"""
Integration coverage for the adaptive routing workplan flow.
"""

from datetime import datetime, timezone

from examples.adaptive_routing_fixture_batch import populate_ledger
from llm_connect.adapter import MockLLMAdapter
from llm_connect.quality import QualityLedger, QualityObservation
from llm_connect.routing import AdaptiveRoutingPolicy, RoutingRule


def append_quality(
    ledger: QualityLedger,
    adapter_id: str,
    quality_score: float,
    cost_usd: float,
    *,
    recorded_at: datetime,
) -> None:
    ledger.append(
        QualityObservation(
            task_type="summarize",
            adapter_id=adapter_id,
            model_id=f"{adapter_id}-model",
            cost_usd=cost_usd,
            quality_score=quality_score,
            latency_ms=100,
            tokens_in=100,
            tokens_out=50,
            recorded_at=recorded_at,
            baseline_adapter_id="baseline",
        )
    )


def test_adaptive_policy_converges_to_cheapest_qualifying_adapter(tmp_path):
    cheap = MockLLMAdapter("cheap")
    mid = MockLLMAdapter("mid")
    smart = MockLLMAdapter("smart")
    ledger = QualityLedger(tmp_path / "quality.jsonl")
    policy = AdaptiveRoutingPolicy(
        rules=[
            RoutingRule(
                "summarize",
                prefer=smart,
                max_cost_per_1k=1.0,
                fallback=mid,
            )
        ],
        ledger=ledger,
        adapters_by_id={"cheap": cheap, "mid": mid, "smart": smart},
        window_size=2,
    )

    assert policy.resolve("summarize", quality_floor=0.8) is smart
    assert policy.resolve("summarize", 2.0, quality_floor=0.8) is mid

    append_quality(
        ledger,
        "cheap",
        quality_score=0.7,
        cost_usd=0.01,
        recorded_at=datetime(2026, 5, 17, 10, tzinfo=timezone.utc),
    )
    append_quality(
        ledger,
        "mid",
        quality_score=0.86,
        cost_usd=0.02,
        recorded_at=datetime(2026, 5, 17, 10, tzinfo=timezone.utc),
    )
    append_quality(
        ledger,
        "smart",
        quality_score=0.95,
        cost_usd=0.05,
        recorded_at=datetime(2026, 5, 17, 10, tzinfo=timezone.utc),
    )

    assert policy.resolve("summarize", quality_floor=0.8) is mid

    append_quality(
        ledger,
        "cheap",
        quality_score=0.95,
        cost_usd=0.01,
        recorded_at=datetime(2026, 5, 17, 11, tzinfo=timezone.utc),
    )

    assert policy.resolve("summarize", quality_floor=0.8) is cheap


def test_fixture_batch_populates_three_candidate_observations_per_task(tmp_path):
    ledger = QualityLedger(tmp_path / "quality.jsonl")

    populate_ledger(ledger)

    observations = ledger.read_all()
    by_task_type: dict[str, set[str]] = {}
    for observation in observations:
        by_task_type.setdefault(observation.task_type, set()).add(observation.adapter_id)

    assert set(by_task_type) == {
        "summarize-source",
        "extract-relations",
        "evaluate-entity",
    }
    assert all(len(adapter_ids) == 3 for adapter_ids in by_task_type.values())