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Allow users to send a sequence of messages to an AI agent in Telegram

Chris CarrChris Carr
13921 views
2/3/2026
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Use Case

When creating chatbots that interface through applications such as Telegram and WhatsApp, users can often sends multiple shorter messages in quick succession, in place of a single, longer message. This workflow accounts for this behaviour.

What it Does

This workflow allows users to send several messages in quick succession, treating them as one coherent conversation instead of separate messages requiring individual responses.

How it Works

  1. When messages arrive, they are stored in a Supabase PostgreSQL table
  2. The system waits briefly to see if additional messages arrive
  3. If no new messages arrive within the waiting period, all queued messages are:
    • Combined and processed as a single conversation
    • Responded to with one unified reply
    • Deleted from the queue

Setup

  1. Create a table in Supabase called message_queue. It needs to have the following columns: user_id (uint8), message (text), and message_id (uint8)
  2. Add your Telegram, Supabase, OpenAI, and PostgreSQL credentials
  3. Activate the workflow and test by sending multiple messages the Telegram bot in one go
  4. Wait ten seconds after which you will receive a single reply to all of your messages

How to Modify it to Your Needs

  • Change the value of Wait Amount in the Wait 10 Seconds node in order to to modify the buffering window
  • Add a System Message to the AI Agent to tailor it to your specific use case
  • Replace the OpenAI sub-node to use a different language model

Telegram AI Agent Sequence Messenger

This n8n workflow enables users to send a sequence of messages to an AI agent directly from Telegram, allowing for multi-turn conversations and maintaining chat history. It leverages a Telegram bot as the interface, an AI agent for processing messages, and a Postgres database for storing chat memory.

What it does

This workflow facilitates an interactive AI agent experience within Telegram by:

  1. Listening for Telegram Messages: It acts as a Telegram bot, triggering whenever a new message is received from a user.
  2. Initializing or Retrieving Chat Memory: It checks for existing chat history for the user in a Supabase (Postgres) database. If no history exists, it initializes a new chat memory.
  3. Processing Messages with an AI Agent: It forwards the user's message, along with the chat history, to an AI Agent powered by an OpenAI Chat Model. The AI Agent processes the message in the context of the ongoing conversation.
  4. Storing Chat Memory: The AI Agent's response and the updated conversation history are then saved back to the Supabase (Postgres) database, ensuring continuity for future interactions.
  5. Responding via Telegram: Finally, the AI Agent's response is sent back to the user through the Telegram bot.

Prerequisites/Requirements

To set up and use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • Telegram Bot Token: A Telegram bot created via BotFather. You will need its API token.
  • OpenAI API Key: An API key for OpenAI to power the AI Chat Model.
  • Supabase Account (or PostgreSQL Database): A Supabase project or any PostgreSQL database to store chat memory. You will need the connection details (host, port, database, user, password, and SSL mode).

Setup/Usage

  1. Import the Workflow:

    • Download the provided JSON file.
    • In your n8n instance, go to "Workflows" and click "New".
    • Click the three dots menu (...) and select "Import from JSON".
    • Paste the JSON content or upload the file.

  2. Configure Credentials:

    • Telegram Trigger & Telegram Node:
      • Click on the "Telegram Trigger" node and then on "Create New Credential" for the Telegram API.
      • Enter your Telegram Bot Token.
      • Repeat this for the "Telegram" node.
    • Supabase Node & Postgres Chat Memory Node:
      • Click on the "Supabase" node and then on "Create New Credential" for Supabase.
      • Enter your Supabase (or PostgreSQL) connection details (Host, Port, Database, User, Password, and SSL Mode).
      • Repeat this for the "Postgres Chat Memory" node.
    • OpenAI Chat Model Node:
      • Click on the "OpenAI Chat Model" node and then on "Create New Credential" for OpenAI API.
      • Enter your OpenAI API Key.

  3. Activate the Workflow:

    • Once all credentials are configured, save the workflow.
    • Click the "Activate" toggle in the top right corner of the n8n editor to enable the workflow.

Now, when users send messages to your configured Telegram bot, the AI agent will respond, remembering previous conversations.

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