Connects the site to a Milvus vector database for AI Search. Milvus can run inside the same DDEV project, on Zilliz Cloud, or on a server of your own. The recipe is the same for all three; only the server, port and token change.
Uses MariaDB's built-in vector type as the vector database for AI Search. The vectors live in the site's own database, with no extra service to run. A separate MariaDB server also works, set in settings.php.
Gives a site a vector index of its own content, so AI features can find pages by meaning rather than by keyword. It is the retrieval layer that Varbase AI Chatbot Base and Varbase AI Answers Base answer from.
The recipe applies Varbase Search Base, adds a search_index display per content type, and creates the content_vector Search API server and index on the site's default vector database. It holds every published node and Canvas page, in all languages, and content is indexed again on save and on cron.
I’m a frontend engineer who enjoys designing and building online stores. I’m developing this open-source Drupal theme based on the visual design of Cherker, an India-based e-commerce business that sells sea buckthorn products and tea.
Cherker’s live store currently runs on Shopify. This project is a separate Drupal implementation for people who want to build a similar kind of storefront with Drupal.
Menu Placement replaces the menu settings of the content edit form with a widget that places content in one or more menus at once, each with its own link title and position.
