GitHub - lancedb/vectordb-recipes: High quality resources & applications for LLMs, multi-modal models and VectorDBs
Vector libraries, like Facebook (Meta) Faiss or Spotify Annoy, provide functionality for working with vector data. In the context of vector search, a vector library is specifically designed to store and perform similarity search on vector embeddings.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
The ideal solution for AI-native vectorDB would be something that would would be easy to set up and should integrate with existing APIs for rapid prototyping but should be able to scale without additional changes.
LanceDB is designed with this approach. Being server-less, it requires no setup — just import and start using. Persisted in HDD, allowing... See more
LanceDB is designed with this approach. Being server-less, it requires no setup — just import and start using. Persisted in HDD, allowing... See more
Ayush Chaurasia • LLMs, RAG, & the missing storage layer for AI
Vector databases can be used to store and serve machine learning models and their corresponding embeddings. The primary application is similarity search (also semantic search),
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
Open source, high-throughput, fault-tolerant vector embedding pipeline
Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably
Simple API endpoint that ingests large volumes of raw data, processes, and stores or returns the vectors quickly and reliably