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Chaîne source @OnePlusGuide · Post #2525 · 24 mai

~ COME ABILITARE I 960 FPS E LA MACRO MODE SU ONEPLUS 7 PRO (OOS CAMERA + ROOT) ~ #OP#OOS#OP7PRO Dopo l'arrivo di queste modalità su OnePlus 7T, è possibile abilitarle anche sul OnePlus 7 Pro. Questa procedura richiede i permessi di root e la camera stock di OxygenOS. É richiesta una versione della Camera pari o superiore alla 3.10.17 (ve la linko) ed è consigliata l'installazione delle build Open Beta di OOS. • Assicurarsi di avere la corretta versione della Camera • Scaricare Preferences Manger (download nei bottoni) • Configurarla e abilitarla ai permessi di root • Entrare nella sezione dell'app Fotocamera • Cercare il file CameraInfo0.xml • Aggiungere una StringSet (con il tasto + in alto) che abbia come key Video960FpsSizes e come valore 1280x720 • Ripetere la stessa procedura nel file CameraInfo5.xml • Aprire il file CameraInfo_3.xml e cercare la variabile IsUWMacroSupported e cambiare il valore da false a true Fatto! Pierre

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GitHub Trends

@githubtrending · Post #15295 · 11/11/2025 17:00

#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

GitHub Trends

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

#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