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.
# n8n WhatsApp Chatbot with AI Agent and Document Q&A
This n8n workflow demonstrates how to build an intelligent WhatsApp chatbot capable of answering questions based on a provided document, leveraging n8n's AI Agent capabilities. It simplifies the process of creating a conversational AI that can interact with users on WhatsApp and retrieve information from a knowledge base.
## What it does
This workflow automates the following steps:
1. **Listens for WhatsApp messages**: Triggers whenever a new message is received on a configured WhatsApp Business Cloud account.
2. **Initializes AI Components (Manual Trigger)**: A manual trigger is used to set up the AI agent's knowledge base.
* **Extracts content from a file**: Reads and processes a document (e.g., a PDF or text file) to extract its content.
* **Loads document data**: Prepares the extracted document content for AI processing.
* **Splits text into chunks**: Breaks down the document into smaller, manageable pieces for efficient embedding and retrieval.
* **Creates embeddings**: Converts the text chunks into numerical vector representations using OpenAI's embedding model.
* **Stores embeddings in a vector store**: Saves these embeddings in a simple in-memory vector store, creating a searchable knowledge base.
* **Configures a Vector Store Question Answer Tool**: Defines a tool that the AI agent can use to query the vector store for answers.
3. **Processes WhatsApp messages with an AI Agent**:
* **Initializes a Simple Memory**: Maintains conversational context for the AI agent.
* **Uses an OpenAI Chat Model**: The core language model for generating responses.
* **Leverages the Vector Store Question Answer Tool**: The AI agent uses this tool to find answers to user questions within the pre-loaded document.
* **Generates a response**: The AI agent formulates a relevant answer based on the conversation and the document content.
4. **Sends WhatsApp response**: Sends the AI-generated answer back to the user via WhatsApp.
## Prerequisites/Requirements
To use this workflow, you will need:
* **n8n instance**: A running n8n instance (self-hosted or n8n Cloud).
* **WhatsApp Business Cloud Account**: Configured with n8n credentials to send and receive messages.
* **OpenAI API Key**: For the Embeddings OpenAI and OpenAI Chat Model nodes.
* **A document file**: The knowledge base (e.g., a PDF, TXT, or similar) that the AI agent will use to answer questions. This file needs to be uploaded to the "Extract from File" node.
## Setup/Usage
1. **Import the workflow**: Download the JSON provided and import it into your n8n instance.
2. **Configure WhatsApp Credentials**:
* In the "WhatsApp Trigger" node, select or create your WhatsApp Business Cloud credential.
* In the "WhatsApp Business Cloud" node, select or create your WhatsApp Business Cloud credential.
3. **Configure OpenAI Credentials**:
* In the "Embeddings OpenAI" node, select or create your OpenAI API credential.
* In the "OpenAI Chat Model" node, select or create your OpenAI API credential.
4. **Upload your document**:
* In the "Extract from File" node, upload the document you want your chatbot to answer questions from.
5. **Initialize the AI Knowledge Base**:
* Click the "Execute Workflow" button on the "When clicking ‘Execute workflow’" (Manual Trigger) node. This will process your document and set up the vector store. **This step only needs to be done once or whenever your document changes.**
6. **Activate the WhatsApp Trigger**:
* Ensure the "WhatsApp Trigger" node is active (toggle it on) to start listening for incoming messages.
7. **Test the chatbot**: Send a message to your WhatsApp Business number and ask a question related to the content of your uploaded document.
The chatbot will then process your message, consult the document via the AI agent, and respond with an answer.
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