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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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@githubtrending · Post #15268 · 11/04/2025, 12:00 PM

#go#blockchain#cloudvpn#golang#golang_library#holepunch#ipfs#ipfs_blockchain#kubernetes#libp2p#mesh#mesh_networks#nat#networking#p2p#p2pvpn#tunnel#vpn EdgeVPN lets you create secure, decentralized private networks using peer-to-peer (p2p) connections without relying on central servers. It can build a VPN that automatically assigns IPs, includes a small DNS server, and protects your network even if tokens leak. You can also use it as a reverse proxy to share TCP services or send files securely over p2p without a VPN connection. It works well for edge devices and development, especially behind NATs, and can be integrated into your own Go programs. This helps you connect devices easily and securely across different networks without complex setup or infrastructure. https://github.com/mudler/edgevpn