M4(文风): style-auditor 双轨(提取指纹/漂移第四审)+ jobs 长任务框架(zombie reaper) + 回炉 refine + GET /style read-back。 M5(生成+扩展): worldbuilder/character-gen(入库 continuity 409 gate + partition_writes 白名单 + schema→JSONB 形变); 网关多 provider 回退链/熔断/能力降级(Anthropic/Gemini 适配器);Skill registry + 表权限沙箱 + 规则; 前端 角色生成器/世界观/Codex/规则页/技能库/⌘K 命令面板。 K1(Kimi Code 订阅接入): OAuth device-flow(kimi-code)+ 静态 Console key(kimi-code-key)两路径; coding 端点 KimiCLI 伪造头(实测 UA allow-list 门禁,缺则 403)+ JSON 模式结构化(thinking ⊥ tool_choice)。 本地联调修复: CORS 中间件;assemble 注入 premise+「写第N章」指令(修空 prompt 400); GET /outline·/draft read-back + 大纲/工作台/审稿页重载;写页 client/server 常量边界 + notFound 健壮化; 字数 toLocaleString locale 水合;审稿页终稿从已存草稿 seed(修 accept 422)。 门禁: backend ruff/mypy(157)/alembic 无漂移/pytest 451 · frontend lint/tsc/vitest/build。 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
192 lines
5.9 KiB
Python
192 lines
5.9 KiB
Python
"""T4.2 style-auditor 双轨契约测试:style_extract / style_drift / refiner spec + schema(C6 扩)。
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契约测试——构造符合 schema 的 mock 响应,校验字段、tier、双轨读写权限。
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提取轨 `StyleFingerprintResult`(16 维带证据);第四审 `StyleDriftReview`(段级相似度);
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回炉 `refiner_spec`(writer 纯文本,output_schema=None)。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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AgentSpec,
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StyleDimension,
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StyleDriftReview,
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StyleDriftSegment,
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StyleFingerprintResult,
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refiner_spec,
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style_drift_spec,
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style_extract_spec,
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)
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# ---- StyleFingerprintResult schema(提取轨)----
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def test_style_fingerprint_parses_mock_response() -> None:
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# Arrange:模拟网关 instructor 校验后的结构化指纹产出(每维带原文证据)
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mock = {
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"dimensions": [
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{
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"name": "句长节奏",
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"value": "短句为主、节奏明快",
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"evidence": ["他一刀劈下。血溅三尺。", "风停了。"],
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},
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{
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"name": "叙事人称",
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"value": "第三人称限知",
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"evidence": ["他不知道门后有什么。"],
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},
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]
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}
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# Act
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fp = StyleFingerprintResult.model_validate(mock)
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# Assert
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assert len(fp.dimensions) == 2
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assert fp.dimensions[0].name == "句长节奏"
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assert fp.dimensions[0].evidence == ["他一刀劈下。血溅三尺。", "风停了。"]
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assert fp.dimensions[1].value == "第三人称限知"
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def test_style_fingerprint_defaults_to_empty_dimensions() -> None:
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assert StyleFingerprintResult().dimensions == []
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def test_style_dimension_evidence_defaults_empty() -> None:
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dim = StyleDimension.model_validate({"name": "用词", "value": "古雅"})
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assert dim.evidence == []
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def test_style_dimension_requires_name_and_value() -> None:
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with pytest.raises(ValidationError):
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StyleDimension.model_validate({"name": "用词"})
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# ---- StyleDriftReview schema(第四审)----
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def test_style_drift_parses_mock_response() -> None:
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mock = {
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"score": 72,
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"segments": [
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{"idx": 3, "score": 40, "label": "机翻腔"},
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{"idx": 7, "score": 55, "label": None},
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],
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}
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review = StyleDriftReview.model_validate(mock)
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assert review.score == 72
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assert len(review.segments) == 2
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assert review.segments[0].idx == 3
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assert review.segments[0].label == "机翻腔"
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assert review.segments[1].label is None
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def test_style_drift_defaults_score_100_empty_segments() -> None:
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# 无指纹优雅降级:默认整体相似度 100、无漂移段
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review = StyleDriftReview()
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assert review.score == 100
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assert review.segments == []
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def test_style_drift_segment_label_optional() -> None:
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seg = StyleDriftSegment.model_validate({"idx": 1, "score": 30})
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assert seg.label is None
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def test_style_drift_segment_requires_idx_and_score() -> None:
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with pytest.raises(ValidationError):
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StyleDriftSegment.model_validate({"idx": 1})
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# ---- style_extract_spec 声明 ----
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def test_style_extract_spec_is_analyst_tier() -> None:
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assert style_extract_spec.tier == "analyst"
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assert style_extract_spec.name == "style_extract"
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def test_style_extract_spec_reads_and_writes_fingerprint() -> None:
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assert style_extract_spec.reads == ["style_fingerprint"]
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assert style_extract_spec.writes == ["style_fingerprint"]
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def test_style_extract_spec_output_schema() -> None:
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assert style_extract_spec.output_schema is StyleFingerprintResult
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def test_style_extract_spec_has_nonempty_system_prompt() -> None:
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assert style_extract_spec.system_prompt.strip()
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# ---- style_drift_spec 声明(第四审,name="style")----
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def test_style_drift_spec_is_light_tier_named_style() -> None:
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# 不变量 #2:第四审用轻量档,只声明 tier;列名/section 名为 "style"
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assert style_drift_spec.tier == "light"
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assert style_drift_spec.name == "style"
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def test_style_drift_spec_is_read_only() -> None:
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# 不变量 #3:四审只读
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assert style_drift_spec.writes == []
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def test_style_drift_spec_reads_fingerprint() -> None:
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assert style_drift_spec.reads == ["style_fingerprint"]
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def test_style_drift_spec_output_schema() -> None:
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assert style_drift_spec.output_schema is StyleDriftReview
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def test_style_drift_spec_prompt_documents_graceful_degrade() -> None:
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# 无指纹→返回 score=100/空段(system_prompt 必须含降级指令,否则 LLM 不知如何兜底)
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assert "100" in style_drift_spec.system_prompt
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# ---- refiner_spec 声明(writer 纯文本回炉)----
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def test_refiner_spec_is_writer_tier() -> None:
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assert refiner_spec.tier == "writer"
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assert refiner_spec.name == "refiner"
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def test_refiner_spec_output_schema_is_none() -> None:
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# 回炉产纯文本(重写段),无结构化 schema
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assert refiner_spec.output_schema is None
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def test_refiner_spec_is_read_only_and_no_writes() -> None:
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# 回炉非持久(不变量 #3):不写库,作者采纳经既有 draft 自动保存合入
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assert refiner_spec.reads == []
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assert refiner_spec.writes == []
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def test_refiner_spec_has_nonempty_system_prompt() -> None:
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assert refiner_spec.system_prompt.strip()
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# ---- 共性:immutable + 是 AgentSpec ----
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def test_style_specs_are_agent_specs() -> None:
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assert isinstance(style_extract_spec, AgentSpec)
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assert isinstance(style_drift_spec, AgentSpec)
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assert isinstance(refiner_spec, AgentSpec)
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def test_style_specs_are_immutable() -> None:
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with pytest.raises(ValidationError):
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style_extract_spec.tier = "writer"
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with pytest.raises(ValidationError):
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style_drift_spec.tier = "writer"
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with pytest.raises(ValidationError):
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refiner_spec.tier = "analyst"
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