xsl
e7076c9c01
dimensions.py 逐行编码需求文档 §4（32 项四要素、缺失显式 skipped）+ VisionProvider 接口位与确定性实现 + 规则引擎联动 rule_hits（T-P3-01/06）。 实现： - dimensions.py：DimensionSpec 恰 32 项（number 1~32 连续，33/34 永不复用）， basic_coverage 口径机器可读：full 10 / label 3 / partial 8 / none 11， 初级覆盖 21/32（BASIC_FULL_KEYS + BASIC_COVERED_KEYS）。 - vision.py：VisionProvider Protocol（派生特征形状写进 docstring，真实 RTMPose/BiRefNet 实现后续按此替换）+ DeterministicVisionProvider（问卷 BMI/自评驱动体型与肤色，sha256(object_key+canonical问卷) 驱动其余枚举， 同输入同输出）+ build_vision_provider（未知名 CONFIG_ERROR）。 - vision_stage.py：derived_features 已存在 → skipped/reused（T-P3-09）； 否则分析 → 写中间态并 flush；photo_meta.quality_flags 透传进产物（T-P3-01）。 - diagnosis_stage.py：32 维恒全键，缺输入显式 skipped+原因（T-P3-06 红线）； 每维四要素 value/confidence/source/evidence/rule_hits + status；构造 RuleContext → RuleService 载入 published 规则 → evaluate，body_shape/color 类命中回落 #5/#19/#21，全量命中聚合进 #28/#30 的 rule_hits 与 evidence； 色板 #19/#20/#21 从 kb_color 按季型读取，库空 → skipped「色板未录入」。 测试：单测 29 项（32 项完整性/编号连续/确定性/工厂拒绝未知名；四要素齐全 性——故意缺问卷+缺视觉断言 32 键全在且全部 skipped 带原因；规则命中进 rule_hits 用内置最小规则集不连库）；集成 1 项（种 2 条 published 规则 → VisionStage → DiagnosisStage：中间态落库与复用 skipped/reused、32 维全键、 rule_hits 出现、kb_color 空时色板 skipped、coverage basic_full=10/32）。 全绿：ruff check/format、mypy packages/report、lint-imports；单测 536 通过 （3 处既有 skip）、集成 46 通过。 偏差说明： 1. 任务文档写 RulesService，实际类名为 RuleService（packages/rules/service.py），按实际代码调用。 2. kb_color 联表键采用四季代码 spring/summer/autumn/winter（仓库无既定口径），已在 vision.py 注释声明。 3. 任务文档只给 basic_coverage 四枚举，需求表格中的「粗判/8色/3色」归入 partial、「Top1」归入 label。
263 lines
11 KiB
Python
263 lines
11 KiB
Python
"""诊断装配：32 维四要素齐全、缺失显式 skipped、规则命中进 rule_hits（T-P3-06）。
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规则求值走纯函数 ``engine.evaluate``（内置最小规则集，不连库）——
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``evaluate_dimensions`` 本身不碰 I/O，这正是它能被穷举输入组合的原因。
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"""
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from __future__ import annotations
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import json
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from dataclasses import asdict
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from typing import Any
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from packages.report.diagnosis_stage import (
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ColorEntry,
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build_rule_context,
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evaluate_dimensions,
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)
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from packages.report.dimensions import DIMENSION_BY_KEY, DIMENSIONS
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from packages.report.vision import DeterministicVisionProvider
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from packages.rules import dsl, engine
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_QUESTIONNAIRE = {
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"gender": "女",
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"height": 165,
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"weight": 50,
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"birthday": "1998-06-01 10:00",
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"occupation": "设计师",
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"core_goals": ["显高", "显瘦", "显白"],
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"occasion_weights": {"通勤": 0.6, "休闲": 0.2, "约会": 0.2},
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"psyche_style": "自然",
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"preferred_colors": ["白色", "蓝色"],
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"disliked_styles": ["前卫"],
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"taboos": ["不接受深V"],
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}
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def _kb_colors_for(season: str) -> list[ColorEntry]:
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"""给定季型的完整色板（base 含中性色命名，覆盖 #19/#20/#21 三个维度）。"""
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return [
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ColorEntry(season_code=season, role="base", hex="#FFFFFF", name_cn="柔白"),
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ColorEntry(season_code=season, role="base", hex="#2B2B2B", name_cn="炭黑"),
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ColorEntry(season_code=season, role="base", hex="#6B6B6B", name_cn="中灰"),
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ColorEntry(season_code=season, role="accent", hex="#0F4C81", name_cn="宝蓝"),
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ColorEntry(season_code=season, role="avoid", hex="#E4E444", name_cn="芥末黄"),
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]
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def _rule(rule_key: str, category: str, conditions: dict[str, Any]) -> dsl.Rule:
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return dsl.Rule.model_validate(
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{
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"rule_key": rule_key,
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"category": category,
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"priority": 90,
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"conditions": conditions,
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"effects": {
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"recommend": [{"slot": "top", "attrs": {"shoulder": ["垫肩"]}}],
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"avoid": [{"slot": "dress", "attrs": {"color": ["荧光绿"]}}],
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"explanation": f"{rule_key} 命中",
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},
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}
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)
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async def _derived() -> dict[str, Any]:
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return await DeterministicVisionProvider().analyze(
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{"object_key": "unit/report-vision.jpg"}, _QUESTIONNAIRE
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)
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async def _verdict(derived: dict[str, Any]) -> engine.RuleVerdict:
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rules = [
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_rule("T16-BODY", "body_shape", {"body_shape": derived["body_shape"]}),
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_rule("T16-COLOR", "color", {"season": derived["season_code"]}),
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]
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return engine.evaluate(rules, build_rule_context(_QUESTIONNAIRE, derived))
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def _by_key(results: list[Any]) -> dict[str, Any]:
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return {r.key: r for r in results}
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def _assert_four_elements(result: Any) -> None:
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# 四要素 + 定位字段：一个都不能少（T-P3-06 验收原文）。
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for field in ("value", "confidence", "source", "evidence", "rule_hits", "status"):
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assert hasattr(result, field)
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assert 0.0 <= result.confidence <= 1.0
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assert result.evidence, f"{result.key} 的 evidence 不能为空"
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assert isinstance(result.rule_hits, list)
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# ── 32 键恒在场（红线） ─────────────────────────────────────────────────────
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async def test_full_inputs_produce_all_32_dimensions() -> None:
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derived = await _derived()
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results = evaluate_dimensions(
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_QUESTIONNAIRE, derived, await _verdict(derived), _kb_colors_for(derived["season_code"])
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)
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assert [r.number for r in results] == list(range(1, 33))
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assert [r.key for r in results] == [spec.key for spec in DIMENSIONS]
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for result in results:
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_assert_four_elements(result)
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assert result.status == "ok", f"{result.key} 应有产出：{result.evidence}"
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async def test_missing_everything_still_returns_32_keys_all_skipped() -> None:
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# 故意缺问卷 + 缺视觉：32 键全在、全部显式 skipped 且带原因（不允许缺键）。
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verdict = engine.evaluate((), dsl.RuleContext())
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results = evaluate_dimensions({}, {}, verdict)
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assert len(results) == 32
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for result in results:
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_assert_four_elements(result)
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assert result.status == "skipped"
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assert result.value is None
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assert result.confidence == 0.0
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assert result.source == "none"
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assert result.evidence # 缺失原因必须显式给出
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async def test_questionnaire_only_keeps_32_keys_with_vision_skipped() -> None:
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# 问卷版轻画像（§3.6）：视觉维度 skipped，问卷维度照常输出。
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verdict = engine.evaluate((), dsl.RuleContext())
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results = evaluate_dimensions(_QUESTIONNAIRE, {}, verdict)
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by_key = _by_key(results)
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assert len(results) == 32
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for key in ("body_shape", "face_shape", "skin_tone", "season_code", "hair_color"):
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assert by_key[key].status == "skipped"
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for key in ("gender", "birthday", "occupation", "psyche_style", "core_goals"):
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assert by_key[key].status == "ok"
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assert by_key[key].source == "questionnaire"
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assert by_key[key].confidence == 0.6
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async def test_assembly_is_deterministic() -> None:
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derived = await _derived()
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verdict = await _verdict(derived)
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colors = _kb_colors_for(derived["season_code"])
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first = evaluate_dimensions(_QUESTIONNAIRE, derived, verdict, colors)
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second = evaluate_dimensions(_QUESTIONNAIRE, derived, verdict, colors)
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assert [asdict(r) for r in first] == [asdict(r) for r in second]
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# ── 规则引擎联动（rule_hits / evidence） ───────────────────────────────────
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async def test_rule_hits_land_on_related_dimensions() -> None:
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derived = await _derived()
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verdict = await _verdict(derived)
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by_key = _by_key(evaluate_dimensions(_QUESTIONNAIRE, derived, verdict))
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# 体型类命中 → #5 体型维度。
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assert "T16-BODY" in by_key["body_shape"].rule_hits
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assert "T16-BODY" in by_key["body_shape"].evidence
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# 核心诉求/偏好与禁忌聚合全部命中（recommend/avoid 服务于诉求与禁忌）。
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for key in ("core_goals", "preferences_taboos"):
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assert set(by_key[key].rule_hits) >= {"T16-BODY", "T16-COLOR"}
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async def test_color_rules_carry_hits_even_when_kb_empty() -> None:
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# kb_color 为空 → 色板 skipped，但色彩规则命中链仍在（可解释性不丢）。
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derived = await _derived()
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verdict = await _verdict(derived)
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by_key = _by_key(evaluate_dimensions(_QUESTIONNAIRE, derived, verdict))
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for key in ("best_colors", "avoid_colors"):
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assert by_key[key].status == "skipped"
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assert "色板未录入" in by_key[key].evidence
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assert "T16-COLOR" in by_key[key].rule_hits
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async def test_rule_derived_taboos_when_questionnaire_empty() -> None:
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# 问卷没有偏好禁忌、但规则有 avoid → #30 以规则为源产出。
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derived = await _derived()
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verdict = await _verdict(derived)
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by_key = _by_key(evaluate_dimensions({}, derived, verdict))
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prefs = by_key["preferences_taboos"]
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assert prefs.status == "ok"
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assert prefs.source == "rule"
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assert prefs.confidence == 0.9
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assert any("回避" in taboo for taboo in prefs.value["taboos"])
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# ── 色板（kb_color）与知识库映射 ───────────────────────────────────────────
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async def test_color_palettes_from_kb_entries() -> None:
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derived = await _derived()
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verdict = await _verdict(derived)
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colors = _kb_colors_for(derived["season_code"])
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by_key = _by_key(evaluate_dimensions(_QUESTIONNAIRE, derived, verdict, colors))
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best = by_key["best_colors"]
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assert best.status == "ok"
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assert len(best.value) <= 8 # 初级口径：最佳色板 8 色
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assert best.source == "derived"
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assert {c.hex for c in colors if c.role != "avoid"} >= {c["hex"] for c in best.value}
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avoid = by_key["avoid_colors"]
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assert avoid.status == "ok"
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assert len(avoid.value) == 1 # 初级口径：避雷色 3 色为上限
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assert avoid.value[0]["name_cn"] == "芥末黄"
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neutral = by_key["neutral_colors"]
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assert neutral.status == "ok"
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assert {c["name_cn"] for c in neutral.value} == {"柔白", "炭黑", "中灰"}
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async def test_other_season_colors_are_not_mixed_in() -> None:
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derived = await _derived()
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verdict = await _verdict(derived)
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# 只录他季色板：本季必须 skipped 而不是混入他季颜色（色板映射按季型联表）。
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other = "summer" if derived["season_code"] != "summer" else "winter"
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by_key = _by_key(evaluate_dimensions(_QUESTIONNAIRE, derived, verdict, _kb_colors_for(other)))
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assert by_key["best_colors"].status == "skipped"
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assert "色板未录入" in by_key["best_colors"].evidence
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assert by_key["neutral_colors"].status == "skipped"
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# ── 融合风格命名与序列化 ───────────────────────────────────────────────────
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async def test_fusion_style_naming_degrades_gracefully() -> None:
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derived = await _derived()
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verdict = await _verdict(derived)
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both = _by_key(evaluate_dimensions(_QUESTIONNAIRE, derived, verdict))["fusion_style_name"]
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assert both.status == "ok"
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assert both.source == "rule"
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assert both.confidence == 0.9
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assert "自然" in both.value # 心理风格侧参与了命名
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only_questionnaire = evaluate_dimensions(
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_QUESTIONNAIRE, {}, engine.evaluate((), dsl.RuleContext())
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)
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fused = _by_key(only_questionnaire)["fusion_style_name"]
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assert fused.status == "ok"
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assert "自然" in fused.value
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async def test_results_serialize_to_json() -> None:
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derived = await _derived()
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verdict = await _verdict(derived)
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payload = [asdict(r) for r in evaluate_dimensions(_QUESTIONNAIRE, derived, verdict)]
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assert len(json.loads(json.dumps(payload, ensure_ascii=False))) == 32
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def test_build_rule_context_maps_fields() -> None:
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derived = {
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"body_shape": "A",
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"season_code": "autumn",
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"face_shape": "圆",
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"body_features": ["溜肩", "短颈"],
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}
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ctx = build_rule_context(_QUESTIONNAIRE, derived)
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assert ctx.body_shape == "A"
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assert ctx.season == "autumn"
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assert ctx.face_shape == "圆"
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assert ctx.features == ("溜肩", "短颈")
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assert ctx.goals == ("显高", "显瘦", "显白")
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assert ctx.style == "自然"
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assert ctx.user_taboos == ("不接受深V",)
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assert ctx.occasion == "通勤" # 占比最高的场景
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assert DIMENSION_BY_KEY["body_shape"].number == 5
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