This n8n workflow automates the process of creating, updating, and utilizing content embeddings from a WordPress website to enhance AI-driven interactions. Triggered manually or periodically, it extracts posts and pages, filters for published and unprotected content, converts HTML to Markdown, and stores the processed data in a vector database via Supabase. It also generates embeddings using OpenAI’s models and maintains history logs. The setup enables real-time or scheduled updates of website content, facilitating AI-powered chatbots and content retrieval applications. Practical use cases include site content management, AI chat support, and dynamic content search enhancement.
Automated WordPress Content & Embedding Management Workflow
| Node Count | >20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryPostgresChat, @n8n/n8n-nodes-langchain.textSplitterTokenSplitter, @n8n/n8n-nodes-langchain.vectorStoreSupabase, aggregate, filter, httpRequest, manualTrigger, markdown, merge, postgres, respondToWebhook, scheduleTrigger, set, splitInBatches, stickyNote, supabase, switch, wordpress |
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