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@@ -482,7 +482,8 @@ JSON输出："""
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recommendations = await self._generate_recommendations(
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tertiary_result, catalogue_result, outline_result,
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actual_first, actual_secondary, actual_tertiary,
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- chapter_classification
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+ chapter_classification,
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+ chunks # 传入 chunks 用于获取实际章节名
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)
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return LightweightCompletenessResult(
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@@ -856,6 +857,62 @@ JSON输出："""
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else:
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return "incomplete"
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+ def _build_section_label_map(self, chunks: List[Dict]) -> Dict[Tuple[str, str], str]:
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+ """
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+ 从 chunks 构建 (first_code, second_code) -> section_label 映射
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+ section_label 格式："第一章编制依据->一、法律法规"
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+ """
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+ label_map: Dict[Tuple[str, str], str] = {}
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+ for chunk in chunks:
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+ metadata = chunk.get("metadata", {})
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+ cat1 = (metadata.get("chapter_classification") or
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+ chunk.get("chapter_classification") or
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+ chunk.get("first_code"))
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+ cat2 = (metadata.get("secondary_category_code") or
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+ chunk.get("secondary_category_code") or
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+ chunk.get("second_code"))
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+ section_label = (metadata.get("section_label") or
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+ chunk.get("section_label") or
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+ "")
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+ if cat1 and cat2 and section_label:
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+ label_map[(cat1, cat2)] = section_label
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+ return label_map
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+
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+ def _get_actual_chapter_name(self, label_map: Dict[Tuple[str, str], str],
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+ first_code: str, second_code: str = None) -> str:
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+ """
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+ 获取实际章节名
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+ - 一级缺失：返回 first_name（保持原逻辑）
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+ - 二级缺失：返回一级章节名（section_label.split('->')[0]）
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+ - 三级缺失：返回二级小节名（section_label.split('->')[-1]）
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+ """
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+ if not second_code:
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+ return self.spec_loader.first_names.get(first_code, first_code)
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+
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+ section_label = label_map.get((first_code, second_code), "")
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+ if not section_label:
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+ # 回退到标准名称
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+ sec_item = self.secondary_specs.get((first_code, second_code))
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+ if sec_item:
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+ return f"{sec_item.first_cn} > {sec_item.second_cn}"
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+ return f"{first_code} > {second_code}"
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+
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+ parts = section_label.split("->")
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+ if len(parts) >= 2:
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+ return parts[-1].strip() # 返回二级小节名
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+ return section_label.strip()
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+
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+ def _get_actual_first_name(self, label_map: Dict[Tuple[str, str], str],
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+ first_code: str) -> str:
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+ """
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+ 获取实际一级章节名（从任意一个该一级下的 section_label 提取）
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+ """
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+ for (fc, sc), label in label_map.items():
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+ if fc == first_code and "->" in label:
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+ return label.split("->")[0].strip()
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+ # 回退到标准名称
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+ return self.spec_loader.first_names.get(first_code, first_code)
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+
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async def _generate_recommendations(
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self,
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tertiary_result: Dict,
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@@ -864,7 +921,8 @@ JSON输出："""
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actual_first: Set[str],
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actual_secondary: Set[Tuple[str, str]],
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actual_tertiary: Set[Tuple[str, str, str]],
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- chapter_classification: Optional[str] = None
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+ chapter_classification: Optional[str] = None,
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+ chunks: List[Dict] = None
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) -> List[Dict[str, Any]]:
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"""
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生成结构化分级改进建议。
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@@ -872,12 +930,15 @@ JSON输出："""
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每条建议包含：
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level : 缺失级别（一级 / 二级 / 三级 / 一致性）
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issue_point : 问题摘要（含级别标识）
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- location : 问题定位路径
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+ location : 问题定位路径（使用实际章节名）
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suggestion : 补充建议（使用LLM生成）
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reason : 规范依据说明（使用LLM生成）
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"""
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recommendations: List[Dict[str, Any]] = []
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+ # 构建 section_label 映射，用于获取实际章节名
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+ label_map = self._build_section_label_map(chunks or [])
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+
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# 确定需要检查的一级分类范围
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if chapter_classification:
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required_first = (
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@@ -939,15 +1000,18 @@ JSON输出："""
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# ── 二级缺失 ──────────────────────────────────────────
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if (cat1, cat2) not in actual_secondary:
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+ # 获取实际一级章节名
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+ actual_first_name = self._get_actual_first_name(label_map, cat1)
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+
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# issue_point 和 reason 使用简单拼接
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- issue_point = f"【二级章节缺失】{first_name} > '{second_name}'整个章节不存在"
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- reason = f"依据《桥梁公司危险性较大工程管理实施细则（2025版）》规定，'{first_name}'下应包含'{second_name}'二级章节，当前正文中未发现该章节内容"
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+ issue_point = f"【二级章节缺失】{actual_first_name} > '{second_name}'整个章节不存在"
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+ reason = f"依据《桥梁公司危险性较大工程管理实施细则（2025版）》规定，'{actual_first_name}'下应包含'{second_name}'二级章节，当前正文中未发现该章节内容"
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# 尝试使用LLM生成 suggestion
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llm_result = await self._generate_recommendation_with_llm(
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level="二级",
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first_code=cat1,
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- first_name=first_name,
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+ first_name=actual_first_name,
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second_code=cat2,
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second_name=second_name,
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first_seq=first_seq,
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@@ -958,12 +1022,12 @@ JSON输出："""
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suggestion = llm_result.get("suggestion")
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else:
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# 回退到简单拼接
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- suggestion = f"请在'{first_name}'下添加'{second_name}'章节内容"
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+ suggestion = f"请在'{actual_first_name}'下添加'{second_name}'章节内容"
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recommendations.append({
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"level": "二级",
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"issue_point": issue_point,
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- "location": f"{first_name} > {second_name}",
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+ "location": actual_first_name, # 二级缺失定位到一级章节
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"suggestion": suggestion,
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"reason": reason,
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"first_seq": first_seq,
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@@ -986,6 +1050,9 @@ JSON输出："""
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if not missing_t_items:
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continue
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+ # 获取实际二级小节名
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+ actual_second_name = self._get_actual_chapter_name(label_map, cat1, cat2)
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+
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# issue_point 和 reason 使用简单拼接（三级缺失）
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# 尝试使用LLM批量生成 suggestion
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llm_result = await self._generate_recommendation_with_llm(
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@@ -1012,7 +1079,7 @@ JSON输出："""
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recommendations.append({
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"level": "三级",
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"issue_point": f"【三级内容缺失】{first_name} > {second_name} > '{t_item.third_cn}'",
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- "location": f"{first_name} > {second_name}",
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+ "location": actual_second_name, # 三级缺失定位到二级小节
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"suggestion": suggestion,
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"reason": f"依据《桥梁公司危险性较大工程管理实施细则（2025版）》规定，'{second_name}'下应包含'{t_item.third_cn}'内容要点",
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"first_seq": first_seq,
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