🚀 GitHub | 2025-06-12 10:22
🔥 今日 GitHub 热门仓库一览
以下是今日最受欢迎的开源项目，每一个都值得你关注！💡
1. ❓ sindresorhus /awesome
⭐⭐ Stars: 366020 • 📈 今日新增: 641 • 语言：Unknown
📝 描述：😎 Awesome lists about all kinds of interesting topics
🤝 Built by：sindresorhus, davisonio, RichardLitt, arthurvr, kdeldycke
2. 🐍 Shubhamsaboo /awesome-llm-apps
⭐ Stars: 35297 • 📈 今日新增: 529 • 语言：Python
📝 描述：Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
🤝 Built by：Shubhamsaboo, Madhuvod, libw0430, AndrewHoh, CodeWithCharan
3. 📦 alphacep /vosk-api
⭐ Stars: 11827 • 📈 今日新增: 387 • 语言：Jupyter Notebook
📝 描述：Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
🤝 Built by：nshmyrev, vadimdddd, nnkalita, lkiesow, nalbion
4. 🐍 jwohlwend /boltz
⭐ Stars: 2686 • 📈 今日新增: 420 • 语言：Python
📝 描述：Official repository for the Boltz biomolecular interaction models
🤝 Built by：jwohlwend, gcorso, ioannisa92, darianyang, latkins
5. 🐍 jdepoix /youtube-transcript-api
⭐ Stars: 4213 • 📈 今日新增: 44 • 语言：Python
📝 描述：This is a python API which allows you to get the transcript/subtitles for a given YouTube video. It also works for automatically generated subtitles and it does not require an API key nor a headless browser, like other selenium based solutions do!
🤝 Built by：jdepoix, crhowell, danielcliu, eseiver, liamrs222
6. ❓ zijie0 /HumanSystemOptimization
⭐ Stars: 17076 • 📈 今日新增: 412 • 语言：Unknown
📝 描述：健康学习到150岁 - 人体系统调优不完全指南
7. 📦 datawhalechina /self-llm
⭐ Stars: 17324 • 📈 今日新增: 448 • 语言：Jupyter Notebook
📝 描述：《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
🤝 Built by：KMnO4-zx, L4HeyXiao, Tsumugii24, Aphasia0515, isaacahahah
8. 🦀 juspay /hyperswitch
⭐ Stars: 20668 • 📈 今日新增: 56 • 语言：Rust
📝 描述：An open source payments switch written in Rust to make payments fast, reliable and affordable
🤝 Built by：hyperswitch-bot, github-actions, SanchithHegde, Narayanbhat166, pixincreate
9. 📦 OpenBMB /MiniCPM
⭐ Stars: 7803 • 📈 今日新增: 63 • 语言：Jupyter Notebook
📝 描述：MiniCPM4: Ultra-Efficient LLMs on End Devices, achieving 5+ speedup on typical end-side chips
🤝 Built by：LDLINGLINGLING, THUCSTHanxu13, ShengdingHu, zh-zheng, xcjthu
🌈 每日开源之旅
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