"""Tests for the Textual monitoring dashboard (tui.py).

Offline, no real router / network. The data layer (``build_model`` and
``fetch_metrics``) is importable without a running TUI, so nearly all
assertions are on the rendered panel PAYLOADS (plain dicts of display rows),
not on pixels. ``App.run_test`` drives the app itself with a stubbed fetcher.

This file imports ``tui`` and ``textual`` deliberately — it is the ONE test
file that may. No non-tui module imports textual.
"""
from __future__ import annotations

import asyncio
import copy
import time
from datetime import datetime

import pytest
import requests
from textual.widgets import DataTable, ProgressBar, Static

import tui
import tui_model
from tui_model import build_model, fetch_metrics
from tui_screens import DecisionDetailScreen, VerdictMixScreen


def _fixture() -> dict:
    """A representative /admin/api/snapshot payload (quota_accounts shape)."""
    return {
        "quota": {
            "period": {
                "start": "2026-07-26",
                "next_reset": "2026-08-26",
                "elapsed_fraction": 0.5,
                "source": "billing_reset_day",
            },
            "accounts": [
                {
                    "provider": "neuralwatt",
                    "shape": "metered_plan",
                    "spend_usd": {"period": 1.25, "attribution_coverage": 1.0},
                    "plan": {"kwh_per_period": 6.25, "used_kwh": 1.25, "used_fraction": 0.2},
                    "pool": None,
                    "burn": {
                        "burn_rate_usd_per_hour": 1.0,
                        "projected_hours_remaining": 8.5,
                    },
                    "credit": {
                        "balance_usd": 8.50,
                        "balance_at": "2026-08-23T09:58:00+00:00",
                        "balance_source": "telemetry",
                    },
                    "energy": {"kwh_30d": 1.25, "calls_30d": 18},
                }
            ],
            "spend": {
                "by_provider_usd": {"neuralwatt": 1.25},
                "total_usd": 1.25,
                "estimated_usd": 0.0,
                "estimate_ratio": None,
            },
            "alarm": {
                "kind": "none",
                "severity": "info",
                "headline": "$1.25 period spend",
            },
        },
        "coverage": {
            "routable_models": 13,
            "with_energy_data": 10,
            "with_proficiency_data": 12,
            "quota": {
                "plan_kwh": 6.25,
                "metered_kwh_30d": 1.25,
                "metered_fraction_of_plan": 0.2,
                "metered_calls_30d": 18,
                "reset_date": "2026-07-26",
                "note": "router-metered only",
                "total_balance_usd": 8.50,
                "by_provider": {
                    "neuralwatt": {
                        "balance_usd": 8.50,
                        "balance_at": "2026-08-23T09:58:00+00:00",
                        "balance_source": "telemetry",
                        "burn_window_hours": 24,
                        "burn_rate_usd_per_hour": 1.0,
                        "projected_hours_remaining": 8.5,
                        "runway_low_warning": False,
                        "runway_note": None,
                    }
                },
                "window_start_30d": "2026-07-24",
                "metered_kwh_period": 0.5,
            },
            "warnings": [
                "3/13 routable models have no reference-workload observations",
                "1/13 routable models have no proficiency data",
            ],
            "flex_default": "auto",
        },
        "recent_decisions": [
            {
                "id": 42,
                "observed_at": "2026-08-23T10:00:00+00:00",
                "kind": "chat",
                "task_category": "coding_general",
                "task_tier": 2,
                "selected_model": "deepseek-v4-flash",
                "selected_provider": "neuralwatt",
                "est_cost_usd": 0.00016,
                "flex_preference": "force-flex",
                "flex_swapped": 1,
                "flex_forced": 1,
            },
            {
                "id": 41,
                "observed_at": "2026-08-23T09:59:00+00:00",
                "kind": "route",
                "task_category": "docs_writing",
                "task_tier": 3,
                "selected_model": "kimi-k2.7-code",
                "selected_provider": "neuralwatt",
                "est_cost_usd": 0.0136,
                "flex_preference": "auto",
                "flex_swapped": 0,
                "flex_forced": 0,
            },
            {
                "id": 40,
                "observed_at": "2026-08-23T09:58:00+00:00",
                "kind": "chat",
                "task_category": "debugging",
                "task_tier": 1,
                "selected_model": None,
                "selected_provider": None,
                "est_cost_usd": None,
            },
        ],
        "per_model": [
            {
                "model_id": "deepseek-v4-flash",
                "provider": "neuralwatt",
                "calls": 12,
                "sum_cost_usd": 0.0012,
                "sum_energy_kwh": 2.5e-05,
                "sum_carbon_g_co2eq": 1.2e-04,
            },
            {
                "model_id": "kimi-k3",
                "provider": "neuralwatt",
                "calls": 4,
                "sum_cost_usd": 0.08,
                "sum_energy_kwh": 1.0e-03,
                "sum_carbon_g_co2eq": 3.0e-03,
            },
            {
                "model_id": "null-energy-model",
                "provider": "openrouter",
                "calls": 5,
                "sum_cost_usd": None,
                "sum_energy_kwh": None,
                "sum_carbon_g_co2eq": None,
            },
        ],
        "verdict_mix": {"ok": 5, "unverifiable": 2, "truncated": 1},
        "top_proficiency": [
            {"model_id": "deepseek-v4-flash", "provider": "neuralwatt",
             "blended_score": 1.0, "source": "self_eval_thin",
             "self_eval_samples": 3}
        ],
        "pinch": {
            "calls_30d": 120,
            "pruned_calls_30d": 30,
            "share_pruned": 0.25,
            "total_tokens_saved": 50000,
            "median_tokens_saved": 1200,
            "dollars_saved_usd_30d": 0.0125,
        },
        "generated_at": "2026-08-23T10:01:00+00:00",
    }


def _enriched_payload() -> dict:
    """A deep copy of _fixture() whose recent_decisions rows carry the six
    T2 data-layer fields, mirroring what /metrics returns after the drift
    catch-up. Row 42 is the popup test's target row (exploration off);
    row 41 is the exploratory pick; row 40 stays a rejection row."""
    data = copy.deepcopy(_fixture())
    enrichments = [
        {
            "profile": "default",
            "exploration": 0,
            "request_id": "chatcmpl-fixture-42",
            "pinch_original_tokens": 120000,
            "pinch_final_tokens": 96122,
            "session_key": "sess-42",
            "observed_at": "2026-08-23T10:00:00+00:00",
        },
        {
            "profile": "default",
            "exploration": 1,
            "request_id": "chatcmpl-fixture-41",
            "pinch_original_tokens": 90000,
            "pinch_final_tokens": 87500,
            "session_key": "sess-41",
            "observed_at": "2026-08-23T09:59:00+00:00",
        },
        {
            "profile": "default",
            "exploration": 0,
            "request_id": None,
            "pinch_original_tokens": None,
            "pinch_final_tokens": None,
            "session_key": "sess-40",
            "observed_at": "2026-08-23T09:58:00+00:00",
        },
    ]
    for row, extra in zip(data["recent_decisions"], enrichments):
        row.update(extra)
    return data


# --------------------------------------------------------------------------
# Direct unit tests of the data layer (no TUI running).
# --------------------------------------------------------------------------


def test_build_model_quota_panel():
    m = build_model(_fixture())
    rows = m["quota"]
    # Plan info is surfaced via per-account rows
    joined = " ".join(r["label"] + "=" + str(r["value"]) for r in rows)
    assert "period_start=2026-07-26" in joined
    assert "next_reset=2026-08-26" in joined
    assert "spend_total_usd=1.25" in joined
    assert "neuralwatt plan_kwh_per_period=6.25" in joined
    assert "neuralwatt used_kwh=1.25" in joined
    assert "neuralwatt used_fraction=0.2" in joined
    assert "neuralwatt calls_30d=18" in joined


def test_build_model_pinch_panel():
    m = build_model(_fixture())
    rows = m["pinch"]
    by_label = {r["label"]: r["value"] for r in rows}
    assert by_label["share_pruned"] == 0.25
    assert by_label["total_tokens_saved"] == 50000
    assert by_label["median_tokens_saved"] == 1200
    assert by_label["dollars_saved_usd_30d"] == 0.0125


def test_build_model_pinch_panel_empty_when_none():
    data = _fixture()
    data["pinch"] = None
    m = build_model(data)
    assert m["pinch"] == []


def test_build_model_quota_panel_includes_period_and_spend():
    m = build_model(_fixture())
    rows = m["quota"]
    by_label = {r["label"]: r["value"] for r in rows}
    assert by_label["period_start"] == "2026-07-26"
    assert by_label["next_reset"] == "2026-08-26"
    assert by_label["spend_total_usd"] == 1.25


def test_build_model_quota_panel_includes_provider_rows():
    """The per-provider quota shape reaches the TUI data model."""
    m = build_model(_fixture())
    rows = m["quota"]
    by_label = {r["label"]: r["value"] for r in rows}
    assert by_label["neuralwatt shape"] == "metered_plan"
    assert by_label["neuralwatt plan_kwh_per_period"] == 6.25
    assert by_label["neuralwatt used_kwh"] == 1.25
    assert by_label["neuralwatt used_fraction"] == 0.2
    assert by_label["neuralwatt burn_rate_usd_per_hour"] == 1.0
    assert by_label["neuralwatt projected_hours_remaining"] == 8.5


def test_build_model_quota_panel_drops_flat_balance_keys():
    """Old flat balance keys must not leak into the TUI row list."""
    m = build_model(_fixture())
    labels = {r["label"] for r in m["quota"]}
    assert "balance_usd" not in labels
    assert "burn_rate_usd_per_hour" not in labels
    assert "total_balance_usd" not in labels


def test_build_model_per_model_lists_seeded_models():
    m = build_model(_fixture())
    rows = m["per_model"]
    assert rows[0]["model"] == "deepseek-v4-flash"
    assert rows[0]["calls"] == 12
    assert rows[1]["model"] == "kimi-k3"
    # every row keeps numeric cost/energy/carbon for display
    assert rows[0]["cost_usd"] == 0.0012
    assert rows[0]["energy_kwh"] == 2.5e-05
    assert rows[0]["carbon_g_co2eq"] == 1.2e-04


def test_build_model_per_model_handles_null_energy():
    """A per-model row with all-NULL cost/energy/carbon must not crash and
    must preserve the None values for the rendering layer."""
    m = build_model(_fixture())
    rows = m["per_model"]
    null_row = [r for r in rows if r["model"] == "null-energy-model"]
    assert len(null_row) == 1
    nr = null_row[0]
    assert nr["cost_usd"] is None
    assert nr["energy_kwh"] is None
    assert nr["carbon_g_co2eq"] is None


def test_build_model_verdict_mix():
    m = build_model(_fixture())
    mix = m["verdict_mix"]
    by_verdict = {r["verdict"]: r["count"] for r in mix}
    assert by_verdict == {"ok": 5, "unverifiable": 2, "truncated": 1}


def test_build_model_recent_decisions_top_rows():
    m = build_model(_fixture())
    rows = m["recent_decisions"]
    # DESC by id: first row is id 42
    assert rows[0]["id"] == 42
    assert rows[0]["kind"] == "chat"
    assert rows[0]["category"] == "coding_general"
    assert rows[0]["tier"] == 2
    assert rows[0]["selected"] == "deepseek-v4-flash"
    assert rows[1]["kind"] == "route"
    assert rows[2]["selected"] == "none"  # no-candidate row renders "none"


def test_build_model_warnings_from_coverage():
    m = build_model(_fixture())
    warnings = m["warnings"]
    assert len(warnings) == 2
    assert "reference-workload" in warnings[0]
    assert "proficiency data" in warnings[1]


def test_build_model_handles_missing_quota():
    """Empty DB / null plan: the quota section is an empty list (renderer hides it)."""
    data = _fixture()
    data["quota"] = None
    data["coverage"]["quota"] = None
    m = build_model(data)
    assert m["quota"] == []


def test_fetch_metrics_returns_parsed_dict(monkeypatch):
    """fetch_metrics hits the right URL and returns parsed JSON."""
    captured = {}

    class _FakeResp:
        def raise_for_status(self):
            return None

        def json(self):
            return {"quota": None, "ok": True}

    def _fake_get(url, timeout=None):
        captured["url"] = url
        captured["timeout"] = timeout
        return _FakeResp()

    monkeypatch.setattr(tui_model.requests, "get", _fake_get)
    out = fetch_metrics("http://testhost:8081")
    assert out == {"quota": None, "ok": True}
    assert captured["url"] == "http://testhost:8081/metrics"


def test_fetch_metrics_raises_on_http_error(monkeypatch):
    class _Err:
        def raise_for_status(self):
            raise RuntimeError("500")

    monkeypatch.setattr(tui_model.requests, "get", lambda *a, **k: _Err())
    with pytest.raises(Exception):
        fetch_metrics("http://x")


def test_fetch_metrics_raises_on_network_error(monkeypatch):
    def _boom(*a, **k):
        raise ConnectionError("refused")

    monkeypatch.setattr(tui_model.requests, "get", _boom)
    with pytest.raises(ConnectionError):
        fetch_metrics("http://x")


# --------------------------------------------------------------------------
# App-level tests via App.run_test with a stubbed fetch_metrics.
# --------------------------------------------------------------------------


class _StubFetcher:
    """Swappable fake for fetch_metrics the App calls."""

    def __init__(self):
        self.payload = None
        self.error = None
        self.calls = 0

    def __call__(self, base_url):
        self.calls += 1
        if self.error is not None:
            raise self.error
        return self.payload


@pytest.mark.parametrize("fetcher_arg", ["callable", "subclass"])
def test_app_run_test_populates_quota_and_model_panels(fetcher_arg):
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        stash = getattr(a, "_last_model", None)
        assert stash is not None, "build_model result was not stashed on the app"
        # quota plan number surfaced
        quota_text = " ".join(
            f"{r['label']}={r['value']}" for r in stash["quota"]
        )
        assert "neuralwatt plan_kwh_per_period=6.25" in quota_text
        # per-model lists the seeded models
        models = {r["model"] for r in stash["per_model"]}
        assert {"deepseek-v4-flash", "kimi-k3"} <= models
        assert stub.calls == 1

    _run_app(app, _assert)


def test_app_run_test_recent_and_warnings_panels():
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        stash = a._last_model
        assert stash["recent_decisions"][0]["selected"] == "deepseek-v4-flash"
        assert len(stash["warnings"]) == 2

    _run_app(app, _assert)


def test_app_run_test_duplicate_model_keys_do_not_crash():
    """Duplicate model ids in the /metrics per_model payload must not raise
    DuplicateKeyError when rendered into #model-table. The source may be a
    poller/anomaly, so the TUI dedups defensively."""
    stub = _StubFetcher()
    payload = _fixture()
    payload["per_model"].append(dict(payload["per_model"][0], calls=99))
    stub.payload = payload

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        mt = a.query_one("#model-table")
        assert mt.row_count == 3, (
            f"expected 3 deduped rows, got {mt.row_count}"
        )
        assert len(payload["per_model"]) == 4
        assert len(a._last_model["per_model"]) == 4

    _run_app(app, _assert)


def test_app_run_test_null_energy_row_renders_safely():
    """A per-model row with NULL cost/energy/carbon must render as
    'n/a' for cost and em-dash for energy/carbon without crashing."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        mt = a.query_one("#model-table", DataTable)
        # Find the null-energy-model row by scanning model names (col 0)
        null_row_idx = None
        for idx in range(mt.row_count):
            cell = mt.get_cell_at((idx, 0))
            if "null-energy-model" in str(cell):
                null_row_idx = idx
                break
        assert null_row_idx is not None, "null-energy-model row not found"
        cost_cell = str(mt.get_cell_at((null_row_idx, 2)))
        kwh_cell = str(mt.get_cell_at((null_row_idx, 3)))
        co2_cell = str(mt.get_cell_at((null_row_idx, 4)))
        assert "n/a" in cost_cell, f"expected n/a for cost, got {cost_cell}"
        assert "\u2014" in kwh_cell, f"expected em-dash for kWh, got {kwh_cell}"
        assert "\u2014" in co2_cell, f"expected em-dash for gCO2eq, got {co2_cell}"

    _run_app(app, _assert)


def test_app_run_test_quota_panel_progress_bar_and_legend():
    """The quota panel renders a ProgressBar and a legend carrying the plan.

    ``#quota-panel`` is a container holding a ``ProgressBar``
    (``#quota-progress``) and a ``Static`` legend (``#quota-legend``). The bar
    is filled to the metered kWh against the plan kWh total, and the legend
    shows the metered / plan / fraction / calls summary.
    """
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        container = a.query_one("#quota-panel")
        assert container is not None

        bar = a.query_one("#quota-progress", ProgressBar)
        assert bar.progress == 1.25
        assert bar.total == 6.25

        legend = a.query_one("#quota-legend", Static)
        text = str(legend.content)
        assert "6.25" in text
        assert "1.25" in text
        assert "period since 2026-07-26" in text

    _run_app(app, _assert)


def test_format_quota_legend_omits_none_when_unmetered():
    """With unmetered (None) values the legend never shows the literal "None".

    The ``metered``/``frac`` rows can be absent (None) for a plan
    that has not been metered yet; they must render as ``n/a`` and the
    returned string must not contain the substring ``"None"``.
    """
    app = tui.DashboardApp(fetcher=_StubFetcher())
    legend = app._format_quota_legend(
        plan=6.25, metered=None, frac=None,
        flex_default=None,
    )
    assert "None" not in legend
    assert "n/a" in legend


def test_format_quota_legend_happy_path_contains_numbers():
    """A fully-populated legend carries the metered / plan values."""
    app = tui.DashboardApp(fetcher=_StubFetcher())
    legend = app._format_quota_legend(
        plan=6.25, metered=1.25, frac=0.2,
    )
    assert "6.25" in legend
    assert "1.25" in legend
    assert "20%" in legend
    assert "None" not in legend


def test_format_quota_legend_distinguishes_period_from_window():
    """The legend shows metered vs plan — period and window labels are
    now appended in _render, not inside _format_quota_legend."""
    app = tui.DashboardApp(fetcher=_StubFetcher())
    legend = app._format_quota_legend(
        plan=6.25, metered=1.25, frac=0.2,
    )
    assert "6.25" in legend
    assert "1.25" in legend
    assert "None" not in legend


def test_format_quota_legend_shows_flex_default():
    """The configured flex default is surfaced in the quota legend readout."""
    app = tui.DashboardApp(fetcher=_StubFetcher())
    legend = app._format_quota_legend(
        plan=6.25, metered=1.25, frac=0.2, flex_default="auto",
    )
    assert "flex default auto" in legend


def test_format_quota_legend_omits_flex_when_absent():
    """No flex default in the payload -> the legend does not claim one."""
    app = tui.DashboardApp(fetcher=_StubFetcher())
    legend = app._format_quota_legend(
        plan=6.25, metered=1.25, frac=0.2,
    )
    assert "flex default" not in legend


def test_app_run_test_quota_bar_hidden_when_plan_unconfigured():
    """No plan configured -> the ProgressBar is hidden (display False).

    The bar is not removed from the DOM; its ``display`` is toggled so the
    "quota not configured" legend still shows and the widget state is kept
    for when a plan is later configured.
    """
    stub = _StubFetcher()
    data = _fixture()
    data["quota"]["accounts"] = []  # no metered_plan account → bar hidden
    data["coverage"] = {"quota": None, "warnings": [], "flex_default": None}
    stub.payload = data

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        bar = a.query_one("#quota-progress", ProgressBar)
        assert bar.display is False, "bar should be hidden when plan unconfigured"

        legend = a.query_one("#quota-legend", Static)
        assert "quota not configured" in str(legend.content)

    _run_app(app, _assert)


def test_app_run_test_failure_shows_error_and_does_not_crash():
    """fetch raising -> error panel visible, run_test completes without raising."""
    stub = _StubFetcher()
    stub.error = ConnectionError("cannot reach router")

    app = tui.DashboardApp(fetcher=stub, base_url="http://127.0.0.1:8080")

    def _assert(a):
        error_widget = a.query_one("#error-panel")
        assert "cannot reach router" in str(error_widget.content)
        assert a._last_error is not None

    _run_app(app, _assert)  # must not raise


def test_app_run_test_decision_table_focused_on_mount():
    """#decision-table is focused by default after the app mounts."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            table = app.query_one("#decision-table")
            assert table.has_focus, "#decision-table should have focus on mount"

    asyncio.run(_go())


def _run_app(app: tui.DashboardApp, body) -> None:
    """Drive the app via Textual App.run_test synchronously.

    ``body(app)`` runs while the app is mounted, so queries and the data
    model are live. Assertion failures inside propagate out of ``asyncio.run``
    as normal test failures.
    """
    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            body(app)

    asyncio.run(_go())


# --------------------------------------------------------------------------
# Auto-refresh, error resilience and keyboard controls.
#
# These drive the app through App.run_test with a tiny REFRESH_SECONDS and no
# real wall-clock sleep. Textual 8.2.8 schedules set_interval timers on the
# asyncio event loop, so repeatedly awaiting ``pilot.pause()`` lets due ticks
# fire without the test asserting on elapsed time or calling time.sleep().
# Assertions are on the re-rendered panel payload (``app._last_model``), not
# on mock-call counts.
# --------------------------------------------------------------------------


class _CountingFetcher:
    """Hands back a metrics payload whose first per-model call count equals
    the invocation number, so each fetch produces a distinct, inspectable
    payload with no script to exhaust."""

    def __init__(self):
        self.calls = 0

    def __call__(self, base_url):
        self.calls += 1
        return _variant(self.calls)


def _variant(calls: int) -> dict:
    """Return a metrics payload whose per-model call count is ``calls``."""
    data = _fixture()
    data["per_model"][0]["calls"] = calls
    return data


def _first_model_calls(app) -> int:
    """Read the re-rendered per-model payload's first row call count."""
    return app._last_model["per_model"][0]["calls"]


def test_auto_refresh_rerenders_updated_payload():
    """Interval ticks re-fetch and re-render: the re-rendered panel tracks the
    fetcher's latest payload.

    No real sleep: the interval is tiny and every tick fires while the event
    loop is pumped through ``pilot.pause()``. The assertion reads the actual
    re-rendered payload back, not a mock-call count.
    """
    fetcher = _CountingFetcher()
    app = tui.DashboardApp(fetcher=fetcher, refresh_seconds=0.05)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            # >1 fetch means an auto-tick fired beyond the on_mount refresh.
            for _ in range(30):
                await pilot.pause()
            assert fetcher.calls > 1
            # The displayed panel reflects the fetcher's newest payload.
            assert _first_model_calls(app) == fetcher.calls
            assert app._refreshing is False

    asyncio.run(_go())


def test_error_resilience_keeps_last_good_data_and_recovers():
    """A transient fetch failure keeps the app running and the last good data
    displayed; a later successful refresh re-renders the new payload.

    A large interval means no stray auto-ticks, so the 2nd fetch is exactly the
    failing one, driven deterministically through the same ``_on_interval``
    callback the timer invokes — no sleep, no timing race.
    """
    calls = {"n": 0}

    def _scripted(base_url):
        calls["n"] += 1
        if calls["n"] == 2:
            raise ConnectionError("transient blip")
        return _variant(calls["n"])

    app = tui.DashboardApp(fetcher=_scripted, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            assert _first_model_calls(app) == 1  # initial good fetch displayed
            # advance one tick (the failing 2nd fetch)
            app._on_interval()
            await pilot.pause()
            assert app._last_error is not None, "transient failure was not seen"
            assert not app._exit, "app must not exit on a transient failure"
            err_widget = app.query_one("#error-panel")
            assert "cannot reach router" in str(err_widget.content)
            assert "visible" in err_widget.classes
            # last good data is still the displayed payload
            assert _first_model_calls(app) == 1
            # recover on the next refresh (3rd fetch, now successful)
            app._on_interval()
            await pilot.pause()
            assert _first_model_calls(app) == 3
            assert app._last_error is None

    asyncio.run(_go())


def test_force_refresh_binding_reloads_on_r():
    """Pressing ``r`` immediately re-fetches and re-renders a new payload."""
    fetcher = _CountingFetcher()
    # A large interval ensures only the forced refresh advances the payload.
    app = tui.DashboardApp(fetcher=fetcher, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            baseline = fetcher.calls
            await pilot.press("r")
            await pilot.pause()
            assert fetcher.calls == baseline + 1
            assert _first_model_calls(app) == fetcher.calls

    asyncio.run(_go())


@pytest.mark.parametrize("key", ["q", "Q", "ctrl+c"])
def test_quit_bindings_exit_app(key):
    """q, Q and Ctrl+C all quit the running app."""
    fetcher = _CountingFetcher()
    app = tui.DashboardApp(fetcher=fetcher, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            assert not app._exit
            await pilot.press(key)
            assert app._exit

    asyncio.run(_go())


@pytest.mark.parametrize(
    "key,panel",
    [
        ("1", "model-table"),
        ("2", "decision-table"),
        ("3", "category-table"),
        ("4", "quota-panel"),
        ("5", "warnings-panel"),
    ],
)
def test_number_bindings_focus_panel(key, panel):
    """Number keys 1-5 focus the corresponding panel."""
    fetcher = _CountingFetcher()
    app = tui.DashboardApp(fetcher=fetcher, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            await pilot.press(key)
            await pilot.pause()
            widget = app.query_one(f"#{panel}")
            assert widget.has_focus, f"{panel} should have focus after {key!r}"

    asyncio.run(_go())


# --------------------------------------------------------------------------
# Cursor persistence across refreshes (decision table).
# --------------------------------------------------------------------------


def _decisions_payload(*ids: int) -> dict:
    """A /metrics payload whose recent_decisions carry the given ids (newest
    first), all otherwise identical to the fixture's first row shape."""
    base = _fixture()["recent_decisions"][0]
    return {"recent_decisions": [dict(base, id=i) for i in ids]}


def test_cursor_persistence_across_refresh():
    """Highlighting a row survives a refresh that shifts it: after a new
    decision is prepended, the cursor follows the same logical decision
    (by stable row key ``str(id)``) instead of resetting to row 0."""
    payloads = [_decisions_payload(42, 41, 40), _decisions_payload(43, 42, 41, 40)]

    class _Scripted:
        def __init__(self):
            self.calls = 0

        def __call__(self, base_url):
            p = payloads[self.calls]
            self.calls += 1
            return p

    fetcher = _Scripted()
    app = tui.DashboardApp(fetcher=fetcher, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            dt = app.query_one("#decision-table")
            # Row 1 is id 41; highlight it.
            dt.focus()
            dt.move_cursor(row=1)
            await pilot.pause()
            assert dt.cursor_coordinate.row == 1
            # Logically the highlighted decision id.
            highlighted_id = app._last_model["recent_decisions"][1]["id"]
            assert highlighted_id == 41

            # Refresh to a payload with a new decision prepended.
            app.action_refresh()
            await pilot.pause()
            assert fetcher.calls == 2
            # id 41 now sits at index 2; the cursor must have followed it.
            assert app._last_model["recent_decisions"][2]["id"] == 41
            assert dt.cursor_coordinate.row == 2, (
                f"cursor reset to {dt.cursor_coordinate.row}; expected 2 "
                "(same logical decision across the refresh)"
            )

    asyncio.run(_go())


def test_cursor_persistence_clamps_when_selected_row_removed():
    """When the highlighted decision disappears from the payload on refresh,
    the cursor rests at row 0 (the default ``clear()`` already set) instead of
    clamping to a stale anchor."""
    payloads = [_decisions_payload(42, 41, 40), _decisions_payload(40, 39)]

    class _Scripted:
        def __init__(self):
            self.calls = 0

        def __call__(self, base_url):
            p = payloads[self.calls]
            self.calls += 1
            return p

    fetcher = _Scripted()
    app = tui.DashboardApp(fetcher=fetcher, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            dt = app.query_one("#decision-table")
            dt.focus()
            dt.move_cursor(row=1)  # id 41
            await pilot.pause()
            assert dt.cursor_coordinate.row == 1

            app.action_refresh()  # id 41 is dropped in the new payload
            await pilot.pause()
            # The cursor rests at the cleared default row 0.
            assert dt.cursor_coordinate.row == 0, (
                f"cursor at {dt.cursor_coordinate.row}; expected 0 "
                "(dropped row should rest at the cleared default)"
            )
            # The table reflects the two-row payload.
            assert app._last_model["recent_decisions"][0]["id"] == 40

    asyncio.run(_go())


@pytest.fixture(autouse=True)
def _no_real_network(monkeypatch):
    """Safety net: even if the fetcher is mis-wired, never hit a real router."""
    def _guard(base_url):
        raise AssertionError(f"real fetch_metrics called with {base_url!r}")

    monkeypatch.setattr(tui, "fetch_metrics", _guard)
    # Also guard the SSE consumer's requests so a stray DecisionStream never
    # reaches the network even if a test forgets to disable live_events.
    import tui_sse

    def _sse_guard(*args, **kwargs):
        raise AssertionError(
            f"real requests.get called from tui_sse with {args!r} {kwargs!r}"
        )

    monkeypatch.setattr(tui_sse.requests, "get", _sse_guard)


# --------------------------------------------------------------------------
# Category breakdown and enriched decision fields (pure data-layer tests).
# --------------------------------------------------------------------------


def test_build_category_breakdown_majority_and_share():
    """One category, two different winners: majority is the most common and
    the share is its fraction of the count."""
    decisions = [
        {"id": 3, "category": "coding_general", "tier": 2, "selected": "a"},
        {"id": 2, "category": "coding_general", "tier": 2, "selected": "a"},
        {"id": 1, "category": "coding_general", "tier": 2, "selected": "b"},
    ]
    rows = tui_model.build_category_breakdown(decisions)
    assert len(rows) == 1
    row = rows[0]
    assert row["category"] == "coding_general"
    assert row["tier"] == 2
    assert row["count"] == 3
    assert row["majority"] == "a"
    assert row["share"] == round(2 / 3, 2)


def test_build_category_breakdown_separates_tiers():
    """Same category, different tiers are separate buckets."""
    decisions = [
        {"id": 2, "category": "coding_general", "tier": 1, "selected": "tiny"},
        {"id": 1, "category": "coding_general", "tier": 3, "selected": "big"},
    ]
    rows = tui_model.build_category_breakdown(decisions)
    assert len(rows) == 2
    tiers = {r["tier"] for r in rows}
    assert tiers == {1, 3}


def test_build_category_breakdown_handles_empty_and_none_selected():
    """No decisions: empty list. Decisions with no selected model get
    majority 'none' and share 1.0 (they all count toward the bucket)."""
    assert tui_model.build_category_breakdown([]) == []

    rows = tui_model.build_category_breakdown(
        [{"id": 1, "category": "x", "tier": 1, "selected": None}]
    )
    assert rows[0]["majority"] == "none"


def test_build_model_recent_decisions_carry_enriched_fields():
    """The enriched /metrics row fields must reach the TUI data model so the
    detail popup can render the full decision in full."""
    data = _fixture()
    # Ensure the fixture's first row has the fields the new model surfaces.
    data["recent_decisions"][0].update(
        {
            "required_context_tokens": 50000,
            "confidence": 0.92,
            "classifier_ms": 1800,
            "classification_source": "classifier",
            "latency_tolerance": "interactive",
            "candidates_considered": 8,
            "runner_up_models": '[{"model_id":"kimi-k3","provider":"neuralwatt"}]',
            "est_proficiency": 0.9,
            "rejected_reason": None,
            "tools": 0,
            "images": 0,
            "json_mode": 0,
            "streamed": 1,
        }
    )
    m = build_model(data)
    row = m["recent_decisions"][0]
    assert row["required_context_tokens"] == 50000
    assert row["confidence"] == 0.92
    assert row["runner_up_models"].startswith("[{")
    assert row["streamed"] == 1
    # The breakdown is always present (even an empty list proves the key).
    assert "category_breakdown" in m


def test_decision_row_projects_flex_fields():
    """decision_row must project the three flex telemetry fields so they reach
    both the /metrics path and the live SSE path (shared by build_model)."""
    row = tui_model.decision_row(
        {
            "flex_preference": "prefer-flex",
            "flex_swapped": 1,
            "flex_forced": 0,
        }
    )
    assert row["flex_preference"] == "prefer-flex"
    assert row["flex_swapped"] == 1
    assert row["flex_forced"] == 0


def test_decision_row_missing_flex_fields_default_to_none():
    """Rows without flex columns (older payloads) yield None, not a crash."""
    row = tui_model.decision_row({"id": 1})
    assert row["flex_preference"] is None
    assert row["flex_swapped"] is None
    assert row["flex_forced"] is None


def test_build_model_threads_flex_default():
    """build_model carries the configured flex default through from coverage."""
    m = build_model(_fixture())
    assert m["flex_default"] == "auto"


def test_flex_indicator_labels():
    """The compact flex cell: plain preference by default, markers on a swap."""
    assert tui._flex_indicator({"flex_preference": "auto",
                                "flex_swapped": 0, "flex_forced": 0}) == "auto"
    assert tui._flex_indicator({"flex_preference": "prefer-flex",
                                "flex_swapped": 1, "flex_forced": 0}) == "prefer-flex!"
    assert tui._flex_indicator({"flex_preference": "force-flex",
                                "flex_swapped": 1, "flex_forced": 1}) == "force!"
    assert tui._flex_indicator({"id": 1}) == ""


def test_app_decision_table_renders_flex_column():
    """The decision table renders a flex indicator per row and the configured
    flex default appears in the UI."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        dt = a.query_one("#decision-table")
        first_row_text = " ".join(str(c) for c in dt.get_row_at(0))
        assert "force!" in first_row_text
        second_row_text = " ".join(str(c) for c in dt.get_row_at(1))
        assert "auto" in second_row_text
        legend = a.query_one("#quota-legend", Static)
        assert "flex default auto" in str(legend.content)

    _run_app(app, _assert)


def test_keys_legend_built_from_short_pairs_dedups_quit():
    """The bottom keys legend is built from compact short pairs and collapses
    the three quit bindings (q/Q/ctrl+c) to a single 'quit'."""
    legend = tui._keys_legend()
    assert isinstance(legend, str)
    # every short key is present
    for key in ("q", "r", "e", "ctrl+v", "1", "2", "3", "4", "5"):
        assert f"[bold]{key}[/bold]" in legend
    # short labels are present
    for label in ("quit", "refresh", "detail", "mix", "model", "decisions",
                  "breakdown", "quota", "warnings"):
        assert label in legend
    # exactly one quit (q/Q/ctrl+c collapsed)
    assert legend.count("quit") == 1


def test_app_run_test_renders_keys_legend():
    """The app renders a #keys-legend Static (not a Footer) carrying the
    full compact legend string regardless of terminal width, so no key is
    truncated away."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        legend = a.query_one("#keys-legend", Static)
        text = str(legend.content)
        # full legend is present (wrapped, not truncated) on a narrow window
        for key in ("q", "r", "e", "2", "5"):
            assert f"[bold]{key}[/bold]" in text
        assert text.count("quit") == 1

    _run_app(app, _assert)


def test_app_run_test_keys_legend_not_truncated_at_narrow_width():
    """At a narrow terminal width the legend's content is intact (wraps rather
    than drops keys), unlike Textual's Footer which would ellipsize."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub)

    async def _go():
        async with app.run_test(size=(40, 30)) as pilot:
            await pilot.pause()
            legend = app.query_one("#keys-legend", Static)
            text = str(legend.content)
            # every short key survives narrow rendering — nothing truncated
            for key in ("q", "r", "e", "ctrl+v", "1", "2", "3", "4", "5"):
                assert f"[bold]{key}[/bold]" in text

    asyncio.run(_go())


# --------------------------------------------------------------------------
# Detail popup and live SSE decision handling (App-level tests).
# --------------------------------------------------------------------------


def test_show_decision_detail_pushes_modal_with_full_row():
    """Pressing ``e`` on the decisions table opens a modal whose body contains
    the full JSON of the selected row — not just the table columns."""
    stub = _StubFetcher()
    stub.payload = _fixture()
    stub.payload["recent_decisions"][0].update(
        {
            "required_context_tokens": 50000,
            "confidence": 0.92,
            "runner_up_models": '[{"model_id":"kimi-k3"}]',
            "rejected_reason": None,
        }
    )
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            # Focus the decisions table and move to the first row, then open
            # the detail popup via the dedicated binding.
            app.query_one("#decision-table").focus()
            await pilot.pause()
            await pilot.press("e")
            await pilot.pause()
            # A modal screen is now active and carries the selected decision.
            from textual.screen import ModalScreen

            assert isinstance(app.screen, ModalScreen)
            decision = app.screen.decision
            assert decision["id"] == 42
            assert decision["required_context_tokens"] == 50000
            assert "kimi-k3" in decision["runner_up_models"]

    asyncio.run(_go())


def test_detail_popup_carries_forensics_fields():
    """The e-key popup carries the six T2 forensics fields — profile,
    exploration, pinch tokens, request_id, session_key — both on the live
    decision dict and in the rendered JSON for a metrics-shaped full row."""
    stub = _StubFetcher()
    stub.payload = _enriched_payload()
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            app.query_one("#decision-table").focus()
            await pilot.pause()
            await pilot.press("e")
            await pilot.pause()
            from textual.screen import ModalScreen

            assert isinstance(app.screen, ModalScreen)
            decision = app.screen.decision
            assert decision["request_id"] == "chatcmpl-fixture-42"
            assert decision["session_key"] == "sess-42"
            assert decision["pinch_original_tokens"] == 120000
            assert decision["pinch_final_tokens"] == 96122
            assert decision["profile"] == "default"
            assert decision["exploration"] == 0

    asyncio.run(_go())

    metrics_row = {
        "id": 43,
        "observed_at": "2026-09-05T12:34:56+00:00",
        "kind": "chat",
        "task_category": "coding_general",
        "task_tier": 2,
        "required_context_tokens": 123456,
        "confidence": 0.91,
        "classifier_ms": 1800,
        "classification_source": "classifier",
        "latency_tolerance": "interactive",
        "candidates_considered": 7,
        "selected_model": "fixture-model",
        "selected_provider": "neuralwatt",
        "runner_up_models": None,
        "est_cost_usd": 0.001,
        "est_proficiency": 0.9,
        "rejected_reason": None,
        "session_key": "sess-43",
        "tools": 0,
        "images": 0,
        "json_mode": 0,
        "streamed": 1,
        "flex_preference": "auto",
        "flex_swapped": 0,
        "flex_forced": 0,
        "request_id": "chatcmpl-fixture-43",
        "exploration": 1,
        "pinch_original_tokens": 120000,
        "pinch_final_tokens": 96122,
        "profile": "default",
    }
    text = DecisionDetailScreen(tui_model.decision_row(metrics_row))._render_text()
    for key in (
        "profile",
        "exploration",
        "pinch_original_tokens",
        "pinch_final_tokens",
        "request_id",
        "session_key",
    ):
        assert key in text


def test_app_run_test_ctrl_v_opens_verdict_popup():
    """Pressing ``ctrl+v`` pushes a VerdictMixScreen modal showing the verdict
    mix rows from the current model, and ``escape`` dismisses it back to the
    main screen."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            await pilot.press("ctrl+v")
            await pilot.pause()

            from textual.screen import ModalScreen

            assert isinstance(app.screen, ModalScreen)
            assert isinstance(app.screen, VerdictMixScreen)
            # The popup carries the fixture's verdict mix.
            by_verdict = {
                row["verdict"]: row["count"] for row in app.screen.verdict_mix
            }
            assert by_verdict == {"ok": 5, "unverifiable": 2, "truncated": 1}
            # The DataTable renders a row per verdict.
            table = app.screen.query_one("#verdict-table")
            assert table.row_count == 3

            # ``escape`` dismisses back to the main dashboard screen.
            await pilot.press("escape")
            await pilot.pause()
            assert not isinstance(app.screen, VerdictMixScreen)

    asyncio.run(_go())


def test_verdict_mix_screen_updates_live_after_refresh():
    """An open VerdictMixScreen modal tracks the newest verdict mix after a
    refresh, rather than staying a static snapshot from when it was opened."""
    stub = _StubFetcher()
    stub.payload = _fixture()

    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            await pilot.press("ctrl+v")
            await pilot.pause()
            by_verdict = {
                row["verdict"]: row["count"] for row in app.screen.verdict_mix
            }
            assert by_verdict == {"ok": 5, "unverifiable": 2, "truncated": 1}

            # The next refresh delivers a new (smaller) verdict mix.
            stub.payload["verdict_mix"] = {"ok": 100, "failed": 5}
            app.action_refresh()
            await pilot.pause()

            by_verdict = {
                row["verdict"]: row["count"] for row in app.screen.verdict_mix
            }
            assert by_verdict == {"ok": 100, "failed": 5}
            table = app.screen.query_one("#verdict-table")
            assert table.row_count == 2

    asyncio.run(_go())


def test_live_decision_inserts_row_at_front_and_rerenders():
    """A decision delivered via the SSE callback is prepended to the model and
    re-renders the decisions and category tables without a full re-fetch."""
    stub = _StubFetcher()
    stub.payload = _fixture()
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            before = len(app._last_model["recent_decisions"])
            # Simulate the SSE consumer handing in a brand-new decision.
            # Same (category, tier) as the fixture's first row so the bucket
            # count for coding_general/tier-2 rises to 2.
            app._handle_live_decision(
                {
                    "id": 999,
                    "kind": "chat",
                    "task_category": "coding_general",
                    "task_tier": 2,
                    "selected_model": "deepseek-v4-flash",
                    "est_cost_usd": 0.0002,
                }
            )
            await pilot.pause()
            after = app._last_model["recent_decisions"]
            assert len(after) == before + 1
            assert after[0]["id"] == 999  # prepended, newest-first
            # The table was re-rendered: the first row shows the new id.
            dt = app.query_one("#decision-table")
            first_row_text = " ".join(str(c) for c in dt.get_row_at(0))
            assert "999" in first_row_text

    asyncio.run(_go())


def test_live_decision_carries_new_fields():
    """A live SSE decision keeps the six T2 fields through the shared
    decision_row projection, so a prompt `e` on a fresh decision shows the
    same forensics as a /metrics-sourced row."""
    stub = _StubFetcher()
    stub.payload = _fixture()
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            app._handle_live_decision(
                {
                    "id": 1001,
                    "kind": "chat",
                    "task_category": "coding_general",
                    "task_tier": 2,
                    "selected_model": "deepseek-v4-flash",
                    "est_cost_usd": 0.0002,
                    "profile": "default",
                    "exploration": 1,
                    "request_id": "chatcmpl-live-1001",
                    "pinch_original_tokens": 120000,
                    "pinch_final_tokens": 96122,
                    "session_key": "sess-live-1001",
                }
            )
            await pilot.pause()
            row = app._last_model["recent_decisions"][0]
            assert row["id"] == 1001
            assert row["profile"] == "default"
            assert row["exploration"] == 1
            assert row["request_id"] == "chatcmpl-live-1001"
            assert row["pinch_original_tokens"] == 120000
            assert row["pinch_final_tokens"] == 96122
            assert row["session_key"] == "sess-live-1001"

    asyncio.run(_go())


def test_live_decision_caps_recent_decisions_at_fifty():
    """The live feed never grows the in-memory list past the /metrics cap, so
    the dashboard's view stays consistent with a /metrics refresh."""
    stub = _StubFetcher()
    # Start with exactly 50 rows so one live addition must evict the oldest.
    base = _fixture()["recent_decisions"][0]
    stub.payload = {"recent_decisions": [dict(base, id=i) for i in range(50, 0, -1)]}
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            assert len(app._last_model["recent_decisions"]) == 50
            app._handle_live_decision(
                {"id": 1, "kind": "chat", "task_category": "x", "task_tier": 1}
            )
            await pilot.pause()
            assert len(app._last_model["recent_decisions"]) == 50

    asyncio.run(_go())


def test_live_decision_dedup_skips_duplicate_id():
    stub = _StubFetcher()
    stub.payload = _fixture()
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            before = len(app._last_model["recent_decisions"])
            app._handle_live_decision(
                {
                    "id": 42,
                    "kind": "chat",
                    "task_category": "coding_general",
                    "task_tier": 2,
                    "selected_model": "deepseek-v4-flash",
                }
            )
            await pilot.pause()
            after = app._last_model["recent_decisions"]
            assert len(after) == before, "duplicate id did not get skipped"
            # first row is id=41 (42 was skipped as duplicate; 42 is now at pos 0)
            assert after[0]["id"] == 42 and after[1]["id"] == 41, (
                "first row is id 42 after dedup"
            )
            app._handle_live_decision(
                {
                    "id": 888,
                    "kind": "route",
                    "task_category": "coding_general",
                    "task_tier": 2,
                    "selected_model": "kimi-k3",
                }
            )
            await pilot.pause()
            assert len(app._last_model["recent_decisions"]) == before + 1
            assert app._last_model["recent_decisions"][0]["id"] == 888

    asyncio.run(_go())


def test_live_decision_new_bucket_rebuilds_breakdown():
    stub = _StubFetcher()
    stub.payload = _fixture()
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            buckets_before = set(
                (r["category"], r["tier"]) for r in app._last_model["category_breakdown"]
            )
            app._handle_live_decision(
                {
                    "id": 1000,
                    "kind": "route",
                    "task_category": "summarization",
                    "task_tier": 1,
                    "selected_model": "qwen3.6-35b",
                }
            )
            await pilot.pause()
            buckets_after = set(
                (r["category"], r["tier"]) for r in app._last_model["category_breakdown"]
            )
            assert ("summarization", 1) in buckets_after - buckets_before
            row = next(
                r
                for r in app._last_model["category_breakdown"]
                if r["category"] == "summarization" and r["tier"] == 1
            )
            assert row["count"] == 1
            assert row["majority"] == "qwen3.6-35b"

    asyncio.run(_go())


# --------------------------------------------------------------------------
# DecisionStream: callback exceptions and stop behavior (tui_sse.py).
# --------------------------------------------------------------------------


class _MockResp:
    def __enter__(self):
        return self

    def __exit__(self, *a):
        pass

    def raise_for_status(self):
        pass

    def iter_lines(self, decode_unicode=False):
        yield "data: {\"id\": 1}"
        raise requests.exceptions.ConnectionError("broken pipe")


def test_callback_raises_doesnt_break_reconnect(monkeypatch):
    """A callback that raises RuntimeError is caught; the stream still
    survives and processes subsequent decisions after a reconnection."""

    import tui_sse

    monkeypatch.setattr(tui_sse.requests, "get", lambda *a, **kw: _MockResp())

    call_count = {"n": 0}

    def failing_callback(decision):
        call_count["n"] += 1
        if call_count["n"] == 1:
            raise RuntimeError("app loop gone")
        # second call succeeds — proves reconnect worked

    s = tui_sse.DecisionStream(
        "http://127.0.0.1",
        failing_callback,
        reconnect_seconds=0.1,
    )
    s.start()
    time.sleep(0.6)
    s.stop()
    s.join(timeout=2)
    assert not s.is_alive()
    assert call_count["n"] >= 2, (
        f"Expected reconnection after callback failure, got {call_count['n']} call(s)"
    )

def test_live_decision_existing_bucket_defers_count_update():
    """A live decision in an existing bucket does NOT trigger an immediate
    count rebuild (fixes finding #9 risk), but the count is updated on the
    next authoritative /metrics poll.
    """
    stub = _StubFetcher()
    stub.payload = _fixture()
    app = tui.DashboardApp(fetcher=stub, refresh_seconds=60)

    async def _go():
        async with app.run_test() as pilot:
            await pilot.pause()
            initial_count = next(
                r["count"] for r in app._last_model["category_breakdown"]
                if r["category"] == "coding_general" and r["tier"] == 2
            )
            assert initial_count == 1
            app._handle_live_decision(
                {"id": 2000, "kind": "chat", "task_category": "coding_general",
                 "task_tier": 2, "selected_model": "deepseek-v4-flash"}
            )
            await pilot.pause()
            count_after_live = next(
                r["count"] for r in app._last_model["category_breakdown"]
                if r["category"] == "coding_general" and r["tier"] == 2
            )
            assert count_after_live == initial_count, "count grew immediately"
            stub.payload["recent_decisions"].append(
                {"id": 2000, "kind": "chat", "task_category": "coding_general",
                 "task_tier": 2, "selected_model": "deepseek-v4-flash"}
            )
            app._on_interval()
            await pilot.pause()
            final_count = next(
                r["count"] for r in app._last_model["category_breakdown"]
                if r["category"] == "coding_general" and r["tier"] == 2
            )
            assert final_count == 2

    asyncio.run(_go())


def test_stopped_stream_exits_without_reconnect_sleep(monkeypatch):
    """After stop(), the thread should NOT wait for reconnect_seconds
    before exiting — the _stopped guard is checked before the sleep."""
    import tui_sse

    class _MockResp:
        def __enter__(self):
            return self

        def __exit__(self, *a):
            pass

        def raise_for_status(self):
            pass

        def iter_lines(self, decode_unicode=False):
            raise requests.exceptions.ConnectionError("closed")

    monkeypatch.setattr(tui_sse.requests, "get", lambda *a, **kw: _MockResp())

    stop_at = time.monotonic()
    s = tui_sse.DecisionStream(
        "http://127.0.0.1",
        lambda x: None,
        reconnect_seconds=5.0,
    )
    s.start()
    # Let the first request attempt begin.
    time.sleep(0.2)
    # Record when stop is called.
    s.stop()
    stopped_at = time.monotonic()
    # Thread should exit BEFORE the 5s reconnect backoff (use 3s as margin).
    s.join(timeout=3)
    assert not s.is_alive(), "Thread should exit promptly after stop()"
    assert stopped_at - stop_at < 3.0, "Thread slept through reconnect_seconds"


def test_format_quota_legend_shows_next_reset_date():
    """When next_reset_date is available, _render appends the period line.
    _format_quota_legend itself no longer takes next_reset_date; it is
    appended in _render."""
    app = tui.DashboardApp(fetcher=_StubFetcher(), refresh_seconds=60)
    legend = app._format_quota_legend(
        plan=6.25,
        metered=1.25,
        frac=0.2,
    )
    assert "6.25" in legend
    assert "1.25" in legend


# --------------------------------------------------------------------------
# T3 — decision table display: time column, profile column, exploration flag.
# --------------------------------------------------------------------------


def test_decision_table_columns_and_order():
    """The table declares exactly ten columns with `time` first.

    Time leads because it is the natural scan axis for a live feed; `flex`
    became `flags` because exploration now shares that cell.
    """
    stub = _StubFetcher()
    stub.payload = _enriched_payload()
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        dt = a.query_one("#decision-table")
        labels = [str(c.label) for c in dt.columns.values()]
        assert labels == [
            "time",
            "id",
            "kind",
            "category",
            "tier",
            "ctx",
            "profile",
            "selected",
            "est $",
            "flags",
        ]

    _run_app(app, _assert)


def test_short_time_renders_hhmmss_and_degrades_quietly():
    """`_short_time` is HH:MM:SS local, and never raises on bad input.

    A malformed timestamp must not take down the whole table render, so the
    unparseable cases return "" rather than propagating ValueError.
    """
    rendered = tui._short_time("2026-08-23T10:00:00+00:00")
    assert len(rendered) == 8 and rendered.count(":") == 2
    # Local conversion, computed the same way the helper does it.
    expected = (
        datetime.fromisoformat("2026-08-23T10:00:00+00:00")
        .astimezone()
        .strftime("%H:%M:%S")
    )
    assert rendered == expected
    # No date component leaks into the cell.
    assert "2026" not in rendered
    for bad in (None, "", "not-a-timestamp", 12345):
        assert tui._short_time(bad) == ""


def test_app_decision_table_profile_column_blank_not_none():
    """`profile` renders its value, and renders BLANK when absent.

    A literal "None" in a dense table reads as a real profile name.
    """
    stub = _StubFetcher()
    data = _enriched_payload()
    data["recent_decisions"][1]["profile"] = None
    stub.payload = data
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        dt = a.query_one("#decision-table")
        labels = [str(c.label) for c in dt.columns.values()]
        profile_at = labels.index("profile")
        assert str(dt.get_row_at(0)[profile_at]) == "default"
        # Absent profile is an empty cell, never the literal "None".
        assert str(dt.get_row_at(1)[profile_at]) == ""

    _run_app(app, _assert)


def test_exploration_flag_and_flags_indicator_compose():
    """`E` marks an exploratory pick and composes with the flex label.

    An epsilon-greedy pick is a random sample, not the ranking's judgement;
    without the marker an operator reads it as the router's answer.
    """
    assert tui._exploration_flag({"exploration": 1}) == "E"
    assert tui._exploration_flag({"exploration": 0}) == ""
    assert tui._exploration_flag({}) == ""
    # Composition: flex label first, then the marker, space separated.
    both = tui._flags_indicator(
        {"flex_preference": "auto", "flex_swapped": 0, "exploration": 1}
    )
    assert both == "auto E"
    # Either alone survives; neither yields an empty cell.
    assert tui._flags_indicator({"exploration": 1}) == "E"
    assert tui._flags_indicator({"flex_preference": "auto"}) == "auto"
    assert tui._flags_indicator({}) == ""


def test_app_decision_table_exploration_flag_renders():
    """Row 41 is the exploratory pick in the fixture; its flags cell shows E."""
    stub = _StubFetcher()
    stub.payload = _enriched_payload()
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        dt = a.query_one("#decision-table")
        exploratory = [str(c) for c in dt.get_row_at(1)]
        assert any("E" == cell or cell.endswith(" E") for cell in exploratory)
        non_exploratory = [str(c) for c in dt.get_row_at(0)]
        assert not any(cell == "E" or cell.endswith(" E") for cell in non_exploratory)

    _run_app(app, _assert)


def test_placeholder_row_matches_column_arity():
    """The empty-state placeholder must have exactly ten cells.

    A short placeholder row raises inside Textual at render time — an arity
    mismatch is a crash, not a cosmetic issue.
    """
    stub = _StubFetcher()
    data = _enriched_payload()
    data["recent_decisions"] = []
    stub.payload = data
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        dt = a.query_one("#decision-table")
        assert len(dt.get_row_at(0)) == len(dt.columns) == 10

    _run_app(app, _assert)


# --------------------------------------------------------------------------
# T4 — quota panel: kWh-only lead, labeled per-provider account rows.
# --------------------------------------------------------------------------


def test_format_small_balance_renders_tiny_and_normal_values():
    assert tui._format_small_balance(None) == "n/a"
    assert tui._format_small_balance(0.0) == "$0.00"
    assert tui._format_small_balance(0.0001) == "<$0.01"
    assert tui._format_small_balance(-0.004) == "~$0.00 (slight overage)"
    assert tui._format_small_balance(8.50) == "$8.50"
    assert tui._format_small_balance(-1.0) == "$-1.00"


def test_format_provider_quota_account_labels_billing_shape():
    """_format_provider_quota_account renders prepaid_credit and metered_plan."""
    prepaid = {
        "provider": "openrouter",
        "shape": "prepaid_credit",
        "spend_usd": {"period": 2.0, "attribution_coverage": 1.0},
        "plan": None,
        "pool": {"total_credits_usd": 5.0, "total_usage_usd": 0.001, "balance_usd": 4.999, "age_seconds": 60},
        "burn": {"burn_rate_usd_per_hour": 0.5, "projected_hours_remaining": 10.0},
        "credit": {"balance_usd": 4.999, "balance_at": "2026-08-23T10:00:00+00:00", "balance_source": "polled"},
        "energy": {"kwh_30d": 0.0, "calls_30d": 0},
    }
    row = tui._format_provider_quota_account(prepaid)
    assert row.startswith("openrouter")
    assert "burn $0.50/h" in row
    assert "runway" in row

    metered = {
        "provider": "neuralwatt",
        "shape": "metered_plan",
        "spend_usd": {"period": 1.25, "attribution_coverage": 1.0},
        "plan": {"kwh_per_period": 6.25, "used_kwh": 1.25, "used_fraction": 0.2},
        "pool": None,
        "burn": None,
        "credit": {"balance_usd": -0.004, "balance_at": "2026-08-23T09:58:00+00:00", "balance_source": "telemetry"},
        "energy": {"kwh_30d": 1.25, "calls_30d": 18},
    }
    row = tui._format_provider_quota_account(metered)
    assert row.startswith("neuralwatt")
    assert "kWh plan" in row

    unmetered = {
        "provider": "provider-a",
        "shape": "unmetered",
        "spend_usd": {"period": 0.0, "attribution_coverage": 1.0},
        "plan": None, "pool": None, "burn": None, "credit": None, "energy": None,
    }
    row = tui._format_provider_quota_account(unmetered)
    assert "provider-a" in row
    assert "unmetered" in row


def test_provider_quota_rows_returns_one_row_per_account_sorted():
    quota_raw = {
        "accounts": [
            {
                "provider": "neuralwatt",
                "shape": "metered_plan",
                "spend_usd": {"period": 0.001, "attribution_coverage": 0.5},
                "plan": {"kwh_per_period": 6.25, "used_kwh": 0.0, "used_fraction": 0.0},
                "pool": None,
                "burn": None,
                "credit": {"balance_usd": 0.0001, "balance_at": None, "balance_source": "telemetry"},
                "energy": {"kwh_30d": 0.0, "calls_30d": 0},
            },
            {
                "provider": "openrouter",
                "shape": "prepaid_credit",
                "spend_usd": {"period": 0.5, "attribution_coverage": 1.0},
                "plan": None,
                "pool": {"total_credits_usd": 5.0, "total_usage_usd": 0.001, "balance_usd": 4.999, "age_seconds": 60},
                "burn": None,
                "credit": {"balance_usd": 4.999, "balance_at": None, "balance_source": "polled"},
                "energy": {"kwh_30d": 0.0, "calls_30d": 0},
            },
        ],
    }
    out = tui._provider_quota_rows(quota_raw)
    assert len(out) == 2
    assert out[0].startswith("neuralwatt")
    assert out[1].startswith("openrouter")


def test_quota_panel_lead_is_kwh_only_and_note_empty():
    """The quota lead is the kWh-plan fraction; the note line stays hidden."""
    stub = _StubFetcher()
    data = _fixture()
    stub.payload = data
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        lead_text = str(a.query_one("#quota-lead", Static).content)
        assert "20% of 6.25 kWh plan" in lead_text
        assert "None" not in lead_text
        assert a.query_one("#quota-note", Static).display is False

    _run_app(app, _assert)


def test_quota_legend_includes_provider_account_rows():
    """The TUI quota legend lists one labeled row per provider after the kWh
    summary line."""
    stub = _StubFetcher()
    data = _fixture()
    stub.payload = data
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        legend = str(a.query_one("#quota-legend", Static).content)
        assert "neuralwatt" in legend
        assert "kWh plan" in legend
        assert "None" not in legend

    _run_app(app, _assert)


def test_quota_legend_lists_polled_provider_with_credits_label():
    """A polled provider row shows the credits label, distinct from a
    telemetry provider's overage label."""
    stub = _StubFetcher()
    data = _fixture()
    data["quota"]["accounts"].append({
        "provider": "openrouter",
        "shape": "prepaid_credit",
        "spend_usd": {"period": 0.5, "attribution_coverage": 1.0},
        "plan": None,
        "pool": {"total_credits_usd": 5.0, "total_usage_usd": 0.001, "balance_usd": 4.999, "age_seconds": 60},
        "burn": None,
        "credit": {"balance_usd": 4.999, "balance_at": "2026-08-23T10:00:00+00:00", "balance_source": "polled"},
        "energy": {"kwh_30d": 0.0, "calls_30d": 0},
    })
    stub.payload = data
    app = tui.DashboardApp(fetcher=stub)

    def _assert(a):
        legend = str(a.query_one("#quota-legend", Static).content)
        assert "openrouter" in legend

    _run_app(app, _assert)


def test_format_small_balance_handles_boundary_and_zero():
    """Exactly ±0.005 renders conventionally (not tiny); zero renders $0.00."""
    assert tui._format_small_balance(0.005) == "$0.01"
    assert tui._format_small_balance(-0.005) == "$-0.01"
    assert tui._format_small_balance(0.0) == "$0.00"


def test_format_provider_quota_account_prepaid_credit():
    """prepaid_credit account renders pool balance and burn info."""
    account = {
        "provider": "openrouter",
        "shape": "prepaid_credit",
        "spend_usd": {"period": 0.5, "attribution_coverage": 1.0},
        "plan": None,
        "pool": {"total_credits_usd": 5.0, "total_usage_usd": 0.001, "balance_usd": 4.999, "age_seconds": 60},
        "burn": None,
        "credit": {"balance_usd": 4.999, "balance_at": "2026-08-23T10:00:00+00:00", "balance_source": "polled"},
        "energy": {"kwh_30d": 0.0, "calls_30d": 0},
    }
    row = tui._format_provider_quota_account(account)
    assert row.startswith("openrouter")
    assert "pool" in row


def test_format_provider_quota_account_unmetered():
    """unmetered account shows minimal info."""
    account = {
        "provider": "provider-x",
        "shape": "unmetered",
        "spend_usd": {"period": 3.25, "attribution_coverage": 0.5},
        "plan": None, "pool": None, "burn": None, "credit": None, "energy": None,
    }
    row = tui._format_provider_quota_account(account)
    assert "provider-x" in row
    assert "unmetered" in row
    assert "$3.25" in row