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import streamlit as st | |
from transformers import pipeline | |
# App Title | |
st.title("π§βπ Advanced AI English Correction & Improvement") | |
# Load Google's FLAN-T5-LARGE model (cached) | |
def load_correction_model(): | |
return pipeline("text2text-generation", model="google/flan-t5-large") | |
correction_model = load_correction_model() | |
# User input | |
user_text = st.text_area("Enter your sentence, paragraph, or text here:", height=200) | |
# Correction and analysis logic | |
if st.button("Correct & Improve"): | |
if not user_text.strip(): | |
st.warning("β οΈ Please enter text to analyze!") | |
else: | |
prompt = f"Correct the grammar, punctuation, and improve readability: {user_text}" | |
corrected_output = correction_model(prompt, max_length=512, clean_up_tokenization_spaces=True) | |
improved_text = corrected_output[0]['generated_text'] | |
# Display Results | |
st.subheader("β Corrected & Improved Text:") | |
st.write(improved_text) | |
# Provide detailed explanation (AI-based) | |
st.subheader("π What's improved:") | |
if user_text != improved_text: | |
st.markdown("- Improved sentence structure & readability.") | |
st.markdown("- Corrected grammar & punctuation.") | |
st.markdown("- Enhanced clarity & coherence.") | |
st.info("Review the corrected text carefully to better understand punctuation, grammar rules, and style improvements.") | |
else: | |
st.success("No issues found. Excellent writing!") | |
# Learning recommendations | |
st.subheader("π Tips to Learn & Improve:") | |
st.markdown(""" | |
- Review punctuation usage (commas, question marks, exclamation points). | |
- Practice sentence structuring for clarity and readability. | |
- Use resources like [Grammarly](https://www.grammarly.com/blog/category/handbook/) and [Purdue OWL](https://owl.purdue.edu/owl/purdue_owl.html) to enhance your writing skills. | |
""") | |