"""Tests for shared persistent status-bar helpers."""

from __future__ import annotations

from datetime import datetime, timedelta
from typing import ClassVar

import pytest
from langchain_core.messages import HumanMessage

from EvoScientist.cli.status_bar import (
    SessionStatusSnapshot,
    apply_assistant_text_to_snapshot,
    apply_user_text_to_snapshot,
    build_session_status_snapshot,
    build_status_fragments,
    build_status_text,
    make_usage_status_snapshot,
    shorten_model_name,
    status_style_name,
    trim_status_text,
)
from EvoScientist.memory import worker_activity
from tests.fakes import FakeGraphGateway, FakeThreadStore


def _render_fragments(fragments: list[tuple[str, str]]) -> str:
    return "".join(text for _, text in fragments)


@pytest.fixture
def reset_memory_activity():
    worker_activity.reset_memory_worker_status_for_tests()
    yield
    worker_activity.reset_memory_worker_status_for_tests()


def _default_snapshot() -> SessionStatusSnapshot:
    return SessionStatusSnapshot(
        model_full="openai/gpt-6",
        model_short="gpt-6",
        context_tokens=12_345,
        context_window=128_000,
        context_percent=10,
    )


def test_build_status_fragments_wide_layout():
    snapshot = SessionStatusSnapshot(
        model_full="openai/gpt-5.4",
        model_short="gpt-5.4",
        context_tokens=12_345,
        context_window=128_000,
        context_percent=10,
    )

    rendered = _render_fragments(
        build_status_fragments(
            snapshot,
            datetime.now() - timedelta(minutes=3),
            100,
        )
    )

    assert "gpt-5.4" in rendered
    assert "12.3K/128K" in rendered
    assert "[█" in rendered
    assert "10%" in rendered
    assert "3m" in rendered


def test_build_status_fragments_shows_saved_memory_counts(
    tmp_path,
    reset_memory_activity,
):
    memory_dir = tmp_path / "memories"
    before = worker_activity.snapshot_memory_outputs(memory_dir)
    worker_activity.mark_memory_worker_started(
        thread_id="thread-1",
        run_id="run-1",
        memory_dir=memory_dir,
        before_outputs=before,
    )
    profile = memory_dir / "profile" / "USER_PROFILE.md"
    profile.parent.mkdir(parents=True)
    profile.write_text("# User profile\n\n- remembered\n", encoding="utf-8")
    observation = memory_dir / "observations" / "global" / "O-1.md"
    observation.parent.mkdir(parents=True)
    observation.write_text("# Observation\n", encoding="utf-8")
    worker_activity.mark_memory_worker_finished("thread-1", "run-1")

    rendered = _render_fragments(
        build_status_fragments(
            _default_snapshot(),
            datetime.now() - timedelta(minutes=3),
            100,
        )
    )

    assert "Saved 1 profile edit, 1 observation" in rendered


def test_build_status_fragments_shows_memory_worker_indicator_when_running(
    tmp_path,
    reset_memory_activity,
):
    worker_activity.mark_memory_worker_started(
        thread_id="thread-1",
        run_id="run-1",
        memory_dir=tmp_path / "memories",
    )

    rendered = _render_fragments(
        build_status_fragments(
            _default_snapshot(),
            datetime.now() - timedelta(minutes=3),
            100,
        )
    )

    assert "🧠" in rendered


def test_build_status_fragments_shows_observation_linker_indicator_when_running(
    reset_memory_activity,
):
    worker_activity.mark_observation_linker_started(
        thread_id="thread-1",
        run_id="run-1",
    )

    rendered = _render_fragments(
        build_status_fragments(
            _default_snapshot(),
            datetime.now() - timedelta(minutes=3),
            100,
        )
    )

    assert "🔗" in rendered
    assert "🧠" not in rendered


def test_build_status_fragments_shows_linked_relation_count(
    reset_memory_activity,
):
    worker_activity.mark_observation_relations_linked(1)

    rendered = _render_fragments(
        build_status_fragments(
            _default_snapshot(),
            datetime.now() - timedelta(minutes=3),
            100,
        )
    )

    assert "Created 1 memory link" in rendered
    assert "🔗" not in rendered


def test_build_status_fragments_hides_memory_indicator_when_idle(
    reset_memory_activity,
):
    fragments = build_status_fragments(
        _default_snapshot(),
        datetime.now() - timedelta(minutes=3),
        100,
    )

    assert not any(style == "class:status-bar-warn" for style, _text in fragments)


def test_build_status_fragments_medium_layout():
    snapshot = SessionStatusSnapshot(
        model_full="openai/gpt-5.4",
        model_short="gpt-5.4",
        context_tokens=48_000,
        context_window=100_000,
        context_percent=48,
    )

    rendered = _render_fragments(
        build_status_fragments(
            snapshot,
            datetime.now() - timedelta(seconds=40),
            60,
        )
    )

    assert "gpt-5.4" in rendered
    assert "48%" in rendered
    assert "40s" in rendered
    assert "/" not in rendered


def test_build_status_fragments_narrow_layout():
    snapshot = SessionStatusSnapshot(
        model_full="anthropic/claude-sonnet-4-20250514",
        model_short=shorten_model_name("anthropic/claude-sonnet-4-20250514"),
        context_tokens=95_000,
        context_window=100_000,
        context_percent=95,
    )

    rendered = _render_fragments(
        build_status_fragments(
            snapshot,
            datetime.now() - timedelta(hours=2),
            40,
        )
    )

    assert snapshot.model_short in rendered
    assert "2h" in rendered
    assert "%" not in rendered


def test_trim_status_text_adds_ellipsis():
    assert trim_status_text("abcdefghijk", 8) == "abcde..."


def test_status_style_name_thresholds():
    assert status_style_name(49) == "good"
    assert status_style_name(50) == "warn"
    assert status_style_name(80) == "warn"
    assert status_style_name(81) == "bad"
    assert status_style_name(95) == "critical"


def test_build_status_text_uses_rich_styles():
    snapshot = SessionStatusSnapshot(
        model_full="openai/gpt-5.4",
        model_short="gpt-5.4",
        context_tokens=10_000,
        context_window=100_000,
        context_percent=10,
    )

    text = build_status_text(snapshot, datetime.now(), 100)

    assert str(text)
    assert text.spans


async def test_build_session_status_snapshot_uses_fallback_window(monkeypatch):
    class _FakeModel:
        model_name: ClassVar[str] = "provider/demo-model"
        profile: ClassVar[dict[str, object]] = {}

    def _fake_count(messages):
        assert len(messages) == 2
        assert messages[-1].content == "pending"
        return 42_000

    monkeypatch.setattr(
        "EvoScientist.cli.status_bar._get_default_chat_model",
        lambda: _FakeModel(),
    )
    monkeypatch.setattr(
        "EvoScientist.cli.status_bar.count_tokens_approximately",
        _fake_count,
    )

    snapshot = await build_session_status_snapshot(
        "thread-1",
        pending_user_text="pending",
        graph_gateway=FakeGraphGateway(
            thread_store=FakeThreadStore(messages=[HumanMessage(content="existing")])
        ),
    )

    assert snapshot.model_full == "provider/demo-model"
    assert snapshot.model_short == "demo-model"
    assert snapshot.context_tokens == 42_000
    assert snapshot.context_window == 200_000
    assert snapshot.context_percent == 21


def test_apply_assistant_text_to_snapshot_updates_context(monkeypatch):
    snapshot = SessionStatusSnapshot(
        model_full="provider/demo-model",
        model_short="demo-model",
        context_tokens=10_000,
        context_window=100_000,
        context_percent=10,
    )

    monkeypatch.setattr(
        "EvoScientist.cli.status_bar.estimate_message_tokens",
        lambda text, message_type="ai": 550,
    )

    updated = apply_assistant_text_to_snapshot(snapshot, "streamed response")

    assert updated.context_tokens == 10_550
    assert updated.context_percent == 11


def test_apply_user_text_to_snapshot_updates_context(monkeypatch):
    snapshot = SessionStatusSnapshot(
        model_full="provider/demo-model",
        model_short="demo-model",
        context_tokens=46_751,
        context_window=163_840,
        context_percent=29,
        context_source="usage",
    )

    monkeypatch.setattr(
        "EvoScientist.cli.status_bar.estimate_message_tokens",
        lambda text, message_type="human": 320,
    )

    updated = apply_user_text_to_snapshot(snapshot, "good")

    assert updated.context_tokens == 47_071
    assert updated.context_percent == 29
    assert updated.context_source == "usage"


def test_make_usage_status_snapshot_marks_usage_source(monkeypatch):
    class _FakeModel:
        model_name: ClassVar[str] = "provider/demo-model"
        profile: ClassVar[dict[str, object]] = {"max_input_tokens": 128_000}

    monkeypatch.setattr(
        "EvoScientist.cli.status_bar._get_default_chat_model",
        lambda: _FakeModel(),
    )

    snapshot = make_usage_status_snapshot(42_000)

    assert snapshot.model_full == "provider/demo-model"
    assert snapshot.model_short == "demo-model"
    assert snapshot.context_tokens == 42_000
    assert snapshot.context_window == 128_000
    assert snapshot.context_percent == 33
    assert snapshot.context_source == "usage"