Unlock WordPress Intelligence with RAG & GenAI
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Leverage the power of Retrieval-Augmented Generation (RAG) and Generative AI to transform your WordPress content into an intelligent, conversational asset. This workflow allows you to ingest and process your website's data, making it accessible and actionable through AI.
About This Workflow
This n8n workflow empowers you to build sophisticated AI applications powered by your WordPress content. It utilizes LangChain's robust capabilities to process your website's data, create embeddings for efficient retrieval, and engage with users through a powerful chat interface. By integrating with OpenAI's cutting-edge language models and storing chat history in PostgreSQL, you can create dynamic Q&A systems, content summarizers, and much more, all directly from your WordPress site's information. The workflow intelligently handles data loading, text splitting, and embedding, ensuring your AI can accurately understand and respond to queries based on your specific content.
Key Features
- Intelligent Content Ingestion: Automatically loads and processes diverse WordPress content types.
- Advanced Text Splitting: Efficiently segments content for optimal AI processing with configurable chunk size and overlap.
- Powerful Embeddings: Leverages OpenAI's
text-embedding-3-smallfor rich semantic understanding of your content. - Conversational AI: Integrates with OpenAI's
gpt-4o-minifor dynamic and context-aware responses. - Persistent Chat History: Utilizes PostgreSQL to store and retrieve conversation history for a seamless user experience.
- Customizable Metadata: Enriches content with essential WordPress metadata like title, URL, publication date, and more.
How To Use
- Trigger Setup: Configure the
When clicking ‘Test workflow’node as your primary trigger for testing or initial setup. For live applications, consider integrating a webhook trigger. - Content Loading: Connect your WordPress content source to the
Default Data Loadernodes. Ensure your JSON data is correctly formatted and includes relevant metadata liketitle,url,content_type,publication_date,modification_date, andid. - Text Processing: Utilize the
Token Splitternodes to break down your content into manageable chunks for the AI. AdjustchunkSizeandchunkOverlapbased on your content and desired AI performance. - Embedding Generation: Connect the output of the
Token Splitterto theEmbeddings OpenAInodes. These nodes will convert your text chunks into numerical representations that AI models can understand. - AI Interaction: Configure the
OpenAI Chat Modelfor generating responses and thePostgres Chat Memoryto store conversation history. TheSet fieldsnode is crucial for formatting the input to the AI, including user queries and relevant document context. - Response Handling: The
Respond to Webhooknode is used to send the AI's generated response back to the user or calling application.
Apps Used
Workflow JSON
{
"id": "6737aa3f-449c-41b6-8e58-994dab1dd930",
"name": "Unlock WordPress Intelligence with RAG & GenAI",
"nodes": 17,
"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: 6737aa3f-449c...
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