This n8n workflow automates the process of handling various media messages received via WhatsApp, such as audio, video, and images, and generates intelligent responses using AI. It starts with a WhatsApp trigger that detects incoming messages, then splits and categorizes them based on their media type through a switch node. Media URLs are fetched and downloaded, allowing AI models to transcribe audio, describe videos, and analyze images for contextual understanding. Additionally, the workflow uses large language models (Google Gemini) to summarize text and extract information, which is fed into an AI agent that formulates a response. Finally, the system replies back to the WhatsApp user, making it a powerful tool for creating intelligent chatbots capable of supporting customer service, information retrieval, and multimedia content processing.
WhatsApp Media Handling & Automated Response Workflow
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.toolWikipedia, httpRequest, set, splitOut, stickyNote, switch, wait, whatsApp, whatsAppTrigger |
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