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.

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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.

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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.