Extract shared build_metric_registry factory (DRY)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

tests/test_advisor_llm_analyzer.py

@@ -0,0 +1,141 @@
+"""Tests for the optimization advisor's direct-LLM analyzer.
+
+These tests inject a fake async chat client so no network call is made. They
+verify that analyze() uses a plain chat.completions call (not the removed
+langchain path), returns the text from choices[0].message.content, embeds the
+worked-example instructions and the low-sample contexts in the prompt, and
+selects the correct token parameter for reasoning vs. legacy models.
+"""
+
+from __future__ import annotations
+
+import asyncio
+
+from rag_eval.advisor.llm_analyzer import analyze, _is_reasoning_model
+from rag_eval.advisor.rules import Diagnosis
+
+
+class _FakeMessage:
+    def __init__(self, content: str) -> None:
+        self.content = content
+
+
+class _FakeChoice:
+    def __init__(self, content: str) -> None:
+        self.message = _FakeMessage(content)
+
+
+class _FakeResponse:
+    def __init__(self, content: str) -> None:
+        self.choices = [_FakeChoice(content)]
+
+
+class _FakeCompletions:
+    def __init__(self, captured: dict) -> None:
+        self._captured = captured
+
+    async def create(self, **kwargs):
+        self._captured.update(kwargs)
+        return _FakeResponse("## faithfulness [警告]\n\n针对该问题的具体优化建议")
+
+
+class _FakeChat:
+    def __init__(self, captured: dict) -> None:
+        self.completions = _FakeCompletions(captured)
+
+
+class _FakeClient:
+    def __init__(self, captured: dict) -> None:
+        self.chat = _FakeChat(captured)
+        self.closed = False
+
+    async def close(self) -> None:
+        self.closed = True
+
+
+class _Settings:
+    ragas_llm_max_tokens = 4096
+
+
+def _diagnosis() -> Diagnosis:
+    return Diagnosis(
+        metric="faithfulness",
+        mean_score=0.55,
+        threshold=0.7,
+        severity="warning",
+        root_causes=["生成未严格 grounding"],
+        suggested_actions=["强化 grounding 约束"],
+        low_samples=[
+            {
+                "sample_id": "s1",
+                "question": "球管寿命如何评估？",
+                "answer": "球管寿命约 3 年。",
+                "ground_truth": "球管寿命取决于使用强度。",
+                "contexts": "球管寿命与扫描负载相关 |||| 高负载会缩短寿命",
+                "faithfulness": 0.4,
+            }
+        ],
+    )
+
+
+def test_analyze_uses_direct_chat_and_returns_content() -> None:
+    captured: dict = {}
+    text = asyncio.run(
+        analyze([_diagnosis()], "scn", "gpt-4o", _Settings(), chat_client=_FakeClient(captured))
+    )
+    assert "优化建议" in text
+    assert captured["model"] == "gpt-4o"
+    prompt = captured["messages"][0]["content"]
+    assert "举例拆解" in prompt          # worked-example instruction present
+    assert "球管寿命与扫描负载相关" in prompt  # low-sample contexts embedded
+    assert "max_tokens" in captured       # legacy model uses max_tokens
+    assert "max_completion_tokens" not in captured
+
+
+def test_analyze_reasoning_model_uses_max_completion_tokens() -> None:
+    captured: dict = {}
+    asyncio.run(
+        analyze([_diagnosis()], "scn", "gpt-5", _Settings(), chat_client=_FakeClient(captured))
+    )
+    assert "max_completion_tokens" in captured
+    assert "max_tokens" not in captured
+
+
+def test_analyze_empty_diagnoses_returns_empty() -> None:
+    assert asyncio.run(analyze([], "scn", "gpt-4o", _Settings())) == ""
+
+
+def test_analyze_closes_client_it_creates(monkeypatch) -> None:
+    """A self-created client is closed in-loop to avoid 'Event loop is closed'."""
+    captured: dict = {}
+    fake = _FakeClient(captured)
+
+    import openai
+    import rag_eval.metrics.factory as factory_mod
+
+    monkeypatch.setattr(openai, "AsyncOpenAI", lambda **kwargs: fake)
+    monkeypatch.setattr(
+        factory_mod, "resolve_openai_client_kwargs", lambda *a, **k: {"api_key": "x"}
+    )
+
+    # No chat_client passed → analyze() builds (and must close) its own client.
+    text = asyncio.run(analyze([_diagnosis()], "scn", "gpt-4o", _Settings()))
+
+    assert "优化建议" in text
+    assert fake.closed is True
+
+
+def test_analyze_does_not_close_injected_client() -> None:
+    """An injected client is owned by the caller and must not be closed."""
+    fake = _FakeClient({})
+    asyncio.run(analyze([_diagnosis()], "scn", "gpt-4o", _Settings(), chat_client=fake))
+    assert fake.closed is False
+
+
+def test_is_reasoning_model_detection() -> None:
+    assert _is_reasoning_model("gpt-5")
+    assert _is_reasoning_model("gpt-5.5")
+    assert _is_reasoning_model("o1-mini")
+    assert _is_reasoning_model("o3")
+    assert not _is_reasoning_model("gpt-4o")
+    assert not _is_reasoning_model("deepseek-v4-flash")