Image search guides for WordPress & WooCommerce

Image search for WordPress & Woocommerce

Image search is becoming more and more common with the advent of AI. It is very useful for many purposes but one of the most important is e-commerce. Using image search, users can upload images to find products that closely resemble what they are looking for, yielding far better conversion rates than text-based search ever would. So what if you wanted to add image search to Woocommerce, the world’s leading solution when it comes to e-commerce platforms. Learn all there is to know about WordPress search by reading our guide. How does image search work ? You can’t add image search to your WordPress or Woocommerce using the default search. The default WordPress search uses basic SQL to search for matching items

WordPress search : Ultimate Guide for 2024

WordPress is the most widely used CMS and single handedly powers 40% of the web. If you haven’t tried it already, it is intuitive, powerful and if you use one of many hosting providers out there, you can easily set up a working website in minutes. But once you made all of your content, how do you ensure that your users can find it. For that, you need a good site search. Many types of search exist : keyword search, AI search, even personalized search. WordPress provides one by default, but it is incredibly slow and ineffective. This guide will go over the benefits of a fast and relevant search and how you could implement third party search engines easily into any WordPress or Woocommerce

Integrate Woocommerce with Algolia

Algolia is the most popular cloud search & recommendations provider. You could want to integrate it into your Woocommerce or WordPress website. Why use Algolia ? Search Algolia provides search of all kinds : simple keyword search, AI/vector search & personalized search. Keyword search is available in the free tier. Keyword search works by matching the keywords in a search query to the ones present in the indexed items/documents. It can be simple and limited without any configuration but Algolia offers multiple features to fine-tune it. For keyword search, you could define synonyms which is useful for expert websites. For example, if you have a medical website, you could need to set “acute myocardial infarction” as a synonym for heart attack.

How to use Weaviate with any Huggingface vectorization model

For more info about Weaviate, check out our documentation. If you’ve ever wanted to use Weaviate but were worried that you couldn’t use the most efficient or relevant vectorization model you want, I have just the thing for you. In this notebook/guide, I have detailed the different steps and code needed to setup Weaviate with any Huggingface vectorization model. TLDR Choose from a wide selection of Huggingface models using the official rankings page. Create your own transformers inference container to be used by Weaviate to vectorize the data. Learn how to add your chosen Huggingface model.. Startup the containers and create the class that will use your new vectorizer model. Send the data to the Weaviate that will now be automatically vectorized by the custom model.

How Weaviate is enhancing customer support with conversational AI

Introduction Customer support is a crucial aspect of any business, as it directly impacts customer satisfaction and loyalty. With the advancements in technology, businesses are now leveraging conversational AI to enhance their customer support services. Weaviate, an open-source knowledge graph tool, is playing a significant role in revolutionizing customer support through its robust conversational AI capabilities. Weaviate and Conversational AI Weaviate is a powerful, scalable, and flexible knowledge graph tool that allows businesses to analyze and understand their unstructured data effectively. It is specifically designed to provide machine learning capabilities and natural language processing (NLP) functionalities. These features enable Weaviate to process and understand human language, making it an ideal choice for conversational AI applications. With Weaviate, customer support can be revolutionized through the

What is Weaviate and how does it work?

Introduction In today’s digital era, data is the king, and as the volume of data grows, it becomes increasingly challenging to extract useful information from it. Weaviate is an open-source vector search engine that solves this problem by providing fast and efficient searches, allowing you to find and extract data easily. This post dives into what Weaviate is, how it works, and how it can help you. What is Weaviate? Weaviate is an open-source, decentralized, and cloud-native vector search engine that allows you to add vector-based search functionality to your application. It uses artificial intelligence and machine learning to enable fast and efficient searches that traditional databases cannot match. It is built to handle millions/billions of vectors. Weaviate allows you to store and search objects

A WooCommerce vector search live demo with Weaviate & CLIP (text & image) embeddings

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 data vectorization is performed by a CLIP model https://weaviate.io/developers/weaviate/modules/retriever-vectorizer-modules/multi2vec-clip/ – Search, filters, facets, sorting, and pagination are performed by query/data similarity within the Weaviate database Demo link: https://demo-woocommerce-flatsome-cloudways-2k-clip.wpsolr.com/shop/ WPSOLR: https://wpsolr.com #wpsolr #weaviate #woocommerce #vectorsearch #vectordatabase #clipmodel