"""Lifespan scan-loop test (v1.1.0 defect fix).

`scan_and_enqueue_tasks` previously had no scheduler — the OpenClaw Worker
wakes every minute but could never pull a task. The lifespan now starts an
asyncio background task that scans executing evals every 60s. This test
verifies that on application startup the scan is actually invoked.
"""
from unittest.mock import MagicMock

from fastapi.testclient import TestClient


def test_lifespan_starts_scan_loop(monkeypatch):
    """Lifespan startup must invoke the intelligent-eval scan loop once."""
    import agenteval.intelligent_eval.task_queue as tq
    import agenteval.web.app as app_mod

    calls: list[int] = []
    real_scan = tq.scan_and_enqueue_tasks

    def fake_scan(session):
        calls.append(1)
        return real_scan(session)

    # The scan loop calls get_session() to open a DB session; replace it with a
    # no-op mock so the test does not touch the real SQLite file.
    monkeypatch.setattr(app_mod, "get_session", lambda: MagicMock())
    monkeypatch.setattr(tq, "scan_and_enqueue_tasks", fake_scan)

    with TestClient(app_mod.app) as client:
        assert client.get("/api/health").status_code == 200

    # The background task runs immediately (before its first 60s sleep).
    assert calls, "scan_and_enqueue_tasks should have been invoked on startup"


def test_trigger_worker_skips_when_no_pending(monkeypatch):
    """No pending task → no docker exec invocation."""
    import asyncio
    import subprocess
    from unittest.mock import MagicMock

    import agenteval.web.app as app_mod

    calls: list = []
    monkeypatch.setattr(app_mod, "_has_pending_task", lambda: False)

    def fake_run(cmd, **kwargs):
        calls.append(cmd)
        return MagicMock(returncode=0, stderr="")

    monkeypatch.setattr(subprocess, "run", fake_run)

    assert asyncio.run(app_mod._trigger_intelligent_worker()) is False
    assert not calls, "should not invoke docker exec when queue is empty"


def test_trigger_worker_calls_docker_exec(monkeypatch):
    """Pending task present → invoke `docker exec openclaw-eval openclaw agent`."""
    import asyncio
    import subprocess
    from unittest.mock import MagicMock

    import agenteval.web.app as app_mod

    calls: list = []
    monkeypatch.setattr(app_mod, "_has_pending_task", lambda: True)

    def fake_run(cmd, **kwargs):
        calls.append(cmd)
        return MagicMock(returncode=0, stderr="")

    monkeypatch.setattr(subprocess, "run", fake_run)

    assert asyncio.run(app_mod._trigger_intelligent_worker()) is True
    assert calls, "docker exec should be invoked"
    joined = " ".join(calls[0])
    assert "docker" in joined and "openclaw" in joined
    assert "agenteval-intelligent-worker" in joined
    assert "--agent" in joined and "main" in joined


def test_trigger_worker_msg_has_execute_semantics(monkeypatch):
    """The trigger message must instruct immediate execution (no cron state).

    `openclaw agent` has no cron state; a bare skill name makes the worker
    skill "decide then wait for the next tick", deadlocking. The message must
    say "立即完成当前任务 / 不要等待下一节拍".
    """
    import asyncio
    import subprocess
    from unittest.mock import MagicMock

    import agenteval.web.app as app_mod

    calls: list = []
    monkeypatch.setattr(app_mod, "_has_pending_task", lambda: True)

    def fake_run(cmd, **kwargs):
        calls.append(cmd)
        return MagicMock(returncode=0, stderr="")

    monkeypatch.setattr(subprocess, "run", fake_run)

    asyncio.run(app_mod._trigger_intelligent_worker())
    joined = " ".join(calls[0])
    assert "不要等待下一节拍" in joined
    assert "立即完成当前任务" in joined
    assert "agenteval-intelligent-worker" in joined
    assert "agenteval-intelligent-analyst" in joined


def test_supplement_execute_session_log(monkeypatch, db_session):
    """Executing eval with deficit and no execute_session log → platform backfills."""
    import agenteval.web.app as app_mod
    from agenteval.intelligent_eval.models import IntelligentEvalStatus
    from agenteval.storage.db import IntelligentEvalDB

    ev = IntelligentEvalDB(
        name="supp-eval", target_id="t1",
        status=IntelligentEvalStatus.EXECUTING.value, started_at=__import__("agenteval.storage.db", fromlist=["utc_now"]).utc_now(),
    )
    ev.set_plan({"time_distribution": [{"time_slot": "0-1h", "sessions": 1}], "estimated_sessions": 1})
    db_session.add(ev)
    db_session.commit()

    assert app_mod._supplement_decision_logs(db_session) == 1
    # second call: already backfilled → 0
    assert app_mod._supplement_decision_logs(db_session) == 0


def test_supplement_start_analysis_log(monkeypatch, db_session):
    """Executing eval with all sessions completed and no start_analysis → backfill."""
    import agenteval.web.app as app_mod
    from agenteval.intelligent_eval.models import IntelligentEvalStatus
    from agenteval.storage.db import IntelligentEvalDB, IntelligentEvalSessionDB, utc_now

    ev = IntelligentEvalDB(
        name="supp-eval2", target_id="t1",
        status=IntelligentEvalStatus.EXECUTING.value, started_at=utc_now(),
    )
    ev.set_plan({"time_distribution": [{"time_slot": "0-1h", "sessions": 1}], "estimated_sessions": 1})
    db_session.add(ev)
    db_session.commit()
    s = IntelligentEvalSessionDB(eval_id=ev.id, target_id=ev.target_id, status="completed", goal="g")
    db_session.add(s)
    db_session.commit()

    assert app_mod._supplement_decision_logs(db_session) == 1