按报告类型归并追加内容并统一导出
This commit is contained in:
parent
fd8369e2f3
commit
2f4d2260c8
@ -2,6 +2,7 @@
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from io import BytesIO
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from pathlib import Path
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from typing import Any
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from docx import Document
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from docx.enum.table import WD_CELL_VERTICAL_ALIGNMENT
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@ -143,6 +144,65 @@ def report_card_lines(card: ReportCard) -> list[tuple[str, str]]:
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return lines
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def _unique_by(items: list[Any], key) -> list[Any]: # noqa: ANN001
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seen: set[Any] = set()
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result: list[Any] = []
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for item in items:
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value = key(item)
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if value in seen:
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continue
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seen.add(value)
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result.append(item)
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return result
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def aggregate_report_data(result: RiskAssessmentResult) -> dict[str, Any]:
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"""Merge appended cards into the report's native sections.
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A card is an input action, not a report section. Its fields are folded
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into the matching section so the browser, PDF and Word output have the
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same information architecture.
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"""
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cards = effective_report_cards(result)
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supplier_cards = [card for card in cards if card.type == "supplier"]
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material_cards = [card for card in cards if card.type == "material"]
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solution_cards = [card for card in cards if card.type == "solution"]
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standards = _unique_by(
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[*result.standard_judgment, *(item for card in cards for item in card.standards)],
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lambda item: (item.category, item.risk_point, item.rule, item.status),
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)
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similar_cases = _unique_by(
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[*result.similar_cases, *(item for card in cards for item in card.similar_cases)],
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lambda item: (
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item.case_id,
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item.date,
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item.product,
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item.problem or item.description,
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item.solution,
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),
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)
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suggestions = _unique_by(
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[*result.ai_suggestions, *(item for card in cards for item in card.suggestions)],
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lambda item: item,
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)
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detected_values = [item for card in cards for item in card.detected_values]
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risks = [(card.title, risk) for card in solution_cards for risk in card.risks]
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analyses = [card for card in solution_cards if card.analysis_base or card.confidence or card.warning]
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return {
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"cards": cards,
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"supplier_cards": supplier_cards,
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"material_cards": material_cards,
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"solution_cards": solution_cards,
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"standards": standards,
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"similar_cases": similar_cases,
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"suggestions": suggestions,
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"detected_values": detected_values,
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"risks": risks,
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"analyses": analyses,
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}
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def _font_name() -> str:
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candidates = [
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Path("C:/Windows/Fonts/msyh.ttc"),
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@ -188,6 +248,10 @@ def build_risk_report_pdf(result: RiskAssessmentResult) -> bytes:
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supplier_name = result.supplier_freq.supplier_name if result.supplier_freq else None
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report_number = f"RP-{result.subject_id[:8]}-{round(result.score)}"
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generated_at = __import__("datetime").datetime.now().strftime("%Y-%m-%d %H:%M")
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report_data = aggregate_report_data(result)
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standards = report_data["standards"]
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similar_cases = report_data["similar_cases"]
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suggestions = report_data["suggestions"]
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story = [
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Paragraph("新品风险预估报告", title),
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Paragraph(f"蝶雅产品部 · 风险预估系统 · 自动生成 · {generated_at}", subtitle),
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@ -268,27 +332,52 @@ def build_risk_report_pdf(result: RiskAssessmentResult) -> bytes:
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]
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supplier = result.supplier_freq
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if supplier and supplier.supplier_name:
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supplier_cards = report_data["supplier_cards"]
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if (supplier and supplier.supplier_name) or supplier_cards:
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supplier_rows = [["维度", "数值", "说明"]]
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if supplier.cooperation_count is not None:
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if supplier and supplier.cooperation_count is not None:
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supplier_rows.append(["合作次数", f"{supplier.cooperation_count} 次", "近三年采购订单去重单据数"])
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if supplier:
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supplier_rows.append(["异常次数", f"{supplier.anomaly_count or 0} 次", "异常案例库统计"])
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if supplier.alpha is not None:
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if supplier and supplier.alpha is not None:
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supplier_rows.append(
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["频次风险系数", f"×{supplier.alpha:.2f}", "α = 1.0 +（采购订单数 / 100）× 0.3，最高1.5"]
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)
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if supplier.tier:
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if supplier and supplier.tier:
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supplier_rows.append(["供应商层级", supplier.tier, supplier.suggestion or ""])
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for card in supplier_cards:
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if card.name:
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supplier_rows.append(["供应商名称", card.name, "供应商画像统计"])
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for label, value in report_card_lines(card):
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if label not in {"卡片类型", "分析对象", "对象类型"}:
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supplier_rows.append([label, value, "追加供应商画像数据"])
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story += [Paragraph("三、供应商合作频次分析", section), table(supplier_rows, [38 * mm, 35 * mm, 87 * mm])]
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story += [Paragraph(f"四、相似案例匹配（{len(result.similar_cases)} 条）", section)]
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if result.similar_cases:
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material_cards = report_data["material_cards"]
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if material_cards:
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story += [Paragraph("四、物料风险分析", section)]
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material_rows = [["物料/字段", "分析结果"]]
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for card in material_cards:
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material_rows.append(
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[
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card.material or card.title,
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"；".join(
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f"{label}：{value}"
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for label, value in report_card_lines(card)
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if label not in {"卡片类型", "分析对象"}
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),
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]
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)
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story.append(table(material_rows, [45 * mm, 115 * mm]))
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story += [Paragraph(f"五、相似案例匹配（{len(similar_cases)} 条）", section)]
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if similar_cases:
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story.append(
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table(
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[["日期", "产品", "问题", "处理方案"]]
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+ [
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[case.date or "未知", case.product or "未命名", case.problem or "未填写", case.solution or "未填写"]
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for case in result.similar_cases
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for case in similar_cases
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],
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[28 * mm, 42 * mm, 48 * mm, 42 * mm],
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)
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@ -296,27 +385,35 @@ def build_risk_report_pdf(result: RiskAssessmentResult) -> bytes:
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else:
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story.append(Paragraph("暂无相关案例，RAG 相似案例检索未返回匹配结果。", small))
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story += [Paragraph("五、预防建议", section)]
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for index, suggestion in enumerate(
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result.ai_suggestions or ["优先针对低分维度安排专项验证，并明确责任人与完成节点。"], 1
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):
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story += [Paragraph("六、预防建议", section)]
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for index, suggestion in enumerate(suggestions or ["优先针对低分维度安排专项验证，并明确责任人与完成节点。"], 1):
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story.append(Paragraph(f"{index}. {suggestion}", body))
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story += [
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Paragraph("六、AI 推理方案（无历史案例场景）", section),
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Paragraph("七、AI 推理方案（无历史案例场景）", section),
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Paragraph(
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"本次评估已采用历史案例与标准库双引擎结论；若后续未匹配到足够历史案例，将基于相似品类、相似物料生成类比方案，并由标准库进行规则兜底。",
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body,
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),
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]
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story += [Paragraph("七、标准判定结果", section)]
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if result.standard_judgment:
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for card in report_data["solution_cards"]:
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if card.analysis_base:
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story.append(Paragraph(f"分析基础：{card.analysis_base}", body))
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if card.confidence:
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story.append(Paragraph(f"置信度：{card.confidence}", body))
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for risk in card.risks:
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story.append(Paragraph(f"{risk.level} · {risk.title}：{risk.detail}", body))
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if card.warning:
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story.append(Paragraph(f"风险提示：{card.warning}", body))
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story += [Paragraph("八、标准判定结果", section)]
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if standards:
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story.append(
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table(
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[["判定维度", "判定标准", "标准来源", "当前状态"]]
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+ [
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[f"{item.category} · {item.risk_point}", item.rule, item.source or "标准文件.xlsx", item.status]
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for item in result.standard_judgment
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for item in standards
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],
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[38 * mm, 55 * mm, 40 * mm, 27 * mm],
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)
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@ -325,18 +422,6 @@ def build_risk_report_pdf(result: RiskAssessmentResult) -> bytes:
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story.append(Paragraph("暂无相关标准。", small))
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story.append(Paragraph("双引擎融合：历史异常经验引擎提供风险优先级，标准库提供可执行的检测阈值与验证任务。", small))
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cards = effective_report_cards(result)
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if cards:
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story += [Paragraph("八、追加卡片分析", section)]
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for index, card in enumerate(cards, 1):
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story.append(Paragraph(f"{index}. {card.title}", body))
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story.append(
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table(
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[["字段", "内容"]] + [[label, value] for label, value in report_card_lines(card)],
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[38 * mm, 122 * mm],
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)
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)
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output = BytesIO()
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doc = SimpleDocTemplate(
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output,
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@ -371,6 +456,10 @@ def build_risk_report_docx(result: RiskAssessmentResult) -> bytes:
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subtitle = document.add_paragraph()
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subtitle.alignment = WD_ALIGN_PARAGRAPH.CENTER
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subtitle.add_run(f"蝶雅产品部 · 风险预估系统 · 自动生成 · {result.subject_id}").font.size = Pt(9)
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report_data = aggregate_report_data(result)
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standards = report_data["standards"]
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similar_cases = report_data["similar_cases"]
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suggestions = report_data["suggestions"]
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def heading(text: str) -> None:
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p = document.add_paragraph()
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@ -454,58 +543,83 @@ def build_risk_report_docx(result: RiskAssessmentResult) -> bytes:
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],
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]
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)
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if result.supplier_freq and result.supplier_freq.supplier_name:
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supplier_cards = report_data["supplier_cards"]
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if (result.supplier_freq and result.supplier_freq.supplier_name) or supplier_cards:
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heading("三、供应商合作频次分析")
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rows = [["维度", "数值", "说明"]]
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if result.supplier_freq.cooperation_count is not None:
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if result.supplier_freq and result.supplier_freq.cooperation_count is not None:
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rows.append(["合作次数", f"{result.supplier_freq.cooperation_count} 次", "近三年采购订单去重单据数"])
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if result.supplier_freq:
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rows.append(["异常次数", f"{result.supplier_freq.anomaly_count or 0} 次", "异常案例库统计"])
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if result.supplier_freq.alpha is not None:
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if result.supplier_freq and result.supplier_freq.alpha is not None:
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rows.append(
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["频次风险系数", f"×{result.supplier_freq.alpha:.2f}", "α = 1.0 +（采购订单数 / 100）× 0.3，最高1.5"]
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)
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if result.supplier_freq.tier:
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if result.supplier_freq and result.supplier_freq.tier:
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rows.append(["供应商层级", result.supplier_freq.tier, result.supplier_freq.suggestion or ""])
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for card in supplier_cards:
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if card.name:
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rows.append(["供应商名称", card.name, "供应商画像统计"])
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for label, value in report_card_lines(card):
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if label not in {"卡片类型", "分析对象", "对象类型"}:
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rows.append([label, value, "追加供应商画像数据"])
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add_table(rows)
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heading(f"四、相似案例匹配（{len(result.similar_cases)} 条）")
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if result.similar_cases:
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material_cards = report_data["material_cards"]
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if material_cards:
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heading("四、物料风险分析")
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rows = [["物料/字段", "分析结果"]]
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for card in material_cards:
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rows.append(
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[
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card.material or card.title,
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"；".join(
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f"{label}：{value}"
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for label, value in report_card_lines(card)
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if label not in {"卡片类型", "分析对象"}
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),
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]
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)
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add_table(rows)
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heading(f"五、相似案例匹配（{len(similar_cases)} 条）")
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if similar_cases:
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add_table(
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[["日期", "产品", "问题", "处理方案"]]
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+ [
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[case.date or "未知", case.product or "未命名", case.problem or "未填写", case.solution or "未填写"]
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for case in result.similar_cases
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for case in similar_cases
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]
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)
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else:
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document.add_paragraph("暂无相关案例，RAG 相似案例检索未返回匹配结果。")
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heading("五、预防建议")
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for index, suggestion in enumerate(
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result.ai_suggestions or ["优先针对低分维度安排专项验证，并明确责任人与完成节点。"], 1
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):
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heading("六、预防建议")
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for index, suggestion in enumerate(suggestions or ["优先针对低分维度安排专项验证，并明确责任人与完成节点。"], 1):
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document.add_paragraph(f"{index}. {suggestion}")
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heading("六、AI 推理方案（无历史案例场景）")
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heading("七、AI 推理方案（无历史案例场景）")
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document.add_paragraph(
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"本次评估已采用历史案例与标准库双引擎结论；若后续未匹配到足够历史案例，将基于相似品类、相似物料生成类比方案，并由标准库进行规则兜底。"
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)
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heading("七、标准判定结果")
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if result.standard_judgment:
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for card in report_data["solution_cards"]:
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if card.analysis_base:
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document.add_paragraph(f"分析基础：{card.analysis_base}")
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if card.confidence:
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document.add_paragraph(f"置信度：{card.confidence}")
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for risk in card.risks:
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document.add_paragraph(f"{risk.level} · {risk.title}：{risk.detail}")
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if card.warning:
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document.add_paragraph(f"风险提示：{card.warning}")
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heading("八、标准判定结果")
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if standards:
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add_table(
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[["判定维度", "判定标准", "标准来源", "当前状态"]]
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+ [
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[f"{item.category} · {item.risk_point}", item.rule, item.source or "标准文件.xlsx", item.status]
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for item in result.standard_judgment
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for item in standards
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]
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)
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else:
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document.add_paragraph("暂无相关标准。")
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document.add_paragraph("双引擎融合：历史异常经验引擎提供风险优先级，标准库提供可执行的检测阈值与验证任务。")
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cards = effective_report_cards(result)
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if cards:
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heading("八、追加卡片分析")
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for index, card in enumerate(cards, 1):
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document.add_paragraph(f"{index}. {card.title}")
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add_table([["字段", "内容"]] + [[label, value] for label, value in report_card_lines(card)])
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output = BytesIO()
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document.save(output)
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return output.getvalue()
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