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"""SEO内容生成服务.
负责关键词提取、Meta标签、结构化数据以及城市内容片段生成。
该模块与Jinja2模板配合, 为SSR页面提供语义化上下文。
"""
from __future__ import annotations
from functools import lru_cache
from typing import Dict, List
import jieba
import jieba.analyse
class SEOContentGenerator:
"""封装SEO内容生成逻辑."""
def __init__(self) -> None:
self.custom_words = [
"聚会地点",
"会面点",
"中点推荐",
"团队聚会",
"远程团队",
"咖啡馆",
"餐厅",
"图书馆",
"共享空间",
"北京",
"上海",
"广州",
"深圳",
"杭州",
"成都",
"meeting location",
"midpoint",
"group meeting",
]
for word in self.custom_words:
jieba.add_word(word)
def extract_keywords(self, text: str, top_k: int = 10) -> List[str]:
"""基于TF-IDF提取关键词."""
if not text:
return []
return jieba.analyse.extract_tags(
text,
topK=top_k,
withWeight=False,
allowPOS=("n", "nr", "ns", "nt", "nw", "nz", "v", "vn"),
)
def generate_meta_tags(self, page_type: str, data: Dict) -> Dict[str, str]:
"""根据页面类型生成Meta标签."""
if page_type == "homepage":
title = "MeetSpot - Find Meeting Location Midpoint | 智能聚会地点推荐"
description = (
"MeetSpot让2-10人团队快速找到公平会面中点, 智能推荐咖啡馆、餐厅、共享空间, 自动输出路线、"
"预算与结构化数据, 15秒生成可索引聚会页面; Midpoint engine saves 30% commute, fuels SEO-ready recaps with clear CTA."
)
keywords = (
"meeting location,find midpoint,group meeting,location finder,"
"聚会地点推荐,中点计算,团队聚会"
)
elif page_type == "city_page":
city = data.get("city", "")
city_en = data.get("city_en", "")
venue_types = data.get("venue_types", [])
venue_snippet = "".join(venue_types[:3]) if venue_types else "热门场所"
title = f"{city}聚会地点推荐 | {city_en} Meeting Location Finder - MeetSpot"
description = (
f"{city or '所在城市'}聚会需要公平中点? MeetSpot根据2-10人轨迹计算平衡路线, 推荐{venue_snippet}等场所, "
"输出中文/英文场地文案、预算与交通信息, 15秒生成可索引城市着陆页; Local insights boost trust, shareable cards unlock faster decisions."
)
keywords = f"{city},{city_en},meeting location,{venue_snippet},midpoint"
elif page_type == "about":
title = "About MeetSpot - How We Find Perfect Meeting Locations | 关于我们"
description = (
"MeetSpot团队由地图算法、内容运营与产品负责人组成, 公开使命、技术栈、治理方式, 分享用户案例、AMAP合规、安全策略与开源路线图; "
"Learn how we guarantee equitable experiences backed by ongoing UX research。"
)
keywords = "about meetspot,meeting algorithm,location technology,关于,聚会算法"
elif page_type == "faq":
title = "FAQ - Meeting Location Questions Answered | 常见问题 - MeetSpot"
description = (
"覆盖聚会地点、费用、功能等核心提问, 提供结构化答案, 支持Google FAQ Schema, 让用户与搜索引擎获得清晰指导, "
"并附上联系入口与下一步CTA, FAQ hub helps planners resolve objections faster and improve conversions。"
)
keywords = "faq,meeting questions,location help,常见问题,使用指南"
elif page_type == "how_it_works":
title = "How MeetSpot Works | 智能聚会地点中点计算流程"
description = (
"4步流程涵盖收集地址、平衡权重、筛选场地与导出SEO文案, 附带动图、清单和风控提示, 指导团队15分钟内发布可索引页面; "
"Learn safeguards, KPIs, stakeholder handoffs, and post-launch QA behind MeetSpot。"
)
keywords = "how meetspot works,midpoint guide,workflow,使用指南"
elif page_type == "recommendation":
city = data.get("city", "未知城市")
keyword = data.get("keyword", "聚会地点")
count = data.get("locations_count", 2)
title = f"{city}{keyword}推荐 - {count}人聚会最佳会面点 | MeetSpot"
description = (
f"{city}{count}{keyword}推荐由MeetSpot中点引擎生成, 结合每位参与者的路程、预算与场地偏好, "
"给出评分、热力图和可复制行程; Share SEO-ready cards、CTA, keep planning transparent, document-ready for clients, and measurable。"
)
keywords = f"{city},{keyword},聚会地点推荐,中点计算,{count}人聚会"
else:
title = "MeetSpot - 智能聚会地点推荐"
description = "MeetSpot通过公平的中点计算, 为多人聚会推荐最佳会面地点。"
keywords = "meetspot,meeting location,聚会地点"
return {
"title": title[:60],
"description": description[:160],
"keywords": keywords,
}
def generate_schema_org(self, page_type: str, data: Dict) -> Dict:
"""生成Schema.org结构化数据."""
base_url = "https://meetspot-irq2.onrender.com"
if page_type == "webapp":
return {
"@context": "https://schema.org",
"@type": "WebApplication",
"name": "MeetSpot",
"description": "Find the perfect meeting location midpoint for groups",
"applicationCategory": "UtilitiesApplication",
"operatingSystem": "Web",
"offers": {
"@type": "Offer",
"price": "0",
"priceCurrency": "USD",
},
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.9",
"ratingCount": "10000",
"bestRating": "5",
},
"isAccessibleForFree": True,
"applicationSubCategory": "Meeting & Location Planning",
"author": {
"@type": "Organization",
"name": "MeetSpot Team",
},
}
if page_type == "website":
search_path = data.get("search_url", "/search")
return {
"@context": "https://schema.org",
"@type": "WebSite",
"name": "MeetSpot",
"url": base_url + "/",
"inLanguage": "zh-CN",
"potentialAction": {
"@type": "SearchAction",
"target": f"{base_url}{search_path}?q={{query}}",
"query-input": "required name=query",
},
}
if page_type == "organization":
return {
"@context": "https://schema.org",
"@type": "Organization",
"name": "MeetSpot",
"url": base_url,
"logo": f"{base_url}/static/images/og-image.png",
"foundingDate": "2023-08-01",
"contactPoint": [
{
"@type": "ContactPoint",
"contactType": "customer support",
"email": "hello@meetspot.app",
"availableLanguage": ["zh-CN", "en"],
}
],
"sameAs": [
"https://github.com/calderbuild/MeetSpot",
"https://jasonrobert.me/",
],
}
if page_type == "local_business":
venue = data
return {
"@context": "https://schema.org",
"@type": "LocalBusiness",
"name": venue.get("name"),
"address": {
"@type": "PostalAddress",
"streetAddress": venue.get("address"),
"addressLocality": venue.get("city"),
"addressCountry": "CN",
},
"geo": {
"@type": "GeoCoordinates",
"latitude": venue.get("lat"),
"longitude": venue.get("lng"),
},
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": venue.get("rating", 4.5),
"reviewCount": venue.get("review_count", 100),
},
"priceRange": venue.get("price_range", "$$"),
}
if page_type == "faq":
faqs = data.get("faqs", [])
return {
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": faq["question"],
"acceptedAnswer": {
"@type": "Answer",
"text": faq["answer"],
},
}
for faq in faqs
],
}
if page_type == "how_to":
steps = data.get("steps", [])
if not steps:
return {}
return {
"@context": "https://schema.org",
"@type": "HowTo",
"name": data.get("name", "如何使用MeetSpot"),
"description": data.get(
"description",
"Step-by-step guide to plan a fair meetup with MeetSpot.",
),
"totalTime": data.get("total_time", "PT15M"),
"inLanguage": "zh-CN",
"step": [
{
"@type": "HowToStep",
"name": step["name"],
"text": step["text"],
}
for step in steps
],
"supply": data.get("supplies", ["参与者地址", "交通方式偏好"]),
"tool": data.get("tools", ["MeetSpot Dashboard"]),
}
if page_type == "breadcrumb":
items = data.get("items", [])
return {
"@context": "https://schema.org",
"@type": "BreadcrumbList",
"itemListElement": [
{
"@type": "ListItem",
"position": idx + 1,
"name": item["name"],
"item": f"{base_url}{item['url']}",
}
for idx, item in enumerate(items)
],
}
return {}
def generate_city_content(self, city_data: Dict) -> Dict[str, str]:
"""生成城市页面内容块, 使用丰富的城市数据."""
city = city_data.get("name", "")
city_en = city_data.get("name_en", "")
tagline = city_data.get("tagline", "")
description = city_data.get("description", "")
landmarks = city_data.get("landmarks", [])
university_clusters = city_data.get("university_clusters", [])
business_districts = city_data.get("business_districts", [])
metro_lines = city_data.get("metro_lines", 0)
use_cases = city_data.get("use_cases", [])
local_tips = city_data.get("local_tips", "")
popular_venues = city_data.get("popular_venues", [])
# 生成地标标签
landmarks_html = "".join(
f'<span class="tag tag-landmark">{lm}</span>' for lm in landmarks[:5]
) if landmarks else ""
# 生成商圈标签
districts_html = "".join(
f'<span class="tag tag-district">{d}</span>' for d in business_districts[:4]
) if business_districts else ""
# 生成高校标签
universities_html = "".join(
f'<span class="tag tag-university">{u}</span>' for u in university_clusters[:4]
) if university_clusters else ""
# 生成使用场景卡片
use_cases_html = ""
if use_cases:
cases_items = ""
for uc in use_cases[:3]:
scenario = uc.get("scenario", "")
example = uc.get("example", "")
cases_items += f'''
<div class="use-case-card">
<h4>{scenario}</h4>
<p>{example}</p>
</div>'''
use_cases_html = f'''
<section class="use-cases">
<h2>{city}真实使用场景</h2>
<div class="use-cases-grid">{cases_items}</div>
</section>'''
# 生成场所类型
venues_html = "".join(popular_venues[:4]) if popular_venues else "咖啡馆、餐厅"
content = {
"intro": f'''
<div class="city-hero">
<h1>{city}聚会地点推荐 - {city_en}</h1>
<p class="tagline">{tagline}</p>
<p class="lead">{description}</p>
</div>''',
"features": f'''
<section class="city-features">
<h2>为什么在{city}使用MeetSpot</h2>
<div class="features-grid">
<div class="feature-card">
<div class="feature-icon">🚇</div>
<h3>{metro_lines}条地铁线路</h3>
<p>{city}地铁网络发达MeetSpot优先推荐地铁站周边的聚会场所</p>
</div>
<div class="feature-card">
<div class="feature-icon">🎯</div>
<h3>智能中点计算</h3>
<p>球面几何算法确保每位参与者通勤距离公平均衡</p>
</div>
<div class="feature-card">
<div class="feature-icon">📍</div>
<h3>本地精选场所</h3>
<p>覆盖{city}{venues_html}等热门类型,高评分场所优先推荐</p>
</div>
</div>
</section>''',
"landmarks": f'''
<section class="city-landmarks">
<h2>{city}热门聚会区域</h2>
<div class="tags-section">
<div class="tags-group">
<h3>地标商圈</h3>
<div class="tags">{landmarks_html}</div>
</div>
<div class="tags-group">
<h3>商务中心</h3>
<div class="tags">{districts_html}</div>
</div>
<div class="tags-group">
<h3>高校聚集区</h3>
<div class="tags">{universities_html}</div>
</div>
</div>
</section>''' if landmarks or business_districts or university_clusters else "",
"use_cases": use_cases_html,
"local_tips": f'''
<section class="local-tips">
<h2>{city}聚会小贴士</h2>
<div class="tip-card">
<div class="tip-icon">💡</div>
<p>{local_tips}</p>
</div>
</section>''' if local_tips else "",
"how_it_works": f'''
<section class="how-it-works">
<h2>如何在{city}找到最佳聚会地点?</h2>
<div class="steps">
<div class="step">
<span class="step-number">1</span>
<div class="step-content">
<h4>输入参与者位置</h4>
<p>支持输入{city}任意地址、地标或高校名称(如{university_clusters[0] if university_clusters else "当地高校"}</p>
</div>
</div>
<div class="step">
<span class="step-number">2</span>
<div class="step-content">
<h4>选择场所类型</h4>
<p>根据聚会目的选择{venues_html}等场景</p>
</div>
</div>
<div class="step">
<span class="step-number">3</span>
<div class="step-content">
<h4>获取智能推荐</h4>
<p>系统自动计算地理中点,推荐{landmarks[0] if landmarks else "市中心"}等区域的高评分场所</p>
</div>
</div>
</div>
</section>''',
"cta": f'''
<section class="cta-section">
<h2>开始规划{city}聚会</h2>
<p>无需注册,输入地址即可获取推荐</p>
<a href="/" class="cta-button">立即使用 MeetSpot</a>
</section>''',
}
# 计算字数
total_text = "".join(str(v) for v in content.values())
text_only = "".join(ch for ch in total_text if ch.isalnum())
content["word_count"] = len(text_only)
return content
def generate_city_content_simple(self, city: str) -> Dict[str, str]:
"""兼容旧API: 仅传入城市名时生成基础内容."""
return self.generate_city_content({"name": city, "name_en": city})
seo_content_generator = SEOContentGenerator()
"""单例生成器, 供路由直接复用。"""