd() / ".env",
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Path(__file__).parent.parent.parent / ".env",
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Path(__file__).parent.parent.parent.parent / ".env",
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]
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for env_path in possible_paths:
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if env_path.exists():
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with open(env_path, "r", encoding="utf-8") as f:
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for line in f:
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line = line.strip()
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if line and not line.startswith("#") and "=" in line:
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key, value = line.split("=", 1)
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# 只在环境变量不存在时才设置
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if key not in os.environ:
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os.environ[key] = value
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break
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# 模块加载时自动读取 .env 文件
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_load_env_file()
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@dataclass
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class AgentConfig:
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"""Causal Inference Agent 配置"""
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# LLM 配置（默认值仅在环境变量和 .env 都不存在时使用）
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llm_base_url: str = "https://glm47flash.cloyir.com/v1"
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llm_model: str = "qwen3.5-35b"
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llm_temperature: float = 0.3
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llm_max_tokens: int = 2048
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llm_api_key: Optional[str] = None
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llm_timeout: int = 120
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llm_max_retries: int = 3
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# 统计筛查配置
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corr_threshold: float = 0.1
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alpha: float = 0.05
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bootstrap_iterations: int = 500
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bootstrap_alpha: float = 0.05
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# 路径配置
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log_path: str = "causal_analysis.log.md"
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output_dir: str = "."
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@classmethod
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def from_env(cls) -> "AgentConfig":
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"""从环境变量加载配置"""
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return cls(
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llm_base_url=os.getenv("LLM_BASE_URL", cls.llm_base_url),
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llm_model=os.getenv("LLM_MODEL", cls.llm_model),
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llm_temperature=float(os.getenv("LLM_TEMPERATURE", str(cls.llm_temperature))),
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llm_max_tokens=int(os.getenv("LLM_MAX_TOKENS", str(cls.llm_max_tokens))),
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llm_api_key=os.getenv("LLM_API_KEY", cls.llm_api_key),
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llm_timeout=int(os.getenv("LLM_TIMEOUT", str(cls.llm_timeout))),
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llm_max_retries=int(os.getenv("LLM_MAX_RETRIES", str(cls.llm_max_retries))),
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corr_threshold=float(os.getenv("CORR_THRESHOLD", str(cls.corr_threshold))),
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alpha=float(os.getenv("ALPHA", str(cls.alpha))),
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bootstrap_iterations=int(
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os.getenv("BOOTSTRAP_ITERATIONS", str(cls.bootstrap_iterations))
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),
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bootstrap_alpha=float(os.getenv("BOOTSTRAP_ALPHA", str(cls.bootstrap_alpha))),
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log_path=os.getenv("LOG_PATH", cls.log_path),
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output_dir=os.getenv("OUTPUT_DIR", cls.output_dir),
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)
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