{"id":10974,"date":"2026-05-23T19:30:06","date_gmt":"2026-05-23T11:30:06","guid":{"rendered":"https:\/\/aeosub.com\/vecpost\/"},"modified":"2026-05-23T19:30:06","modified_gmt":"2026-05-23T11:30:06","slug":"vecpost","status":"publish","type":"post","link":"https:\/\/aeosub.com\/zh\/vecpost\/","title":{"rendered":"VecPost AI Search for Posts"},"content":{"rendered":"
\n\n\n\n\n\n\n\n
Developer<\/th>\nkrunalbalas<\/a><\/td>\n<\/tr>\n
Version<\/th>\nv1.0.0<\/td>\n<\/tr>\n
Active Installs<\/th>\n0 +<\/td>\n<\/tr>\n
Requires \/ Tested<\/th>\n6.1 \/ 6.9.4<\/td>\n<\/tr>\n
Last Updated<\/th>\n2026-05-23 10:33am GMT<\/td>\n<\/tr>\n
Official Link<\/th>\nView Details \u2192<\/a><\/td>\n<\/tr>\n<\/table><\/div>\n
AI-powered semantic search for WordPress posts. Understands meaning, not just keywords. Powered by OpenAI or Google Gemini.<\/div>\n

VecPost AI Search for Posts replaces WordPress’s default SQL LIKE search with vector-based semantic search. Instead of matching exact words, it understands the meaning<\/em> of a search query.<\/p>\n

Example:<\/strong> A user searching “heart workouts” will find your post titled “Best cardiovascular exercises” – even though no words overlap – because the meanings are similar.<\/p>\n

How It Works<\/h4>\n
    \n
  1. When you publish a post, the plugin sends its content to your chosen AI provider (OpenAI or Google Gemini) to generate a vector embedding – a list of numbers that represents the meaning of the text.<\/li>\n
  2. These numbers are stored in your database.<\/li>\n
  3. When a user searches, their query is also converted to numbers, and the plugin finds posts whose numbers are closest – meaning most semantically similar.<\/li>\n<\/ol>\n

    Features<\/h4>\n
      \n
    • Semantic search powered by OpenAI (text-embedding-3-small<\/code> or text-embedding-3-large<\/code>) or Google Gemini (gemini-embedding-001<\/code>)<\/li>\n
    • Hybrid re-ranking: combines semantic similarity with keyword matching for best results<\/li>\n
    • Gutenberg block and shortcode [vecpost_semantic_search]<\/code> for easy placement<\/li>\n
    • Bulk indexer with progress bar for existing posts<\/li>\n
    • WP-CLI support: wp vecpost-semantic-search index<\/code>, wp vecpost-semantic-search status<\/code>, wp vecpost-semantic-search search \"query\"<\/code><\/li>\n
    • Configurable scoring thresholds via Settings -> VecPost – AI Semantic Search for Posts<\/li>\n
    • Automatic re-indexing when you switch embedding models<\/li>\n
    • Results cached via WordPress object cache (Redis\/Memcached compatible)<\/li>\n<\/ul>\n

      Third-Party Services<\/h4>\n

      This plugin sends post content to external AI APIs to generate embeddings. By using this plugin, you agree to the terms of service and privacy policies of your chosen provider:<\/p>\n

        \n
      • OpenAI:<\/strong> https:\/\/openai.com\/policies\/privacy-policy | https:\/\/openai.com\/policies\/terms-of-use<\/li>\n
      • Google Gemini:<\/strong> https:\/\/policies.google.com\/privacy | https:\/\/ai.google.dev\/terms<\/li>\n<\/ul>\n

        No data is sent without your API key being configured. Data is only transmitted when posts are published or during bulk indexing.<\/p>\n

        Performance Note<\/h4>\n

        Semantic search requires loading all embeddings into PHP memory for comparison. This works well for sites with up to approximately 1,500 posts. For larger sites, a dedicated vector database (pgvector, Qdrant, or Pinecone) is recommended.<\/p>\n","protected":false},"excerpt":{"rendered":"

        AI-powered semantic search for WordPress posts. Understands meaning, not just keywords. Powered by OpenAI or Google Gemini.<\/p>","protected":false},"author":1,"featured_media":9317,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[252],"tags":[821,1854,558,1855,1856,555],"class_list":["post-10974","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-trends","tag-ai-search","tag-embeddings","tag-openai","tag-search","tag-semantic-search","tag-wordpress-plugin"],"_links":{"self":[{"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/posts\/10974","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/comments?post=10974"}],"version-history":[{"count":0,"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/posts\/10974\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/media\/9317"}],"wp:attachment":[{"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/media?parent=10974"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/categories?post=10974"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aeosub.com\/zh\/wp-json\/wp\/v2\/tags?post=10974"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}