test: split llm-core temperature tests (#4935)

tests/test_llm_core_temperature_reasoning.py

@@ -0,0 +1,111 @@
+"""Regression tests: OpenAI reasoning models reject a non-default temperature.
+
+o1/o3/o4/gpt-5 only accept the default temperature (1); sending an explicit
+value — even 0.0 — returns HTTP 400 "Only the default (1) value is supported".
+The OpenAI-compatible payload builders must omit the temperature field for these
+models so chat (with a non-default preset) and endpoint probing don't break.
+"""
+import httpx
+import pytest
+
+from src import llm_core
+
+
+@pytest.mark.parametrize(
+    "model",
+    ["o1", "o1-mini", "o3", "o3-mini", "o4-mini", "gpt-5", "gpt-5-mini",
+     "openrouter/openai/o3-mini", "OpenAI/GPT-5", "kimi-for-coding"],
+)
+def test_reasoning_models_restrict_temperature(model):
+    assert llm_core._restricts_temperature(model) is True
+
+
+@pytest.mark.parametrize(
+    "model",
+    ["gpt-4o", "gpt-4.1", "gpt-3.5-turbo", "gpt-4.5-preview",
+     "claude-3-5-sonnet", "llama3.1", "", None],
+)
+def test_normal_models_allow_temperature(model):
+    assert llm_core._restricts_temperature(model) is False
+
+
+def _capture_openai_payload(
+    monkeypatch,
+    model,
+    temperature,
+    url="https://api.openai.com/v1/chat/completions",
+):
+    """Run a synchronous OpenAI-compatible call and return the posted JSON body."""
+    llm_core._response_cache.clear()
+    seen = {}
+
+    def fake_post(url, headers=None, json=None, timeout=None):
+        seen["json"] = json
+        request = httpx.Request("POST", url)
+        return httpx.Response(
+            200,
+            request=request,
+            json={"choices": [{"message": {"content": "OK"}}]},
+        )
+
+    monkeypatch.setattr(llm_core.httpx, "post", fake_post)
+    result = llm_core.llm_call(
+        url,
+        model,
+        [{"role": "user", "content": "Say OK"}],
+        temperature=temperature,
+        max_tokens=5,
+    )
+    assert result == "OK"
+    return seen["json"]
+
+
+def test_reasoning_model_payload_omits_temperature(monkeypatch):
+    payload = _capture_openai_payload(monkeypatch, "o3-mini", 0.0)
+    assert "temperature" not in payload
+    # Reasoning models also use max_completion_tokens, which must survive.
+    assert payload["max_completion_tokens"] == 5
+
+
+def test_kimi_for_coding_payload_omits_temperature(monkeypatch):
+    payload = _capture_openai_payload(monkeypatch, "kimi-for-coding", 0.1)
+    assert "temperature" not in payload
+    assert payload["max_tokens"] == 5
+
+
+def test_normal_model_payload_keeps_temperature(monkeypatch):
+    payload = _capture_openai_payload(monkeypatch, "gpt-4o", 0.2)
+    assert payload["temperature"] == 0.2
+    assert payload["max_tokens"] == 5
+
+
+def test_normal_model_payload_keeps_temperature_above_one(monkeypatch):
+    # OpenAI/local providers may validly use temperatures above 1.0; the clamp
+    # is Anthropic-only and must not touch this path.
+    payload = _capture_openai_payload(monkeypatch, "gpt-4o", 1.2)
+    assert payload["temperature"] == 1.2
+
+
+def test_chatgpt_subscription_payload_omits_max_output_tokens():
+    # ChatGPT Subscription Codex API does not support max_output_tokens —
+    # passing it returns HTTP 400 "Unsupported parameter: max_output_tokens".
+    # The payload should NOT include max_output_tokens regardless of max_tokens.
+    payload = llm_core._build_chatgpt_responses_payload(
+        "gpt-5.1-codex",
+        [{"role": "user", "content": "Say OK"}],
+        temperature=0.2,
+        max_tokens=37,
+    )
+
+    assert "max_output_tokens" not in payload
+
+
+def test_chatgpt_subscription_payload_omits_max_output_tokens_when_zero():
+    payload = llm_core._build_chatgpt_responses_payload(
+        "gpt-5.1-codex",
+        [{"role": "user", "content": "Say OK"}],
+        temperature=0.2,
+        max_tokens=0,
+    )
+
+    assert "max_output_tokens" not in payload