docs/Translator/Translator.md

API Documentation for Lenylvt/Translator-API

This documentation explains how to interact with the Translator API using both Python and JavaScript.

API Endpoint

To interact with this API, you have the option to use the gradio_client Python library or the @gradio/client JavaScript package.

Python Usage

Step 1: Installation

First, install the gradio_client library if it's not already installed.

pip install gradio_client

Step 2: Making a Request

Locate the API endpoint for the function you intend to use. Replace the placeholder values in the snippet below with your actual input data. If accessing a private Space, you may need to include your Hugging Face token.

API Name: /predict

from gradio_client import Client

client = Client("Lenylvt/Translator-API")
result = client.predict(
    "Hello!!",  # str in 'text' Textbox component
    "en",       # Source Language (ISO 639-1 code, e.g., 'en' for English) in 'Source Language' Dropdown component
    "es",       # Target Language (ISO 639-1 code, e.g., 'es' for Spanish) in 'Target Language' Dropdown component
    api_name="/predict"
)
print(result)

Return Type(s):

• A str representing the translated text output in the 'output' Textbox component.

🔴 If you have this error : 'Failed to load model for aa to ab: Helsinki-NLP/opus-mt-aa-ab is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with huggingface-cli login or by passing token=<your_token>', its because the language is not available.

JavaScript Usage

Step 1: Installation

Install the @gradio/client package if it's not already in your project.

npm i -D @gradio/client

Step 2: Making a Request

As with Python, identify the API endpoint that matches your requirement. Replace the placeholders with your data. If this is a private Space, don't forget to include your Hugging Face token.

API Name: /predict

import { client } from "@gradio/client";

const app = await client("Lenylvt/Translator-API");
const result = await app.predict("/predict", [        
    "Hello!!", // string in 'text' Textbox component        
    "en",      // string representing ISO 639-1 code for Source Language in 'Source Language' Dropdown component        
    "es",      // string representing ISO 639-1 code for Target Language in 'Target Language' Dropdown component
]);

console.log(result.data);

Return Type(s):

• A string representing the translated text output in the 'output' Textbox component.

🔴 If you have this error : 'Failed to load model for aa to ab: Helsinki-NLP/opus-mt-aa-ab is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with huggingface-cli login or by passing token=<your_token>', its because the language is not available.