iomgaa
eecb86e27a
- Add generate-v2 subparser with --config, --store-dir, --db-path, --seed, and --dry-run arguments to tools/generate_questions.py - Implement _run_generate_v2 async handler: config loading, video discovery, DI client construction, TreeIndex loading, pipeline invocation, and result persistence - Add scripts/generate_questions_v2.sh following build_trees.sh conventions (source .env, conda run python path, MODE=mock support) - Update app/question_gen/__init__.py to export full v2 public API: run_pipeline_v2, PipelineConfig, PipelineResult, QuestionFamilySpec, ALL_FAMILIES, CandidateQuestion, generate_one_v2, GateReport, run_gates - Add QuestionGenStore.load_progress() for pipeline resumption - Add integration tests for CLI help and dry-run behavior - Update test_question_gen_api to match expanded __all__ Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
103 lines
3.3 KiB
Python
103 lines
3.3 KiB
Python
"""generate-v2 CLI 子命令集成测试 — 验证 CLI 入口、dry-run 模式与参数解析。
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测试策略：
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- test_subcommand_help: 验证子命令注册成功、--help 返回码 0 且包含 --config
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- test_dry_run: 验证 dry-run 模式不调用 LLM/VLM，仅输出统计信息
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"""
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from __future__ import annotations
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import subprocess
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import sys
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from pathlib import Path
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PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent
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class TestCLIGenerateV2:
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"""generate-v2 子命令 CLI 集成测试。"""
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def test_subcommand_help(self) -> None:
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"""验证 generate-v2 子命令已注册，--help 正确退出并包含 --config 参数说明。"""
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result = subprocess.run(
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[
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sys.executable,
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str(PROJECT_ROOT / "tools" / "generate_questions.py"),
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"generate-v2",
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"--help",
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],
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capture_output=True,
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text=True,
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timeout=30,
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)
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assert result.returncode == 0, f"stderr: {result.stderr}"
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assert "--config" in result.stdout
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assert "--store-dir" in result.stdout
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assert "--dry-run" in result.stdout
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def test_dry_run(self, tmp_path: Path) -> None:
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"""验证 dry-run 模式：加载配置、计算 slot，但不调用 LLM/VLM。
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通过创建最小 config + 临时 store-dir 来验证 dry-run 的快速退出行为。
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"""
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# 创建最小配置文件
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config_path = tmp_path / "config.yaml"
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config_path.write_text(
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"""\
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question_gen_v2:
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family_ratios:
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retrieval: 0.30
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reasoning: 0.25
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enumeration: 0.20
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visual: 0.15
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spatial: 0.10
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gate:
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blind_answer_model: "mock"
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leak_test_model: "mock"
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key_verify_model: "mock"
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multi_true_model: "mock"
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dedup_threshold: 0.85
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retry_limit: 3
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heavy_sample_rate: 0.15
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heavy_agent_model: "mock"
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output_dir: "{output_dir}"
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per_type: 2
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concurrency: 2
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seed: 42
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""".format(output_dir=str(tmp_path / "output")),
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encoding="utf-8",
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)
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# 创建 store-dir 结构：至少一个带 tree.json 的视频目录
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store_dir = tmp_path / "store"
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videos_dir = store_dir / "videos"
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video_dir = videos_dir / "test_video_001"
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video_dir.mkdir(parents=True)
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# 最小 tree.json（仅需存在）
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(video_dir / "tree.json").write_text("{}", encoding="utf-8")
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db_path = tmp_path / "question_gen.db"
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result = subprocess.run(
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[
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sys.executable,
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str(PROJECT_ROOT / "tools" / "generate_questions.py"),
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"generate-v2",
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"--config",
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str(config_path),
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"--store-dir",
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str(store_dir),
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"--db-path",
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str(db_path),
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"--dry-run",
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],
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capture_output=True,
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text=True,
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timeout=30,
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)
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assert result.returncode == 0, f"stderr: {result.stderr}"
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# dry-run 应输出 slot 统计信息到 stderr（loguru 输出）
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assert "dry-run" in result.stderr.lower() or "slot" in result.stderr.lower()
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# 确保没有创建 telemetry db（意味着未初始化 LLM 客户端）
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# DB 可能会被创建用于 store，但不应有 telemetry 调用
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