from src.models import UsageSummary
from src.pricing import estimate_cost_usd, normalize_model_for_pricing


def test_normalize_model_for_pricing() -> None:
    assert normalize_model_for_pricing("gpt-5.4-mini") == "gpt-5.4-mini"
    assert normalize_model_for_pricing("gpt-5.4-mini-2026-05-01") == "gpt-5.4-mini"
    assert normalize_model_for_pricing("unknown-model") == "unknown-model"


def test_estimate_cost_with_cached_tokens() -> None:
    usage = UsageSummary(
        input_tokens=100_000,
        cached_input_tokens=20_000,
        output_tokens=50_000,
        total_tokens=150_000,
    )
    cost, model = estimate_cost_usd("gpt-5.4-mini", usage)
    assert model == "gpt-5.4-mini"
    assert cost is not None
    # Non-cached input: 80k at $0.75/M = 0.06
    # Cached input: 20k at $0.075/M = 0.0015
    # Output: 50k at $4.50/M = 0.225
    assert abs(cost - 0.2865) < 1e-9


def test_estimate_cost_unknown_model_returns_none() -> None:
    usage = UsageSummary(input_tokens=10, output_tokens=10)
    cost, model = estimate_cost_usd("my-new-model", usage)
    assert model == "my-new-model"
    assert cost is None