app.py

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from transformers import pipeline
import torch
import os

# Version: 2026-01-15 - Updated model
app = FastAPI(title="Ibani Translator API")

# Model configuration
MODEL_ID = "williampepple1/ibani-translator"

print(f"Loading model {MODEL_ID}...")
try:
    # Use pipeline for easy inference
    # device=-1 forces CPU usage which is what HF Spaces free tier provides
    # force_download=True ensures we get the latest model version
    translator = pipeline(
        "translation", 
        model=MODEL_ID, 
        device=-1,
        model_kwargs={"force_download": True}
    )
    print("Model loaded successfully!")
except Exception as e:
    print(f"Error loading model: {e}")
    translator = None

class TranslationRequest(BaseModel):
    text: str

@app.get("/")
def read_root():
    return {"status": "healthy", "model": MODEL_ID}

@app.post("/translate")
async def translate(request: TranslationRequest):
    if translator is None:
        raise HTTPException(status_code=503, detail="Model not loaded")
    
    try:
        result = translator(request.text)
        return {
            "translated_text": result[0]['translation_text'],
            "original_text": request.text
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))