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Source channel @githubtrending · Post #14826 · Jun 12

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#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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UXLINK

@uxlink_community · Post #470 · 05/10/2025, 05:27 AM

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最近の日本Web3界隈で目立つのが、UXLINKの存在感。🇯🇵🔍 CNPとの提携を皮切りに、日本ローカルの強力なIPとの協業が加速⚡ オンチェーン/オフチェーン両方でのコミュニティ展開に加え、 Web2企業とのクロスパートナー戦略も水面下で進行中🤝 “ユーザー起点のWeb3ソーシャル”という文脈で、 UXLINKは今、日本で一番面白い動きをしているかもしれない。🚀 #UXLINK#Web3JP#CNP#ソーシャルレイヤー#CommunityDriven One of the most quietly significant players gaining traction in Japan’s Web3 scene 🇯🇵👀#UXLINK Following its recent collaboration with CNP—a top domestic IP—UXLINK is making inroads across both native Web3 communities and mainstream Web2 circles 🤝 IRL activations, on-chain social dynamics, and a clear long-term strategy signal a serious Japan play 🎯 If you're tracking the rise of social infrastructure in Asia’s Web3 movement, this is one to watch. 📡 #UXLINK#Web3Japan#CommunityLayer#CNP#Web3Social

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