lhl
d01e1b720f
- 步骤0: 新增中文镜像模板 scripts/make_zh_template.py 与 samples/概要设计书模板_中文.docx（7章锚点原样保留） - 步骤1: config.WriterConfig.output_language→Settings.writer；GenerationContext.output_language + to_vars.language_instruction（zh/ja/auto）；writer_agent【语言约束】改引变量；context_builder/orchestrator/run_trial 透传 --output-language - 步骤A: 新建 src/genesis/writer/language.py（detect_script/resolve_expected_language/find_language_violations）；WriterAgent.generate_chapter 按期望语言强制、违规重试、耗尽硬失败；max_retries 默认 1→2 - 步骤B: _format_impact 影响调查标签按 output_language 本地化（zh 新建/变更/删除/警告） - 步骤C: eval scorer 第 11 维度 language_consistency（不可验证=满分，不拉低总分）；ChapterArtifact.expected_language；QAValidator.validate_doc 透传；QALoop.run 透传 output_language - 测试: test_zh_template/test_language_plumbing/test_writer_language/test_scorer_language/test_language_coverage，并更新 test_phase5_e2e - 全量 pytest 424 passed / 99.15%（覆盖率门槛 99% 达标）
56 lines
2.0 KiB
Python
56 lines
2.0 KiB
Python
import pytest
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from types import SimpleNamespace
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from pathlib import Path
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from docx import Document
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from genesis.data_models import StructuredSource
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from genesis.parsers.word_template_parser import WordTemplateParser
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from genesis.qa.qa_loop import QALoop
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class FakeEngine:
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def chat_structured(self, *, session_id, prompt, variables, schema, retry_count=2):
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cid = variables.get("title", "x")
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# 日文模板章节（标题含假名）→ 返回日文正文，满足语言一致性强制
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return SimpleNamespace(
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data={
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"title": cid,
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"blocks": [
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{"type": "heading", "level": 2, "text": f"{cid} 小節"},
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{"type": "paragraph", "text": "本機能はFakeLLMにより生成された十分な説明内容であり、書込規則を満たす。"},
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{"type": "table", "caption": "示例表", "rows": [["列1", "列2"], ["値1", "値2"]]},
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],
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},
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status="ok",
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)
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def _all_text(doc: Document) -> str:
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parts = [p.text for p in doc.paragraphs]
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for tbl in doc.tables:
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for row in tbl.rows:
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for cell in row.cells:
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parts.append(cell.text)
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return "\n".join(parts)
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def test_phase5_e2e_fake_llm(tmp_path):
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template = Path("samples/phase5-slice/template.docx")
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if not template.exists():
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pytest.skip("样本模板缺失，跳过 e2e")
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parsed = WordTemplateParser().parse(str(template))
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ss = StructuredSource(
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template=parsed, tables=[], rule_docs=[], image_analyses=[], existing_system=None, comments=[]
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)
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out = tmp_path / "e2e_out.docx"
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loop = QALoop(max_rounds=2)
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report = loop.run(
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ss, str(out), samples_dir="nonexistent_dir_xyz", engine=FakeEngine(), template_path=str(template)
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)
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assert report.passed is True
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loaded = Document(str(out))
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text = _all_text(loaded)
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assert "本機能はFakeLLMにより生成された十分な説明内容" in text
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assert "示例表" in text
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