How to use Weaviate to store and query vector embeddings

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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"

  • 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.

  • 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​.

  • 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.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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