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Create app.py

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  1. app.py +36 -0
app.py ADDED
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+ import streamlit as st
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+ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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+ import torch
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+
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+ # Load pre-trained model and tokenizer (Grammar correction model)
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+ @st.cache_resource
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+ def load_model():
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+ model_name = "prithivida/grammar_error_correcter_v1"
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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+ return tokenizer, model
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+
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+ tokenizer, model = load_model()
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+
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+ # Function to correct grammar
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+ def correct_grammar(text):
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+ input_text = "gec: " + text
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+ inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True)
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+ outputs = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
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+ corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ return corrected_text
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+
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+ # Streamlit UI
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+ st.title("📝 Grammar Correction App")
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+ st.write("Enter a sentence or paragraph below, and the AI will correct any grammatical errors.")
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+
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+ user_input = st.text_area("Your Text", height=200, placeholder="Type or paste your text here...")
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+
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+ if st.button("Correct Grammar"):
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+ if user_input.strip():
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+ with st.spinner("Correcting grammar..."):
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+ corrected = correct_grammar(user_input)
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+ st.subheader("✅ Corrected Text")
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+ st.success(corrected)
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+ else:
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+ st.warning("Please enter some text to correct.")