This workflow creates an AI-powered WhatsApp chatbot designed to handle diverse media messages and provide context-aware responses. It integrates with Google Docs to import product documentation, indexes content into MongoDB with vector embeddings for fast semantic search, and uses OpenAI GPT-4 to generate intelligent replies. When a user sends a message via WhatsApp, the workflow classifies the message type (text, audio, image, document), fetches relevant media or documents, and utilizes language models for translation, analysis, or response generation. The system maintains conversational memory to deliver accurate, personalized interactions. Practical applications include customer support, technical documentation retrieval, and interactive FAQ sessions through WhatsApp.

Node Count

>20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.openAi, @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter, @n8n/n8n-nodes-langchain.vectorStoreMongoDBAtlas, code, extractFromFile, googleDocs, httpRequest, manualTrigger, set, stickyNote, switch, whatsApp, whatsAppTrigger