"""Model inference for the arena.

Two call shapes, both Ollama:

  • ``chat()`` — ``/api/chat`` with a system prompt + message history, used for
    DELIBERATE turns (conversational planning/critique). Returns text + a token
    estimate for the cost axis.
  • code generation reuses ``bench/completion.py`` (raw ``/api/generate``) so the
    IMPLEMENT phase gets a clean HumanEval/MBPP-style continuation, exactly like
    the capability benchmark.

Keeping inference here (not in ``cmd_chat``) honours the no-edit rule: the arena
drives its own inference and merely *posts* the result into the real room.
"""

from __future__ import annotations

from dataclasses import dataclass

import requests


@dataclass
class ChatReply:
    text: str
    ok: bool
    tokens: dict
    error: str | None = None


def _est_tokens(text: str) -> int:
    # cheap, deterministic estimate (~4 chars/token); real usage when Ollama
    # returns eval counts is preferred and used when present.
    return max(1, len(text) // 4)


def chat(model: str, system: str, messages: list[dict], *,
         host: str = "http://127.0.0.1:11434", temperature: float = 0.4,
         num_predict: int = 320, timeout: float = 120.0) -> ChatReply:
    """One chat turn. ``messages`` is a list of {role, content} (no system)."""
    payload = {
        "model": model, "stream": False,
        "messages": [{"role": "system", "content": system}, *messages],
        "options": {"temperature": temperature, "num_predict": num_predict},
    }
    try:
        r = requests.post(f"{host}/api/chat", json=payload, timeout=timeout)
        r.raise_for_status()
        data = r.json()
    except Exception as e:  # noqa: BLE001 — surface as a failed turn
        return ChatReply("", False, {"in": 0, "out": 0}, str(e))
    text = data.get("message", {}).get("content", "")
    tok = {"in": data.get("prompt_eval_count") or _est_tokens(system +
              "".join(m["content"] for m in messages)),
           "out": data.get("eval_count") or _est_tokens(text)}
    return ChatReply(text.strip(), True, tok)