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-# -*- coding: utf-8 -*-
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-"""
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-黄金三章检查工具 v2.0 (LLM-Driven)
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-
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-功能：检测小说前三章是否符合"黄金三章"标准
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-
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-v2.0 重大升级：
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-- 保留关键词预检作为快速模式
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-- 新增 LLM 深度评估模式（AI Native）
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-- 生成结构化评估 Prompt，解析 XML 评估结果
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-
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-核心检查点：
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-- 第 1 章：300 字内主角出场 + 金手指线索 + 强冲突开局
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-- 第 2 章：金手指展示 + 初次小胜 + 即时爽点
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-- 第 3 章：悬念钩子 + 下一阶段预告 + 爽点密度 >= 1
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-
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-使用方法：
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-python golden_three_checker.py --auto # 快速关键词模式
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-python golden_three_checker.py --auto --mode llm # LLM 深度评估（推荐）
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-python golden_three_checker.py --auto --generate-prompt # 仅生成评估 Prompt
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-"""
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-
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-import sys
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-import os
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-import re
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-import json
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-import argparse
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-from pathlib import Path
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-
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-from runtime_compat import enable_windows_utf8_stdio
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-from typing import Dict, List, Optional, Any
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-
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-# 导入项目定位和章节路径模块
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-from project_locator import resolve_project_root
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-from chapter_paths import find_chapter_file
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-
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-# Windows UTF-8 输出修复
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-if sys.platform == "win32":
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- enable_windows_utf8_stdio()
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-
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-
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-# ============================================================================
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-# LLM 评估 Prompt 模板
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-# ============================================================================
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-
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-LLM_EVALUATION_PROMPT = """你是一位网文编辑，专门负责评估小说开篇的"黄金三章"质量。
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-
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-请根据以下标准，对这三章内容进行专业评估：
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-
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-## 黄金三章标准
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-
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-### 第 1 章核心检查点：
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-1. **主角 300 字内出场**：主角是否在前 300 字内登场？身份是否清晰？
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-2. **金手指线索**：是否有金手指/外挂的暗示或线索？
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-3. **强冲突开局**：开篇是否有足够强的冲突/危机/矛盾？
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-
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-### 第 2 章核心检查点：
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-1. **金手指展示**：金手指是否有明确展示？读者能否理解其能力？
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-2. **初次小胜**：主角是否获得了第一次小规模胜利/成功？
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-3. **即时爽点**：是否有让读者感到爽快/满足的场景？
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-
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-### 第 3 章核心检查点：
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-1. **悬念钩子**：章节结尾是否有悬念？能否驱动读者继续阅读？
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-2. **下一阶段预告**：是否暗示了接下来的剧情走向/新挑战？
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-3. **爽点密度**：本章是否至少有 1 个明显的爽点场景？
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-
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----
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-
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-## 待评估内容
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-
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-### 第 1 章
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-```
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-{chapter1_content}
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-```
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-
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-### 第 2 章
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-```
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-{chapter2_content}
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-```
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-
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-### 第 3 章
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-```
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-{chapter3_content}
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-```
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-
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----
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-
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-## 输出要求
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-
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-请以如下 XML 格式输出你的评估结果（务必严格遵循格式）：
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-
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-```xml
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-<golden_three_assessment>
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- <chapter num="1">
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- <check name="主角300字内出场" passed="true|false" score="0-100">
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- <evidence>具体证据/引用原文</evidence>
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- <suggestion>如未通过，给出改进建议</suggestion>
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- </check>
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- <check name="金手指线索" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- <check name="强冲突开局" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- </chapter>
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-
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- <chapter num="2">
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- <check name="金手指展示" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- <check name="初次小胜" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- <check name="即时爽点" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- </chapter>
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-
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- <chapter num="3">
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- <check name="悬念钩子" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- <check name="下一阶段预告" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- <check name="爽点密度>=1" passed="true|false" score="0-100">
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- <evidence>具体证据</evidence>
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- <suggestion>改进建议</suggestion>
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- </check>
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- </chapter>
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-
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- <overall_score>0-100</overall_score>
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- <verdict>优秀|良好|需改进|严重不足</verdict>
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- <top_issues>
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- <issue priority="1">最需要改进的问题</issue>
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- <issue priority="2">次要问题</issue>
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- </top_issues>
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-</golden_three_assessment>
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-```
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-
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-现在开始评估：
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-"""
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-
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-
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-class GoldenThreeChecker:
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- """黄金三章检查器 v2.0"""
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-
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- def __init__(self, chapter_files: List[str], mode: str = "keyword"):
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- """
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- 初始化检查器
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-
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- Args:
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- chapter_files: 章节文件路径列表（必须是前3章）
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- mode: 检查模式 ("keyword" 快速模式, "llm" LLM评估模式)
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- """
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- if len(chapter_files) != 3:
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- raise ValueError("必须提供前 3 章的文件路径")
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-
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- self.chapter_files = chapter_files
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- self.mode = mode
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- self.chapters: List[Dict[str, Any]] = []
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- self.results: Dict[str, Any] = {
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- "mode": mode,
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- "ch1": {"主角300字内出场": False, "金手指线索": False, "强冲突开局": False, "详细": {}},
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- "ch2": {"金手指展示": False, "初次小胜": False, "即时爽点": False, "详细": {}},
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- "ch3": {"悬念钩子": False, "下一阶段预告": False, "爽点密度>=1": False, "详细": {}},
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- }
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-
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- def load_chapters(self) -> None:
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- """加载章节内容"""
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- for i, file_path in enumerate(self.chapter_files):
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- if not os.path.exists(file_path):
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- raise FileNotFoundError(f"文件不存在: {file_path}")
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-
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- with open(file_path, 'r', encoding='utf-8') as f:
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- content = f.read()
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- self.chapters.append({
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- "number": i + 1,
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- "path": file_path,
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- "content": content,
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- "word_count": len(re.sub(r'\s+', '', content))
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- })
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-
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- # ============================================================================
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- # 快速关键词模式（保留原有逻辑）
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- # ============================================================================
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-
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- def check_chapter1_keywords(self) -> None:
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- """检查第1章（关键词模式）"""
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- content = self.chapters[0]["content"]
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- first_300_chars = content[:300]
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-
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- # 检查1: 主角 300 字内出场
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- protagonist_keywords = ["林天", "我", "主角", "少年", "他", "叶凡", "萧炎", "楚枫"]
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- for keyword in protagonist_keywords:
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- if keyword in first_300_chars:
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- self.results["ch1"]["主角300字内出场"] = True
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- self.results["ch1"]["详细"]["主角出场关键词"] = keyword
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- break
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-
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- # 检查2: 金手指线索
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- golden_finger_keywords = [
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- "系统", "空间", "重生", "穿越", "戒指", "老爷爷",
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- "器灵", "传承", "血脉", "觉醒", "签到", "任务", "面板", "属性"
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- ]
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- found = [kw for kw in golden_finger_keywords if kw in content]
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- self.results["ch1"]["金手指线索"] = len(found) > 0
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- self.results["ch1"]["详细"]["金手指关键词"] = found
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-
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- # 检查3: 强冲突开局
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- conflict_keywords = [
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- "退婚", "羞辱", "嘲讽", "废物", "落魄", "危机",
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- "追杀", "绝境", "被困", "重伤", "濒死", "灭族"
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- ]
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- found = [kw for kw in conflict_keywords if kw in content]
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- self.results["ch1"]["强冲突开局"] = len(found) > 0
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- self.results["ch1"]["详细"]["冲突关键词"] = found
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-
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- def check_chapter2_keywords(self) -> None:
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- """检查第2章（关键词模式）"""
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- content = self.chapters[1]["content"]
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-
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- system_display_keywords = ["【", "╔", "姓名", "境界", "力量", "属性", "获得", "奖励", "升级"]
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- found = [kw for kw in system_display_keywords if kw in content]
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- self.results["ch2"]["金手指展示"] = len(found) >= 2
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- self.results["ch2"]["详细"]["展示关键词"] = found
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-
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- victory_keywords = ["击败", "胜利", "获胜", "成功", "通过", "突破", "秒杀", "碾压"]
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- found = [kw for kw in victory_keywords if kw in content]
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- self.results["ch2"]["初次小胜"] = len(found) > 0
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- self.results["ch2"]["详细"]["胜利关键词"] = found
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-
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- cool_keywords = ["震惊", "不可能", "怎么会", "全场哗然", "目瞪口呆", "难以置信"]
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- found = [kw for kw in cool_keywords if kw in content]
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- self.results["ch2"]["即时爽点"] = len(found) >= 2
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- self.results["ch2"]["详细"]["爽点关键词"] = found
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-
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- def check_chapter3_keywords(self) -> None:
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- """检查第3章（关键词模式）"""
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- content = self.chapters[2]["content"]
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- last_300_chars = content[-300:]
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-
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- suspense_keywords = ["？", "！", "危机", "即将", "突然", "就在这时", "阴影", "杀机"]
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- found = [kw for kw in suspense_keywords if kw in last_300_chars]
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- self.results["ch3"]["悬念钩子"] = len(found) >= 2
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- self.results["ch3"]["详细"]["悬念关键词"] = found
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-
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- preview_keywords = ["秘境", "大比", "选拔", "试炼", "任务", "挑战", "前往", "即将"]
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- found = [kw for kw in preview_keywords if kw in content]
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- self.results["ch3"]["下一阶段预告"] = len(found) > 0
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- self.results["ch3"]["详细"]["预告关键词"] = found
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-
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- cool_count = sum(content.count(kw) for kw in ["震惊", "不可能", "全场哗然", "天才", "击败", "获得"])
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- self.results["ch3"]["爽点密度>=1"] = cool_count >= 1
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- self.results["ch3"]["详细"]["爽点统计"] = cool_count
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-
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- # ============================================================================
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- # LLM 评估模式
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- # ============================================================================
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-
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- def generate_llm_prompt(self) -> str:
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- """生成 LLM 评估 Prompt"""
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- # 截取每章内容（避免过长）
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- max_chars_per_chapter = 6000
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-
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- ch1 = self.chapters[0]["content"][:max_chars_per_chapter]
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- ch2 = self.chapters[1]["content"][:max_chars_per_chapter]
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- ch3 = self.chapters[2]["content"][:max_chars_per_chapter]
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-
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- prompt = LLM_EVALUATION_PROMPT.format(
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- chapter1_content=ch1,
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- chapter2_content=ch2,
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- chapter3_content=ch3
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- )
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- return prompt
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-
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- def parse_llm_response(self, xml_response: str) -> Dict[str, Any]:
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- """解析 LLM 返回的 XML 评估结果"""
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- results: Dict[str, Any] = {
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- "mode": "llm",
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- "ch1": {"详细": {}},
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- "ch2": {"详细": {}},
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- "ch3": {"详细": {}},
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- "overall_score": 0,
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- "verdict": "",
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- "top_issues": []
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- }
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-
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- # 提取 overall_score
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- score_match = re.search(r'<overall_score>(\d+)</overall_score>', xml_response)
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- if score_match:
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- results["overall_score"] = int(score_match.group(1))
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-
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- # 提取 verdict
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- verdict_match = re.search(r'<verdict>([^<]+)</verdict>', xml_response)
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- if verdict_match:
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- results["verdict"] = verdict_match.group(1).strip()
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-
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- # 提取每章的检查点
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- chapter_pattern = re.compile(
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- r'<chapter num="(\d)">(.*?)</chapter>',
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- re.DOTALL
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- )
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- check_pattern = re.compile(
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- r'<check name="([^"]+)" passed="(true|false)" score="(\d+)">\s*'
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- r'<evidence>([^<]*)</evidence>\s*'
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- r'<suggestion>([^<]*)</suggestion>\s*'
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- r'</check>',
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- re.DOTALL
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- )
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-
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- for chapter_match in chapter_pattern.finditer(xml_response):
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- chapter_num = chapter_match.group(1)
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- chapter_content = chapter_match.group(2)
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- chapter_key = f"ch{chapter_num}"
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-
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- for check_match in check_pattern.finditer(chapter_content):
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- check_name = check_match.group(1)
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- passed = check_match.group(2) == "true"
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- score = int(check_match.group(3))
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- evidence = check_match.group(4).strip()
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- suggestion = check_match.group(5).strip()
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-
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- results[chapter_key][check_name] = passed
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- results[chapter_key]["详细"][check_name] = {
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- "score": score,
|
|
|
- "evidence": evidence,
|
|
|
- "suggestion": suggestion
|
|
|
- }
|
|
|
-
|
|
|
- # 提取 top_issues
|
|
|
- issue_pattern = re.compile(r'<issue priority="(\d)">([^<]+)</issue>')
|
|
|
- for issue_match in issue_pattern.finditer(xml_response):
|
|
|
- priority = int(issue_match.group(1))
|
|
|
- issue_text = issue_match.group(2).strip()
|
|
|
- results["top_issues"].append({"priority": priority, "issue": issue_text})
|
|
|
-
|
|
|
- return results
|
|
|
-
|
|
|
- # ============================================================================
|
|
|
- # 报告生成
|
|
|
- # ============================================================================
|
|
|
-
|
|
|
- def calculate_score(self) -> tuple:
|
|
|
- """计算总体得分"""
|
|
|
- total_checks = 0
|
|
|
- passed_checks = 0
|
|
|
-
|
|
|
- for chapter_key in ["ch1", "ch2", "ch3"]:
|
|
|
- for check_key, check_value in self.results[chapter_key].items():
|
|
|
- if check_key != "详细" and isinstance(check_value, bool):
|
|
|
- total_checks += 1
|
|
|
- if check_value:
|
|
|
- passed_checks += 1
|
|
|
-
|
|
|
- score = (passed_checks / total_checks) * 100 if total_checks > 0 else 0
|
|
|
- return score, passed_checks, total_checks
|
|
|
-
|
|
|
- def generate_report(self) -> str:
|
|
|
- """生成检查报告"""
|
|
|
- score, passed, total = self.calculate_score()
|
|
|
-
|
|
|
- report = []
|
|
|
- report.append("=" * 60)
|
|
|
- report.append(f"黄金三章诊断报告 (模式: {self.mode})")
|
|
|
- report.append("=" * 60)
|
|
|
- report.append(f"\n总体得分: {score:.1f}% ({passed}/{total} 项通过)\n")
|
|
|
-
|
|
|
- # 第 1 章
|
|
|
- report.append("-" * 60)
|
|
|
- report.append("【第 1 章】检查结果")
|
|
|
- report.append("-" * 60)
|
|
|
- for check_name in ["主角300字内出场", "金手指线索", "强冲突开局"]:
|
|
|
- passed = self.results["ch1"].get(check_name, False)
|
|
|
- icon = "✅" if passed else "❌"
|
|
|
- report.append(f"{icon} {check_name}: {'通过' if passed else '未通过'}")
|
|
|
-
|
|
|
- # 显示详细信息
|
|
|
- detail = self.results["ch1"]["详细"].get(check_name)
|
|
|
- if isinstance(detail, dict):
|
|
|
- if detail.get("evidence"):
|
|
|
- report.append(f" └─ 证据: {detail['evidence'][:100]}...")
|
|
|
- if not passed and detail.get("suggestion"):
|
|
|
- report.append(f" └─ 建议: {detail['suggestion']}")
|
|
|
- elif isinstance(detail, list) and detail:
|
|
|
- report.append(f" └─ 关键词: {', '.join(detail[:5])}")
|
|
|
-
|
|
|
- # 第 2 章
|
|
|
- report.append("\n" + "-" * 60)
|
|
|
- report.append("【第 2 章】检查结果")
|
|
|
- report.append("-" * 60)
|
|
|
- for check_name in ["金手指展示", "初次小胜", "即时爽点"]:
|
|
|
- passed = self.results["ch2"].get(check_name, False)
|
|
|
- icon = "✅" if passed else "❌"
|
|
|
- report.append(f"{icon} {check_name}: {'通过' if passed else '未通过'}")
|
|
|
- detail = self.results["ch2"]["详细"].get(check_name)
|
|
|
- if isinstance(detail, dict) and detail.get("evidence"):
|
|
|
- report.append(f" └─ 证据: {detail['evidence'][:100]}...")
|
|
|
- elif isinstance(detail, list) and detail:
|
|
|
- report.append(f" └─ 关键词: {', '.join(detail[:5])}")
|
|
|
-
|
|
|
- # 第 3 章
|
|
|
- report.append("\n" + "-" * 60)
|
|
|
- report.append("【第 3 章】检查结果")
|
|
|
- report.append("-" * 60)
|
|
|
- for check_name in ["悬念钩子", "下一阶段预告", "爽点密度>=1"]:
|
|
|
- passed = self.results["ch3"].get(check_name, False)
|
|
|
- icon = "✅" if passed else "❌"
|
|
|
- report.append(f"{icon} {check_name}: {'通过' if passed else '未通过'}")
|
|
|
- detail = self.results["ch3"]["详细"].get(check_name)
|
|
|
- if isinstance(detail, dict) and detail.get("evidence"):
|
|
|
- report.append(f" └─ 证据: {detail['evidence'][:100]}...")
|
|
|
-
|
|
|
- # 改进建议
|
|
|
- report.append("\n" + "=" * 60)
|
|
|
- report.append("【改进建议】")
|
|
|
- report.append("=" * 60)
|
|
|
-
|
|
|
- if score < 60:
|
|
|
- report.append("\n🔴 警告: 开篇吸引力不足，严重影响读者留存率！")
|
|
|
- elif score < 80:
|
|
|
- report.append("\n🟡 注意: 开篇有改进空间")
|
|
|
- else:
|
|
|
- report.append("\n✅ 很好！开篇符合黄金三章标准")
|
|
|
-
|
|
|
- # LLM 模式的额外信息
|
|
|
- if self.mode == "llm" and self.results.get("top_issues"):
|
|
|
- report.append("\n优先修复：")
|
|
|
- for issue in self.results["top_issues"]:
|
|
|
- report.append(f" {issue['priority']}. {issue['issue']}")
|
|
|
-
|
|
|
- report.append("\n" + "=" * 60)
|
|
|
- return "\n".join(report)
|
|
|
-
|
|
|
- def run(self) -> None:
|
|
|
- """执行检查"""
|
|
|
- print("正在加载章节...")
|
|
|
- self.load_chapters()
|
|
|
-
|
|
|
- print(f"✅ 已加载 {len(self.chapters)} 章")
|
|
|
- for ch in self.chapters:
|
|
|
- print(f" - 第 {ch['number']} 章: {ch['word_count']} 字")
|
|
|
- print(f"\n正在执行检查 (模式: {self.mode})...\n")
|
|
|
-
|
|
|
- if self.mode == "keyword":
|
|
|
- self.check_chapter1_keywords()
|
|
|
- self.check_chapter2_keywords()
|
|
|
- self.check_chapter3_keywords()
|
|
|
- report = self.generate_report()
|
|
|
- print(report)
|
|
|
-
|
|
|
- elif self.mode == "llm":
|
|
|
- prompt = self.generate_llm_prompt()
|
|
|
- print("=" * 60)
|
|
|
- print("LLM 评估模式：请将以下 Prompt 发送给 Claude/GPT")
|
|
|
- print("=" * 60)
|
|
|
- print("\n--- PROMPT START ---\n")
|
|
|
- print(prompt[:2000] + "\n...[内容已截断，完整版见输出文件]...")
|
|
|
- print("\n--- PROMPT END ---\n")
|
|
|
-
|
|
|
- # 保存完整 prompt
|
|
|
- output_dir = Path(".webnovel")
|
|
|
- output_dir.mkdir(exist_ok=True)
|
|
|
- prompt_file = output_dir / "golden_three_prompt.md"
|
|
|
- with open(prompt_file, 'w', encoding='utf-8') as f:
|
|
|
- f.write(prompt)
|
|
|
- print(f"📄 完整 Prompt 已保存至: {prompt_file}")
|
|
|
- print("\n💡 使用方法：")
|
|
|
- print(" 1. 将 Prompt 发送给 Claude/GPT")
|
|
|
- print(" 2. 获取 XML 格式的评估结果")
|
|
|
- print(" 3. 运行: python golden_three_checker.py --parse-response <response.xml>")
|
|
|
-
|
|
|
- # 保存结果
|
|
|
- output_dir = Path(".webnovel")
|
|
|
- output_dir.mkdir(exist_ok=True)
|
|
|
- output_file = output_dir / "golden_three_report.json"
|
|
|
- with open(output_file, 'w', encoding='utf-8') as f:
|
|
|
- json.dump(self.results, f, ensure_ascii=False, indent=2)
|
|
|
- print(f"\n📄 详细结果已保存至: {output_file}")
|
|
|
-
|
|
|
-
|
|
|
-def main():
|
|
|
- parser = argparse.ArgumentParser(
|
|
|
- description="黄金三章检查工具 v2.0 (LLM-Driven)",
|
|
|
- formatter_class=argparse.RawDescriptionHelpFormatter,
|
|
|
- epilog="""
|
|
|
-示例：
|
|
|
- # 快速关键词模式（默认）
|
|
|
- python golden_three_checker.py --auto
|
|
|
-
|
|
|
- # LLM 深度评估模式（推荐）
|
|
|
- python golden_three_checker.py --auto --mode llm
|
|
|
-
|
|
|
- # 解析 LLM 返回的评估结果
|
|
|
- python golden_three_checker.py --parse-response response.xml
|
|
|
-""".strip(),
|
|
|
- )
|
|
|
-
|
|
|
- parser.add_argument("chapter_files", nargs="*", help="前三章文件路径")
|
|
|
- parser.add_argument("--auto", action="store_true", help="自动定位前三章文件")
|
|
|
- parser.add_argument("--mode", choices=["keyword", "llm"], default="keyword",
|
|
|
- help="检查模式: keyword(快速) / llm(深度)")
|
|
|
- parser.add_argument("--project-root", default=None, help="项目根目录")
|
|
|
- parser.add_argument("--parse-response", metavar="FILE", help="解析 LLM 返回的 XML 文件")
|
|
|
-
|
|
|
- args = parser.parse_args()
|
|
|
-
|
|
|
- # 解析 LLM 响应模式
|
|
|
- if args.parse_response:
|
|
|
- if not os.path.exists(args.parse_response):
|
|
|
- print(f"❌ 文件不存在: {args.parse_response}")
|
|
|
- sys.exit(1)
|
|
|
-
|
|
|
- with open(args.parse_response, 'r', encoding='utf-8') as f:
|
|
|
- xml_content = f.read()
|
|
|
-
|
|
|
- checker = GoldenThreeChecker(["dummy"] * 3, mode="llm")
|
|
|
- checker.results = checker.parse_llm_response(xml_content)
|
|
|
-
|
|
|
- print("=" * 60)
|
|
|
- print("LLM 评估结果解析")
|
|
|
- print("=" * 60)
|
|
|
- print(json.dumps(checker.results, ensure_ascii=False, indent=2))
|
|
|
- sys.exit(0)
|
|
|
-
|
|
|
- # 正常检查模式
|
|
|
- chapter_files = []
|
|
|
-
|
|
|
- if args.auto or not args.chapter_files:
|
|
|
- try:
|
|
|
- project_root = resolve_project_root(args.project_root)
|
|
|
- except FileNotFoundError as e:
|
|
|
- print(f"❌ {e}")
|
|
|
- sys.exit(1)
|
|
|
-
|
|
|
- for i in range(1, 4):
|
|
|
- chapter_path = find_chapter_file(project_root, i)
|
|
|
- if chapter_path:
|
|
|
- chapter_files.append(str(chapter_path))
|
|
|
- else:
|
|
|
- print(f"❌ 找不到第 {i} 章文件")
|
|
|
- sys.exit(1)
|
|
|
-
|
|
|
- print(f"📂 项目根目录: {project_root}")
|
|
|
- print(f"📄 检测到前三章: {', '.join(Path(f).name for f in chapter_files)}\n")
|
|
|
- else:
|
|
|
- if len(args.chapter_files) < 3:
|
|
|
- print("用法: python golden_three_checker.py <第1章路径> <第2章路径> <第3章路径>")
|
|
|
- sys.exit(1)
|
|
|
- chapter_files = args.chapter_files[:3]
|
|
|
-
|
|
|
- try:
|
|
|
- checker = GoldenThreeChecker(chapter_files, mode=args.mode)
|
|
|
- checker.run()
|
|
|
- except Exception as e:
|
|
|
- print(f"❌ 错误: {e}")
|
|
|
- import traceback
|
|
|
- traceback.print_exc()
|
|
|
- sys.exit(1)
|
|
|
-
|
|
|
-
|
|
|
-if __name__ == "__main__":
|
|
|
- main()
|
lingfengQAQ