72b3c81146
写→审链新增第五审「人物塑造」（灵感③/D2）：advisory 单维——仅建议、不阻断
验收（不进 conflicts、不碰 assert_conflicts_resolved、不入 REVIEW_RESERVED_NAMES）；
只做人物塑造、不做氛围。
- SPEC characterization_spec（analyst，reads=("characters",)，writes=()）+
prompts/characterization.md（只读、显式忽略文本长度与辞藻华丽度、引用逐字片段+置信度）
- schema CharacterizationReview{issues[...]}（全字段默认值守解析韧性）+ 注册 catalog
- 计数三处 22→23 + regen prompt_hashes.json（仅加一条）
- DB chapter_reviews 加 characterization JSONB nullable 列（迁移 f6a7b8c9d0e1）
- 接线：graph REVIEW_SPECS 追加 · chain ReviewRecordRepo · collect(extract/record) ·
review_repo(Protocol/Sql/_to_view/ReviewView) · sse(event/factory/section) · normalize 自动纳入
- 契约 ReviewHistoryItem 加 characterization（gen:api 已重生成）
- 前端 sse/history/useReviewStream + CharacterizationPanel（只展示无裁决 UI、置信度降序+低置信折叠）+ ReviewReport 挂面板
- 测试 test_characterization_does_not_block_accept + 计数/golden + collect/normalize + 前端 reducer/normalize/parse
守不变量 #2/#3/#9；依赖 ⑧（motive/appearance 作客观锚点）。
116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
"""灵感③ 人物塑造续审契约测试：CharacterizationReview schema + characterization_spec。
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advisory 单维——仅建议、不阻断验收（D2）。
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契约测试——构造符合 schema 的 mock 响应，校验字段默认值降级、tier、只读（writes==()）、
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输出 schema 派生。人物塑造是 advisory：**不加入 REVIEW_RESERVED_NAMES**。不联网、无 DB。
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"""
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from __future__ import annotations
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import pytest
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from pydantic import ValidationError
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from ww_agents import (
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REVIEW_RESERVED_NAMES,
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AgentSpec,
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CharacterizationIssue,
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CharacterizationReview,
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characterization_spec,
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)
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# ---- CharacterizationReview schema ----
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def test_characterization_parses_mock_response() -> None:
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# Arrange：模拟网关 instructor 校验后的结构化产出（每条带逐字引用 + 置信度）
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mock = {
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"issues": [
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{
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"character": "沈砚",
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"aspect": "动机一致性",
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"where": "第4段决斗前退缩",
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"quote": "他忽然转身就走，什么也没说。",
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"diagnosis": "与人物卡既定「护妹至死」动机断裂，无过渡",
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"suggestion": "让退缩扣回护妹动机（如察觉陷阱护妹先撤）",
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"confidence": 0.82,
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}
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]
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}
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# Act
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review = CharacterizationReview.model_validate(mock)
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# Assert
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assert len(review.issues) == 1
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issue = review.issues[0]
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assert issue.character == "沈砚"
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assert issue.aspect == "动机一致性"
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assert issue.quote == "他忽然转身就走，什么也没说。"
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assert issue.confidence == pytest.approx(0.82)
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def test_characterization_defaults_to_empty_issues() -> None:
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# 无人物卡 / 无问题 → 空 issues（默认值降级，仿 StyleDriftReview 韧性）
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review = CharacterizationReview()
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assert review.issues == []
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def test_characterization_issue_all_fields_have_defaults() -> None:
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# 畸形/缺字段守韧性：全字段给默认值，空 dict 也能解析
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issue = CharacterizationIssue.model_validate({})
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assert issue.character == ""
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assert issue.aspect == ""
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assert issue.where == ""
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assert issue.quote == ""
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assert issue.diagnosis == ""
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assert issue.suggestion == ""
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assert issue.confidence == 0.0
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def test_characterization_issue_partial_fields_ok() -> None:
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# 缺 confidence/quote 时仍解析（降级默认），不抛
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issue = CharacterizationIssue.model_validate({"character": "阿黎", "diagnosis": "扁平"})
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assert issue.character == "阿黎"
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assert issue.diagnosis == "扁平"
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assert issue.confidence == 0.0
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# ---- characterization_spec 声明（analyst 档，advisory 单维）----
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def test_characterization_spec_is_analyst_tier() -> None:
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# 不变量 #2：只声明档位，不写 model
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assert characterization_spec.tier == "analyst"
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assert characterization_spec.name == "characterization"
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def test_characterization_spec_is_read_only() -> None:
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# 不变量 #3：审查只读，唯一落库=collect 留痕
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assert characterization_spec.writes == ()
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def test_characterization_spec_reads_characters() -> None:
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# 以人物卡 motive/appearance 为客观锚点
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assert characterization_spec.reads == ("characters",)
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def test_characterization_spec_output_schema() -> None:
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assert characterization_spec.output_schema is CharacterizationReview
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def test_characterization_spec_prompt_ignores_length_and_diction() -> None:
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# 对抗 LLM-judge 冗长/辞藻偏见：prompt 必须显式声明忽略文本长度与辞藻华丽度
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prompt = characterization_spec.system_prompt
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assert "忽略文本长度与辞藻华丽度" in prompt
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def test_characterization_not_in_review_reserved_names() -> None:
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# advisory：不进受信保留名（不阻断验收、无 conflicts 通道）
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assert "characterization" not in REVIEW_RESERVED_NAMES
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def test_characterization_spec_is_agent_spec_and_immutable() -> None:
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assert isinstance(characterization_spec, AgentSpec)
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with pytest.raises(ValidationError):
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characterization_spec.tier = "writer"
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