app.py

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

app = FastAPI()

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

model = AutoModelForSeq2SeqLM.from_pretrained(
    "ai4bharat/indictrans2-indic-indic-1B", trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(
    "ai4bharat/indictrans2-indic-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], src_lang: str, target_lang: str):
    try:
        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,
            )

        return generated_tokens
    except Exception as e:
        return str(e)


@app.get("/")
def read_root():
    return {"Hello": "World"}


class TranslateRequest(BaseModel):
    sentences: List[str]
    src_lang: str
    target_lang: str


@app.post("/translate/")
def translate(request: TranslateRequest):
    try:
        result = translate_text(request.sentences, request.src_lang, request.target_lang)
        return result
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))