williampepple1/ibani-translator-backend
Domain:
natural language processingRecord type:
softwaremodel
Creator:
wil
Host:
# Ibani Translator Backend
This is a Node.js Express backend for the Ibani Translator, using the Hugging Face model williampepple1/ibani-translator.
## Prerequisites
- Node.js (v16 or higher)
- A Hugging Face API Token (Recommended for Inference API)
## Getting Started
1. **Install Dependencies:**
```bash
npm install
```
2. **Setup Environment Variables:**
Create a `.env` file in the root directory and add your Hugging Face Access Token:
```env
PORT=5000
HUGGING_FACE_ACCESS_TOKEN=your_token_here
```
3. **Run the Server:**
- Development mode: `npm run dev`
- Production mode: `npm run start`
## API Endpoints
### 1. Health Check
- **URL:** `/health`
- **Method:** `GET`
- **Success Response:** `{"status": "UP", "model": "williampepple1/ibani-translator", ...}`
### 2. Translate
- **URL:** `/api/translate`
- **Method:** `POST`
- **Body:**
```json
{
"text": "I eat fish"
}
```
- **Success Response:**
```json
{
"original_text": "I eat fish",
"translated_text": "A mine í-njí ríerí",
"source_language": "English",
"target_language": "Ibani",
"success": true
}
```
## Local Execution with Transformers.js (Optional)
If you wish to run the model locally on your machine without an API key, you can use `@xenova/transformers`.
Note: This requires the model to have ONNX weights. If they are not available, the Inference API approach is the most reliable.
## Model Details
- **Base Model**: `Helsinki-NLP/opus-mt-en-mul`
- **Language Pair**: English → Ibani
- **Developer**: William Pepple