This n8n workflow automates the processing of multimedia messages received via WhatsApp. It captures incoming messages, identifies message types (audio, video, image, or text), and then employs AI services to transcribe, describe, or summarize the content. The workflow uses multiple nodes: a WhatsApp trigger to receive messages, switch nodes to route message types, and specialized nodes to download media, transcribe audio, describe videos, and analyze images. Additionally, it integrates GPT-based AI models and Google’s Gemini for multimodal content analysis. The final step involves generating a natural language reply to the user, which can include factual information, summaries, or descriptions, then sends the response back through WhatsApp. This setup is ideal for building intelligent chatbots capable of handling diverse media inputs and providing meaningful interactions, such as customer support, information retrieval, or automated content analysis.
Automated WhatsApp Media Processing and AI 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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