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# 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.
```python
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`
```python
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.
```bash
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`
```javascript
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.** |