from datetime import datetime
from zoneinfo import ZoneInfo

import pytest

from llm_connect.models import LLMResponse
from llm_connect.usage import (
    UsageEvent,
    UsageLedger,
    default_usage_ledger_path,
    event_from_response,
    maybe_record_usage,
    suppress_auto_usage_record,
    week_window,
)


def test_default_ledger_path_env_and_xdg():
    assert default_usage_ledger_path(env={"LLM_CONNECT_USAGE_LEDGER": "/tmp/u.jsonl"}) == (
        __import__("pathlib").Path("/tmp/u.jsonl")
    )
    path = default_usage_ledger_path(env={"XDG_DATA_HOME": "/tmp/xdg"})
    assert path.as_posix().endswith("llm-connect/usage.jsonl")
    assert "xdg" in path.as_posix()


def test_usage_ledger_append_and_sum_range(tmp_path):
    ledger = UsageLedger(tmp_path / "usage.jsonl")
    berlin = ZoneInfo("Europe/Berlin")
    monday = datetime(2026, 8, 3, 10, 0, tzinfo=berlin)  # Monday
    sunday = datetime(2026, 8, 2, 12, 0, tzinfo=berlin)  # previous Sunday

    ledger.append(
        UsageEvent(
            provider="openrouter",
            model_id="moonshotai/kimi-k3",
            prompt_tokens=100,
            completion_tokens=50,
            total_tokens=150,
            cost_usd=0.001,
            cost_eur=0.00092,
            cost_source="rate_table:moonshotai/kimi-k3",
            fx_source="snapshot:2026-08-03",
            source="cli",
            recorded_at=monday,
        )
    )
    ledger.append(
        UsageEvent(
            provider="openrouter",
            model_id="moonshotai/kimi-k3",
            prompt_tokens=10,
            completion_tokens=5,
            total_tokens=15,
            cost_usd=0.0001,
            cost_eur=0.000092,
            cost_source="rate_table:moonshotai/kimi-k3",
            source="cli",
            recorded_at=sunday,
        )
    )

    start, end = week_window(
        "current",
        now=datetime(2026, 8, 5, 18, 0, tzinfo=berlin),
        tz="Europe/Berlin",
    )
    summary = ledger.sum_range(start, end)

    assert summary.event_count == 1
    assert summary.prompt_tokens == 100
    assert summary.total_tokens == 150
    assert summary.cost_eur == pytest.approx(0.00092)

    last_start, last_end = week_window(
        "last",
        now=datetime(2026, 8, 5, 18, 0, tzinfo=berlin),
        tz="Europe/Berlin",
    )
    last_summary = ledger.sum_range(last_start, last_end)
    assert last_summary.event_count == 1
    assert last_summary.total_tokens == 15


def test_week_window_current_and_last():
    berlin = ZoneInfo("Europe/Berlin")
    now = datetime(2026, 8, 5, 15, 30, tzinfo=berlin)  # Wednesday
    start, end = week_window("current", now=now, tz="Europe/Berlin")
    assert start.weekday() == 0
    assert start.hour == 0
    assert end == now

    last_start, last_end = week_window("last", now=now, tz="Europe/Berlin")
    assert (last_end - last_start).days == 7
    assert last_end == start


def test_event_from_response_estimates_kimi_cost():
    response = LLMResponse(
        content="hi",
        model="moonshotai/kimi-k3",
        usage={"prompt_tokens": 1000, "completion_tokens": 1000, "total_tokens": 2000},
    )
    event = event_from_response(response, provider="openrouter", source="cli", fx=1.0)

    assert event.cost_usd == pytest.approx(0.018)
    assert event.cost_eur == pytest.approx(0.018)
    assert event.cost_source == "rate_table:moonshotai/kimi-k3"


def test_maybe_record_usage_opt_in(tmp_path, monkeypatch):
    ledger = tmp_path / "usage.jsonl"
    monkeypatch.setenv("LLM_CONNECT_USAGE_LEDGER", str(ledger))
    response = LLMResponse(
        content="x",
        model="moonshotai/kimi-k3",
        usage={"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
        metadata={"provider": "openrouter"},
    )

    event = maybe_record_usage(response, provider="openrouter", source="library")
    assert event is not None
    assert ledger.is_file()
    assert UsageLedger(ledger).read_all()[0].source == "library"

    with suppress_auto_usage_record():
        assert maybe_record_usage(response, provider="openrouter", source="library") is None