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example-weaviate-vector-embeddings
Companion code repository for my blog post, "How to use Weaviate to store and query vector embeddings"
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Weaviate
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
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The example project for this blog post demonstrates how to embed texts into vectors, store them in Weaviate, and perform semantic search to find the most contextually similar documents to the input query. All of the code for this blog post can be found on GitHub at the companion code repository.
In this tutorial, I introduce Weaviate, an open-source vector database, with the thenlper/gte-base embedding model from Alibaba, through Hugging Face's transformers library.