Selig
f1a6df4ca4
- Add code-interpreter, kokoro-tts, remotion-best-practices, research-to-paper-slides, summarize, tavily-tool to source repo - skill-review: add main/xiaoming agent mapping in handler.ts + SKILL.md - tts-voice: handler.ts updates from agent workspace Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
499 lines
27 KiB
Python
499 lines
27 KiB
Python
#!/usr/bin/env python3
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import argparse
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import json
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import html
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import shutil
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from pathlib import Path
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from typing import Any
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MODES = {'academic', 'business', 'pitch'}
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LEVELS = {'v2', 'v3', 'v4'}
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LEVEL_NOTES = {
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'v2': '基礎交付版：paper/slides/speaker-notes/deck',
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'v3': '洞察強化版：v2 + insights + 每張圖逐頁解讀',
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'v4': '正式交付版：v3 + 更正式 deck 視覺 + PDF-ready 工作流',
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}
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def read_json(path: Path) -> dict[str, Any]:
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return json.loads(path.read_text(encoding='utf-8'))
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def read_text(path: Path) -> str:
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return path.read_text(encoding='utf-8')
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def find_plots(analysis_dir: Path) -> list[Path]:
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return sorted([p for p in analysis_dir.glob('*.png') if p.is_file()])
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def build_key_findings(summary: dict[str, Any]) -> list[str]:
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findings: list[str] = []
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for name, meta in summary.get('columnProfiles', {}).items():
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if 'mean' in meta and meta.get('mean') is not None:
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findings.append(f"欄位「{name}」平均值約為 {meta['mean']:.2f}，總和約為 {meta['sum']:.2f}。")
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elif meta.get('topValues'):
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top = meta['topValues'][0]
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findings.append(f"欄位「{name}」最常見值為「{top['value']}」，出現 {top['count']} 次。")
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if len(findings) >= 6:
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break
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if not findings:
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findings.append('資料已完成初步整理，但尚缺少足夠特徵以自動歸納具體發現。')
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return findings
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def build_method_text(summary: dict[str, Any]) -> str:
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rows = summary.get('rows', 0)
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cols = summary.get('columns', 0)
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parsed_dates = summary.get('parsedDateColumns', [])
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parts = [f"本研究以一份包含 {rows} 筆資料、{cols} 個欄位的資料集作為分析基礎。"]
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if parsed_dates:
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parts.append(f"其中已自動辨識日期欄位：{', '.join(parsed_dates)}。")
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parts.append("分析流程包含欄位剖析、數值摘要、類別分布觀察，以及圖表化初步探索。")
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return ''.join(parts)
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def build_limitations(summary: dict[str, Any], mode: str) -> list[str]:
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base = [
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'本版本內容依據自動分析結果生成，仍需依情境補充背景、語境與論證細節。',
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'目前主要反映描述性分析與初步視覺化結果，尚未自動進行嚴格因果推論或完整驗證。',
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]
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if mode == 'pitch':
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base[0] = '本版本適合作為提案底稿，但對外簡報前仍需補上商業敘事、案例與風險說明。'
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elif mode == 'business':
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base[0] = '本版本可支援內部決策討論，但正式匯報前仍建議補充商務脈絡與對照基準。'
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elif mode == 'academic':
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base[0] = '本版本可作為論文或研究報告草稿，但正式提交前仍需補足文獻回顧、研究問題與方法論細節。'
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if not summary.get('plots'):
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base.append('本次分析未包含圖表產物，因此視覺化證據仍需後續補充。')
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return base
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def classify_plot(name: str) -> str:
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low = name.lower()
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if low.startswith('hist_'):
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return 'histogram'
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if low.startswith('bar_'):
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return 'bar'
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if low.startswith('line_'):
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return 'line'
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return 'plot'
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def interpret_plot(plot: Path, mode: str) -> dict[str, str]:
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kind = classify_plot(plot.name)
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base = {
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'histogram': {
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'title': f'圖表解讀：{plot.name}',
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'summary': '這張 histogram 用來觀察數值欄位的分布狀態、集中區域與可能的離群位置。',
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'so_what': '若資料分布偏斜或過度集中，後續可考慮分群、分層或補充異常值檢查。',
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},
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'bar': {
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'title': f'圖表解讀：{plot.name}',
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'summary': '這張 bar chart 適合比較不同類別或分組之間的量體差異，幫助快速辨識高低落差。',
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'so_what': '若類別差異明顯，後續可針對高表現或低表現組別追查原因與策略。',
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},
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'line': {
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'title': f'圖表解讀：{plot.name}',
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'summary': '這張 line chart 用於觀察時間序列變化，幫助辨識趨勢、波動與可能轉折點。',
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'so_what': '若趨勢持續上升或下降，建議進一步比對外部事件、季節性與干預因素。',
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},
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'plot': {
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'title': f'圖表解讀：{plot.name}',
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'summary': '這張圖表提供一個視覺化切面，有助於快速掌握資料重點與分布特徵。',
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'so_what': '建議將圖表與主要論點對齊，補上更具體的背景解讀。',
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},
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}[kind]
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if mode == 'pitch':
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base['so_what'] = '簡報時應直接說明這張圖支持了哪個主張，以及它如何增加說服力。'
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elif mode == 'business':
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base['so_what'] = '建議把這張圖對應到 KPI、風險或下一步行動，方便管理層做判斷。'
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elif mode == 'academic':
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base['so_what'] = '建議將這張圖與研究問題、假設或比較基準一起討論，以提升論證完整度。'
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return base
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def build_insights(summary: dict[str, Any], plots: list[Path], mode: str) -> list[str]:
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insights: list[str] = []
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numeric = []
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categorical = []
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for name, meta in summary.get('columnProfiles', {}).items():
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if 'mean' in meta and meta.get('mean') is not None:
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numeric.append((name, meta))
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elif meta.get('topValues'):
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categorical.append((name, meta))
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for name, meta in numeric[:3]:
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insights.append(f"數值欄位「{name}」平均約 {meta['mean']:.2f}，範圍約 {meta['min']:.2f} 到 {meta['max']:.2f}。")
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for name, meta in categorical[:2]:
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top = meta['topValues'][0]
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insights.append(f"類別欄位「{name}」目前以「{top['value']}」最常見（{top['count']} 次），值得作為第一輪聚焦對象。")
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if plots:
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insights.append(f"本次已生成 {len(plots)} 張圖表，可直接支撐逐頁圖表解讀與口頭報告。")
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if mode == 'pitch':
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insights.append('對外提案時，建議把最強的一項數據證據前置，讓聽眾先記住價值主張。')
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elif mode == 'business':
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insights.append('內部決策簡報時，建議把洞察轉成 KPI、優先順序與負責人。')
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elif mode == 'academic':
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insights.append('學術/研究情境下，建議將洞察進一步轉成研究問題、比較架構與後續驗證方向。')
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return insights
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def make_insights_md(title: str, mode: str, summary: dict[str, Any], plots: list[Path]) -> str:
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insights = build_insights(summary, plots, mode)
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plot_notes = [interpret_plot(p, mode) for p in plots]
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lines = [f"# {title}｜Insights", '', f"- 模式：`{mode}`", '']
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lines.append('## 關鍵洞察')
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lines.extend([f"- {x}" for x in insights])
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lines.append('')
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if plot_notes:
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lines.append('## 圖表解讀摘要')
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for note in plot_notes:
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lines.append(f"### {note['title']}")
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lines.append(f"- 解讀：{note['summary']}")
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lines.append(f"- 延伸：{note['so_what']}")
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lines.append('')
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return '\n'.join(lines).strip() + '\n'
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def make_paper(title: str, audience: str, purpose: str, mode: str, level: str, summary: dict[str, Any], report_md: str, plots: list[Path], insights_md: str | None = None) -> str:
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findings = build_key_findings(summary)
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method_text = build_method_text(summary)
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limitations = build_limitations(summary, mode)
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plot_refs = '\n'.join([f"- `{p.name}`" for p in plots]) or '- 無'
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findings_md = '\n'.join([f"- {x}" for x in findings])
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limitations_md = '\n'.join([f"- {x}" for x in limitations])
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if mode == 'academic':
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sections = f"## 摘要\n\n本文面向{audience}，以「{purpose}」為導向，整理目前資料分析結果並形成學術/研究草稿。\n\n## 研究背景與問題意識\n\n本文件根據既有分析產物自動整理，可作為研究報告、論文初稿或研究提案的起點。\n\n## 研究方法\n\n{method_text}\n\n## 研究發現\n\n{findings_md}\n\n## 討論\n\n目前結果可支撐初步描述性討論，後續可進一步補上研究假設、比較對照與方法嚴謹性。\n\n## 限制\n\n{limitations_md}\n\n## 結論\n\n本分析已形成研究性文件的結構基礎，適合進一步擴展為正式研究報告。"
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elif mode == 'business':
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sections = f"## 執行摘要\n\n本文面向{audience}，目的是支援「{purpose}」的商務溝通與內部決策。\n\n## 商務背景\n\n本文件根據既有分析產物自動整理，適合作為內部簡報、策略討論或管理層報告的第一版。\n\n## 分析方法\n\n{method_text}\n\n## 關鍵洞察\n\n{findings_md}\n\n## 商業意涵\n\n目前資料已足以支撐一輪決策討論，建議進一步對照 KPI、目標值與外部環境。\n\n## 風險與限制\n\n{limitations_md}\n\n## 建議下一步\n\n建議針對最具決策價值的指標建立定期追蹤與後續驗證流程。"
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else:
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sections = f"## Pitch Summary\n\n本文面向{audience}，用於支援「{purpose}」的提案、募資或說服型簡報。\n\n## Opportunity\n\n本文件根據既有分析產物自動整理，可作為提案 deck 與口頭簡報的第一版底稿。\n\n## Evidence\n\n{method_text}\n\n## Key Takeaways\n\n{findings_md}\n\n## Why It Matters\n\n目前結果已可形成明確敘事雛形，後續可補上市場機會、競品比較與具體行動方案。\n\n## Risks\n\n{limitations_md}\n\n## Ask / Next Step\n\n建議將數據證據、主張與下一步行動整合成對外一致的提案版本。"
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insight_section = ''
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if insights_md:
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insight_section = f"\n## 洞察摘要\n\n{insights_md}\n"
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return f"# {title}\n\n- 模式：`{mode}`\n- 等級：`{level}` — {LEVEL_NOTES[level]}\n- 對象：{audience}\n- 目的：{purpose}\n\n{sections}\n\n## 圖表與視覺化資產\n\n{plot_refs}{insight_section}\n## 附錄：原始自動分析摘要\n\n{report_md}\n"
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def make_slides(title: str, audience: str, purpose: str, mode: str, summary: dict[str, Any], plots: list[Path], level: str) -> str:
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findings = build_key_findings(summary)
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rows = summary.get('rows', 0)
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cols = summary.get('columns', 0)
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if mode == 'academic':
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slides = [
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('封面', [f'標題：{title}', f'對象：{audience}', f'目的：{purpose}', f'等級：{LEVEL_NOTES[level]}']),
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('研究問題', ['定義研究背景與核心問題', '說明本次分析欲回答的主題']),
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('資料概況', [f'資料筆數：{rows}', f'欄位數：{cols}', '已完成基本欄位剖析與摘要']),
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('方法', ['描述性統計', '類別分布觀察', '視覺化探索']),
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('研究發現', findings[:3]),
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('討論', ['解釋主要發現的可能意義', '連結研究問題與資料結果']),
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('限制', build_limitations(summary, mode)[:2]),
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('後續研究', ['補充文獻回顧', '加入比較基準與進階分析']),
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('結論', ['本份簡報可作為研究報告或論文簡報的第一版底稿']),
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]
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elif mode == 'business':
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slides = [
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('封面', [f'標題：{title}', f'對象：{audience}', f'目的：{purpose}', f'等級：{LEVEL_NOTES[level]}']),
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('決策問題', ['這份分析要支援什麼決策', '為什麼現在需要處理']),
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('資料概況', [f'資料筆數：{rows}', f'欄位數：{cols}', '已完成基本資料盤點']),
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('分析方法', ['描述性統計', '類別分布觀察', '視覺化探索']),
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('關鍵洞察', findings[:3]),
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('商業意涵', ['把數據結果轉成管理層可理解的含義', '指出可能影響的目標或 KPI']),
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('風險與限制', build_limitations(summary, mode)[:2]),
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('建議行動', ['列出近期可執行事項', '定義需要追蹤的指標']),
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('結語', ['本份簡報可作為正式管理簡報的第一版底稿']),
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]
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else:
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slides = [
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('封面', [f'標題：{title}', f'對象：{audience}', f'目的：{purpose}', f'等級：{LEVEL_NOTES[level]}']),
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('痛點 / 機會', ['說明這份分析解決什麼問題', '點出為什麼值得關注']),
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('證據基礎', [f'資料筆數：{rows}', f'欄位數：{cols}', '已完成資料摘要與圖表探索']),
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('方法', ['描述性統計', '類別觀察', '關鍵圖表整理']),
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('核心亮點', findings[:3]),
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('為什麼重要', ['連結價值、影響與說服力', '把發現轉成可傳達的敘事']),
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('風險', build_limitations(summary, mode)[:2]),
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('Next Step / Ask', ['明確提出下一步', '對齊資源、合作或決策需求']),
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('結語', ['本份 deck 可作為提案或募資簡報的第一版底稿']),
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]
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parts = [f"# {title}｜簡報稿\n\n- 模式：`{mode}`\n- 等級：`{level}` — {LEVEL_NOTES[level]}\n"]
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slide_no = 1
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for heading, bullets in slides:
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parts.append(f"## Slide {slide_no} — {heading}")
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parts.extend([f"- {x}" for x in bullets])
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parts.append('')
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slide_no += 1
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if level in {'v3', 'v4'} and plots:
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for plot in plots:
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note = interpret_plot(plot, mode)
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parts.append(f"## Slide {slide_no} — {note['title']}")
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parts.append(f"- 圖檔：{plot.name}")
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parts.append(f"- 解讀：{note['summary']}")
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parts.append(f"- 延伸：{note['so_what']}")
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parts.append('')
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slide_no += 1
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return '\n'.join(parts).strip() + '\n'
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def make_speaker_notes(title: str, mode: str, summary: dict[str, Any], plots: list[Path], level: str) -> str:
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findings = build_key_findings(summary)
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findings_md = '\n'.join([f"- {x}" for x in findings])
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opener = {
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'academic': '先交代研究背景、研究問題與資料來源，再說明這份內容是研究草稿第一版。',
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'business': '先講這份分析支援哪個決策，再交代這份內容的管理價值與時間敏感性。',
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'pitch': '先抓住聽眾注意力，說明痛點、機會與這份資料為何值得相信。',
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}[mode]
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closer = {
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'academic': '結尾時回到研究限制與後續研究方向。',
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'business': '結尾時回到建議行動與追蹤機制。',
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'pitch': '結尾時回到 ask、資源需求與下一步承諾。',
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}[mode]
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parts = [
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f"# {title}｜Speaker Notes",
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'',
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f"- 模式：`{mode}`",
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f"- 等級：`{level}` — {LEVEL_NOTES[level]}",
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'',
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'## 開場',
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f"- {opener}",
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'',
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'## 重點提示',
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findings_md,
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'',
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]
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if level in {'v3', 'v4'} and plots:
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parts.extend(['## 逐圖口頭提示', ''])
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for plot in plots:
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note = interpret_plot(plot, mode)
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parts.append(f"### {plot.name}")
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parts.append(f"- {note['summary']}")
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parts.append(f"- {note['so_what']}")
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||
parts.append('')
|
||
parts.extend(['## 收尾建議', f"- {closer}", '- 針對最重要的一張圖，多講一層其背後的意義與行動建議。', ''])
|
||
return '\n'.join(parts)
|
||
|
||
|
||
def make_deck_html(title: str, audience: str, purpose: str, slides_md: str, plots: list[Path], mode: str, level: str) -> str:
|
||
if level == 'v4':
|
||
theme = {
|
||
'academic': {'primary': '#0f172a', 'accent': '#334155', 'bg': '#eef2ff', 'hero': 'linear-gradient(135deg,#0f172a 0%,#1e293b 55%,#475569 100%)'},
|
||
'business': {'primary': '#0b3b66', 'accent': '#1d4ed8', 'bg': '#eff6ff', 'hero': 'linear-gradient(135deg,#0b3b66 0%,#1d4ed8 60%,#60a5fa 100%)'},
|
||
'pitch': {'primary': '#4c1d95', 'accent': '#7c3aed', 'bg': '#faf5ff', 'hero': 'linear-gradient(135deg,#4c1d95 0%,#7c3aed 60%,#c084fc 100%)'},
|
||
}[mode]
|
||
primary = theme['primary']
|
||
accent = theme['accent']
|
||
bg = theme['bg']
|
||
hero = theme['hero']
|
||
plot_map = {p.name: p for p in plots}
|
||
else:
|
||
primary = '#1f2937'
|
||
accent = '#2563eb'
|
||
bg = '#f6f8fb'
|
||
hero = None
|
||
plot_map = {p.name: p for p in plots}
|
||
|
||
slide_blocks = []
|
||
current = []
|
||
current_title = None
|
||
for line in slides_md.splitlines():
|
||
if line.startswith('## Slide '):
|
||
if current_title is not None:
|
||
slide_blocks.append((current_title, current))
|
||
current_title = line.replace('## ', '', 1)
|
||
current = []
|
||
elif line.startswith('- 模式：') or line.startswith('- 等級：') or line.startswith('# '):
|
||
continue
|
||
else:
|
||
current.append(line)
|
||
if current_title is not None:
|
||
slide_blocks.append((current_title, current))
|
||
|
||
sections = []
|
||
for heading, body in slide_blocks:
|
||
body_html = []
|
||
referenced_plot = None
|
||
for line in body:
|
||
line = line.strip()
|
||
if not line:
|
||
continue
|
||
if line.startswith('- 圖檔：'):
|
||
plot_name = line.replace('- 圖檔：', '', 1).strip()
|
||
referenced_plot = plot_map.get(plot_name)
|
||
body_html.append(f"<li>{html.escape(line[2:])}</li>")
|
||
elif line.startswith('- '):
|
||
body_html.append(f"<li>{html.escape(line[2:])}</li>")
|
||
else:
|
||
body_html.append(f"<p>{html.escape(line)}</p>")
|
||
img_html = ''
|
||
if referenced_plot and level in {'v3', 'v4'}:
|
||
img_html = f"<div class='plot-single'><img src='{html.escape(referenced_plot.name)}' alt='{html.escape(referenced_plot.name)}' /><div class='plot-caption'>圖：{html.escape(referenced_plot.name)}</div></div>"
|
||
list_items = ''.join(x for x in body_html if x.startswith('<li>'))
|
||
paras = ''.join(x for x in body_html if x.startswith('<p>'))
|
||
list_html = f"<ul>{list_items}</ul>" if list_items else ''
|
||
if level == 'v4':
|
||
sections.append(
|
||
f"<section class='slide'><div class='slide-top'><div class='eyebrow'>{html.escape(mode.upper())}</div>"
|
||
f"<div class='page-tag'>{html.escape(heading.split(' — ')[0])}</div></div><h2>{html.escape(heading)}</h2>{paras}{list_html}{img_html}</section>"
|
||
)
|
||
else:
|
||
sections.append(f"<section class='slide'><h2>{html.escape(heading)}</h2>{paras}{list_html}{img_html}</section>")
|
||
|
||
if level == 'v4':
|
||
css = f"""
|
||
@page {{ size: A4 landscape; margin: 0; }}
|
||
@media print {{
|
||
body {{ background: #fff; padding: 0; }}
|
||
.slide {{ box-shadow: none; margin: 0; min-height: 100vh; border-radius: 0; page-break-after: always; page-break-inside: avoid; border-top-width: 16px; border-top-style: solid; border-top-color: {accent}; }}
|
||
.hero {{ box-shadow: none; margin: 0; min-height: 100vh; border-radius: 0; }}
|
||
}}
|
||
body {{ font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, 'Noto Sans CJK TC', sans-serif; background: {bg}; margin: 0; padding: 32px; color: {primary}; }}
|
||
.hero {{ max-width: 1180px; margin: 0 auto 32px; padding: 56px 64px; border-radius: 32px; background: {hero}; color: white; box-shadow: 0 32px 64px rgba(15,23,42,.15); display: flex; flex-direction: column; justify-content: center; min-height: 500px; }}
|
||
.hero h1 {{ margin: 12px 0 20px; font-size: 52px; line-height: 1.2; letter-spacing: -0.02em; font-weight: 800; text-wrap: balance; }}
|
||
.hero p {{ margin: 8px 0; font-size: 20px; opacity: .9; font-weight: 400; }}
|
||
.hero-meta {{ display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 16px; margin-top: 48px; }}
|
||
.hero-card {{ background: rgba(255,255,255,.1); border: 1px solid rgba(255,255,255,.2); border-radius: 20px; padding: 20px 24px; backdrop-filter: blur(10px); }}
|
||
.hero-card strong {{ display: block; font-size: 14px; text-transform: uppercase; letter-spacing: 0.05em; opacity: 0.8; margin-bottom: 6px; }}
|
||
.slide {{ background: #fff; border-radius: 32px; padding: 48px 56px; margin: 0 auto 32px; max-width: 1180px; min-height: 660px; box-shadow: 0 16px 48px rgba(15,23,42,.08); page-break-after: always; border-top: 16px solid {accent}; position: relative; overflow: hidden; display: flex; flex-direction: column; }}
|
||
.slide::after {{ content: ''; position: absolute; right: -80px; top: -80px; width: 240px; height: 240px; background: radial-gradient(circle, {bg} 0%, rgba(255,255,255,0) 70%); pointer-events: none; }}
|
||
.slide-top {{ display: flex; justify-content: space-between; align-items: center; margin-bottom: 24px; z-index: 1; }}
|
||
h1, h2 {{ margin-top: 0; font-weight: 700; }}
|
||
h2 {{ font-size: 36px; margin-bottom: 24px; color: {primary}; letter-spacing: -0.01em; }}
|
||
.slide p {{ font-size: 20px; line-height: 1.6; color: #334155; margin-bottom: 16px; }}
|
||
.slide ul {{ line-height: 1.6; font-size: 22px; padding-left: 28px; color: #1e293b; margin-top: 8px; flex-grow: 1; }}
|
||
.slide li {{ position: relative; padding-left: 8px; }}
|
||
.slide li + li {{ margin-top: 14px; }}
|
||
.slide li::marker {{ color: {accent}; font-weight: bold; }}
|
||
.eyebrow {{ display: inline-flex; align-items: center; padding: 8px 16px; border-radius: 999px; background: {bg}; color: {accent}; font-weight: 800; font-size: 13px; letter-spacing: .1em; box-shadow: 0 2px 8px rgba(0,0,0,0.04); }}
|
||
.page-tag {{ color: #94a3b8; font-size: 14px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.05em; }}
|
||
.plot-single {{ margin-top: auto; text-align: center; padding-top: 24px; position: relative; display: flex; flex-direction: column; align-items: center; justify-content: center; }}
|
||
.plot-single img {{ max-width: 100%; max-height: 380px; border: 1px solid #e2e8f0; border-radius: 20px; background: #f8fafc; box-shadow: 0 12px 32px rgba(15,23,42,.06); padding: 8px; }}
|
||
.plot-caption {{ margin-top: 14px; font-size: 15px !important; color: #64748b !important; font-style: italic; text-align: center; background: #f1f5f9; padding: 6px 16px; border-radius: 999px; }}
|
||
""".strip()
|
||
hero_html = (
|
||
f"<div class='hero'><div class='eyebrow'>{html.escape(mode.upper())}</div>"
|
||
f"<h1>{html.escape(title)}</h1><p>適用對象：{html.escape(audience)}</p><p>目的：{html.escape(purpose)}</p>"
|
||
f"<div class='hero-meta'>"
|
||
f"<div class='hero-card'><strong>等級</strong><br>{html.escape(level)} — {html.escape(LEVEL_NOTES[level])}</div>"
|
||
f"<div class='hero-card'><strong>圖表數量</strong><br>{len(plots)}</div>"
|
||
f"<div class='hero-card'><strong>輸出定位</strong><br>正式 deck / PDF-ready</div>"
|
||
f"</div></div>"
|
||
)
|
||
else:
|
||
css = f"""
|
||
body {{ font-family: Arial, 'Noto Sans CJK TC', sans-serif; background: {bg}; margin: 0; padding: 24px; color: {primary}; }}
|
||
.hero {{ max-width: 1100px; margin: 0 auto 24px; padding: 8px 6px; }}
|
||
.slide {{ background: #fff; border-radius: 18px; padding: 32px; margin: 0 auto 24px; max-width: 1100px; box-shadow: 0 8px 28px rgba(0,0,0,.08); page-break-after: always; border-top: 10px solid {accent}; }}
|
||
h1, h2 {{ margin-top: 0; }}
|
||
h1 {{ font-size: 40px; }}
|
||
ul {{ line-height: 1.7; }}
|
||
.plot-single {{ margin-top: 18px; text-align: center; }}
|
||
img {{ max-width: 100%; border: 1px solid #ddd; border-radius: 12px; background: #fff; }}
|
||
.plot-caption {{ margin-top: 10px; font-size: 14px; color: #6b7280; font-style: italic; }}
|
||
""".strip()
|
||
hero_html = (
|
||
f"<div class='hero'><h1>{html.escape(title)}</h1><p>對象：{html.escape(audience)}</p>"
|
||
f"<p>目的：{html.escape(purpose)}</p><p>等級：{html.escape(level)} — {html.escape(LEVEL_NOTES[level])}</p></div>"
|
||
)
|
||
|
||
return (
|
||
"<!doctype html><html><head><meta charset='utf-8'>"
|
||
f"<title>{html.escape(title)}</title><style>{css}</style></head><body>"
|
||
+ hero_html
|
||
+ ''.join(sections)
|
||
+ "</body></html>"
|
||
)
|
||
|
||
|
||
def main() -> int:
|
||
parser = argparse.ArgumentParser(
|
||
description='Generate paper/slides bundle from analysis outputs',
|
||
epilog=(
|
||
'Levels: '
|
||
'v2=基礎交付版（paper/slides/speaker-notes/deck）； '
|
||
'v3=洞察強化版（v2 + insights + 每張圖逐頁解讀）； '
|
||
'v4=正式交付版（v3 + 更正式 deck 視覺 + PDF-ready 工作流）'
|
||
),
|
||
)
|
||
parser.add_argument('--analysis-dir', required=True)
|
||
parser.add_argument('--output-dir', required=True)
|
||
parser.add_argument('--title', default='研究分析草稿')
|
||
parser.add_argument('--audience', default='決策者')
|
||
parser.add_argument('--purpose', default='研究報告')
|
||
parser.add_argument('--mode', default='business', choices=sorted(MODES))
|
||
parser.add_argument(
|
||
'--level',
|
||
default='v4',
|
||
choices=sorted(LEVELS),
|
||
help='輸出等級：v2=基礎交付版；v3=洞察強化版；v4=正式交付版（預設）',
|
||
)
|
||
args = parser.parse_args()
|
||
|
||
analysis_dir = Path(args.analysis_dir).expanduser().resolve()
|
||
output_dir = Path(args.output_dir).expanduser().resolve()
|
||
output_dir.mkdir(parents=True, exist_ok=True)
|
||
|
||
summary_path = analysis_dir / 'summary.json'
|
||
report_path = analysis_dir / 'report.md'
|
||
if not summary_path.exists():
|
||
raise SystemExit(f'Missing summary.json in {analysis_dir}')
|
||
if not report_path.exists():
|
||
raise SystemExit(f'Missing report.md in {analysis_dir}')
|
||
|
||
summary = read_json(summary_path)
|
||
report_md = read_text(report_path)
|
||
plots = find_plots(analysis_dir)
|
||
insights_md = make_insights_md(args.title, args.mode, summary, plots) if args.level in {'v3', 'v4'} else None
|
||
|
||
paper_md = make_paper(args.title, args.audience, args.purpose, args.mode, args.level, summary, report_md, plots, insights_md)
|
||
slides_md = make_slides(args.title, args.audience, args.purpose, args.mode, summary, plots, args.level)
|
||
speaker_notes = make_speaker_notes(args.title, args.mode, summary, plots, args.level)
|
||
deck_html = make_deck_html(args.title, args.audience, args.purpose, slides_md, plots, args.mode, args.level)
|
||
|
||
for plot in plots:
|
||
dest = output_dir / plot.name
|
||
if dest != plot:
|
||
shutil.copy2(plot, dest)
|
||
|
||
(output_dir / 'paper.md').write_text(paper_md, encoding='utf-8')
|
||
(output_dir / 'slides.md').write_text(slides_md, encoding='utf-8')
|
||
(output_dir / 'speaker-notes.md').write_text(speaker_notes, encoding='utf-8')
|
||
(output_dir / 'deck.html').write_text(deck_html, encoding='utf-8')
|
||
if insights_md:
|
||
(output_dir / 'insights.md').write_text(insights_md, encoding='utf-8')
|
||
|
||
manifest_outputs = {
|
||
'paper': str(output_dir / 'paper.md'),
|
||
'slides': str(output_dir / 'slides.md'),
|
||
'speakerNotes': str(output_dir / 'speaker-notes.md'),
|
||
'deckHtml': str(output_dir / 'deck.html'),
|
||
}
|
||
if insights_md:
|
||
manifest_outputs['insights'] = str(output_dir / 'insights.md')
|
||
|
||
manifest = {
|
||
'title': args.title,
|
||
'audience': args.audience,
|
||
'purpose': args.purpose,
|
||
'mode': args.mode,
|
||
'level': args.level,
|
||
'levelNote': LEVEL_NOTES[args.level],
|
||
'analysisDir': str(analysis_dir),
|
||
'outputs': manifest_outputs,
|
||
'plots': [str(p) for p in plots],
|
||
}
|
||
(output_dir / 'bundle.json').write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding='utf-8')
|
||
print(json.dumps(manifest, ensure_ascii=False, indent=2))
|
||
return 0
|
||
|
||
|
||
if __name__ == '__main__':
|
||
raise SystemExit(main())
|