cb9b16e5a8
包含： - 核心配置文件（AGENTS.md, SOUL.md, USER.md等） - 记忆系统（memory/文件夹） - 技能库（skills/文件夹） - 小说内容（novel/文件夹） - .gitignore配置
131 lines
4.0 KiB
Python
131 lines
4.0 KiB
Python
"""
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Tomato Novel (番茄小说) Genre Fetcher
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Fetches trending genres/data from 番茄小说
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【说明】
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- 此脚本为可选功能，用于主动爬取番茄热门题材做推荐
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- 主要流程：用户直接指定题材，无需爬取
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- 如需使用：python tomato_fetch.py <output_dir>
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- 如果网站屏蔽爬取，使用示例数据或用户手动提供题材
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【推荐用法】
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用户直接说："我想写一本都市异能的小说"
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→ 跳过此脚本，直接进入大纲生成
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"""
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import urllib.request
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import json
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import re
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from pathlib import Path
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def fetch_tomato_rankings():
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"""
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Fetch popular genres/themes from 番茄小说
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Returns:
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dict: genre data for analysis
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"""
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# 番茄小说热门分类页面
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# Note: 实际爬取可能需要处理反爬机制
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urls = [
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"https://fanqienovel.com/library/",
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"https://fanqienovel.com/rank/",
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]
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genres_data = {
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"source": "番茄小说",
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"fetch_time": None,
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"genres": []
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}
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# Placeholder implementation
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# 实际使用时需要根据番茄网站的HTML结构调整解析逻辑
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# 热门题材示例数据（实际应从网站抓取）
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popular_genres = [
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{
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"name": "都市异能",
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"trend_score": 95,
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"description": "现代都市背景下的超能力/系统故事",
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"avg_words": 800000,
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"hot_books": ["书名A", "书名B"]
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},
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{
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"name": "玄幻修仙",
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"trend_score": 90,
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"description": "传统修仙、升级打怪",
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"avg_words": 1200000,
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"hot_books": ["书名C", "书名D"]
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},
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{
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"name": "历史架空",
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"trend_score": 85,
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"description": "穿越历史、权谋争霸",
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"avg_words": 1000000,
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"hot_books": ["书名E"]
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},
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{
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"name": "游戏竞技",
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"trend_score": 80,
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"description": "电竞、游戏世界",
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"avg_words": 600000,
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"hot_books": ["书名F"]
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},
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{
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"name": "科幻末世",
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"trend_score": 75,
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"description": "末日生存、星际文明",
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"avg_words": 900000,
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"hot_books": ["书名G"]
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}
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]
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genres_data["genres"] = popular_genres
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genres_data["fetch_time"] = "manual_sample" # 实际应为时间戳
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return genres_data
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def save_genre_data(data, book_dir):
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"""Save fetched genre data"""
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output_path = Path(book_dir) / "genre_data.json"
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with open(output_path, 'w', encoding='utf-8') as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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print(f"Genre data saved to: {output_path}")
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def format_genre_for_prompt(genres_data):
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"""Format genre data for the analysis prompt"""
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lines = ["=== 番茄小说热门题材数据 ===", ""]
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for g in genres_data.get("genres", []):
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lines.append(f"题材: {g['name']}")
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lines.append(f"热度: {g['trend_score']}/100")
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lines.append(f"描述: {g['description']}")
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lines.append(f"常见字数: {g['avg_words']:,} 字")
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lines.append(f"代表作: {', '.join(g['hot_books'])}")
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lines.append("")
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return "\n".join(lines)
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if __name__ == "__main__":
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import sys
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if len(sys.argv) < 2:
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print("Usage: tomato_fetch.py <output_dir>")
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print("Fetches genre data from 番茄小说 for novel planning")
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sys.exit(1)
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output_dir = sys.argv[1]
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Path(output_dir).mkdir(parents=True, exist_ok=True)
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print("Fetching tomato novel genre data...")
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# In full implementation, this would actually scrape the website
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data = fetch_tomato_rankings()
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save_genre_data(data, output_dir)
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# Also save formatted version for prompts
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formatted = format_genre_for_prompt(data)
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formatted_path = Path(output_dir) / "genre_data_formatted.txt"
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with open(formatted_path, 'w', encoding='utf-8') as f:
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f.write(formatted)
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print(f"Formatted data saved to: {formatted_path}")
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