pipeline.py

from transformers import T5ForConditionalGeneration, T5Tokenizer
from googletrans import Translator
from transformers import pipeline

class GOTSummarizer:
    def __init__(self):
        self.model = T5ForConditionalGeneration.from_pretrained("iamomtiwari/NLP-Model")
        self.tokenizer = T5Tokenizer.from_pretrained("iamomtiwari/NLP-Model")
        self.translator = Translator()
    
    def summarize(self, text, max_length=150):
        inputs = self.tokenizer("summarize: " + text, return_tensors="pt", truncation=True)
        outputs = self.model.generate(**inputs, max_length=max_length)
        return self.tokenizer.decode(outputs[0], skip_special_tokens=True)
    
    def translate(self, text, lang='hi'):
        return self.translator.translate(text, dest=lang).text