"""Simple LLM helper for workbooks using Mirascope."""

import os
from typing import TypeVar

from mirascope.core import Messages, openai
from pydantic import BaseModel

T = TypeVar("T", bound=BaseModel)

# Configure from environment (defaults match .env.example)
_api_key = os.getenv("LLM_API_KEY", "")
_base_url = os.getenv("LLM_API_URL", "https://litellm-notrack.app.monadical.io")
_model = os.getenv("LLM_MODEL", "GLM-4.5-Air-FP8-dev")

if _api_key:
    os.environ["OPENAI_API_KEY"] = _api_key
if _base_url:
    base = _base_url.rstrip("/")
    os.environ["OPENAI_BASE_URL"] = base if base.endswith("/v1") else f"{base}/v1"


async def llm_call(
    prompt: str,
    response_model: type[T],
    system_prompt: str = "You are a helpful assistant.",
    model: str | None = None,
) -> T:
    """Make a structured LLM call.

    Args:
        prompt: The user prompt
        response_model: Pydantic model for structured output
        system_prompt: System instructions
        model: Override the default model

    Returns:
        Parsed response matching the response_model schema
    """
    use_model = model or _model

    @openai.call(model=use_model, response_model=response_model)
    async def _call(sys: str, usr: str) -> openai.OpenAIDynamicConfig:
        return {
            "messages": [
                Messages.System(sys),
                Messages.User(usr),
            ]
        }

    return await _call(system_prompt, prompt)