import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

#tokenizer = AutoTokenizer.from_pretrained("human-centered-summarization/financial-summarization-pegasus")

#model = AutoModelForSeq2SeqLM.from_pretrained("human-centered-summarization/financial-summarization-pegasus")

#pipe = pipeline(task="summarization", 
                #model=model,
                #tokenizer=tokenizer,)

pipe = pipeline(task="summarization", model = "human-centered-summarization/financial-summarization-pegasus")

with open('text1.txt') as f:
    text1 = f.read()

gr.Interface.from_pipeline(pipe, 
                    title="Financial Summarization",
                    description="Financial Summarization using Pegasus. Model can be found at https://huggingface.co/human-centered-summarization/financial-summarization-pegasus",
                    examples=[text1]
                    ).launch()