How to Translate Large Texts in n8n Using GPT (Ready-to-Use Workflow)
How to Translate Large Texts in n8n Using GPT (Ready-to-Use Workflow)
🔥 Complete and practical tutorial showing how to import a workflow into n8n 2.1 that performs unlimited text translations, automatically saving the translated content into .txt files inside a local folder.
🔥 The video demonstrates how to use Form Trigger to define the target language and the text to be translated, eliminating the need to manually split large texts in interfaces like ChatGPT or similar tools.
🔥 The workflow processes the input text, passes through configuration nodes, enters an AI Agent node that automatically splits the content into parts, processes the translation using a GPT model, recombines all translated parts, and finishes by ensuring idiomatic consistency, organization, and correct disk saving.
🔥 The entire flow was designed to support translations with more than 100,000 characters in a single run, maintaining stability, content integrity, and adherence to the linguistic rules of the selected language.
The goal of this tutorial is to demonstrate:
✔ How to correctly import workflows in n8n version 2
✔ How to use Form Trigger to define language and input text
✔ How to process large volumes of text with AI Agent and GPT
✔ How to automatically split, translate, and recombine long texts
✔ How to save translations as .txt files in local folders
✔ How to ensure consistency and organization in high-volume translations
Stack used in this video:
✔ n8n version 2 (self-hosted)
✔ Form Trigger / Form Input
✔ AI Agent + Node Codes (text processing and chunking)
✔ GPT (translation with idiomatic rules)
✔ Saving files (.txt) to a local folder
✔ Docker Desktop on Windows
⚠️ Important note:
For this workflow to function correctly, n8n version 2 must be properly installed and configured. We provide a specific video on our channel teaching how to correctly install n8n v2 in a local environment.
#n8n, #n8nV2, #n8nWorkflow, #n8nImport,
#FormTrigger, #AIWorkflow, #GPT, #TextTranslation,
#Automation, #Workflow, #SelfHosted, #DockerDesktop