#go #anns #cloud_native #distributed #embedding_database #embedding_similarity #embedding_store #faiss #golang #hnsw #image_search #llm #nearest_neighbor_search #tensor_database #vector_database #vector_search #vector_similarity #vector_store

Milvus is an open-source vector database designed for embedding similarity search and AI applications. It makes unstructured data search more accessible and provides a consistent user experience across different deployment environments. Key features include millisecond search on trillion vector datasets, simplified unstructured data management, reliable and always-on operations, high scalability, and hybrid search capabilities. Milvus is cloud-native, supports multiple SDKs, and has a strong community with extensive documentation and support channels like Discord and mailing lists. Using Milvus benefits users by enabling fast and efficient vector searches, simplifying data management, and ensuring reliability and scalability in their applications.

https://github.com/milvus-io/milvus

#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

#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