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Hi callin.io Community! Help a Newbie Create an AI Consultant with Message Accumulation

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dv.cherni
(@dv-cherni)
Posts: 1
New Member
Topic starter
 

Hello everyone! I'm developing an AI consultant within Telegram and have encountered a slight hurdle with the workflow implementation.

My Current Task: I need to collect user messages for approximately 10-15 seconds before forwarding them to the AI model. The goals are to:

  • Ensure comprehensive conversation context is gathered.
  • Decrease the frequency of API calls.
  • Enhance the quality of responses.

What I’ve Already Tried:

  • Utilized the Telegram Trigger.
  • Planned to use OpenAI/OpenRouter for generating responses.
  • Intend to implement temporary message storage within the workflow.

Questions for the Community:

  1. What is the recommended method for implementing message buffering in callin.io?
  2. What are the best practices for managing sequential messages?
  3. Are there any existing templates or examples available for this type of workflow?

I would greatly appreciate any advice or guidance!

:folded_hands:

My Tech Stack:

  • callin.io
  • Telegram
  • OpenAI/OpenRouter
 
Posted : 12/07/2025 10:50 am
(@lechusai)
Posts: 10
Member Admin
 

What you’re describing (waiting 10–15s before sending messages to the model) isn’t natively supported in callin.io. The default flow is always “event → action → response” with no buffering.

Options that work today

  1. Make or Zapier

    • Connect Telegram as the trigger.

    • Add a Delay of 10–15 seconds.

    • While the delay runs, store incoming messages in Storage (Make) or Storage by Zapier.

    • Once the delay finishes, concatenate all stored messages and send them to your model (OpenAI/OpenRouter).

  2. Buffer management

    • Use the Telegram chat_id as the storage key.

    • Each new message gets appended to that list.

    • When the delay is up, fetch the list, clear it, and forward it to the model.

    • For clarity, add separators like “---” between messages so the model understands they’re sequential.

  3. Best practices

    • Define an inactivity window (e.g., if >15s without new messages, flush the buffer).

    • A 10–15s window usually balances context gathering with acceptable latency.

    • Don’t concatenate endless text—keep it to coherent chunks for better model responses.

 
Posted : 19/09/2025 8:08 am
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