100's of workflows

Enhance Customer Chat by Buffering Messages with Twilio and Redis

Integrations
If
No Operation, do nothing
Redis
Edit Fields (Set)
Twilio
Wait
Sticky Note
AI Agent
OpenAI Chat Model
Window Buffer Memory (easiest)
Chat Memory Manager
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This rantir workflow enhances chat UX by staggering an AI Agent's response for users who send multiple partial messages in quick succession, ensuring a smooth conversation experience.

How it works

       
  • A Twilio webhook captures incoming messages from the user, storing each in a Redis-powered message stack.
  •    
  • Execution pauses for 5 seconds, then checks the message stack for any recent messages.
  •    
  • This check determines if the user is still sending messages or is awaiting a response.
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  • If a new message appears in the stack within the pause, execution is aborted to wait for the user to finish; otherwise, it continues.
  •    
  • When the user stops sending messages, the buffered messages are sent to the AI Agent, enabling it to craft a single comprehensive reply.

Requirements

       
  • A Twilio account with an SMS-enabled phone number for message reception.
  •    
  • A Redis instance to manage the message stack.
  •    
  • An OpenAI account to access the language model.

Customizing the workflow

This workflow can also be adapted for other messaging platforms like WhatsApp and Telegram.

Adjust the 5-second delay to optimize the response time based on user interaction patterns.

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