Complete business WhatsApp AI-Powered RAG Chatbot using OpenAI

The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot.

How it works:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.