from __future__ import annotations

import os
from dataclasses import dataclass
from pathlib import Path

from dotenv import load_dotenv


ROOT_DIR = Path(__file__).resolve().parents[2]
load_dotenv(ROOT_DIR.parent / ".env")
load_dotenv(ROOT_DIR / ".env")


def _bool(name: str, default: bool = False) -> bool:
    value = os.getenv(name)
    if value is None:
        return default
    return value.strip().lower() in {"1", "true", "yes", "on"}


@dataclass(frozen=True)
class Settings:
    app_env: str = os.getenv("APP_ENV", "development")
    workspace_id: str = os.getenv("WORKSPACE_ID", "local-workspace")
    data_dir: Path = Path(os.getenv("DATA_DIR", str(ROOT_DIR / "data")))
    demo_fallback: bool = _bool("DEMO_FALLBACK", True)
    llm_base_url: str = os.getenv("LLM_BASE_URL", "https://api.openai.com/v1").rstrip("/")
    llm_api_key: str = os.getenv("LLM_API_KEY", "")
    llm_model: str = os.getenv("LLM_MODEL", "gpt-4o-mini")
    embedding_base_url: str = os.getenv("EMBEDDING_BASE_URL", "https://api.openai.com/v1").rstrip("/")
    embedding_api_key: str = os.getenv("EMBEDDING_API_KEY", "")
    embedding_model: str = os.getenv("EMBEDDING_MODEL", "text-embedding-3-small")
    embedding_dimensions: int = int(os.getenv("EMBEDDING_DIMENSIONS", "1536"))
    embedding_min_score: float = float(os.getenv("EMBEDDING_MIN_SCORE", "0.35"))
    database_url: str = os.getenv(
        "DATABASE_URL",
        "postgresql://memory:memory@localhost:54329/memory_agents",
    )
    redis_url: str = os.getenv("REDIS_URL", "redis://localhost:6379/0")
    letta_base_url: str = os.getenv("LETTA_BASE_URL", "http://localhost:8283").rstrip("/")
    letta_api_key: str = os.getenv("LETTA_API_KEY", "")
    letta_enabled: bool = _bool("LETTA_ENABLED")
    mem0_enabled: bool = _bool("MEM0_ENABLED")
    reme_enabled: bool = _bool("REME_ENABLED")
    memu_enabled: bool = _bool("MEMU_ENABLED")


settings = Settings()
if not 0.0 <= settings.embedding_min_score <= 1.0:
    raise ValueError("EMBEDDING_MIN_SCORE 必须在 0 到 1 之间")
settings.data_dir.mkdir(parents=True, exist_ok=True)

# Some optional SDKs, especially Mem0's default local client, look for the
# conventional OpenAI environment names. Keep the project-facing configuration
# unified while making those SDKs inherit the same OpenAI-compatible endpoint.
if settings.llm_api_key:
    os.environ.setdefault("OPENAI_API_KEY", settings.llm_api_key)
    os.environ.setdefault("DEEPSEEK_API_KEY", settings.llm_api_key)
if settings.llm_base_url:
    os.environ.setdefault("OPENAI_BASE_URL", settings.llm_base_url)
    os.environ.setdefault("OPENAI_API_BASE", settings.llm_base_url)
    os.environ.setdefault("LLM_BACKEND", "openai")
    os.environ.setdefault("LLM_API_KEY", settings.llm_api_key)
    os.environ.setdefault("LLM_BASE_URL", settings.llm_base_url)
    os.environ.setdefault("LLM_MODEL_NAME", settings.llm_model)