ZNJJ-api-server/src/core/config.py

import os
from dotenv import load_dotenv

load_dotenv()

class Config:
    PROJECT_NAME = "Flexible Employment Analysis API"
    API_V1_STR = "/api/v1"
    SECRET_KEY = os.getenv("SECRET_KEY", "your-secret-key")
    DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///./test.db")
    DEBUG = os.getenv("DEBUG", "false").lower() in ("true", "1", "t")
    
    # FastGPT Configuration
    FASTGPT_API_KEY = os.getenv("ANALYSIS_AUTH_TOKEN")
    FASTGPT_BASE_URL = os.getenv("ANALYSIS_SERVICE_URL")
    FASTGPT_APP_ID = os.getenv("APP_ID")
    
    # Chat backend switch（作业 2）
    # "fastgpt" 保持现有行为；"langgraph" 使用内存图 fake 回复。
    AGENT_BACKEND = os.getenv("AGENT_BACKEND", "fastgpt")

    # LLM provider（作业 4）：fake 为脚本化假模型，离线可运行；
    # openai 为真实 provider（OpenAI 兼容接口）。
    AGENT_LLM_PROVIDER = os.getenv("AGENT_LLM_PROVIDER", "fake")
    LLM_MODEL = os.getenv("LLM_MODEL", "fake-reply-model")
    LLM_BASE_URL = os.getenv("LLM_BASE_URL", "")
    LLM_API_KEY = os.getenv("LLM_API_KEY", "")
    LLM_TIMEOUT_SECONDS = float(os.getenv("LLM_TIMEOUT_SECONDS", "30"))
    LLM_MAX_RETRIES = int(os.getenv("LLM_MAX_RETRIES", "2"))
    
    @classmethod
    def validate(cls):
        """Validate required configuration."""
        # TODO(作业 2): 语音管线仍依赖 FastGPT。当前仅按文本后端开关校验；
        # 接入语音开关后，需要单独校验语音路径所需配置。
        if cls.AGENT_BACKEND not in ("fastgpt", "langgraph"):
            raise ValueError(
                f"AGENT_BACKEND must be 'fastgpt' or 'langgraph', got {cls.AGENT_BACKEND!r}"
            )
        if cls.AGENT_LLM_PROVIDER not in ("fake", "openai"):
            raise ValueError(
                "AGENT_LLM_PROVIDER must be 'fake' or 'openai', "
                f"got {cls.AGENT_LLM_PROVIDER!r}"
            )
        if cls.AGENT_LLM_PROVIDER == "openai" and (
            not cls.LLM_API_KEY or not cls.LLM_BASE_URL
        ):
            raise ValueError(
                "AGENT_LLM_PROVIDER=openai requires LLM_API_KEY and LLM_BASE_URL"
            )
        if cls.AGENT_BACKEND != "fastgpt":
            return
        required = [
            ("FASTGPT_BASE_URL (ANALYSIS_SERVICE_URL)", cls.FASTGPT_BASE_URL),
            ("FASTGPT_API_KEY (ANALYSIS_AUTH_TOKEN)", cls.FASTGPT_API_KEY),
            ("FASTGPT_APP_ID (APP_ID)", cls.FASTGPT_APP_ID),
        ]
        missing = [name for name, value in required if not value]
        if missing:
            raise ValueError(f"Missing required environment variables: {', '.join(missing)}")