Empower Your Website with AI-Powered Search and Chat
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Seamlessly integrate Retrieval-Augmented Generation (RAG) and Generative AI into your WordPress site. This workflow enables your website to intelligently answer user questions based on its content, leveraging advanced embeddings and chat models.
About This Workflow
This n8n workflow transforms your WordPress content into a knowledge base for an AI-powered application. It leverages the power of Langchain to process your website's data, create embeddings, and enable intelligent conversational interactions. The workflow first fetches content from your WordPress site, converts it into a format suitable for AI processing, and then generates embeddings using OpenAI. These embeddings are stored and used to provide contextually relevant answers to user queries. It also incorporates chat memory to maintain conversation history, ensuring a natural and engaging user experience. Finally, it responds to webhook requests, making it ready to be integrated into your application.
Key Features
- Intelligent Content Understanding: Utilizes RAG to understand and retrieve information from your WordPress posts and pages.
- AI-Powered Q&A: Enables users to ask questions and receive accurate, context-aware answers powered by advanced LLMs.
- Seamless Integration: Designed to be easily integrated with your existing WordPress setup via webhooks.
- Persistent Chat Memory: Maintains conversation context for a more fluid and personalized user experience.
- Customizable Embeddings: Leverages OpenAI embeddings to create a rich semantic understanding of your content.
How To Use
- Trigger Setup: Configure the 'When clicking ‘Test workflow’' node to initiate the workflow.
- Content Ingestion: Use the 'Default Data Loader' and 'Embeddings OpenAI' nodes to process and embed your WordPress content. Ensure your JSON data includes fields like
title,url,content_type,publication_date,modification_date, andid. - Text Splitting: Employ the 'Token Splitter' node to segment your content into manageable chunks for embedding.
- AI Model Configuration: Set up the 'OpenAI Chat Model' with your preferred model (e.g.,
gpt-4o-mini). - Chat Memory: Configure the 'Postgres Chat Memory' node to store and retrieve conversation history, specifying your
tableName. - Data Preparation for Response: Utilize the 'Set fields' node to format the retrieved documents and extract necessary session and chat input data.
- Webhook Integration: Connect the 'Respond to Webhook' node to send AI-generated responses back to your application.
- Data Fetching (Optional): The 'Postgres' node can be used to fetch the last workflow execution timestamp for tracking purposes.
- Markdown Conversion (Optional): The 'Markdown' node can be used to convert fetched content to Markdown if needed.
Apps Used
Workflow JSON
{
"id": "6a1217af-07e2-4786-a258-b0ba20aae46b",
"name": "Empower Your Website with AI-Powered Search and Chat",
"nodes": 28,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 6a1217af-07e2...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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