"""Agent call logging — cost, performance, error tracking."""
import time
from contextlib import asynccontextmanager
from typing import AsyncIterator

from app.config import settings
from app.db import log_agent_call


@asynccontextmanager
async def logged_agent_call(
    agent_name: str,
    project_id: str | None = None,
    actor: str | None = None,
    request_id: str | None = None,
    model: str | None = None,
) -> AsyncIterator[dict]:
    """Context manager that logs agent call on exit."""
    start = time.monotonic()
    entry = {
        "agent_name": agent_name,
        "project_id": project_id or settings.default_project,
        "actor": actor,
        "request_id": request_id,
        "model": model or settings.llm_model,
        "prompt_chars": 0,
        "response_chars": 0,
        "latency_ms": 0,
        "status": "error",
        "error_message": None,
    }
    try:
        yield entry
        entry["status"] = "success"
    except Exception as exc:
        entry["status"] = "error"
        entry["error_message"] = str(exc)[:500]
    finally:
        entry["latency_ms"] = int((time.monotonic() - start) * 1000)
        try:
            await log_agent_call(entry)
        except Exception:
            pass