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It looks impossible at first sight. You will have to: – Install each search engine server – Create each index with the right schema –

Description: – WooCommerce with the Flatsome theme are hosted on Cloudways – WPSOLR plugin is installed and configured – Weaviate is installed on a Google Cloud Kubernetes cluster https://weaviate.io/developers/weaviate/installation/kubernetes/ – The

Description: – WooCommerce with the Flatsome theme are hosted on Cloudways – WPSOLR plugin is installed and configured – Weaviate is installed on a Google Cloud Kubernetes cluster https://weaviate.io/developers/weaviate/installation/kubernetes/ – The

The problem: SBERT models https://www.sbert.net/ are trained to build a similarity embedding between a query and a passage. The problem is that queries and passages are

Demo link: https://demo-woocommerce-flatsome-cloudways-2k-openai.wpsolr.com/shop/   Description: – WooCommerce with the Flatsome theme are hosted on Cloudways – WPSOLR plugin is installed and configured – Weaviate is installed on a Google Cloud

– Classical search – Anything around BM25 statistical scoring. Including #elasticsearch , Apache #solr, Algolia, and WPSOLR https://www.wpsolr.com. – Classical search AI augmented – Still the classical engines, but with

You do not have to wonder or spend weeks prototyping anymore. With WPSOLR ‘s SeMI Technologies Weaviate integration, you can just: – Install docker Weaviate locally with

And a big motivation to add a thin layer of fine-tuning (labeling?) to #wpsolr‘s WooCommerce SeMI Technologies search integration ! It’s pretty straightforward with OpenAI

WPSOLR documentation: https://www.wpsolr.com/guide/configuration-step-by-step-schematic/configure-your-indexes/create-a-google-retail-index/ #wpsolr #woocommerce #retail # search #retailsearch

Modules already supported, with full WooCommerce integration (suggestions, facets, filters, pagination, sort, …): – Weaviate Transformers module – Weaviate CLIP module – Weaviate Hugging Face

(And they are also the two OSS vector search databases supporting aggregation, which make them to my opinion the best contenders for e-commerce vector search)

SeMI Technologies released Weaviate v 1.17.0 with a new hybrid search, and an alpha setting to set how much search is pure dense/vector or pure