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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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#miaospeed#dev版 #4.3.2 ✅同步Miaospeed 4.3.1 ✅更新Clash内核 Clash v1.13.0 ✅修复STUN无法传参问题 ✅ipv6 stack 读取问题 ✅默认 ipv6 检测脚本换为更激进的[2606:4700:4700:.1111] ✅增加一个新的动态测速文件方式, DYNAMIC:ALL (欢迎提交测速文件地址) ❌尝试更新Clash.META内核失败,保留原本的版本

#miaospeed#release#v4.3.3 ✅同步Miaospeed 4.3.1 ✅更新Clash内核 Clash v1.13.0 ✅修复STUN无法传参问题 ✅PING和UDP的DNS预解析 ✅ipv6 stack 读取问题 ✅默认 ipv6 检测脚本换为更激进的[2606:4700:4700:.1111] ✅增加一个新的动态测速文件方式, DYNAMIC:ALL (欢迎提交测速文件地址) ✅Miaoko传入STUN或pingAddress无法解析自动切换Miaospeed内置地址 地址:https://github.com/moshaoli688/miaospeed/releases/tag/v4.3.3