semi-technologies/weaviate

Weaviate is an open source vector database that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.

GoShellAssemblyCPythonDockerfilegraphqlsearch-engineinformation-retrievalnearest-neighbor-searchsemantic-search-engineimage-searchrecommender-systemvectorsapproximate-nearest-neighbor-searchsemantic-searchsimilarity-searchmlopshnswweaviatevector-searchvector-databaseneural-searchvector-search-enginehybrid-searchgenerative-search
This is stars and forks stats for /semi-technologies/weaviate repository. As of 27 Apr, 2024 this repository has 7764 stars and 490 forks.

Weaviate Overview Weaviate is an open source vector database that is robust, scalable, cloud-native, and fast. If you just want to get started, great! Try: the quickstart tutorial if you are looking to use Weaviate, or the contributor guide if you are looking to contribute to the project. And you can find our documentation here. If you have a bit more time, stick around and check out our summary below 😉 Why Weaviate? With Weaviate, you can turn your text, images and more into a searchable vector...
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