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Source channel @yxvmcom · Post #21 · Nov 10

#Features 我们打开了一项新的功能,此功能目前处于测试阶段,我们将此功能命名为 AnyLAN,你可以使用它快速的建立内网,并且不消耗你的公网流量。 目前此功能分为2个场景: 1. 同节点内网 2. 不同节点内网(2个节点或以上) 我们这里提供一份简易的教程供大家参考:https://yxvm.com/index.php?rp=/knowledgebase/2/How-to-use-AnyLAN.html 需要开启此功能,你必须购买相应产品(目前免费) LAN (必须同节点持有2个以上VPS才可购买): https://yxvm.com/cart.php?pid=44&promocode=DLCH0P1DN7 AnyLAN(必须俩个或以上节点持有VPS才可购买):https://yxvm.com/cart.php?pid=45&promocode=83YHPHA6QG *LAN 限速500Mbps AnyLAN限速100Mbps

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@githubtrending · Post #15438 · 01/26/2026, 11:30 AM

#python#agents#ai#ai_engineer#ai_engineering#copilot#data_science#data_scientist#generative_ai#gpt#machine_learning#ml_engineer#ml_engineering#openai AI Data Science Team is a free Python library with AI agents that speed up your data work 10X by handling loading, cleaning, visualization, EDA, feature engineering, modeling, and SQL tasks. Its flagship AI Pipeline Studio app creates visual, reproducible pipelines you can run with Streamlit after easy install (Python 3.10+, OpenAI or Ollama). This saves you hours on repetitive jobs, boosts accuracy, and lets you focus on insights and business results. https://github.com/business-science/ai-data-science-team

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@githubtrending · Post #14808 · 06/08/2025, 01:00 PM

#rust#ai#ai_engineering#anthropic#artificial_intelligence#deep_learning#genai#generative_ai#gpt#large_language_models#llama#llm#llmops#llms#machine_learning#ml#ml_engineering#mlops#openai#python#rust TensorZero is a free, open-source tool that helps you build and improve large language model (LLM) applications by using real-world data and feedback. It gives you one simple API to connect with all major LLM providers, collects data from your app’s use, and lets you easily test and improve prompts, models, and strategies. You can see how your LLMs perform, compare different options, and make them smarter, faster, and cheaper over time—all while keeping your data private and under your control. This means you get better results with less effort and cost, and your apps keep improving as you use them[1][2][3]. https://github.com/tensorzero/tensorzero