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Source channel @githubtrending · Post #15200 · Oct 6

#php#ehr#emr#fhir#global_health#health#healthcare#hit#international#linux#medical#medical_informatics#medical_information#medical_records#openemr#osx#php#practice_management#proprietary_counterparts#sponsors#windows OpenEMR is a free, open-source electronic health records (EHR) and medical practice management software that works on many platforms like Windows, Linux, and Mac. It offers features such as patient scheduling, electronic billing, integrated health records, and support for both outpatient and inpatient care. It supports modern standards like FHIR for easy and secure data sharing between healthcare providers. OpenEMR is highly customizable, allowing you to tailor it to your specific needs, and it is ONC certified, ensuring compliance with healthcare regulations. Using OpenEMR can save costs compared to paid EHRs and gives you control over your patient data while benefiting from a supportive community and free resources. https://github.com/openemr/openemr

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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