test(review): 新增 pytest 离线回归网，锁定 dwg_review 既有行为
在改动审查流水线（确定性检查前置 / 结论结构化 / 证据交叉校验）之前， 先立一张离线、确定性、秒级的回归网。 - tests/fakes.py：假 LLM + 假 MCP 基座 + 响应构造器（ok_text/ok_image/err） + make_ctx/make_evidence，绝不触网、不读密钥 - 10 个模块共 134 用例： mcp_client / llm_client / cad_tools / checklist / config / planning / evidence / review / report / annotator - pytest.ini（testpaths=tests）+ requirements-dev.txt + 根 conftest.py （sys.path + RENDER_WAIT=0 / REPORT_DIR=tmp fixture）
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"""`dwg_review.llm_client` 单元测试（绝不真实调用 LLM）。"""
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import base64
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import io
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import pytest
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from dwg_review import config
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from dwg_review import llm_client as llm_module
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from dwg_review.llm_client import LlmClient, LlmError, downsample_image_b64
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from tests.fakes import llm_text
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# ---------------------------------------------------------------------------
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# 假 OpenAI SDK
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# ---------------------------------------------------------------------------
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class _Completions:
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def __init__(self, outer):
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self.outer = outer
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def create(self, **kwargs):
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self.outer.kwargs.append(kwargs)
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if self.outer.raises:
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raise RuntimeError("upstream boom")
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return self.outer.result
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class _Chat:
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def __init__(self, outer):
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self.completions = _Completions(outer)
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class _FakeOpenAI:
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def __init__(self, **kwargs):
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self.init_kwargs = kwargs
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self.kwargs = []
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self.raises = False
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self.result = None
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self.chat = _Chat(self)
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@pytest.fixture
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def fake_openai(monkeypatch):
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monkeypatch.setattr(llm_module, "OpenAI", _FakeOpenAI)
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monkeypatch.setattr(llm_module.time, "sleep", lambda *_: None)
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return _FakeOpenAI
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def build_client(fake_openai, **kw):
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return LlmClient(api_key="sk-test", **kw)
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# ---------------------------------------------------------------------------
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# 构造
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# ---------------------------------------------------------------------------
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def test_init_requires_api_key(monkeypatch):
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monkeypatch.setattr(config, "API_KEY", "")
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with pytest.raises(LlmError):
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LlmClient()
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def test_init_passes_key_and_base_url(fake_openai):
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client = LlmClient(api_key="sk-abc", base_url="https://example.test")
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assert client._client.init_kwargs["api_key"] == "sk-abc"
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assert client._client.init_kwargs["base_url"] == "https://example.test"
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def test_init_uses_config_defaults(fake_openai, monkeypatch):
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monkeypatch.setattr(config, "MODEL_NAME", "test-model")
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monkeypatch.setattr(config, "BASE_URL", "https://cfg.test")
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client = LlmClient(api_key="sk-abc")
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assert client.model == "test-model"
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assert client._client.init_kwargs["base_url"] == "https://cfg.test"
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# ---------------------------------------------------------------------------
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# chat / chat_text
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# ---------------------------------------------------------------------------
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def test_chat_returns_raw_response(fake_openai):
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client = build_client(fake_openai)
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client._client.result = llm_text("hi")
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resp = client.chat([{"role": "user", "content": "x"}])
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assert resp.choices[0].message.content == "hi"
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def test_chat_includes_tools_only_when_present(fake_openai):
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client = build_client(fake_openai)
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client._client.result = llm_text("x")
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client.chat([{"role": "user", "content": "x"}])
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assert "tools" not in client._client.kwargs[0]
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client.chat([{"role": "user", "content": "x"}], tools=[{"type": "function"}])
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assert client._client.kwargs[1]["tools"] == [{"type": "function"}]
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def test_chat_wraps_exception_into_llmerror(fake_openai):
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client = build_client(fake_openai)
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client._client.raises = True
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with pytest.raises(LlmError):
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client.chat([{"role": "user", "content": "x"}], retries=0)
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def test_chat_retries_then_succeeds(fake_openai):
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client = build_client(fake_openai)
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class Flaky(_Completions):
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def __init__(self, outer):
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super().__init__(outer)
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self.n = 0
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def create(self, **kwargs):
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self.n += 1
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if self.n < 3:
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raise RuntimeError("transient")
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return llm_text("ok")
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client._client.chat.completions = Flaky(client._client)
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resp = client.chat([{"role": "user", "content": "x"}], retries=2)
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assert resp.choices[0].message.content == "ok"
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assert client._client.chat.completions.n == 3
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def test_chat_text_returns_assistant_text(fake_openai):
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client = build_client(fake_openai)
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client._client.result = llm_text("报告正文")
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assert client.chat_text("sys", "user") == "报告正文"
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def test_image_content_format():
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block = LlmClient.image_content("QUJD", "image/jpeg")
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assert block == {
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"type": "image_url",
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"image_url": {"url": "data:image/jpeg;base64,QUJD"},
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}
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# ---------------------------------------------------------------------------
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# 截图下采样
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# ---------------------------------------------------------------------------
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def test_downsample_passthrough_without_pil(monkeypatch):
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monkeypatch.setattr(llm_module, "HAS_PIL", False)
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assert downsample_image_b64("QUJD", "image/png", max_edge=10) == ("QUJD", "image/png")
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def test_downsample_passthrough_when_max_edge_zero():
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assert downsample_image_b64("QUJD", "image/png", max_edge=0) == ("QUJD", "image/png")
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def test_downsample_passthrough_when_no_resize_needed():
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pytest.importorskip("PIL")
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from PIL import Image
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buf = io.BytesIO()
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Image.new("RGB", (100, 80), "white").save(buf, format="PNG")
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b64 = base64.b64encode(buf.getvalue()).decode("ascii")
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out, mime = downsample_image_b64(b64, "image/png", max_edge=1280)
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assert out == b64 and mime == "image/png"
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def test_downsample_resizes_large_image():
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pytest.importorskip("PIL")
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from PIL import Image
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buf = io.BytesIO()
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Image.new("RGB", (2000, 1000), "white").save(buf, format="PNG")
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b64 = base64.b64encode(buf.getvalue()).decode("ascii")
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out, mime = downsample_image_b64(b64, "image/png", max_edge=500)
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assert mime == "image/png"
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img = Image.open(io.BytesIO(base64.b64decode(out)))
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assert max(img.size) <= 500
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def test_downsample_converts_to_jpeg():
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pytest.importorskip("PIL")
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from PIL import Image
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buf = io.BytesIO()
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Image.new("RGB", (2000, 1000), "white").save(buf, format="PNG")
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b64 = base64.b64encode(buf.getvalue()).decode("ascii")
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out, mime = downsample_image_b64(b64, "image/png", max_edge=400, fmt="jpeg")
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assert mime == "image/jpeg"
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assert Image.open(io.BytesIO(base64.b64decode(out))).format == "JPEG"
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def test_downsample_bad_base64_returns_original():
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pytest.importorskip("PIL")
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bad = base64.b64encode(b"this is not an image").decode("ascii")
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assert downsample_image_b64(bad, "image/png", max_edge=10) == (bad, "image/png")
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