import pytest

from ai_platform.lead_scoring.domain.scoring import (
    Rule,
    ScoringConfiguration,
    derive_metrics,
    score_rules,
)

CAPTURED = "2025-09-25T10:00:00Z"


def _msg(sender, sent_at):
    return {"sender_type": sender, "sent_at": sent_at}


def _conv(*messages):
    return {"messages": list(messages)}


def _metrics(*conversations):
    return derive_metrics({"captured_at": CAPTURED, "conversations": list(conversations)})


def test_counts_and_turns_use_timestamps_not_array_order():
    conversations = [
        _conv(
            _msg("agent", "2025-09-25T11:00:00Z"),
            _msg("contact", "2025-09-25T09:00:00Z"),
            _msg("agent", "2025-09-25T10:00:00Z"),
        ),
        _conv(_msg("contact", "2025-09-25T11:00:00Z"), _msg("agent", "2025-09-25T10:00:00Z")),
    ]
    metrics = _metrics(*conversations)
    for conversation in conversations:
        conversation["messages"].reverse()

    assert metrics["conversation_turn_count"] == 4
    assert metrics["contact_started_conversation_count"] == 1
    assert metrics["contact_message_count"] == 2
    assert _metrics(*conversations) == metrics


@pytest.mark.parametrize(
    ("sent_at", "hours", "days"),
    [
        ("2025-09-25T08:46:00Z", 1.23, 0.05),
        ("2025-09-25T08:00:00+02:00", 4.0, 0.17),
        ("2025-09-25T11:00:00Z", 0.0, 0.0),
    ],
)
def test_contact_recency_is_rounded_clamped_and_timezone_aware(sent_at, hours, days):
    metrics = _metrics(_conv(_msg("contact", "not-a-timestamp"), _msg("contact", sent_at)))

    assert metrics["contact_message_recency_hours"] == hours
    assert metrics["contact_message_recency_days"] == days


def test_no_contact_messages_means_no_recency_and_no_return():
    metrics = _metrics(_conv(), _conv(_msg("agent", "2025-09-25T09:00:00Z")))

    assert metrics["conversation_count"] == 2
    assert metrics["contact_message_count"] == 0
    assert metrics["contact_message_recency_hours"] is None
    assert metrics["customer_initiated_return"] is False


def test_customer_initiated_return_uses_chronology_and_breaks_ties_by_position():
    agent = _conv(_msg("agent", "2025-09-25T08:00:00Z"))
    contact = _conv(_msg("contact", "2025-09-25T09:00:00Z"))
    later = _conv(_msg("contact", "2025-09-25T10:00:00Z"))
    tie_agent = _conv(_msg("agent", "2025-09-25T07:00:00Z"))
    tie_contact = _conv(_msg("contact", "2025-09-25T07:00:00Z"))

    assert _metrics(later, _conv(), agent, contact)["customer_initiated_return"] is True
    assert _metrics(contact, later, agent)["contact_started_conversation_count"] == 2
    assert _metrics(tie_agent, tie_contact)["customer_initiated_return"] is True
    assert _metrics(tie_contact, tie_agent)["customer_initiated_return"] is False


def test_caller_rules_see_the_derived_metrics_and_booleans_never_match_numbers():
    snapshot = {
        "captured_at": CAPTURED,
        "lead_profile": {"name": "Example", "email": "a@example.invalid", "custom_fields": {}},
        "conversations": [
            _conv(_msg("contact", "2025-09-24T10:00:00Z"), _msg("agent", "2025-09-25T09:00:00Z")),
            _conv(_msg("bot", "2025-09-25T09:30:00Z")),
        ],
    }
    rules = (
        Rule("profile", "metrics.profile_field_count", "eq", 2, 1),
        Rule("conversations", "metrics.conversation_count", "eq", 2, 1),
        Rule("messages", "metrics.message_count", "eq", 3, 1),
        Rule("contacts", "metrics.contact_message_count", "eq", 1, 1),
        Rule("turns", "metrics.conversation_turn_count", "eq", 3, 1),
        Rule("started", "metrics.contact_started_conversation_count", "eq", 1, 1),
        Rule("recency", "metrics.contact_message_recency_days", "eq", 1.0, 1),
        Rule("bool-as-number", "metrics.customer_initiated_return", "eq", 1, 1),
    )

    score, breakdown = score_rules(snapshot, ScoringConfiguration(rules, 1.0, 0.0))

    assert score == 7
    assert [item["matched"] for item in breakdown] == [True] * 7 + [False]