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Chaîne source @OnePlusGuide · Post #3170 · 18 août

🔻ONEPLUS CERCA DEI TESTER PER LE ALPHA DI ONEPLUS 9 E 9 PRO🔻 #OP9#OP9PRO#ALPHA#S OnePlus cerca dei tester per il programma OxygenOS CBT (software di livello alpha) su 9 e 9 Pro. Chi aderirà, potrà testare in anteprima le novità di OxygenOS, ma dovrà rispettare un accordo di riservatezza e interagire attivamente con gli sviluppatori OnePlus. A questo punto è facile pensare che le prime build saranno già basate su Android 12 con la nuova base di codice unita a ColorOS. Credete di essere adatti? Potete iscrivervi qui e provare a prendervi uno dei 200 posti disponibili. Pierre — Il nostro canale 👉🏻@oneplusguide I nostri gruppi 👉🏻@oneplusitcommunity

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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