app.py

import streamlit as st
from transformers import pipeline

# Create a text2text-generation pipeline
pipe = pipeline("text2text-generation", model="kaist-ai/prometheus-13b-v1.0")

st.title("Text Classification Model")
uploaded_file = st.file_uploader("Upload an image:")

if uploaded_file is not None:
    # Read the uploaded image
    image = Image.open(uploaded_file)

    # Extract text from the image using OCR
    ocr_results = extract_text(image)
    extracted_text = " ".join([res[1] for res in ocr_results])
    st.markdown("**Extracted text:**")
    st.markdown(extracted_text)

    # Generate an explanation for the extracted text using the Hugging Face pipeline
    explanation = pipe(extracted_text, max_length=100, do_sample=True)[0]["generated_text"]
    st.markdown("**Explanation:**")
    st.markdown(explanation)

else:
    st.markdown("Please upload an image to extract text and get an explanation.")