Building Your First WhatsApp Chatbot

This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's 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 HTTP request node and its text contents extracted.
• The text contents are then uploaded to the in-memory vector store to build a knowledgebase 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 catalogue 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 setup 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 datasource and behaviour as required.

Requirements

• WhatsApp Business Account
• OpenAI for LLM

Customising this workflow

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