awesome-stars category by language update by github actions cron, cre…

…ated by starred

README.md

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 ## HTML 
 
-- [unclecode/crawl4ai](https://github.com/unclecode/crawl4ai) - 🚀🤖 Crawl4AI: Crawl Smarter, Faster, Freely. For AI.
+- [unclecode/crawl4ai](https://github.com/unclecode/crawl4ai) - 🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper
 - [htmlstreamofficial/preline](https://github.com/htmlstreamofficial/preline) - Preline UI is an open-source set of prebuilt UI components based on the utility-first Tailwind CSS framework.
 - [rootsongjc/awesome-cloud-native](https://github.com/rootsongjc/awesome-cloud-native) - A curated list for awesome cloud native tools, software and tutorials.  - https://jimmysong.io/awesome-cloud-native/
 - [evildmp/diataxis-documentation-framework](https://github.com/evildmp/diataxis-documentation-framework) - A systematic approach to creating better documentation.
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 - [google/mesop](https://github.com/google/mesop) - Rapidly build AI apps in Python
 - [piku/piku](https://github.com/piku/piku) - The tiniest PaaS you've ever seen. Piku allows you to do git push deployments to your own servers.
 - [2noise/ChatTTS](https://github.com/2noise/ChatTTS) - A generative speech model for daily dialogue.
-- [ngc660sec/NGCBot](https://github.com/ngc660sec/NGCBot) - 一个基于✨HOOK机制的微信机器人，支持🌱安全新闻定时推送【FreeBuf，先知，安全客，奇安信攻防社区】，👯Kfc文案，⚡备案查询，⚡手机号归属地查询，⚡WHOIS信息查询，🎉星座查询，⚡天气查询，🌱摸鱼日历，⚡微步威胁情报查询， 🐛美女视频，⚡美女图片，👯帮助菜单。📫 支持积分功能，⚡支持自动拉人，⚡检测广告，🌱自动群发，👯Ai回复，😄自定义程度丰富，小白也可轻松上手！
+- [ngc660sec/NGCBot](https://github.com/ngc660sec/NGCBot) - 一个基于✨HOOK机制的微信机器人，支持🌱安全新闻定时推送【FreeBuf，先知，安全客，奇安信攻防社区】，👯Kfc文案，⚡漏洞查询，⚡手机号归属地查询，⚡知识库查询，🎉星座查询，⚡天气查询，🌱摸鱼日历，⚡微步威胁情报查询， 🐛视频，⚡图片，👯帮助菜单。📫 支持积分功能，⚡支持自动拉人，，🌱自动群发，👯Ai回复，⚡视频号解析，😄自定义程度丰富，小白也可轻松上手！
 - [livekit/agents](https://github.com/livekit/agents) - Build real-time multimodal AI applications 🤖🎙️📹
 - [ScrapeGraphAI/Scrapegraph-ai](https://github.com/ScrapeGraphAI/Scrapegraph-ai) - Python scraper based on AI
 - [Skyvern-AI/skyvern](https://github.com/Skyvern-AI/skyvern) - Automate browser-based workflows with LLMs and Computer Vision