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）
119 lines
4.8 KiB
Python
119 lines
4.8 KiB
Python
"""库级端到端试运行驱动（真实 LLM / 离线 Fake）。
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用法:
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python scripts/run_trial.py [--fake] [--output out.docx] ...
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默认输入为 samples/ 下既有样本（追加改修·股票场景 + sunOnly 既有系统 + 真实概要设计书模板）。
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真实模式需先在 .env 配置 GENESIS_INFERENCE__API_KEY（见 README「运行说明」），
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缺失时抛 LLMNotConfiguredError 并给出配置提示；--fake 为离线确定性引擎，无需 key。
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输出:
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概要设计书 docx + 影响调查书 impact-report.json（默认写至 output/，不入库）。
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"""
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from __future__ import annotations
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import argparse
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import json
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import sys
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from pathlib import Path
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from types import SimpleNamespace
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ROOT = Path(__file__).resolve().parents[1]
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if str(ROOT / "src") not in sys.path:
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sys.path.insert(0, str(ROOT / "src"))
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from genesis.impact.impact_agent import impact_report_to_dict # noqa: E402
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from genesis.parsers.source_aggregator import SourceParser # noqa: E402
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from genesis.writer.orchestrator import WriteOrchestrator # noqa: E402
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class FakeEngine:
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"""离线确定性引擎：章节正文固定为占位文本（用于无 key 验证整条管线）。"""
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def chat_structured(self, *, session_id, prompt, variables, schema, retry_count=2):
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return SimpleNamespace(
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data={
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"title": variables["title"],
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"blocks": [{"type": "paragraph", "text": "自动生成内容"}],
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},
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status="ok",
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)
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def _parse_args(argv: list[str] | None) -> argparse.Namespace:
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p = argparse.ArgumentParser(description="概要设计书自动生成试运行")
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p.add_argument("--requirement", default=str(ROOT / "samples" / "要件定義_追加改修_股票.xlsx"),
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help="要件定义 Excel（可多个，逗号分隔）")
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p.add_argument("--template", default=str(ROOT / "samples" / "概要設計書テンプレート.docx"),
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help="概要设计书 Word 模板")
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p.add_argument("--rules", nargs="*", default=[
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str(ROOT / "samples" / "概要設計做成説明書.docx"),
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str(ROOT / "samples" / "記入規則.docx"),
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], help="写入规则/记入规则 docx（可多个）")
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p.add_argument("--existing-system", default=str(ROOT / "samples" / "existing-system"),
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help="既有系统源码目录（追加/改修场景）")
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p.add_argument("--language", default="java", help="既有系统开发语言（默认 java，None=自动探测）")
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p.add_argument("--output-language", default="auto",
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choices=["auto", "zh", "ja"], help="输出语言：auto=与标题一致，zh=简体中文，ja=日文")
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p.add_argument("--samples-dir", default=str(ROOT / "samples"), help="样本资产根目录")
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p.add_argument("--output", default=str(ROOT / "output" / "output.docx"), help="概要设计书输出路径")
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p.add_argument("--impact-report", default=str(ROOT / "output" / "impact-report.json"),
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help="影响调查书 JSON 输出路径")
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p.add_argument("--fake", action="store_true", help="离线 Fake 引擎（无需 API key）")
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return p.parse_args(argv)
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def main(argv: list[str] | None = None) -> dict:
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args = _parse_args(argv if argv is not None else sys.argv[1:])
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if args.fake:
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engine = FakeEngine()
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else:
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from genesis.inference.factory import build_inference_engine # noqa: E402
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engine = build_inference_engine()
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ss = SourceParser().parse(
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requirement_paths=[args.requirement],
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template_path=args.template,
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rule_paths=list(args.rules),
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existing_system_path=args.existing_system,
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existing_system_language=args.language,
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)
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out_path = Path(args.output)
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out_path.parent.mkdir(parents=True, exist_ok=True)
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orch = WriteOrchestrator()
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contents = orch.generate(
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ss, str(out_path),
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samples_dir=args.samples_dir,
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engine=engine,
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template_path=str(Path(args.template)),
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output_language=args.output_language,
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)
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report = ss.impact_report
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if report is None:
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raise RuntimeError("影响调查未执行（未提供既有系统或门控未触发）")
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report_path = Path(args.impact_report)
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report_path.parent.mkdir(parents=True, exist_ok=True)
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report_path.write_text(
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json.dumps(impact_report_to_dict(report), ensure_ascii=False, indent=2),
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encoding="utf-8",
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)
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summary = dict(report.summary)
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print(f"章节数: {len(contents)}")
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print(f"影响调查: {json.dumps(summary, ensure_ascii=False)}")
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print(f"概要设计书: {out_path}")
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print(f"影响调查书: {report_path}")
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return {
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"chapters": len(contents),
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"summary": summary,
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"output": str(out_path),
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"impact_report": str(report_path),
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}
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if __name__ == "__main__":
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main()
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