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AnnLite is a lightweight and embeddable library for fast and filterable approximate nearest neighbor search (ANNS). It allows to search for nearest neighbors in a dataset of millions of points with a Pythonic API. A simple API is designed to be used with Python. It is easy to use and intuitive to set up to production. The library uses a highly optimized approximate nearest neighbor search algorithm (HNSW) to search for nearest neighbors. The library allows you to search for nearest neighbors within a subset of the dataset. Smooth integration with neural search ecosystem including Jina and DocArray, so that users can easily expose search API with gRPC and/or HTTP. The library is easy to install and use. It is designed to be used with Python. To support search with filters, the annlite must be created with colums parameter, which is a series of fields you want to filter by.
Features
- Simple API is designed to be used with Python. It is easy to use and intuitive to set up to production
- The library uses a highly optimized approximate nearest neighbor search algorithm (HNSW) to search for nearest neighbors
- The library allows you to search for nearest neighbors within a subset of the dataset
- Smooth integration with neural search ecosystem including Jina and DocArray
- Users can easily expose search API with gRPC and/or HTTP
- The library is easy to install and use. It is designed to be used with Python
Project Samples
