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Source channel @githubtrending · Post #15100 · Aug 29

#typescript#commerce#e_commerce#javascript#marketplace#marketplace_solution#medusa#medusajs#medusajs_v2#multi_vendor#multi_vendor_ecommerce#multivendor_ecommerce#nodejs#open_source#shopping_cart Mercur is a free, open-source platform that lets you build and run your own multi-vendor marketplace with full control over your data, infrastructure, and customizations. It combines the ease of SaaS with the freedom of open source, so you avoid transaction fees and vendor lock-in. Built on modern MedusaJS technology, Mercur supports both B2C and B2B marketplaces, offering customizable storefronts, admin and vendor panels, and integrations like Stripe for payments. This means you can create a unique, scalable marketplace tailored to your business needs without relying on costly or restrictive platforms. It requires some technical skill but gives you complete ownership and flexibility. https://github.com/mercurjs/mercur

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@githubtrending · Post #15295 · 11/11/2025, 05:00 PM

#python#ai#faiss#gpt_oss#langchain#llama_index#llm#localstorage#offline_first#ollama#privacy#python#rag#retrieval_augmented_generation#vector_database#vector_search#vectors LEANN is a tiny, powerful vector database that lets you turn your laptop into a personal AI assistant capable of searching millions of documents using 97% less storage than traditional systems without losing accuracy. It works by storing a compact graph and computing embeddings only when needed, saving huge space and keeping your data private on your device. You can search your files, emails, browser history, chat logs, live data from platforms like Slack and Twitter, and even codebases—all locally without cloud costs. This means fast, private, and efficient AI-powered search and retrieval on your own laptop. https://github.com/yichuan-w/LEANN

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@githubtrending · Post #15168 · 09/25/2025, 12:30 PM

#python#ai#context#embedded#faiss#knowledge_base#knowledge_graph#llm#machine_learning#memory#nlp#offline_first#opencv#python#rag#retrieval_augmented_generation#semantic_search#vector_database#video_processing Memvid lets you store millions of text pieces inside a single MP4 video file using QR codes, making your data 50-100 times smaller than usual databases. You can search this video instantly in under 100 milliseconds without needing servers or internet after setup. It works offline, is easy to use with simple Python code, and supports PDFs and chat with your data. The upcoming version 2 will add features like continuous memory updates, shareable capsules, fast local caching, and better video compression, making your AI memory smarter, faster, and more flexible. This means you get a powerful, portable, and efficient way to manage and search huge knowledge bases quickly and easily. https://github.com/Olow304/memvid