Real-time chat translation with DeepL

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Important notice

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

1. Workflow Overview

Who is this for? This workflow is intended for users, workers, creatives or students who want to translate languages quickly and automatically via text chat. translating a sentence will take ti...

Best for

Personal Productivity automation workflows
Multimodal AI automation workflows
intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.deepl, n8n-nodes-base.noop, n8n-nodes-base.stickynote

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Real-time chat translation with DeepL
Workflow name: Real-time chat translation with DeepL

Who is this for?

This workflow is intended for users, workers, creatives or students who want to translate languages quickly and automatically via text chat. translating a sentence will take time and seem impractical, with this the results will be practical and save time. This is also a form of devotion to the community at n8n and the n8n company, as well as devotion to users and students so that reality is no longer tiring and is able to answer the problems of existing reality.

How does it work?

Easy explanation:

Trigger Chat functions as a place or container for inputting text or sentences to be translated and the results come out directly here. Then the DeepL node will become the translation machine, here there are already parameters, the language can be adjusted, and the last node is useful for after the DeepL node no more operations appear And enjoy this workflow that suits you.

Setup instructions

Complete what is in the node as stated in the notes column. You need a "Credential Account" on the DeepL node, then select the language. If you already have an account, just connect it, and if not, create it first, you can register it by following the guide from n8n, it's very easy. Because here it is neatly and cleanly arranged. Then, save and run, test the workflow and activate the workflow. This workflow is ready to use.

Requirements

As a reminder:

There must be (if not, make sure it is registered) in each "Credential Account" by following the guide on how to create it, n8n's guide is very complete Don't forget to save, and make sure the workflow is active.

How to customize this workflow to your needs

You can directly set the parameters in the language, so that the suitability is also high when working on tasks and answering them.

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 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 2 - DeepL

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

Block 3 - No Operation, do nothing

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

Block 4 - Sticky Note

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

Block 5 - Sticky Note1

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

Block 6 - Sticky Note2

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

3. Summary Table

Workflow	Real-time chat translation with DeepL
Complexity	intermediate
Nodes	6
Categories	Personal Productivity, Multimodal AI
Author	Ghufran Ridhawi
Published	31 May 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4532/4532.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

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

Download workflow JSON Original n8n.io source Personal Productivity workflows Multimodal AI workflows

Frequently asked questions

What does Real-time chat translation with DeepL do?

Who is this for? This workflow is intended for users, workers, creatives or students who want to translate languages quickly and automatically via text chat. translating a sentence will take ti...

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 Personal Productivity, Multimodal AI use case.

Ghufran Ridhawi

8 workflows

Nodes

@n8n/n8n-nodes-langchain.chattrigger n8n-nodes-base.deepl n8n-nodes-base.noop n8n-nodes-base.stickynote

Complexity

intermediate

Published 31 May 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/4532/4532.json

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Real-time chat translation with DeepL

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Who is this for?

How does it work?

Setup instructions

Requirements

How to customize this workflow to your needs

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When chat message received

Block 2 - DeepL

Block 3 - No Operation, do nothing

Block 4 - Sticky Note

Block 5 - Sticky Note1

Block 6 - Sticky Note2

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions