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.