This n8n workflow automates the process of handling chat messages, analyzing user input, and generating relevant WordPress post suggestions. It starts with a webhook trigger that receives chat messages and uses multiple AI-powered nodes to classify, process, and understand user intent. The workflow includes modules for keyword extraction, article search, and content retrieval, leveraging LangChain’s language models and agents to produce tailored article recommendations. It also features steps for parsing structured data, querying specific WordPress posts, and enriching responses. This setup is ideal for creating an interactive chatbot that offers personalized content suggestions, enhances website engagement, and streamlines content curation workflows.
Automated WordPress Post Recommendations via Chatbot
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainRetrievalQa, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatMistralCloud, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.memoryManager, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.retrieverWorkflow, @n8n/n8n-nodes-langchain.textClassifier, @n8n/n8n-nodes-langchain.toolWorkflow, aggregate, code, executeWorkflow, executeWorkflowTrigger, executionData, httpRequest, respondToWebhook, set, splitOut, stickyNote, switch |
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