208 lines
6.1 KiB
Python
208 lines
6.1 KiB
Python
"""
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Reader-Pull Checker (追读力检查器)
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检查钩子强度、期待管理、追读力：
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- 章节开头的钩子
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- 章节结尾的悬念
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- 追读力债务
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"""
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from dataclasses import dataclass, field
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from typing import List, Dict, Any, Optional
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@dataclass
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class ReaderPullIssue:
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"""追读力问题"""
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chapter: int
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issue_type: str # weak_hook / no_ending_hook / debt_high
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description: str
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severity: str
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@dataclass
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class ReaderPullReport:
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"""追读力检查报告"""
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chapter: int
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hook_strength: float # 0-1
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ending_hook: bool
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debt_level: float
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issues: List[ReaderPullIssue] = field(default_factory=list)
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passed: bool = True
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summary: str = ""
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class ReaderPullChecker:
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"""
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追读力检查器
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检查：
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1. 章节开头的钩子强度
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2. 章节结尾的悬念
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3. 追读力债务水平
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"""
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# 强钩子关键词
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STRONG_HOOK_KEYWORDS = [
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"危机", "危险", "困境", "生死", "抉择", "真相",
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"震惊", "意外", "转折", "揭秘", "冲突", "大战"
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]
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# 结尾悬念关键词
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ENDING_HOOK_KEYWORDS = [
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"然而", "但是", "就在这时", "突然", "意外",
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"未完待续", "敬请期待", "欲知后事", "悬念",
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"却不知道", "更大的"
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]
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# 悬念关键词
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SUSPENSE_KEYWORDS = [
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"悬念", "伏笔", "暗示", "预示", "危机", "威胁"
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]
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def __init__(self):
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self.chapter_debts: List[float] = []
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def check_chapter(
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self,
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chapter_num: int,
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chapter_text: str,
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previous_debt: float = 0.0
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) -> ReaderPullReport:
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"""检查单章追读力"""
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# 分析开头钩子
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opening = chapter_text[:500] if len(chapter_text) > 500 else chapter_text
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hook_strength = self._analyze_hook_strength(opening)
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# 分析结尾悬念
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ending = chapter_text[-500:] if len(chapter_text) > 500 else chapter_text
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ending_hook = self._has_ending_hook(ending)
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# 计算本章追读力债务
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debt_level = self._calculate_debt_level(chapter_text, hook_strength, ending_hook)
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report = ReaderPullReport(
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chapter=chapter_num,
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hook_strength=hook_strength,
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ending_hook=ending_hook,
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debt_level=debt_level
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)
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# 检测问题
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if hook_strength < 0.3:
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report.issues.append(ReaderPullIssue(
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chapter=chapter_num,
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issue_type="weak_hook",
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description="章节开头钩子较弱，可能无法吸引读者",
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severity="medium"
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))
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if not ending_hook:
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report.issues.append(ReaderPullIssue(
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chapter=chapter_num,
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issue_type="no_ending_hook",
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description="章节结尾缺少悬念，读者缺乏继续阅读的动力",
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severity="high"
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))
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# 检查追读力债务
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total_debt = previous_debt + debt_level
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if total_debt > 80:
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report.issues.append(ReaderPullIssue(
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chapter=chapter_num,
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issue_type="debt_high",
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description=f"追读力债务过高（{total_debt:.0f}），建议释放",
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severity="critical"
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))
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self.chapter_debts.append(debt_level)
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report.passed = len([i for i in report.issues if i.severity == "critical"]) == 0
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if report.passed:
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report.summary = f"钩子强度 {hook_strength:.0%}，追读力债务 {total_debt:.0f}"
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else:
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report.summary = f"发现问题: {', '.join(i.issue_type for i in report.issues)}"
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return report
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def _analyze_hook_strength(self, opening: str) -> float:
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"""分析钩子强度"""
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if not opening:
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return 0.0
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strength = 0.3 # 基础分
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# 检查强钩子关键词
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strong_count = sum(1 for kw in self.STRONG_HOOK_KEYWORDS if kw in opening)
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strength += min(0.4, strong_count * 0.1)
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# 检查疑问句
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question_count = opening.count('?') + opening.count('？')
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strength += min(0.2, question_count * 0.1)
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# 检查省略号（制造悬念）
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ellipsis_count = opening.count('...')
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strength += min(0.1, ellipsis_count * 0.05)
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return min(1.0, strength)
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def _has_ending_hook(self, ending: str) -> bool:
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"""检查结尾是否有悬念"""
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if not ending:
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return False
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# 检查结尾悬念关键词
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for kw in self.ENDING_HOOK_KEYWORDS:
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if kw in ending:
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return True
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# 检查是否以冲突/悬念结尾
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suspense_ending = ["？", "！", "……"]
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if any(ending.strip().endswith(s) for s in suspense_ending):
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return True
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return False
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def _calculate_debt_level(
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self,
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text: str,
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hook_strength: float,
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ending_hook: bool
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) -> float:
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"""计算追读力债务"""
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debt = 0.0
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# 无开头钩子
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if hook_strength < 0.3:
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debt += 20
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# 无结尾悬念
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if not ending_hook:
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debt += 30
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# 积累的悬念/伏笔
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unresolved_count = 0
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for kw in self.SUSPENSE_KEYWORDS:
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unresolved_count += text.count(kw)
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debt += min(30, unresolved_count * 5)
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# 钩子强度可以抵消部分债务
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debt -= hook_strength * 20
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return max(0, min(100, debt))
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def get_arc_reader_pull(self, start_chapter: int, end_chapter: int) -> Dict[str, Any]:
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"""分析情节弧的追读力"""
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if not self.chapter_debts:
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return {"status": "no_data"}
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relevant = self.chapter_debts[start_chapter - 1:end_chapter]
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return {
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"chapters": f"{start_chapter}-{end_chapter}",
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"avg_hook_strength": sum(h.hook_strength for h in self.chapter_debts[start_chapter-1:end_chapter]) / len(relevant) if relevant else 0,
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"avg_debt": sum(relevant) / len(relevant) if relevant else 0,
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"debt_trend": relevant[-1] - relevant[0] if len(relevant) > 1 else 0
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}
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