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Detect toxic language in Telegram messages

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow detects toxic language (such as profanity, insults, threats) in messages sent via Telegram. This blog tutorial ex...

Best for

  • Miscellaneous automation workflows
  • AI Summarization automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.telegramtrigger, n8n-nodes-base.googleperspective, n8n-nodes-base.if, n8n-nodes-base.telegram, n8n-nodes-base.noop

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Lorena.

Original n8n.io source

1.1 Workflow description

Title
Detect toxic language in Telegram messages
Workflow name
Detect toxic language in Telegram messages

This workflow detects toxic language (such as profanity, insults, threats) in messages sent via Telegram. This blog tutorial explains how to configure the workflow nodes step-by-step.

Telegram Trigger: triggers the workflow when a new message is sent in a Telegram chat.

Google Perspective: analyzes the text of the message and returns a probability value between 0 and 1 of how likely it is that the content is toxic.

IF: filters messages with a toxic probability value above 0.7.

Telegram: sends a message in the chat with the text "I don't tolerate toxic language" if the probability value is above 0.7.

NoOp: takes no action if the probability value is below 0.7.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Telegram Trigger

Type / Role
n8n-nodes-base.telegramTrigger - telegramTrigger
Config choices
Version 1

Block 2 - Google Perspective

Type / Role
n8n-nodes-base.googlePerspective - googlePerspective
Config choices
Version 1

Block 3 - IF

Type / Role
n8n-nodes-base.if - if
Config choices
Version 1

Block 4 - Telegram

Type / Role
n8n-nodes-base.telegram - telegram
Config choices
Version 1

Block 5 - NoOp

Type / Role
n8n-nodes-base.noOp - noOp
Config choices
Version 1

3. Summary Table

Workflow Detect toxic language in Telegram messages
Complexity intermediate
Nodes 5
Categories Miscellaneous, AI Summarization
Author Lorena
Published 03 Sept 2021

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/1216/1216.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Detect toxic language in Telegram messages do?

This workflow detects toxic language (such as profanity, insults, threats) in messages sent via Telegram. This blog tutorial ex...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Miscellaneous, AI Summarization use case.