WordPress RAG & GenAI App with Content Chat
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Automate the creation of embeddings for your WordPress content, enabling a RAG-based Generative AI application. This workflow supports chat functionality for enhanced user experience on your website.
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About This Workflow
Overview
This n8n workflow empowers you to build a Retrieval Augmented Generation (RAG) and Generative AI (GenAI) application powered by your WordPress website's content. It automates the process of fetching WordPress posts and pages, converting them into embeddings using OpenAI, and preparing them for use in a conversational AI model. The workflow is structured into three main conceptual parts: initial embedding creation, upserting embeddings into a vector store (implicitly handled by Langchain components), and enabling chat functionality using OpenAI chat models and PostgreSQL for chat history.
This is particularly useful for building intelligent chatbots, search functionalities, or content summarization tools that directly leverage your website's data, ensuring the AI provides accurate and contextually relevant responses based on your published content.
Key Features
- Fetches all posts and pages from a WordPress site.
- Generates embeddings for content using OpenAI's models.
- Splits text content into manageable chunks for embedding.
- Supports storing and retrieving chat history using PostgreSQL.
- Enables real-time chat interactions powered by OpenAI's chat models.
How To Use
- Configure WordPress Nodes: Set up the
WordPress - Get all postsandWordPress - Get all pagesnodes with your WordPress site's credentials. - Configure OpenAI Nodes: Set up the
Embeddings OpenAInodes with your OpenAI API key and desired embedding model (e.g.,text-embedding-3-small). - Configure Chat Nodes: Set up the
OpenAI Chat Modelwith your preferred model (e.g.,gpt-4o-mini) and thePostgres Chat Memorynode with your PostgreSQL connection details and table name. - Set up Trigger: Use a
When clicking ‘Test workflow’or a webhook trigger to initiate the embedding process or chat interaction. - Process Content: The
Default Data LoaderandToken Splitternodes handle the preparation of your WordPress content for embedding. - Manage Chat History: The
Postgres Chat Memorynode ensures that chat conversations are persisted and can be recalled for context. - Respond to User: The
Respond to Webhooknode (if using a webhook trigger) sends the AI's response back to the user.
Apps Used
Workflow JSON
{
"id": "3388cb86-7663-4962-ae4f-2d59c619a21e",
"name": "WordPress RAG & GenAI App with Content Chat",
"nodes": 0,
"category": "WordPress Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 3388cb86-7663...
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