Drupal and RAG: AI Chatbot Demonstration Highlights Semantic Search

AI hand illustration

At DrupalCon Barcelona, the potential of Drupal AI integrations took center stage. Inspired by these advancements, Brainsum recreated a use case for a RAG (Retrieval-Augmented Generation) chatbot, writes Peter Pónya, CTO of the organization. This AI-driven chatbot enables semantic search, leveraging a vector database to index website content for accurate query handling.

Key features include typo recognition and recipe suggestions beyond the indexed database. For instance, the chatbot identifies "dairy-free" despite a typo like "diary." It can also suggest meals using unindexed ingredients or offer vegan and vegetarian options.

The system combines Drupal CMS for content management, Milvus as the vector database, and OpenAI's LLM for natural language processing. It supports full self-hosting and customizable behaviour, ensuring privacy and flexibility. Drupal modules like AI Core, AI Search, and AI Chatbot power the integration.

This innovative solution highlights the potential for leveraging AI within organizations using open-source tools.

Visit the demo site to explore more.

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