103 lines
3.3 KiB
Python
103 lines
3.3 KiB
Python
"""Regression tests: OpenAI reasoning models reject a non-default temperature.
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o1/o3/o4/gpt-5 only accept the default temperature (1); sending an explicit
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value — even 0.0 — returns HTTP 400 "Only the default (1) value is supported".
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The OpenAI-compatible payload builders must omit the temperature field for these
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models so chat (with a non-default preset) and endpoint probing don't break.
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"""
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import httpx
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import pytest
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from src import llm_core
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@pytest.mark.parametrize(
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"model",
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["o1", "o1-mini", "o3", "o3-mini", "o4-mini", "gpt-5", "gpt-5-mini",
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"openrouter/openai/o3-mini", "OpenAI/GPT-5"],
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)
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def test_reasoning_models_restrict_temperature(model):
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assert llm_core._restricts_temperature(model) is True
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@pytest.mark.parametrize(
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"model",
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["gpt-4o", "gpt-4.1", "gpt-3.5-turbo", "gpt-4.5-preview",
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"claude-3-5-sonnet", "llama3.1", "", None],
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)
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def test_normal_models_allow_temperature(model):
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assert llm_core._restricts_temperature(model) is False
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def _capture_openai_payload(monkeypatch, model, temperature):
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"""Run a synchronous OpenAI-compatible call and return the posted JSON body."""
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llm_core._response_cache.clear()
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seen = {}
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def fake_post(url, headers=None, json=None, timeout=None):
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seen["json"] = json
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request = httpx.Request("POST", url)
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return httpx.Response(
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200,
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request=request,
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json={"choices": [{"message": {"content": "OK"}}]},
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)
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monkeypatch.setattr(llm_core.httpx, "post", fake_post)
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result = llm_core.llm_call(
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"https://api.openai.com/v1/chat/completions",
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model,
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[{"role": "user", "content": "Say OK"}],
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temperature=temperature,
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max_tokens=5,
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)
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assert result == "OK"
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return seen["json"]
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def test_reasoning_model_payload_omits_temperature(monkeypatch):
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payload = _capture_openai_payload(monkeypatch, "o3-mini", 0.0)
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assert "temperature" not in payload
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# Reasoning models also use max_completion_tokens, which must survive.
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assert payload["max_completion_tokens"] == 5
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def test_normal_model_payload_keeps_temperature(monkeypatch):
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payload = _capture_openai_payload(monkeypatch, "gpt-4o", 0.2)
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assert payload["temperature"] == 0.2
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assert payload["max_tokens"] == 5
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def test_normal_model_payload_keeps_temperature_above_one(monkeypatch):
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# OpenAI/local providers may validly use temperatures above 1.0; the clamp
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# is Anthropic-only and must not touch this path.
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payload = _capture_openai_payload(monkeypatch, "gpt-4o", 1.2)
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assert payload["temperature"] == 1.2
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def _anthropic_payload(temperature):
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return llm_core._build_anthropic_payload(
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"claude-3-5-sonnet",
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[{"role": "user", "content": "Hi"}],
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temperature,
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max_tokens=5,
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)
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def test_anthropic_payload_clamps_above_one():
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# Anthropic rejects temperature > 1.0 (e.g. the Nietzsche preset's 1.2).
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assert _anthropic_payload(1.2)["temperature"] == 1.0
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def test_anthropic_payload_keeps_in_range():
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assert _anthropic_payload(0.7)["temperature"] == 0.7
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def test_anthropic_payload_clamps_negative():
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assert _anthropic_payload(-0.5)["temperature"] == 0.0
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def test_anthropic_payload_none_temperature_does_not_crash():
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payload = _anthropic_payload(None)
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assert payload["temperature"] is None
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