Trusted by WordPress agencies and developers for its:
Fast and relevant on sites with hundreds of thousands of products and posts.
WPSolr is the WordPress site search plugin that is compatible with the most searches. Tired of your current search engine, switch to another one in 30 minutes or less.
Automatically index post types, taxonomies, custom fields, images, Pdf files and any other type of WordPress data.
WPSolr has included dozens of extensions, filters, actions and options to adapt to all situations.
Keyword search is the most simple and least intensive form of search. Most of the traditional keyword search engines are based on the Apache Lucene library. These search engines will try to match the words in the query to words in the indexed documents.
Semantic search, or vector search, is a more intensive form of search that uses AI to understand the context and intent of the sentences or words in the query and tries to find the most relevant results based on the aforementioned context, not the literal matches of the words.
Image search allows you to use the power of AI to return items based on the image’s content that matches the text in the search queries.
The user asks a question and will receive a generated text based on the relevent indexed documents or data.
Searching with 100 languages is no longer a dream. With AI you can now send queries in spanish or french and return relevant english objects.
Personalized search is a type of search that leverages AI to analyze individual users’ actions on your website to surface the most relevant content to them, whether they search or navigate.
Recommendations can increase CTR by up to 70%
Send user events to get accurate suggestions personalized for each visitor
Choose recommendation models like similar items, most trendy, best seller, bought with …
Concepts The traditional boolean operators are AND or NOT are very effective when programming or doing SQL requests but are not as good for search relevancy. The Apache Lucene
WordPress common security vulnerabilities When trying to setup the perfect experience for your users, create a plugin or a theme, you could need to write code. Here are the common
Have you ever wondered how search engines and libraries like Lucene, Solr and Elasticsearch work? They use inverted indexes which are faster and more efficient than forward indexes since the
Have you tried GenerateBlocks? Recently started new website creation projects so I thought I would try out WordPress pagebuilders other than good old Elementor. Somebody suggested Generateblocks and thought I
How does the default WordPress search works ? Learn how the default WordPress search works. Why it’s making lose money It works by sending a basic SQL query to the
Have you have installed your search engine like Elasticsearch, Opensearch or Apache Solr but found the results unsatisfying. It seems just setting up your search is not enough, you could optimize
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
Qdrant is a vector database & vector similarity search engine. You can import your own data into Qdrant to be used but first you need to create the embeddings. I have
RAG sends the retrieved information to a generative model to construct a specific response. A typical example is an SEO consultant summarizing documents relating to a common topic. But let’s
WooCommerce & WordPress search is such an underrated topic for successful projects, and for good reasons. Indeed, many agencies and site owners wonder if a scalable and precise search worth
Announcing new wpsolr.com docker search demos for OpenSearch Project, Elastic #Elasticsearch, The Apache Software Foundation #Solr, Vespa.ai, Weaviate. — Why? — Testing WooCommerce with any search engine can be challenging. — Docker to the rescue — Being able to pull a
Announcing new wpsolr.com series of self-signed certificate tutorials for OpenSearch Project, Elasticsearch, Apache Solr, Vespa.ai, Weaviate. Docker and Kubernetes. Because installing security on your self-hosted search engine should not be a daunting task.
Including: – Elastic Elasticsearch – The Apache Software Foundation Solr – OpenSearch Project Opensearch – Algolia – Weaviate – Vespa.ai
Each new WPSOLR release is tested with SearchStax to guarantee a perfect continuation of service. You can try the demo for Searchstax with WooCommerce on Cloudways: https://lnkd.in/dPVxZ5QK Or read the documentation for Searchstax with wpsolr.com: https://lnkd.in/dpZ5pJ3H
Check now some WooCommerce semantic search demos with Weaviate https://lnkd.in/dzucnPtZ
Videos tutorials Coming soon… This guide shows how to install the Weaviate vector database using Docker compose with any vectorizing model you want. It will
Videos tutorials Coming soon… Requirements You will also need the ingest attachments plugin if you need to search files. Learn how to install and configure opensearch in
1. GPT4All module Weaviate text2vec-gpt4all use GPT4All, which supports generating high quality embeddings of arbitrary length documents of text using a CPU optimized contrastively trained Sentence Transformer. Create a docker
1. Reranker – Transformers module The Reranker – Transformers is a Weaviate module for reranking search results. It uses the cross-encoder sentence transformers to reorder results with a powerful semantic
1. Reranker – Cohere module The Reranker – Cohere is a Weaviate module for reranking search results. It uses The Cohere Rerank API to reorder results with a powerful semantic
1. Google PaLM vectorizer Google PaLM vectorizer uses the Google PaLM API to create Embeddings (vectors) from data. Vectorizing from large language models is CPU intensive, often requires GPUs,
1. Hybrid search With all Weaviate vectorizers (including CLIP image search), you can also perform an hybrid search to get both precision (only relevant results first) and recall (all relevant
1. Question Answering module The Question and Answer (Q&A) module is a Weaviate module for answer extraction from data. It uses BERT-related models for finding and extracting answers. During the
1. Cohere vectorizer Cohere vectorizer uses the Cohere API to create Embeddings (vectors) from data. Vectorizing from large language models is CPU intensive, often requires GPUs, and can be very
1. OpenAI vectorizer OpenAI vectorizer uses the OpenAI API to create Embeddings (vectors) from data. Vectorizing from large language models is CPU intensive, often requires GPUs, and can be very
1. HuggingFace vectorizer HuggingFace vectorizer uses the HuggingFace API to vectorize data. Vectorizing from transformers models is CPU intensive, often requires GPUs, and can be very ineffective without proper optimisations.
1. CLIP vectorizer CLIP vectorizer use CLIP models that can retrieve text and images from text queries. Create a docker compose file from Weaviate wizzard : select the CLIP
1. Transformers module Transformers vectorizer use models children of the “BERT” model brought by Google, which led to the current machine learning/artificial intelligence revolution. Create a docker compose file
From WPSOLR 22.3. You will learn how to create a Weaviate index for WordPress and WooCommerce with a few clicks. 1 – What is Weaviate search? “Weaviate is a
Setup WPSOLR and Google Retail search From WPSOLR 22.6. You will learn how to create a Google Retail search API index for WooCommerce with a few clicks.
