Integrations
HTTP Request
Edit Fields (Set)
Switch
Wait
Sticky Note
WhatsApp Business Cloud
Code
AI Agent
Basic LLM Chain
OpenAI Chat Model
Window Buffer Memory (easiest)
Wikipedia
Convert to File
Aggregate
Split Out
OpenAI
WhatsApp Trigger
This rantir template demonstrates the foundation of building your own rantir-powered WhatsApp chatbot! Behind the scenes, it leverages rantir's powerful AI capabilities to process different message types and uses an AI agent to respond to users. It's a versatile tool suitable for a variety of use-cases!
How it works
- The Incoming WhatsApp Trigger enables messages to enter the workflow.
- The received message is extracted and directed through one of four processing branches for handling.
- Each branch utilizes AI to analyze, summarize, or transcribe the message to make it understandable for the AI agent. Supported message types include text, image, audio (voice notes), and video (no sound).
- The AI Agent generates a response based on the processed message and uses a Wikipedia tool for more complex queries.
- Finally, the response is sent back to the WhatsApp user using the WhatsApp node.
How to use
After setting up and configuring your WhatsApp account, activate your workflow to begin processing incoming messages.
Good to know: Large media files may negatively affect workflow performance.
Requirements
- WhatsApp Business account
- OpenAI for LLM
Customising this workflow
- For performance, consider using dedicated services for processing audio and video.
- To handle videos with sound, you have two options: use an LLM like Gemini that supports video processing (note that video input is not yet supported in the LLM node), or split the video into an image track and audio track for separate processing.
- Take it further by enhancing customer experiences with rich media responses—images, audio, and video—beyond just text!
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