504 lines
21 KiB
Python
504 lines
21 KiB
Python
#!/usr/bin/env python3
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"""
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平台适配文章撰写
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根据大纲和平台配置(字数/格式/配图要求),为知乎/公众号/小红书各平台生成适配内容
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"""
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import json, datetime, logging, sys, re
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from pathlib import Path
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from typing import Dict, List
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PROJECT_ROOT = Path(__file__).parent.parent
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sys.path.insert(0, str(PROJECT_ROOT))
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sys.path.insert(0, str(PROJECT_ROOT / 'platform' / 'backend'))
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from db_helper import get_topic_by_id, update_topic_status, save_article
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try:
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from app.core.nvidia_client import call_llm
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HAVE_LLM = True
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except ImportError:
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HAVE_LLM = False
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import mistune
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DATA_DIR = PROJECT_ROOT / "automation" / "data"
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OUTLINE_DIR = DATA_DIR / "outlines"
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TEMPLATES_DIR = PROJECT_ROOT / "automation" / "templates"
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LOGS_DIR = PROJECT_ROOT / "automation" / "logs"
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TODAY = datetime.datetime.now().strftime("%Y-%m-%d")
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GEN_TIME = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler(LOGS_DIR / f"writer_{TODAY}.log"),
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logging.StreamHandler()
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]
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)
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logger = logging.getLogger(__name__)
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_md_parser = mistune.create_markdown()
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_FALLBACK_PLATFORM_CONFIG = {
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"zhihu": {"max_chars": 3000, "style": "深度长文分析", "min_chars": 1500},
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"wechat": {"max_chars": 1500, "style": "亲切口语化", "min_chars": 800},
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"xiaohongshu": {"max_chars": 800, "style": "图文笔记,emoji+标签", "min_chars": 300},
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}
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def _load_platform_config() -> dict:
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try:
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from app.database import SessionLocal
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from app.models import PlatformConfig
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db = SessionLocal()
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configs = db.query(PlatformConfig).all()
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db.close()
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result = {}
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for c in configs:
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result[c.platform] = {
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"max_chars": c.max_words or _FALLBACK_PLATFORM_CONFIG.get(c.platform, {}).get("max_chars", 3000),
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"style": c.default_format or _FALLBACK_PLATFORM_CONFIG.get(c.platform, {}).get("style", "深度内容"),
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"min_chars": c.min_words or _FALLBACK_PLATFORM_CONFIG.get(c.platform, {}).get("min_chars", 300),
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}
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return result
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except Exception:
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pass
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return dict(_FALLBACK_PLATFORM_CONFIG)
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PLATFORM_CONFIG = _load_platform_config()
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class Writer:
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def __init__(self, topic_id: str):
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self.topic_id = topic_id
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self.topic = self._load_topic()
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outline_file = OUTLINE_DIR / TODAY / f"{topic_id}_outline.md"
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if not outline_file.exists():
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raise FileNotFoundError(f"Outline not found: {outline_file}")
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self.outline_content = outline_file.read_text(encoding='utf-8')
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research_file = DATA_DIR / "research" / TODAY / f"{topic_id}_research.md"
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self.research_notes = research_file.read_text(encoding='utf-8') if research_file.exists() else ""
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def _load_topic(self) -> Dict:
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topic = get_topic_by_id(self.topic_id)
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if not topic:
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raise ValueError(f"Topic {self.topic_id} not found")
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return topic
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def _clean_title(self, title: str) -> str:
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title = re.sub(r'[((]约\s*\d+字[))]', '', title)
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title = re.sub(r'[((]MVP[))]', '', title)
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title = re.sub(r'[((][^))]*?[))]', '', title)
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return title.strip()
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def _parse_outline_sections(self) -> List[Dict]:
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sections = []
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current = None
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for line in self.outline_content.splitlines():
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if line.startswith("# "):
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if current:
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sections.append(current)
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current = {"level": 1, "title": line[2:].strip(), "content": "", "section_type": "normal"}
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elif line.startswith("## "):
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if current:
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sections.append(current)
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title = line[3:].strip()
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stype = "noise" if title in ("文章大纲", "大纲", "文章结构", "结构") else "normal"
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current = {"level": 2, "title": title, "content": "", "section_type": stype}
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elif line.startswith("### "):
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if current:
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sections.append(current)
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current = {"level": 3, "title": line[4:].strip(), "content": "", "section_type": "normal"}
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else:
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if current and line.strip():
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current['content'] = current.get('content', '') + line + "\n"
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if current:
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sections.append(current)
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return sections
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@staticmethod
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def _clean_markdown(text: str) -> str:
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lines = text.split('\n')
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cleaned = []
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in_code_fence = False
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for line in lines:
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if line.strip().startswith('```'):
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in_code_fence = not in_code_fence
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continue
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if in_code_fence:
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continue
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line = re.sub(r'^#{1,6}\s+', '', line)
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line = re.sub(r'^[\-\*\+]\s+', '', line)
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line = re.sub(r'^\d+[\.\)]\s+', '', line)
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line = re.sub(r'\*{1,3}([^*]+)\*{1,3}', r'\1', line)
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cleaned.append(line)
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return '\n'.join(cleaned).strip()
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@staticmethod
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def _is_outline_noise(line: str) -> bool:
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stripped = line.strip()
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if not stripped:
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return True
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if stripped.startswith('---'):
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return True
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if '大纲生成时间' in stripped:
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return True
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if stripped.startswith('*大纲'):
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return True
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if re.match(r'^\*{0,3}【[^】]*】\*{0,3}\s*$', stripped):
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return True
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return False
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def _is_bullet_only(self, text: str) -> bool:
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"""检查内容是否主要是要点列表(大纲格式),需要 LLM 展开"""
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lines = [l.strip() for l in text.split('\n') if l.strip()]
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if not lines:
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return False
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bullet_count = sum(1 for l in lines if l.startswith(('- ', '* ', '**', '+ ')))
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return bullet_count / len(lines) > 0.4
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def _expand_section(self, section: Dict) -> str:
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content = section.get('content', '').strip()
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# 大纲要点格式(>40% 行以 -/*/** 开头)应始终由 LLM 展开为连贯段落
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if HAVE_LLM and self._is_bullet_only(content):
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logger.info(f"使用 LLM 扩写章节(要点→段落): {section['title']}")
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prompt = f"""你是一个资深作者,正在写一篇关于「{self.topic['title']}」的文章。请写「{section['title']}」这一节。
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今天日期:{datetime.datetime.now().strftime('%Y年%m月%d日')}。
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笔记要点:
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{content}
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【输出要求】
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输出3-6段纯粹、流畅的段落文字,每节内容根据平台需求控制在200-800字之间。
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格式:
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- 禁止任何标题/列表/格式标记(#、-、*、1.、**等)
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- 每段3-5句,段间空行分隔
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- 用「你」或「我们」视角,自然口语化
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内容要求(让文章在各平台能被推荐):
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- 开头直接切入痛点或反常识观点,抓住注意力
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- 每个观点配具体案例或数据(用「据统计」「调研显示」等),不要空泛说理
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- 有独特判断和立场,避免正确废话
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- 回答「所以呢」——读者看完能带走什么
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- 结尾有情绪感召力,让人想点赞/收藏/转发
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直接输出段落正文,不要任何附加说明。"""
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try:
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expanded = call_llm(prompt, temperature=0.6)
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if expanded:
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cleaned = self._clean_markdown(expanded.strip())
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if cleaned:
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return cleaned
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except Exception as e:
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logger.warning(f"LLM 扩写失败: {e}")
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# Fallback: 将 bullet points 展开为段落(过滤噪音行)
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lines = [l.strip() for l in content.split('\n') if not self._is_outline_noise(l)]
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if lines:
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sentences = []
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for line in lines:
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text = line
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for prefix in ['- ', '* ', '1. ', '2. ', '3. ', '4. ', '5. ']:
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if line.startswith(prefix):
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text = line[len(prefix):]
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break
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text = text.strip()
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if text:
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if text[-1] not in '。!?;':
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text += '。'
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sentences.append(text)
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if sentences:
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result = ' '.join(sentences)
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return self._clean_markdown(result)
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return ''
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def generate_full_markdown(self) -> str:
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sections = self._parse_outline_sections()
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parts = []
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for sec in sections:
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if sec['level'] == 1:
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if sec.get('content'):
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expanded = self._expand_section(sec)
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if expanded:
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parts.append(expanded + "\n")
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continue
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# 跳过大纲结构噪音节点
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title_stripped = sec['title'].strip()
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if title_stripped in ('文章大纲', '大纲', '文章结构', '结构'):
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continue
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if sec.get('section_type') == 'noise':
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continue
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heading = f"{'#' * sec['level']} {sec['title']}"
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parts.append(heading)
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if sec.get('content'):
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expanded = self._expand_section(sec)
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parts.append(expanded + "\n")
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full_md = "\n".join(parts).strip()
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return full_md
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def _adapt_for_platform(self, markdown: str, platform: str) -> str:
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cfg = PLATFORM_CONFIG[platform]
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max_c = cfg['max_chars']
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lines = markdown.split('\n')
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if platform == "xiaohongshu":
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result = []
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char_count = 0
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for line in lines:
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if char_count >= max_c:
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break
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if line.startswith('## '):
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line = f"## ✨ {line[3:]}"
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elif line.startswith('### '):
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line = f"### 💡 {line[4:]}"
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result.append(line)
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char_count += len(line)
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adapted = '\n'.join(result)
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if adapted.count('#') == 0:
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adapted = f"# {self.topic['title']}\n\n{adapted}"
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return adapted
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if platform == "wechat":
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result = []
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for line in lines:
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line = line.replace('我', '你')
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if line.startswith('### '):
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result.append(f"\n**{line[4:]}**\n")
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elif line.startswith('## '):
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result.append(f"\n**{line[3:]}**\n")
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elif line.strip() and len(line) > 80:
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sentences = [s.strip() for s in line.replace('。', '。\n').split('\n') if s.strip()]
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for s in sentences:
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if s:
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result.append(s)
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else:
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result.append(line)
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adapted = '\n'.join(result)
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return adapted
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return markdown
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def _get_platform_tags(self, platform: str) -> str:
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field = self.topic.get('field', '')
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title = self.topic.get('title', '')
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core = self.topic.get('core_concept', '')
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tag_prompts = {
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"zhihu": f"为以下文章生成知乎标签(3-5个)。标题:{title} 领域:{field} 核心观点:{core} 每个2-4字。直接输出标签,空格分隔。不要输出思考过程。",
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"wechat": f"为以下文章生成公众号标签(3-5个)。标题:{title} 领域:{field} 核心观点:{core} 每个2-4字。直接输出标签,空格分隔。不要输出思考过程。",
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"xiaohongshu": f"为以下文章生成小红书标签(3-5个)。标题:{title} 领域:{field} 核心观点:{core} 每个2-4字。直接输出标签,空格分隔。不要输出思考过程。",
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}
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if HAVE_LLM:
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prompt = tag_prompts.get(platform, f"根据文章信息生成适合{platform}的标签。标题:{title} 领域:{field} 核心观点:{core} 直接输出标签,空格分隔。")
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try:
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tags_text = call_llm(prompt, temperature=0.2)
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if tags_text:
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tags = [t.strip('#') for t in tags_text.strip().split() if t.strip('#')]
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if tags:
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return " ".join(f'<span class="tag">{t}</span>' for t in tags[:5])
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except Exception:
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pass
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tags = []
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if field:
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import re
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parts = re.split(r'[/、与和及]', field)
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for p in parts:
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p = p.strip()
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if len(p) >= 2:
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tags.append(p)
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if len(parts) == 1 and len(parts[0]) > 4:
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for i in range(0, len(parts[0]), 2):
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chunk = parts[0][i:i+2]
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if len(chunk) == 2:
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tags.append(chunk)
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tags.pop(0)
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platform_extra = {"zhihu": ["职场"], "xiaohongshu": ["生活"]}
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for t in platform_extra.get(platform, []):
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if t not in tags:
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tags.append(t)
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if not tags:
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tags = ["科技"]
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seen = set()
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return " ".join(f'<span class="tag">{t}</span>' for t in tags if t not in seen and not seen.add(t))
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def _optimize_title(self, platform: str) -> str:
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original = self.topic['title']
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if not HAVE_LLM:
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return original
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title_templates = {
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"zhihu": f"""你是一个知乎用户,在给自己的深度回答起高点击率标题。
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原文标题:{original}
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领域:{self.topic.get('field', '')}
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要求:
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- 有信息量:一看就知道能解决什么问题
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- 含知乎搜索关键词(SEO),利用知乎搜索联想热词
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- 带数字或对比最好(「3个方法」「从…到…」)
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- 20字以内
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- 参考知乎真实高赞标题风格,不要套路句式
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- 避免「如何…」废句式、「XXX指南/手册/全攻略」
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- 有观点、有态度,不是中性描述
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- 直击目标读者痛点或好奇心
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- 直接输出3个标题选项,每行一个,不要输出思考过程
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生成 3 个选项,每行一个。""",
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"wechat": f"""你是一个公众号作者,在给可能10万+的文章起标题。
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原文标题:{original}
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领域:{self.topic.get('field', '')}
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要求:
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- 制造好奇心和点击欲,让人觉得不点开会错过
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- 包含微信搜索关键词(微信SEO),利用搜一搜热门词
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- 口语化,不要书面腔
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- 不要感叹号堆砌,不要「重磅/震惊/紧急」
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- 字数15-25字最佳
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- 有情绪感召力:共鸣/好奇/焦虑/期待
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- 参考近期10万+标题的语气节奏
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- 直接输出3个标题选项,每行一个,不要输出思考过程
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生成 3 个选项,每行一个。""",
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"xiaohongshu": f"""你是一个小红书用户,在给笔记起能上热门推荐的标题。
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原文标题:{original}
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领域:{self.topic.get('field', '')}
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要求:
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- 20字以内
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- 采用爆款模式:数字+结果/痛点+方案/反常识观点/对比式
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- 包含小红书搜索关键词(SEO),利用搜索下拉热词
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- 带1个精准emoji点缀,不要三个起堆
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- 有场景感/结果感/获得感
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- 不要「必看/收藏/码住」
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- 像真实用户写的,不是运营写的
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- 参考小红书搜索热榜标题风格
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- 直接输出3个标题选项,每行一个,不要输出思考过程
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生成 3 个选项,每行一个。""",
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}
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prompt = title_templates.get(platform, f"给以下文章改个吸引人的{platform}标题:{original}")
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try:
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resp = call_llm(prompt, temperature=0.7)
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titles = []
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for line in resp.strip().split('\n'):
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line = line.strip()
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if not line:
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continue
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line = re.sub(r'^\d+[.、)\s]+', '', line)
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line = line.strip('*#- \t')
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if line:
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titles.append(line)
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if titles:
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logger.info(f"标题优化 [{platform}]: {titles[0][:50]}...")
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return titles[0]
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except Exception as e:
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logger.warning(f"标题优化失败: {e}")
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return original
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def generate_platform_html(self, markdown: str, platform: str) -> str:
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title = self._optimize_title(platform)
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adapted = self._adapt_for_platform(markdown, platform)
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tpl_path = TEMPLATES_DIR / f"{platform}.html"
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if tpl_path.exists():
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template = tpl_path.read_text(encoding='utf-8')
|
||
else:
|
||
template = "<!DOCTYPE html><html><head><meta charset='UTF-8'><title>{{TITLE}}</title><meta name='viewport' content='width=device-width'><style>body{max-width:800px;margin:0 auto;padding:20px;font-family:-apple-system,sans-serif;line-height:1.8}</style></head><body><h1>{{TITLE}}</h1><!-- CONTENT --></body></html>"
|
||
|
||
html = template.replace("{{TITLE}}", title).replace("{{DATE}}", TODAY).replace("{{GEN_TIME}}", GEN_TIME)
|
||
html_content = _md_parser(adapted)
|
||
|
||
# WeChat: insert topic-relevant image at start of body
|
||
if platform == "wechat":
|
||
import base64
|
||
topic_title = self.topic.get('title', title)
|
||
topic_field = self.topic.get('field', '')
|
||
safe_title = topic_title.replace('&', '&').replace('<', '<').replace('>', '>').replace('"', '"').replace("'", ''')
|
||
safe_field = topic_field.replace('&', '&').replace('<', '<').replace('>', '>')
|
||
lines = []
|
||
chars_per_line = 24
|
||
for i in range(0, len(safe_title), chars_per_line):
|
||
lines.append(safe_title[i:i+chars_per_line])
|
||
if not lines:
|
||
lines = ['配图']
|
||
line_y = 220 - (len(lines) - 1) * 20
|
||
title_texts = ''.join(f'<text x="540" y="{line_y + i*55}" font-size="36" fill="#1a1a1a" font-weight="bold">{l}</text>' for i, l in enumerate(lines))
|
||
field_text = f'<text x="540" y="{line_y + len(lines)*55 + 30}" font-size="20" fill="#98a2b3">{safe_field}</text>' if safe_field else ''
|
||
img_svg = f'''<svg xmlns="http://www.w3.org/2000/svg" width="1080" height="600" viewBox="0 0 1080 600" style="width:100%;max-width:1080px;border-radius:8px;background:linear-gradient(135deg,#f0f4ff,#e8f0fe)">
|
||
<rect width="1080" height="600" fill="url(#bg)"/>
|
||
<defs><linearGradient id="bg" x1="0%" y1="0%" x2="100%" y2="100%"><stop offset="0%" style="stop-color:#f0f4ff"/><stop offset="100%" style="stop-color:#e8f0fe"/></linearGradient></defs>
|
||
<g transform="translate(540,300)" text-anchor="middle" font-family="-apple-system,BlinkMacSystemFont,Helvetica Neue,PingFang SC,Microsoft YaHei,sans-serif">
|
||
<rect x="-60" y="-100" width="120" height="4" rx="2" fill="#409eff"/>
|
||
{title_texts}
|
||
{field_text}
|
||
<text y="100" font-size="14" fill="#c0c4cc">宇之然 · 配图(可替换)</text>
|
||
</g></svg>'''
|
||
img_b64 = 'data:image/svg+xml;base64,' + base64.b64encode(img_svg.encode('utf-8')).decode('ascii')
|
||
img_tag = f'<p><img src="{img_b64}" alt="{safe_title}" style="width:100%;max-width:1080px;border-radius:8px;"></p>\n'
|
||
h1_end = html_content.find('</h1>')
|
||
if h1_end != -1:
|
||
html_content = html_content[:h1_end + 5] + '\n' + img_tag + html_content[h1_end + 5:]
|
||
else:
|
||
html_content = img_tag + html_content
|
||
|
||
html = html.replace("<!-- CONTENT -->", html_content)
|
||
|
||
# 防御:清理可能在 LLM 输出中混入的 markdown 代码围栏和文件头
|
||
html = re.sub(r'^```+\w*\s*\n?', '', html)
|
||
html = html.strip()
|
||
|
||
tags_html = self._get_platform_tags(platform)
|
||
if tags_html:
|
||
html = html.replace("<!-- TAGS -->", tags_html)
|
||
else:
|
||
html = html.replace("<!-- TAGS -->", "")
|
||
|
||
return html
|
||
|
||
def save_html(self, html: str, platform: str) -> str:
|
||
try:
|
||
save_article(self.topic_id, platform, html)
|
||
logger.info(f"文章写入数据库: {platform}_{self.topic_id}")
|
||
return f"db:{platform}_{self.topic_id}"
|
||
except Exception as e:
|
||
logger.warning(f"数据库保存失败: {e}")
|
||
return ""
|
||
|
||
def mark_draft(self):
|
||
update_topic_status(self.topic_id, 'review')
|
||
logger.info(f"选题 {self.topic_id} 状态已更新为待审查(数据库)")
|
||
|
||
def run(self):
|
||
logger.info("开始撰写阶段")
|
||
markdown = self.generate_full_markdown()
|
||
results = {}
|
||
for platform in ["zhihu", "wechat", "xiaohongshu"]:
|
||
html = self.generate_platform_html(markdown, platform)
|
||
results[platform] = str(self.save_html(html, platform))
|
||
self.mark_draft()
|
||
logger.info(f"撰写完成,状态已更新为待审查")
|
||
return {"ok": True, "files": results}
|
||
|
||
def main():
|
||
import argparse
|
||
parser = argparse.ArgumentParser()
|
||
parser.add_argument('--topic-id', required=True, help='选题ID')
|
||
args = parser.parse_args()
|
||
|
||
w = Writer(args.topic_id)
|
||
result = w.run()
|
||
print(json.dumps(result, ensure_ascii=False))
|
||
sys.exit(0 if result['ok'] else 1)
|
||
|
||
if __name__ == "__main__":
|
||
main()
|