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Source channel @githubtrending · Post #15137 · Sep 12

#typescript#design#docs#gatsby#handbook#posthog#tailwindcss PostHog.com is the website and code repository for PostHog, an open-source product analytics platform that helps you track user behavior, test new features, and improve your product all in one place. You can run the website locally by installing Node and Yarn, cloning the repo, and starting the development server. The site includes product docs, blogs, tutorials, and tools like job listings and pricing calculators. This setup lets you customize and contribute to the site easily, making it useful if you want to understand or improve PostHog’s platform or help develop its content and features. It supports collaboration and learning for developers and product teams. https://github.com/PostHog/posthog.com

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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