generated from kgod/ai-review-template
105 lines
3.5 KiB
Python
105 lines
3.5 KiB
Python
from __future__ import annotations
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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 dotenv import load_dotenv
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BACKEND_ROOT = Path(__file__).resolve().parents[1]
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DEFAULT_ENV_FILE = BACKEND_ROOT / ".env"
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def _as_bool(value: str | None, default: bool) -> bool:
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if value is None:
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return default
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normalized = value.strip().lower()
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if normalized in {"1", "true", "yes", "on"}:
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return True
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if normalized in {"0", "false", "no", "off"}:
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return False
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raise ValueError(f"Invalid boolean configuration value: {value!r}")
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def _as_int(name: str, value: str | None, default: int) -> int:
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if value is None:
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return default
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parsed = int(value)
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if parsed < 0:
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raise ValueError(f"{name} must be non-negative")
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return parsed
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def _as_float(name: str, value: str | None, default: float) -> float:
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if value is None:
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return default
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parsed = float(value)
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if parsed <= 0:
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raise ValueError(f"{name} must be positive")
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return parsed
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@dataclass(frozen=True, slots=True)
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class Settings:
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"""Runtime settings with the API key deliberately hidden from repr output."""
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llm_provider: str = "auto"
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openai_api_key: str | None = field(default=None, repr=False)
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openai_base_url: str | None = None
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openai_model: str = "gpt-4o-mini"
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openai_timeout_seconds: float = 30.0
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openai_max_retries: int = 2
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structured_output_retries: int = 1
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structured_output_mode: str = "json_schema"
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fallback_to_rules: bool = True
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@property
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def use_openai(self) -> bool:
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if self.llm_provider == "openai":
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if not self.openai_api_key:
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raise ValueError("OPENAI_API_KEY is required when LLM provider is openai")
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return True
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if self.llm_provider == "rule":
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return False
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if self.llm_provider != "auto":
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raise ValueError("RESUME_AGENT_LLM_PROVIDER must be auto, openai, or rule")
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return bool(self.openai_api_key)
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def load_settings(env_file: str | Path | None = None) -> Settings:
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selected_file = Path(
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env_file or os.getenv("RESUME_AGENT_ENV_FILE", str(DEFAULT_ENV_FILE))
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)
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load_dotenv(selected_file, override=False)
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mode = os.getenv("OPENAI_STRUCTURED_OUTPUT_MODE", "json_schema").strip().lower()
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if mode not in {"json_schema", "json_object"}:
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raise ValueError(
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"OPENAI_STRUCTURED_OUTPUT_MODE must be json_schema or json_object"
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)
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provider = os.getenv("RESUME_AGENT_LLM_PROVIDER", "auto").strip().lower()
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settings = Settings(
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llm_provider=provider,
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openai_api_key=os.getenv("OPENAI_API_KEY") or None,
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openai_base_url=os.getenv("OPENAI_BASE_URL") or None,
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openai_model=os.getenv("OPENAI_MODEL", "gpt-4o-mini").strip(),
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openai_timeout_seconds=_as_float(
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"OPENAI_TIMEOUT_SECONDS", os.getenv("OPENAI_TIMEOUT_SECONDS"), 30.0
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),
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openai_max_retries=_as_int(
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"OPENAI_MAX_RETRIES", os.getenv("OPENAI_MAX_RETRIES"), 2
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),
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structured_output_retries=_as_int(
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"OPENAI_STRUCTURED_OUTPUT_RETRIES",
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os.getenv("OPENAI_STRUCTURED_OUTPUT_RETRIES"),
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1,
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),
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structured_output_mode=mode,
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fallback_to_rules=_as_bool(
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os.getenv("RESUME_AGENT_LLM_FALLBACK_TO_RULES"), True
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),
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)
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if not settings.openai_model:
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raise ValueError("OPENAI_MODEL cannot be blank")
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return settings
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