| |
| """ |
| AIGC检测报告生成器 - HTML全文标注版 |
| 生成带有颜色标注的完整文档检测报告 |
| """ |
|
|
| import json |
| import numpy as np |
| from pathlib import Path |
| from datetime import datetime |
| from typing import Dict, List, Tuple |
| import argparse |
|
|
|
|
| class HTMLReportGenerator: |
| """HTML报告生成器 - 全文标注版""" |
| |
| def __init__(self, result_data: Dict, docx_path: str, paragraphs: List[str]): |
| self.data = result_data |
| self.docx_path = Path(docx_path) |
| self.paragraphs = paragraphs |
| self.report_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") |
| self.report_id = f"MBA-AIGC-{datetime.now().strftime('%Y%m%d%H%M%S')}" |
| |
| def generate(self, output_path: str): |
| """生成HTML报告""" |
| html = self._build_html() |
| with open(output_path, 'w', encoding='utf-8') as f: |
| f.write(html) |
| print(f"✓ HTML报告已生成: {output_path}") |
| |
| def _build_html(self) -> str: |
| """构建完整HTML文档""" |
| return f"""<!DOCTYPE html> |
| <html lang="zh-CN"> |
| <head> |
| <meta charset="UTF-8"> |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> |
| <title>MBA论文AIGC检测报告 - {self.data.get('risk_level', '未知')}</title> |
| <style> |
| @import url('https://fonts.googleapis.com/css2?family=Noto+Serif+SC:wght@400;600;700&family=Noto+Sans+SC:wght@300;400;500;700&display=swap'); |
| |
| :root {{ |
| --primary: #1a365d; |
| --primary-light: #2c5282; |
| --accent: #c53030; |
| --accent-light: #e53e3e; |
| --warning: #d69e2e; |
| --success: #276749; |
| --bg-paper: #faf9f7; |
| --bg-card: #ffffff; |
| --text-primary: #1a202c; |
| --text-secondary: #4a5568; |
| --border: #e2e8f0; |
| |
| /* 风险等级颜色 */ |
| --risk-low-bg: #dcfce7; |
| --risk-low-text: #166534; |
| --risk-low-border: #86efac; |
| |
| --risk-medium-bg: #fef3c7; |
| --risk-medium-text: #92400e; |
| --risk-medium-border: #fcd34d; |
| |
| --risk-high-bg: #fee2e2; |
| --risk-high-text: #991b1b; |
| --risk-high-border: #fca5a5; |
| |
| --risk-critical-bg: #fecaca; |
| --risk-critical-text: #7f1d1d; |
| --risk-critical-border: #f87171; |
| }} |
| |
| * {{ margin: 0; padding: 0; box-sizing: border-box; }} |
| |
| body {{ |
| font-family: 'Noto Sans SC', -apple-system, sans-serif; |
| background: var(--bg-paper); |
| color: var(--text-primary); |
| line-height: 1.8; |
| }} |
| |
| .container {{ max-width: 1400px; margin: 0 auto; padding: 20px; }} |
| |
| /* 报告头部 */ |
| .report-header {{ |
| background: linear-gradient(135deg, var(--primary) 0%, var(--primary-light) 100%); |
| color: white; |
| padding: 40px; |
| border-radius: 12px; |
| margin-bottom: 24px; |
| box-shadow: 0 10px 40px rgba(26, 54, 93, 0.3); |
| }} |
| |
| .report-badge {{ |
| display: inline-block; |
| background: rgba(255,255,255,0.2); |
| padding: 6px 14px; |
| border-radius: 20px; |
| font-size: 12px; |
| font-weight: 500; |
| letter-spacing: 1px; |
| margin-bottom: 16px; |
| }} |
| |
| .report-title {{ |
| font-family: 'Noto Serif SC', serif; |
| font-size: 28px; |
| font-weight: 700; |
| margin-bottom: 20px; |
| }} |
| |
| .report-meta {{ |
| display: grid; |
| grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); |
| gap: 12px; |
| font-size: 13px; |
| opacity: 0.9; |
| }} |
| |
| /* 核心指标 */ |
| .metrics-bar {{ |
| display: flex; |
| gap: 20px; |
| margin-bottom: 24px; |
| flex-wrap: wrap; |
| }} |
| |
| .metric-item {{ |
| flex: 1; |
| min-width: 200px; |
| background: white; |
| padding: 24px; |
| border-radius: 12px; |
| box-shadow: 0 2px 8px rgba(0,0,0,0.08); |
| border-left: 4px solid var(--primary); |
| }} |
| |
| .metric-item.warning {{ border-left-color: var(--warning); }} |
| .metric-item.danger {{ border-left-color: var(--accent); }} |
| |
| .metric-value {{ |
| font-family: 'Noto Serif SC', serif; |
| font-size: 36px; |
| font-weight: 700; |
| color: var(--primary); |
| line-height: 1; |
| }} |
| |
| .metric-value.warning {{ color: var(--warning); }} |
| .metric-value.danger {{ color: var(--accent); }} |
| |
| .metric-label {{ |
| font-size: 12px; |
| color: var(--text-secondary); |
| text-transform: uppercase; |
| letter-spacing: 0.5px; |
| margin-bottom: 8px; |
| }} |
| |
| .risk-badge {{ |
| display: inline-flex; |
| align-items: center; |
| gap: 6px; |
| padding: 6px 14px; |
| border-radius: 20px; |
| font-size: 13px; |
| font-weight: 600; |
| margin-top: 12px; |
| }} |
| |
| .risk-badge.low {{ background: var(--risk-low-bg); color: var(--risk-low-text); }} |
| .risk-badge.medium {{ background: var(--risk-medium-bg); color: var(--risk-medium-text); }} |
| .risk-badge.high {{ background: var(--risk-high-bg); color: var(--risk-high-text); }} |
| .risk-badge.critical {{ background: var(--risk-critical-bg); color: var(--risk-critical-text); }} |
| |
| /* 图例 */ |
| .legend-bar {{ |
| background: white; |
| padding: 16px 24px; |
| border-radius: 12px; |
| margin-bottom: 24px; |
| box-shadow: 0 2px 8px rgba(0,0,0,0.08); |
| display: flex; |
| gap: 24px; |
| flex-wrap: wrap; |
| align-items: center; |
| }} |
| |
| .legend-title {{ |
| font-weight: 600; |
| color: var(--text-primary); |
| margin-right: 12px; |
| }} |
| |
| .legend-item {{ |
| display: flex; |
| align-items: center; |
| gap: 8px; |
| font-size: 13px; |
| color: var(--text-secondary); |
| }} |
| |
| .legend-color {{ |
| width: 20px; |
| height: 20px; |
| border-radius: 4px; |
| border: 2px solid transparent; |
| }} |
| |
| /* 全文容器 */ |
| .document-container {{ |
| background: white; |
| border-radius: 12px; |
| padding: 48px 60px; |
| box-shadow: 0 2px 12px rgba(0,0,0,0.08); |
| font-family: 'Noto Serif SC', 'SimSun', serif; |
| font-size: 16px; |
| line-height: 2; |
| }} |
| |
| /* 段落样式 */ |
| .para {{ |
| margin-bottom: 16px; |
| padding: 16px 20px; |
| border-radius: 8px; |
| border-left: 4px solid transparent; |
| position: relative; |
| transition: all 0.2s ease; |
| }} |
| |
| .para:hover {{ |
| box-shadow: 0 2px 8px rgba(0,0,0,0.1); |
| transform: translateX(4px); |
| }} |
| |
| /* 风险等级样式 */ |
| .para.low {{ |
| background: var(--risk-low-bg); |
| border-left-color: var(--risk-low-border); |
| }} |
| |
| .para.medium {{ |
| background: var(--risk-medium-bg); |
| border-left-color: var(--risk-medium-border); |
| }} |
| |
| .para.high {{ |
| background: var(--risk-high-bg); |
| border-left-color: var(--risk-high-border); |
| }} |
| |
| .para.critical {{ |
| background: var(--risk-critical-bg); |
| border-left-color: var(--risk-critical-border); |
| }} |
| |
| .para-header {{ |
| display: flex; |
| justify-content: space-between; |
| align-items: center; |
| margin-bottom: 8px; |
| font-family: 'Noto Sans SC', sans-serif; |
| }} |
| |
| .para-num {{ |
| font-size: 12px; |
| font-weight: 600; |
| color: var(--text-secondary); |
| background: rgba(255,255,255,0.6); |
| padding: 4px 10px; |
| border-radius: 12px; |
| }} |
| |
| .para-score {{ |
| display: flex; |
| align-items: center; |
| gap: 8px; |
| font-size: 13px; |
| font-weight: 600; |
| }} |
| |
| .para-score.low {{ color: var(--risk-low-text); }} |
| .para-score.medium {{ color: var(--risk-medium-text); }} |
| .para-score.high {{ color: var(--risk-high-text); }} |
| .para-score.critical {{ color: var(--risk-critical-text); }} |
| |
| .para-text {{ |
| text-indent: 2em; |
| color: var(--text-primary); |
| }} |
| |
| /* 统计面板 */ |
| .stats-panel {{ |
| display: grid; |
| grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); |
| gap: 16px; |
| margin-bottom: 24px; |
| }} |
| |
| .stat-item {{ |
| background: white; |
| padding: 20px; |
| border-radius: 12px; |
| text-align: center; |
| box-shadow: 0 2px 8px rgba(0,0,0,0.08); |
| }} |
| |
| .stat-value {{ |
| font-size: 28px; |
| font-weight: 700; |
| color: var(--primary); |
| margin-bottom: 4px; |
| }} |
| |
| .stat-label {{ |
| font-size: 12px; |
| color: var(--text-secondary); |
| }} |
| |
| /* 建议区域 */ |
| .suggestions {{ |
| background: white; |
| border-radius: 12px; |
| padding: 32px; |
| margin-top: 24px; |
| box-shadow: 0 2px 12px rgba(0,0,0,0.08); |
| }} |
| |
| .suggestions h2 {{ |
| font-family: 'Noto Serif SC', serif; |
| font-size: 20px; |
| color: var(--primary); |
| margin-bottom: 20px; |
| padding-bottom: 12px; |
| border-bottom: 2px solid var(--border); |
| }} |
| |
| .suggestion-list {{ |
| list-style: none; |
| }} |
| |
| .suggestion-list li {{ |
| padding: 16px 0; |
| border-bottom: 1px solid var(--border); |
| display: flex; |
| gap: 16px; |
| }} |
| |
| .suggestion-num {{ |
| width: 28px; |
| height: 28px; |
| background: var(--primary); |
| color: white; |
| border-radius: 50%; |
| display: flex; |
| align-items: center; |
| justify-content: center; |
| font-size: 13px; |
| font-weight: 600; |
| flex-shrink: 0; |
| }} |
| |
| .suggestion-content h4 {{ |
| font-weight: 600; |
| margin-bottom: 4px; |
| }} |
| |
| .suggestion-content p {{ |
| font-size: 14px; |
| color: var(--text-secondary); |
| }} |
| |
| /* 免责声明 */ |
| .disclaimer {{ |
| background: #f8fafc; |
| border: 1px solid var(--border); |
| border-radius: 12px; |
| padding: 24px; |
| margin-top: 24px; |
| text-align: center; |
| font-size: 13px; |
| color: var(--text-secondary); |
| }} |
| |
| /* 打印样式 */ |
| @media print {{ |
| .container {{ padding: 0; }} |
| .document-container {{ box-shadow: none; }} |
| .para {{ break-inside: avoid; }} |
| }} |
| |
| @media (max-width: 768px) {{ |
| .document-container {{ padding: 24px; }} |
| .metrics-bar {{ flex-direction: column; }} |
| }} |
| </style> |
| </head> |
| <body> |
| <div class="container"> |
| {self._render_header()} |
| {self._render_metrics()} |
| {self._render_stats()} |
| {self._render_legend()} |
| {self._render_full_text()} |
| {self._render_suggestions()} |
| {self._render_footer()} |
| </div> |
| </body> |
| </html>""" |
| |
| def _render_header(self) -> str: |
| """渲染报告头部""" |
| filename = self.docx_path.name |
| return f""" |
| <header class="report-header"> |
| <div class="report-badge">AIGC检测全文报告 · CONFIDENTIAL</div> |
| <h1 class="report-title">MBA论文AIGC检测报告</h1> |
| <div class="report-meta"> |
| <div>报告编号: {self.report_id}</div> |
| <div>检测时间: {self.report_time}</div> |
| <div>文件名: {filename}</div> |
| <div>检测系统: MBA-AIGC-Detector v1.0 (CNKI校准版)</div> |
| </div> |
| </header>""" |
| |
| def _render_metrics(self) -> str: |
| """渲染核心指标""" |
| score = self.data.get('doc_calibrated_score', 0) * 100 |
| raw_score = self.data.get('doc_raw_score', 0) * 100 |
| risk = self.data.get('risk_level', '未知') |
| |
| if '低' in risk: |
| risk_class = 'low' |
| card_class = '' |
| elif '中' in risk: |
| risk_class = 'medium' |
| card_class = 'warning' |
| elif '较高' in risk: |
| risk_class = 'high' |
| card_class = 'danger' |
| else: |
| risk_class = 'critical' |
| card_class = 'danger' |
| |
| return f""" |
| <div class="metrics-bar"> |
| <div class="metric-item {card_class}"> |
| <div class="metric-label">文档级AIGC分数 (CNKI校准)</div> |
| <div class="metric-value {card_class}">{score:.1f}%</div> |
| <span class="risk-badge {risk_class}">{risk}</span> |
| </div> |
| <div class="metric-item"> |
| <div class="metric-label">原始检测分数</div> |
| <div class="metric-value">{raw_score:.1f}%</div> |
| </div> |
| </div>""" |
| |
| def _render_stats(self) -> str: |
| """渲染统计面板""" |
| ai_count = self.data.get('ai_paragraph_count', 0) |
| total = self.data.get('total_paragraphs', 0) |
| human_count = total - ai_count |
| ratio = self.data.get('ai_ratio', 0) * 100 |
| |
| |
| paras = self.data.get('paragraph_results', []) |
| low_count = sum(1 for p in paras if p['calibrated_score'] * 100 < 15) |
| medium_count = sum(1 for p in paras if 15 <= p['calibrated_score'] * 100 < 30) |
| high_count = sum(1 for p in paras if 30 <= p['calibrated_score'] * 100 < 50) |
| critical_count = sum(1 for p in paras if p['calibrated_score'] * 100 >= 50) |
| |
| return f""" |
| <div class="stats-panel"> |
| <div class="stat-item"> |
| <div class="stat-value">{total}</div> |
| <div class="stat-label">总段落数</div> |
| </div> |
| <div class="stat-item"> |
| <div class="stat-value" style="color: var(--accent);">{ai_count}</div> |
| <div class="stat-label">AI疑似段落</div> |
| </div> |
| <div class="stat-item"> |
| <div class="stat-value" style="color: var(--success);">{human_count}</div> |
| <div class="stat-label">人工疑似段落</div> |
| </div> |
| <div class="stat-item"> |
| <div class="stat-value" style="color: var(--warning);">{medium_count + high_count + critical_count}</div> |
| <div class="stat-label">中高风险段落</div> |
| </div> |
| </div>""" |
| |
| def _render_legend(self) -> str: |
| """渲染图例""" |
| return """ |
| <div class="legend-bar"> |
| <span class="legend-title">📊 段落风险等级标注:</span> |
| <div class="legend-item"> |
| <div class="legend-color" style="background: var(--risk-low-bg); border-color: var(--risk-low-border);"></div> |
| <span>低风险 (<15%)</span> |
| </div> |
| <div class="legend-item"> |
| <div class="legend-color" style="background: var(--risk-medium-bg); border-color: var(--risk-medium-border);"></div> |
| <span>中风险 (15-30%)</span> |
| </div> |
| <div class="legend-item"> |
| <div class="legend-color" style="background: var(--risk-high-bg); border-color: var(--risk-high-border);"></div> |
| <span>较高风险 (30-50%)</span> |
| </div> |
| <div class="legend-item"> |
| <div class="legend-color" style="background: var(--risk-critical-bg); border-color: var(--risk-critical-border);"></div> |
| <span>高风险 (>50%)</span> |
| </div> |
| </div>""" |
| |
| def _render_full_text(self) -> str: |
| """渲染带标注的全文""" |
| results = self.data.get('paragraph_results', []) |
| |
| |
| result_map = {p['para_id']: p for p in results} |
| |
| paras_html = [] |
| for i, text in enumerate(self.paragraphs): |
| if not text.strip(): |
| continue |
| |
| result = result_map.get(i, {}) |
| score = result.get('calibrated_score', 0) * 100 |
| is_ai = result.get('is_ai', False) |
| triggered = result.get('triggered_by', 'N/A') |
| |
| |
| if score < 15: |
| risk_class = 'low' |
| risk_text = '低风险' |
| elif score < 30: |
| risk_class = 'medium' |
| risk_text = '中风险' |
| elif score < 50: |
| risk_class = 'high' |
| risk_text = '较高风险' |
| else: |
| risk_class = 'critical' |
| risk_text = '高风险' |
| |
| |
| display_text = text[:500] + ('...' if len(text) > 500 else '') |
| |
| paras_html.append(f""" |
| <div class="para {risk_class}"> |
| <div class="para-header"> |
| <span class="para-num">段落 {i+1}</span> |
| <span class="para-score {risk_class}"> |
| AIGC: {score:.1f}% | {risk_text} | 模型: {triggered} |
| </span> |
| </div> |
| <div class="para-text">{display_text}</div> |
| </div>""") |
| |
| return f""" |
| <div class="document-container"> |
| <h2 style="font-family: 'Noto Sans SC', sans-serif; font-size: 18px; color: var(--primary); margin-bottom: 24px; padding-bottom: 12px; border-bottom: 2px solid var(--border);"> |
| 📄 检测文档全文 (带风险标注) |
| </h2> |
| {''.join(paras_html)} |
| </div>""" |
| |
| def _render_suggestions(self) -> str: |
| """渲染建议""" |
| score = self.data.get('doc_calibrated_score', 0) * 100 |
| |
| if score < 15: |
| risk_desc = "低风险" |
| suggestions = [ |
| ("整体评估良好", "文档AIGC分数在正常范围内，未发现明显的AI生成痕迹。"), |
| ("继续保持", "建议保持当前的写作风格，注重个人观点和原创性表达。"), |
| ] |
| elif score < 30: |
| risk_desc = "中风险" |
| suggestions = [ |
| ("重点复核", "建议对黄色标注(中风险)的段落进行人工审查和改写。"), |
| ("增加原创性", "在疑似AI段落中增加个人观点、案例分析、实地调研数据。"), |
| ("改写优化", "对模板化表达进行改写，使用更自然的语言风格。"), |
| ] |
| elif score < 50: |
| risk_desc = "较高风险" |
| suggestions = [ |
| ("深度审查", "文档存在明显的AI生成痕迹，建议进行全面审查和改写。"), |
| ("重构内容", "对橙色/红色标注段落进行深度改写，增加原创分析。"), |
| ("数据支撑", "补充原始调研数据、访谈记录等一手资料。"), |
| ] |
| else: |
| risk_desc = "高风险" |
| suggestions = [ |
| ("紧急处理", "文档高度疑似AI生成，建议暂停提交，进行全面重写。"), |
| ("重新撰写", "建议基于个人研究重新撰写论文，确保学术诚信。"), |
| ("导师沟通", "立即与导师沟通，说明情况并寻求指导。"), |
| ] |
| |
| items = ''.join([ |
| f""" |
| <li> |
| <div class="suggestion-num">{i+1}</div> |
| <div class="suggestion-content"> |
| <h4>{title}</h4> |
| <p>{desc}</p> |
| </div> |
| </li>""" |
| for i, (title, desc) in enumerate(suggestions) |
| ]) |
| |
| return f""" |
| <div class="suggestions"> |
| <h2>💡 修改建议 ({risk_desc})</h2> |
| <ul class="suggestion-list"> |
| {items} |
| </ul> |
| </div>""" |
| |
| def _render_footer(self) -> str: |
| """渲染页脚""" |
| return f""" |
| <div class="disclaimer"> |
| <p><strong>免责声明</strong></p> |
| <p>本系统输出仅供参考，不构成对学术不端行为的直接认定，也不替代学校官方检测系统或CNKI等权威检测结果。</p> |
| <p style="margin-top: 8px;">MBA-AIGC-Detector v1.0 | 报告生成时间: {self.report_time}</p> |
| </div>""" |
|
|
|
|
| def main(): |
| from pathlib import Path |
| |
| parser = argparse.ArgumentParser(description='生成HTML格式AIGC检测报告(全文标注版)') |
| parser.add_argument('--json', type=str, required=True, help='检测结果JSON文件路径') |
| parser.add_argument('--docx', type=str, required=True, help='原始DOCX文件路径') |
| parser.add_argument('--output', '-o', type=str, required=True, help='输出HTML文件路径') |
| |
| args = parser.parse_args() |
| |
| |
| with open(args.json, 'r', encoding='utf-8') as f: |
| data = json.load(f) |
| |
| |
| import sys |
| sys.path.insert(0, str(Path(__file__).parent)) |
| from document_processor import DocumentProcessor |
| |
| processor = DocumentProcessor() |
| paragraphs = processor.process(Path(args.docx)) |
| |
| |
| generator = HTMLReportGenerator(data, args.docx, paragraphs) |
| generator.generate(args.output) |
|
|
|
|
| if __name__ == '__main__': |
| main() |
|
|
