This n8n template builds a simple WhatsApp chatbot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer users’ questions. This template is intended to help introduce n8n users interested in building with WhatsApp.

How it works

This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot. A product brochure is imported via the HTTP request node and its text contents extracted.

The text contents are then uploaded to the in-memory vector store to build a knowledge base for the chatbot. A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out. The customer’s message is sent to the AI Agent, which queries the product catalog using the vector store tool. The Agent’s response is sent back to the user via the WhatsApp node.

How to use

Once you’ve set up and configured your WhatsApp account and credentials, first populate the vector store by clicking the “Test Workflow” button. Next, activate the workflow to enable the WhatsApp chatbot. Message your designated WhatsApp number and you should receive a message from the AI sales agent. Tweak the data source and behavior as required.

Requirements

– WhatsApp Business Account
– OpenAI for LLM

Customizing this workflow

– Upgrade the vector store to Qdrant for persistence and production use-cases.
– Handle different WhatsApp message types for a more rich and engaging experience for customers.