app.py

import streamlit as st

import transformers
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("summarization", model="google/pegasus-xsum")

st.title("NLP APP")
option = st.sidebar.selectbox(
    "Choose a task",
    ("Summarization", "Translation", "Emotion Detection", "Image Generation")
)
if option == "Summarization":
    st.title("Text Summarization")
    text = st.text_area("Enter text to summarize")
        if st.button("Summarize"):
            if text:
                summary = summarizer(text)[0]["summary_text"]
                st.write("Summary:", summary)
            else:
                st.write("Please enter text to summarize.")

else:
    st.title("None")