Quick overview
This workflow turns a WhatsApp Business number into a multimodal assistant by handling text, voice notes, images, and videos, using OpenAI (GPT-5 for chat/vision and audio transcription) plus Google Gemini for video understanding, and replying back on WhatsApp with per-user conversation memory and Wikipedia lookups.
How it works
- Triggers on incoming WhatsApp messages and splits the payload to process each message individually.
- Captures sender details and shared configuration (models, memory window, system prompt, and reply length) and routes the message based on whether it is text, audio, image, or video.
- For voice notes, it fetches the media from WhatsApp, downloads the audio file, and transcribes it with OpenAI.
- For images and videos, it fetches and downloads the media from WhatsApp, then describes images with OpenAI vision and describes/transcribes videos with Google Gemini.
- Normalizes the resulting text (original text or media description) along with any caption and the sender phone number into a single message format.
- Uses an OpenAI-powered agent with per-sender conversation memory and a Wikipedia tool to generate a concise reply in the user’s language.
- Cleans and truncates the reply for WhatsApp-friendly formatting and sends it back to the original sender via WhatsApp.
Setup
- Connect WhatsApp Business Cloud credentials for both the WhatsApp Trigger and WhatsApp nodes, then select your WhatsApp Business phone number ID in the send-reply step.
- Add an OpenAI API credential for chat, image understanding (vision), and audio transcription.
- Add a Google Gemini (PaLM) API credential for the video description request.
- Review the Configuration values (models, system prompt, memory context window, and max reply length) to match your needs before activating the workflow.
Additional info
Build a multimodal AI assistant on WhatsApp with GPT-5 and Gemini
Need help customizing?
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