Heptabase可视化笔记工具指南

#!/usr/bin/env python3"""Visual Note Card Manager - 视觉笔记卡片管理器. 模拟Heptabase核心功能：白板卡片管理、双向链接、PDF标注转卡片、大纲导出.""" from dataclasses import dataclass, fieldfrom typing import List, Optional, Dictfrom enum import Enum  class CardType(Enum):    """卡片类型枚举."""    CONCEPT = "concept"    METHOD = "method"    EVIDENCE = "evidence"    QUESTION = "question"    INSIGHT = "insight"  @dataclassclass Card:    """笔记卡片."""    card_id: str    title: str    content: str = ""    card_type: CardType = CardType.CONCEPT    tags: List[str] = field(default_factory=list)    links: List[str] = field(default_factory=list)    source_pdf: Optional[str] = None    source_page: Optional[int] = None    position: tuple = (0, 0)     def add_link(self, other_id: str):        if other_id not in self.links:            self.links.append(other_id)     def add_tag(self, tag: str):        if tag not in self.tags:            self.tags.append(tag)  @dataclassclass Whiteboard:    """白板画布."""    name: str    cards: Dict[str, Card] = field(default_factory=dict)    sections: List[dict] = field(default_factory=list)     def add_card(self, card: Card):        self.cards[card.card_id] = card     def link_cards(self, card_a_id: str, card_b_id: str):        if card_a_id in self.cards and card_b_id in self.cards:            self.cards[card_a_id].add_link(card_b_id)            self.cards[card_b_id].add_link(card_a_id)     def get_backlinks(self, card_id: str) -> List[str]:        backlinks = []        for cid, card in self.cards.items():            if card_id in card.links and cid != card_id:                backlinks.append(cid)        return backlinks     def find_by_tag(self, tag: str) -> List[Card]:        return [c for c in self.cards.values() if tag in c.tags]     def get_card_network(self) -> dict:        hub_cards = sorted(            self.cards.values(),            key=lambda c: len(c.links),            reverse=True        )[:5]        isolated = [c for c in self.cards.values() if len(c.links) == 0]        return {            "total_cards": len(self.cards),            "total_links": sum(len(c.links) for c in self.cards.values()) // 2,            "hub_cards": [{"id": c.card_id, "title": c.title, "links": len(c.links)} for c in hub_cards],            "isolated_cards": len(isolated)        }  class PDFAnnotationImporter:    """PDF标注导入器."""     def __init__(self, whiteboard: Whiteboard):        self.wb = whiteboard     def import_highlight(self, pdf_name, page, text, color, card_type):        color_map = {            "yellow": ("key_argument", "关键论点"),            "blue": ("method_detail", "方法细节"),            "green": ("experiment_result", "实验结果"),            "pink": ("to_verify", "待验证")        }        tag, type_label = color_map.get(color, ("general", "一般"))         card_id = f"card_{pdf_name}_{page}_{len(self.wb.cards)}"        card = Card(            card_id=card_id,            title=f"[{type_label}] {text[:40]}...",            content=text,            card_type=card_type,            tags=[tag, pdf_name.replace(".pdf", "")],            source_pdf=pdf_name,            source_page=page        )        self.wb.add_card(card)        return card  class OutlineExporter:    """大纲导出器."""     @staticmethod    def export_to_markdown(whiteboard, ordered_ids):        lines = ["# Paper Outline\n"]        for i, card_id in enumerate(ordered_ids):            card = whiteboard.cards.get(card_id)            if card:                lines.append(f"## {i+1}. {card.title}\n")                lines.append(f"{card.content}\n")                if card.source_pdf:                    lines.append(f"*Source: {card.source_pdf}, p.{card.source_page}*\n")                backlinks = whiteboard.get_backlinks(card_id)                if backlinks:                    lines.append(f"*Related: {', '.join(backlinks)}*\n")        return "\n".join(lines)  if __name__ == "__main__":    wb = Whiteboard(name="Federated Learning Research")    importer = PDFAnnotationImporter(wb)     c1 = importer.import_highlight("fedavg.pdf", 3, "FedAvg通过平均本地模型参数实现联邦学习", "yellow", CardType.METHOD)    c2 = importer.import_highlight("fedprox.pdf", 5, "FedProx添加近端项解决异构性问题", "yellow", CardType.METHOD)    c3 = importer.import_highlight("fedavg.pdf", 7, "实验显示非IID数据下准确率下降15%", "green", CardType.EVIDENCE)    c4 = importer.import_highlight("dp-fed.pdf", 4, "差分隐私保护联邦学习中的梯度信息", "blue", CardType.CONCEPT)     wb.link_cards(c1.card_id, c2.card_id)    wb.link_cards(c1.card_id, c3.card_id)    wb.link_cards(c1.card_id, c4.card_id)     print("=== Card Network ===")    network = wb.get_card_network()    for k, v in network.items():        if isinstance(v, list):            print(f"  {k}:")            for item in v:                print(f"    - {item}")        else:            print(f"  {k}: {v}")     print("\n=== Tag Search ===")    dp_cards = wb.find_by_tag("dp-fed")    for c in dp_cards:        print(f"  {c.card_id}: {c.title}")     print("\n=== Outline Export ===")    outline = OutlineExporter.export_to_markdown(wb, [c1.card_id, c4.card_id, c2.card_id, c3.card_id])    print(outline)