app.py

from fastapi import FastAPI
from typing import List
import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
from IndicTransToolkit import IndicProcessor
from fastapi.middleware.cors import CORSMiddleware

import os

os.environ["HF_HOME"] = "/.cache"
# Initialize FastAPI
app = FastAPI()

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Initialize models and processors
model = AutoModelForSeq2SeqLM.from_pretrained(
    "ai4bharat/indictrans2-en-indic-1B", trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(
    "ai4bharat/indictrans2-en-indic-1B", trust_remote_code=True
)
ip = IndicProcessor(inference=True)
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
model = model.to(DEVICE)


def translate_text(sentences: List[str], target_lang: str):
    try:
        src_lang = "eng_Latn"
        batch = ip.preprocess_batch(sentences, src_lang=src_lang, tgt_lang=target_lang)
        inputs = tokenizer(
            batch,
            truncation=True,
            padding="longest",
            return_tensors="pt",
            return_attention_mask=True,
        ).to(DEVICE)

        with torch.no_grad():
            generated_tokens = model.generate(
                **inputs,
                use_cache=True,
                min_length=0,
                max_length=256,
                num_beams=5,
                num_return_sequences=1,
            )

        with tokenizer.as_target_tokenizer():
            generated_tokens = tokenizer.batch_decode(
                generated_tokens.detach().cpu().tolist(),
                skip_special_tokens=True,
                clean_up_tokenization_spaces=True,
            )

        translations = ip.postprocess_batch(generated_tokens, lang=target_lang)
        return {
            "translations": translations,
            "source_language": src_lang,
            "target_language": target_lang,
        }
    except Exception as e:
        raise Exception(f"Translation failed: {str(e)}")


# FastAPI routes
@app.get("/health")
async def health_check():
    return {"status": "healthy"}


@app.post("/translate")
async def translate_endpoint(sentences: List[str], target_lang: str):
    try:
        result = translate_text(sentences=sentences, target_lang=target_lang)
        return result
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))