from copy import deepcopy

import pytest
from pydantic import ValidationError

from ai_platform.presentation.http.schemas import RunRequest


@pytest.mark.parametrize(
    ("field", "operator", "value"),
    [
        ("custom_fields.interest.region", "eq", "north"),
        ("lead_profile.email", "exists", None),
        ("lead_profile.custom_fields.course", "contains", "IELTS"),
        ("metrics.profile_field_count", "gte", 1),
        ("metrics.conversation_count", "gte", 1),
        ("metrics.conversation_turn_count", "gte", 3),
        ("metrics.contact_started_conversation_count", "eq", 1),
        ("metrics.contact_message_recency_hours", "gte", 1.5),
        ("metrics.customer_initiated_return", "eq", True),
        ("metrics.customer_initiated_return", "ne", False),
        ("metrics.customer_message_count", "exists", None),
    ],
)
def test_rules_accept_supported_customer_field_paths(valid_run_payload, field, operator, value):
    data = deepcopy(valid_run_payload)
    data["scoring_config"]["rules"][0].update(field=field, operator=operator, value=value)

    request = RunRequest.model_validate(data)

    assert request.scoring_config.rules[0].field == field


@pytest.mark.parametrize(
    ("field", "operator", "value", "points"),
    [
        ("snapshot.conversations", "exists", None, 1),
        ("custom_fields..region", "eq", "north", 1),
        ("metrics.unknown_metric", "eq", 1, 1),
        ("metrics.conversation_turn_count", "eq", 1.0, 1),
        ("metrics.contact_started_conversation_count", "contains", 1, 1),
        ("metrics.customer_message_count", "gt", True, 1),
        ("metrics.contact_message_recency_days", "contains", 1, 1),
        ("metrics.contact_message_recency_hours", "contains", 1, 1),
        ("metrics.customer_initiated_return", "eq", 1, 1),
        ("metrics.customer_initiated_return", "ne", 0, 1),
        ("metrics.customer_initiated_return", "gt", True, 1),
        ("metrics.customer_initiated_return", "contains", True, 1),
        ("metrics.customer_initiated_return", "exists", None, 1),
        ("custom_fields.age", "gte", "18", 1),
        ("custom_fields.age", "gt", True, 1),
        ("custom_fields.age", "eq", None, 1),
        ("custom_fields.age", "exists", "not-null", 1),
        ("custom_fields.region", "eq", {"value": "north"}, 1),
        ("custom_fields.tags", "contains", ["nested"], 1),
        ("custom_fields.age", "eq", 18, True),
        ("custom_fields.age", "eq", 18, 1.5),
    ],
)
def test_rules_reject_invalid_paths_values_and_points(
    valid_run_payload, field, operator, value, points
):
    data = deepcopy(valid_run_payload)
    data["scoring_config"]["rules"][0].update(
        field=field, operator=operator, value=value, points=points
    )

    with pytest.raises(ValidationError):
        RunRequest.model_validate(data)


def test_rule_values_enforce_size_limits(valid_run_payload):
    data = deepcopy(valid_run_payload)
    data["scoring_config"]["rules"][0]["value"] = "x" * 1_001

    with pytest.raises(ValidationError, match="1000 characters"):
        RunRequest.model_validate(data)

    data["scoring_config"]["rules"][0].update(operator="contains", value=["x"] * 101)
    with pytest.raises(ValidationError, match="100 items"):
        RunRequest.model_validate(data)


def test_scoring_weights_reject_boolean_and_string_types(valid_run_payload):
    for rule_weight, ai_weight in ((True, 0), (0.5, "0.5")):
        data = deepcopy(valid_run_payload)
        data["scoring_config"]["rule_weight"] = rule_weight
        data["scoring_config"]["ai_weight"] = ai_weight

        with pytest.raises(ValidationError):
            RunRequest.model_validate(data)