72 lines
2.3 KiB
Python
72 lines
2.3 KiB
Python
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from app.analyzer import LLMClient, build_analysis_prompt, select_relevant_skills
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from app.config import ProviderConfig
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from app.docx_parser import ParsedDocument
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from app.skill_loader import Skill
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class DummyResponse:
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def raise_for_status(self) -> None:
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return None
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def json(self) -> dict:
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return {"choices": [{"message": {"content": "分析结果"}}]}
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class DummySession:
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def __init__(self) -> None:
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self.calls = []
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def post(self, url: str, **kwargs):
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self.calls.append((url, kwargs))
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return DummyResponse()
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def test_select_relevant_skills_prefers_matching_text() -> None:
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parsed = ParsedDocument(
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filename="srs.docx",
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text="软件需求规格说明 CSCI 能力需求 接口需求 合格性规定",
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paragraphs=[],
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headings=[],
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tables=[],
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)
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skills = [
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Skill("requirements", "软件需求规格说明", "需求文档", "编写软件需求", "需求能力接口", None),
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Skill("deployment", "部署准备", "部署文档", "软件部署交付", "安装部署", None),
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]
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selected = select_relevant_skills(parsed, skills, max_skills=1)
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assert [skill.slug for skill in selected] == ["requirements"]
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def test_llm_client_posts_openai_compatible_payload() -> None:
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provider = ProviderConfig(
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api_key="secret",
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base_url="https://api.deepseek.com/v1/chat/completions",
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max_tokens=99,
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model="deepseek-chat",
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temperature=0.1,
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)
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session = DummySession()
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client = LLMClient(provider, session=session)
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content = client.complete("检查文档")
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assert content == "分析结果"
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url, kwargs = session.calls[0]
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assert url == "https://api.deepseek.com/v1/chat/completions"
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assert kwargs["headers"]["Authorization"] == "Bearer secret"
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assert kwargs["json"]["model"] == "deepseek-chat"
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assert kwargs["json"]["messages"][0]["content"] == "检查文档"
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def test_build_analysis_prompt_contains_document_and_skill() -> None:
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parsed = ParsedDocument("a.docx", "正文", [], [], [])
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skill = Skill("s1", "技能一", "描述", "使用条件", "规范内容", None)
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prompt = build_analysis_prompt(parsed, [skill])
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assert "a.docx" in prompt
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assert "技能一" in prompt
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assert "符合项" in prompt
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