Automated WhatsApp Chatbot with Document Retrieval and AI Responses

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This n8n workflow creates an intelligent WhatsApp-based AI chatbot that can handle both document uploads and user queries intelligently. When a message is received, it detects whether the message contains a document or a question. For documents, the workflow downloads the file, converts it to text, generates embeddings using OpenAI, and stores them in Supabase for future retrieval. If the message is a query, the workflow converts the query into embeddings, searches for relevant context within the stored documents, and leverages Google Gemini 2.5 Flash to generate a concise, context-aware reply. The final response is sent back to the user via WhatsApp. This setup is ideal for building knowledge bases, FAQ bots, or customer support assistants that leverage document processing and AI for intelligent interactions.

Node Count

11 – 20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.vectorStoreSupabase, httpRequest, stickyNote, switch, whatsApp, whatsAppTrigger

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