"""Token-parameter selection for provider setup (REAL src.llm_core).

Split from `test_provider_classification.py` to keep the token-param quirk
separate from provider identification and error formatting.

  * `_uses_max_completion_tokens` — the gpt-5 / o-series quirk that the probe
    and chat payload builders branch on.

conftest.py stubs the heavy deps (sqlalchemy, src.database), so importing the
real module is side-effect free.
"""
import pytest

from src.llm_core import _uses_max_completion_tokens


# ── _uses_max_completion_tokens ──
# gpt-5 / o-series need `max_completion_tokens`; everything else `max_tokens`.

class TestUsesMaxCompletionTokens:
    @pytest.mark.parametrize("model", [
        "gpt-5", "gpt-5.2", "gpt-5-mini", "o1", "o1-preview", "o3", "o3-mini",
        "o4-mini", "gpt-4.5", "gpt-4.5-preview", "openrouter/openai/o3",
    ])
    def test_requires_max_completion_tokens(self, model):
        assert _uses_max_completion_tokens(model) is True

    @pytest.mark.parametrize("model", [
        # gpt-4o must NOT be confused with the o-series ("o4"/"o1" tokens).
        "gpt-4o", "gpt-4o-mini", "gpt-4.1", "claude-opus-4", "llama-3.3-70b",
        "deepseek-chat", "", None,
    ])
    def test_uses_plain_max_tokens(self, model):
        assert _uses_max_completion_tokens(model) is False