WordPress Semantic Search with RAG: Turning Research into a Plugin
In this video, I extend the RAG project into a concrete product: a semantic search engine integrated into WordPress via a custom plugin, fully built with Claude Code.
Instead of limiting the RAG to a chatbot, I reuse its research corpus to create a powerful semantic search layer on top of WordPress content.
The idea is simple:
– Extract and structure the RAG knowledge base
– Index it using embeddings
– Enable semantic search directly inside WordPress
A practical use case:
An HR Director filtering CVs against job descriptions using semantic matching instead of keyword search.
In my case, I apply it to content and articles, enhancing WordPress native search with AI-driven relevance.
This video covers:
– Extracting the RAG corpus
– Designing a semantic search pipeline
– Building a WordPress plugin powered by embeddings
– Extending WordPress search capabilities with AI
This demonstrates how a RAG project can evolve into multiple usable products beyond chat.
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Tag(s) : AI, AI-generated, Anaconda
Categorie(s) : Agile, AI, AI tools, Anaconda, API