"""LM Studio model integration for Trifecta-Bro.

Model id: Brettapps/trifecta-bro/v1

This module is the bridge between Trifecta-Bro and LM Studio's `lms` server
(OpenAI-compatible API on http://localhost:1234/v1). It is installed here now;
the Obsidian-vault backend wiring is added later once the model weights / prompt
pipeline are ready.

Responsibilities today:
  - Resolve the LM Studio server base URL.
  - Expose `Brettapps/trifecta-bro/v1` as the canonical model identifier.
  - Provide a health check so the rest of the app can detect when the model
    is unavailable and fall back to the open-source `TrifectaPredictor`.

Responsibilities later (vault backend):
  - Load the *Fields & Form* note from the Obsidian vault.
  - Build the Hermes trifecta prompt.
  - Call the LM Studio model and parse the response back into predictions.
"""

from __future__ import annotations

import os
import urllib.request
from dataclasses import dataclass

# Canonical model identifier used by Trifecta-Bro against LM Studio.
MODEL_ID = "Brettapps/trifecta-bro/v1"

# LM Studio serves an OpenAI-compatible API by default on this port.
DEFAULT_LMSTUDIO_BASE_URL = "http://localhost:1234/v1"

# The `lms` server only accepts a chat/completions call for a model that is
# loaded. We expose the id here so the server can be primed with:
#     lms load Brettapps/trifecta-bro/v1
# (or by importing the GGUF into LM Studio's model library).


@dataclass
class LMStudioStatus:
    reachable: bool
    base_url: str
    model_id: str
    detail: str = ""


def resolve_base_url() -> str:
    """Return the LM Studio base URL, allowing override via env."""
    return os.environ.get("LMSTUDIO_BASE_URL", DEFAULT_LMSTUDIO_BASE_URL).rstrip("/")


def get_model_id() -> str:
    """Canonical model identifier for Trifecta-Bro v1."""
    return MODEL_ID


def health_check(base_url: str | None = None, timeout: float = 3.0) -> LMStudioStatus:
    """Check whether the LM Studio server is up and lists our model.

    This is a lightweight probe of the /v1/models endpoint. It does not require
    the model to be loaded to report reachability.
    """
    url = (base_url or resolve_base_url()) + "/models"
    try:
        req = urllib.request.Request(url, headers={"Accept": "application/json"})
        with urllib.request.urlopen(req, timeout=timeout) as resp:
            body = resp.read().decode("utf-8", "ignore")
        reachable = resp.status == 200  # type: ignore[attr-defined]
        detail = "ok" if reachable else f"status {getattr(resp, 'status', '?')}"
        # Peek whether our model id is present (non-fatal if not).
        if reachable and MODEL_ID not in body:
            detail = "server up; model not loaded"
        return LMStudioStatus(
            reachable=reachable,
            base_url=(base_url or resolve_base_url()),
            model_id=MODEL_ID,
            detail=detail,
        )
    except Exception as exc:  # noqa: BLE001 - network probe, report failure
        return LMStudioStatus(
            reachable=False,
            base_url=(base_url or resolve_base_url()),
            model_id=MODEL_ID,
            detail=str(exc) or "unreachable",
        )