đź’¬ Building your first WhatsApp chatbot
⚡ 474,783 views · 💬 Lead Nurturing & AI Sales Agents
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.
đź”— Nodes Used
HTTP Request, WhatsApp Business Cloud, AI Agent, Embeddings OpenAI, OpenAI Chat Model, Simple Memory
đź“Ą Import
Download workflow.json and import into n8n:
Workflow menu → Import from File