Building Your First WhatsApp Chatbot

Description

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.