app.py

import gradio as gr
from optimum.onnxruntime import ORTModelForSeq2SeqLM
from transformers import pipeline
import logging

logger = logging.Logger()
logger.setLevel(logging.INFO)
# File handler (for logging to file)
file_handler = logging.FileHandler("sc_summ.log", encoding='utf-8')
file_handler.setLevel(logging.INFO)
file_formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
file_handler.setFormatter(file_formatter)
logger.addHandler(file_handler)  

def get_summarizer():
    model = ORTModelForSeq2SeqLM.from_pretrained(
        "shorecode/t5-efficient-tiny-summarizer-general-purpose-v3"
    )        
    return pipeline(
        "summarization",
        model=model,
        tokenizer="shorecode/t5-efficient-tiny-summarizer-general-purpose-v3",
    )

def summarize(src):
    try:
        summary = SUMMARY_MODEL(
            src,
            max_new_tokens=4000,
            min_length=20,
            no_repeat_ngram_size=2,
            num_beams=3, 
        )
        return summary
    except Exception as e:
        logger.error(f"An error occured while summarizing: {e}")
        return "An error occurred"

def greet(name):
    return "Hello " + name + "!!"

demo = gr.Interface(fn=summarize, inputs="text", outputs="text")
demo.launch()