{"repo":"MinishLab/vicinity","free":true,"listed":false,"github":"https://github.com/MinishLab/vicinity","clone":"git clone https://github.com/MinishLab/vicinity.git","description":"Lightweight Nearest Neighbors with Flexible Backends","language":"Python","stars":350,"topics":["embeddings","vector-database","ai","python","annoy","faiss","hnsw","hnswlib"],"license":"MIT","category":"databases-storage","readme_excerpt":"Lightweight Nearest Neighbors with Flexible Backends Quickstart • Main Features • Supported Backends • Installation Vicinity is a light-weight, low-dependency vector store. It provides a simple and intuitive interface for nearest neighbor search, with support for different backends and evaluation. There are many nearest neighbors packages and methods out there. However, we found it difficult to compare them. Every package has its own interface, quirks, and limitations, and learning a new package can be time-consuming. In addition to that, how do you effectively evaluate different packages? How do you know which one is the best for your use case? This is where Vicinity comes in. Instead of learning a new interface for each new package or backend, Vicinity provides a unified interface for all backends. This allows you to easily experiment with different indexing methods and distance metrics and choose the best one for your use case. Vicinity also provides a simple way to evaluate the performance of different backends, allowing you to measure the queries per second and recall. Quickstart Install the package with: Optionally, install specific backends and integrations, or simply install all of them with: The following code snippet demonstrates how to use Vicinity for nearest neighbor search: Saving and loading a vector store: Pushing and loading a vector store from the Hugging Face Hub (note that you can optionally add the model used for generating embeddings to the metadata, e.g","default_branch":null,"files":null,"tree":[],"storefront":"/r/MinishLab","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/MinishLab/vicinity/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}