import os
from pydantic_settings import BaseSettings

class Settings(BaseSettings):
    # App
    APP_TITLE: str = "LightRAG Knowledge Base API"
    APP_VERSION: str = "1.0"
    HOST: str = "0.0.0.0"
    PORT: int = 9600

    # Data
    DATA_DIR: str = "./index_data"

    # LLM (Text) - vLLM
    LLM_BINDING: str = "vllm" # ollama, vllm, openai
    LLM_BINDING_HOST: str = "http://192.168.6.115:8002/v1" # vLLM OpenAI API base
    LLM_MODEL: str = "qwen2.5-7b-awq"
    LLM_KEY: str = "EMPTY" # vLLM default key

    # LLM (Vision) - vLLM
    VL_BINDING_HOST: str = "http://192.168.6.115:8001/v1"
    VL_MODEL: str = "qwen2.5-vl-3b-awq"
    VL_KEY: str = "EMPTY"
    
    # Embedding - TEI
    EMBEDDING_BINDING: str = "tei" # ollama, tei, openai
    EMBEDDING_BINDING_HOST: str = "http://192.168.6.115:8003" # TEI usually exposes /embed
    EMBEDDING_MODEL: str = "BAAI/bge-m3" # model id in TEI
    EMBEDDING_KEY: str = "EMPTY"
    
    # Rerank - TEI
    RERANK_ENABLED: bool = True
    RERANK_BINDING_HOST: str = "http://192.168.6.115:8004"
    RERANK_MODEL: str = "BAAI/bge-reranker-v2-m3"
    RERANK_KEY: str = "EMPTY"
    
    # RAG Config
    EMBEDDING_DIM: int = 1024
    MAX_TOKEN_SIZE: int = 8192
    MAX_RAG_INSTANCES: int = 3  # 最大活跃 RAG 实例数
    
    class Config:
        env_file = ".env"
        env_file_encoding = 'utf-8'
        extra = "ignore"  # 忽略多余的环境变量

settings = Settings()