Professional HTML Text Translator with UrlsLab

Translate web content between languages while preserving HTML structure, using AI and UrlsLab plugin. Email addresses and URLs remain unchanged, ensuring accurate, context-aware translations for multilingual websites or content teams.

Flows

How the AI Flow works

Receive Text Input.: User submits text (with HTML) to be translated.
Prepare Translation Prompt.: Construct a prompt with source and target languages, specifying which parts (like emails and URLs) must remain unchanged.
Generate Translation.: An AI model translates the text while preserving HTML and excluding emails/URLs from translation.
Display Translated Output.: The translated text, with original structure and protected elements, is shown to the user.

Prompts used in this flow

Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.

Prompt

Create a prompt template with dynamic variables ({input}, {human_input}, {context}, {chat_history}, {system_message}).

                Translete following text from {source_lang} to {target_lang}:
{input}

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

See ChatInput

Prompt Component in FlowHunt

Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.

See Prompt Component in FlowHunt

Generator

Explore the Generator component in FlowHunt—powerful AI-driven text generation using your chosen LLM model. Effortlessly create dynamic chatbot responses by combining prompts, optional system instructions, and even images as input, making it a core tool for building intelligent, conversational workflows.

See Generator

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

See Chat Output

Flow description

Purpose and benefits

This workflow automates the process of translating text between languages while preserving the original HTML structure, making it ideal for translating web content, emails, or any structured text where format integrity is crucial. It’s especially useful for professionals, webmasters, and content teams who need to localize web pages or documents at scale, ensuring URLs and email addresses remain unchanged and the output is clean and ready for use.

Workflow Purpose and Utility

Professional Translation: Converts text from a specified source language to a target language.
Maintains HTML Structure: Ensures that the HTML formatting of the input text is preserved in the translated output.
Preserves URLs & Emails: Email addresses and URLs within the text remain intact and are not translated, ensuring functional links and contact information are preserved.
No Extra Output: The flow generates only the translated text—no commentary, extra content, or formatting changes are added.
Integration with UrlsLab: Ideal for scenarios where you want to combine translation with the UrlsLab WordPress plugin, facilitating streamlined web localization workflows.

Step-by-Step Process

Step	Component	Functionality
1	Chat Input	User provides the text to translate, along with source and target languages.
2	Prompt Template	The workflow creates a dynamic prompt using the input and language parameters, instructing the LLM on the task.
3	Generator (LLM)	The prompt is processed by a Language Model, which performs the translation according to the strict rules.
4	Chat Output	The translated message is displayed to the user, ready for use or further integration.

Detailed Flow Structure

Input: The user enters the text to be translated via the Chat Input node. This can include HTML content, web page snippets, or any structured text.
Prompt Generation: The Prompt Template node assembles a translation prompt, inserting dynamic variables for source language, target language, and the user’s input.
Text Generation: The Generator node sends the prompt to a Large Language Model (LLM), which performs the translation, ensuring that HTML tags, URLs, and email addresses are untouched.
Output Delivery: The result from the LLM is passed to the Chat Output node, which presents the translated and structurally preserved text to the user.

Why This Workflow Is Useful for Scaling and Automation

Efficiency: Eliminates manual copying, pasting, and reformatting by automating translation and preserving important web structures.
Consistency: Ensures translations follow strict rules, reducing the risk of broken links or misplaced formatting common in bulk or manual translation.
Scalability: Can be integrated into larger pipelines or triggered in bulk, enabling teams to localize numerous pages or documents quickly.
Seamless Integration: Works well with tools like UrlsLab, making it suitable for automating translation tasks in WordPress or other web environments.

Example Use Cases

Translating blog posts or articles for multilingual websites without breaking HTML structure.
Localizing web application UI text where links and contact info must remain functional.
Bulk translation of emails or newsletters, ensuring addresses and hyperlinks are preserved.

In summary, this workflow brings together translation accuracy, structural preservation, and automation, making it an essential tool for anyone needing reliable, scalable, and integration-friendly language translation—especially for web content.

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