But while vector search is, while embeddings are, sometimes the full integration is not …
Let’s face it, most e-commerce demos start with some notebook python code to:
– Load data
– Tweak some parameters, like vocabulary size and tokenizer types
– Download and call embedding models
– Store vectors in the vector database
After that, you’ll have to build the code to replace your actual E-Commerce SQL search with the vector search.
But how to:
– Build facets and filters ?
– Index your data in real-time, as soon as your data is updated ?
– Re-index all your data in batches, from time to time ?
– Monitor your conversion rates ?
– Compare search results from several search engines ?
– Display suggestions ?
Previously, the vector search was the bottom of the iceberg.
Nowadays, vector search is mainstream enough to build nice toy demos.
What is now often missing is the whole plug & play framework for your specific E-Commerce platform.
Something like WPSOLR: a plugin to manage all the complexity of integrating a vector database like Weaviate in your WooCommerce search.