n8n AI Customer Support Business Intelligence
Contributed by Sabrina Ramonov 🍄. From the community directory at agents.sabrina.dev, republished with permission and full credit.
The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot.
How it works:Webhook Setup: The workflow begins by setting up webhooks for verification and response. The Verify webhook receives GET requests and sends back a verification code, while the Respond webhook handles incoming POST requests from Meta regarding WhatsApp messages.
Message Handling: Once a message is received, the workflow checks if the incoming JSON contains a user message. If it does, the message is processed further; otherwise, a generic response is sent.
AI Agent Interaction: The user's message is passed to the AI Agent node, which uses a conversational agent with a predefined system message tailored for an electronics store. This ensures that the AI provides accurate and professional responses based on the knowledge base.
Knowledge Base Utilization: The AI Agent references a knowledge base stored in Qdrant, a vector database. Documents from Google Drive are downloaded, vectorized using OpenAI embeddings, and stored in Qdrant for retrieval during conversations.
Response Generation: The AI Agent generates a response using the OpenAI chat model (gpt-4o-mini) and sends it back to the user via WhatsApp.
Set up steps:
1. Create Qdrant Collection:
- Update the QDRANTURL and COLLECTION variables in the workflow.
- Use the Create collection HTTP request node to initialize the collection in Qdrant.
2. Vectorize Documents:
- Configure the Get folder and Download Files nodes to fetch documents from a specified Google Drive folder.
- Use the Embeddings OpenAI node to generate embeddings for the downloaded files.
- Store the vectorized documents in Qdrant using the Qdrant Vector Store node.
3. Configure Webhooks:
- Ensure both Verify and Respond webhooks have the same URL.
- Set the Verify webhook to use the GET HTTP method and the Respond webhook to use the POST HTTP method.
4. Set Up AI Agent:
- Define the system prompt for the AI Agent, specifying guidelines for product information, technical support, customer service, and knowledge base usage.
- Link the AI Agent to the OpenAI chat model and configure any additional tools as needed.
5. Test Workflow:
- Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all components are functioning correctly.
- Monitor the flow of data through the nodes and verify that responses are being generated and sent accurately.
By following these steps, the workflow will be fully operational, enabling a robust AI-powered chatbot capable of handling customer inquiries via WhatsApp.
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Tools used: OpenAI, Qdrant, Google Drive
Download the workflow template (JSON)
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