cfc/cfc-langgraph/app/config.py

from pydantic_settings import BaseSettings
from typing import Optional


class Settings(BaseSettings):
    # LLM
    llm_api_key: str
    llm_base_url: str = "https://api.deepseek.com/v1"
    llm_model: str = "deepseek-chat"
    # 部分模型(如 kimi-k2.6)仅允许 temperature=1，统一从配置读取便于切换模型时调整
    llm_temperature: float = 1.0

    # Embedding
    embedding_api_key: Optional[str] = None
    embedding_base_url: Optional[str] = None
    embedding_model: str = "text-embedding-v3"

    # Java Backend
    java_base_url: str = "http://localhost:9082"
    java_context_url: Optional[str] = None

    # LangSmith
    langchain_tracing_v2: bool = False
    langchain_api_key: Optional[str] = None
    langchain_project: str = "cfc-langgraph"

    # Service
    service_host: str = "0.0.0.0"
    service_port: int = 9000
    log_level: str = "info"

    # Dify Fallback
    dify_base_url: Optional[str] = None
    dify_tongue_api_key: Optional[str] = None

    # Chroma
    chroma_db_path: str = "./data/chroma_db"

    model_config = {"env_file": ".env", "env_file_encoding": "utf-8"}

    @property
    def effective_embedding_api_key(self) -> str:
        return self.embedding_api_key or self.llm_api_key

    @property
    def effective_embedding_base_url(self) -> str:
        return self.embedding_base_url or self.llm_base_url

    @property
    def effective_java_context_url(self) -> str:
        return self.java_context_url or f"{self.java_base_url}/api/ai/context"


settings = Settings()