from __future__ import annotations

import os
from functools import lru_cache
from pathlib import Path
from typing import Any, Literal

import yaml
from pydantic import BaseModel

Provider = Literal["openai", "anthropic"]
DEFAULT_CONFIG_PATHS = ["config.yml", "config.yaml", "/config/config.yml", "/config/config.yaml"]


class LLMSettings(BaseModel):
    provider: Provider = "openai"
    api_key: str = "none"
    model: str = "qwen2.5-7b-instruct.q4_k_m"
    base_url: str = "http://ollama.internal.henryhosted.com:9292/v1"
    temperature: float = 0.1
    timeout_seconds: float = 60
    max_retries: int = 3


def _load_yaml_config() -> dict[str, Any]:
    explicit = os.getenv("EMAIL_CLASSIFIER_CONFIG") or os.getenv("APP_CONFIG_FILE")
    candidates = [explicit] if explicit else DEFAULT_CONFIG_PATHS
    for candidate in candidates:
        if not candidate:
            continue
        path = Path(candidate)
        if not path.exists() or not path.is_file():
            continue
        data = yaml.safe_load(path.read_text()) or {}
        if not isinstance(data, dict):
            raise ValueError(f"Config file must contain a mapping/object: {path}")
        llm = data.get("llm", data)
        if not isinstance(llm, dict):
            raise ValueError(f"LLM config must be a mapping/object: {path}")
        return llm
    return {}


def _env_or_yaml(env_name: str, yaml_data: dict[str, Any], yaml_key: str, default: Any) -> Any:
    value = os.getenv(env_name)
    if value is not None:
        return value
    if yaml_key in yaml_data and yaml_data[yaml_key] is not None:
        return yaml_data[yaml_key]
    return default


@lru_cache(maxsize=1)
def get_settings() -> LLMSettings:
    yaml_data = _load_yaml_config()
    return LLMSettings(
        provider=_env_or_yaml("LLM_PROVIDER", yaml_data, "provider", "openai"),
        api_key=_env_or_yaml("LLM_API_KEY", yaml_data, "api_key", "none"),
        model=_env_or_yaml("LLM_MODEL", yaml_data, "model", "qwen2.5-7b-instruct.q4_k_m"),
        base_url=_env_or_yaml("LLM_BASE_URL", yaml_data, "base_url", "http://ollama.internal.henryhosted.com:9292/v1"),
        temperature=float(_env_or_yaml("LLM_TEMPERATURE", yaml_data, "temperature", 0.1)),
        timeout_seconds=float(_env_or_yaml("LLM_TIMEOUT_SECONDS", yaml_data, "timeout_seconds", 60)),
        max_retries=int(_env_or_yaml("LLM_MAX_RETRIES", yaml_data, "max_retries", 3)),
    )


def get_request_settings(
    provider: str | None = None,
    model: str | None = None,
    base_url: str | None = None,
    api_key: str | None = None,
    temperature: float | None = None,
) -> LLMSettings:
    base = get_settings()
    data = base.model_dump()
    if provider is not None:
        data["provider"] = provider
    if model is not None:
        data["model"] = model
    if base_url is not None:
        data["base_url"] = base_url
    if api_key is not None:
        data["api_key"] = api_key
    if temperature is not None:
        data["temperature"] = temperature
    return LLMSettings(**data)