Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+import re
+
+# Load grammar correction model
+@st.cache_resource
+def load_corrector():
+    return pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
+
+# Load explanation model
+@st.cache_resource
+def load_explainer():
+    return pipeline("text2text-generation", model="google/flan-t5-large")
+
+grammar_corrector = load_corrector()
+explainer = load_explainer()
+
+# App UI
+st.title("🧠 Advanced Grammar Correction Assistant")
+st.write("Enter a sentence. I’ll fix it and explain the correction in detail.")
+
+user_input = st.text_area("✍️ Enter your sentence below:", height=100)
+
+if st.button("Correct & Explain"):
+    if user_input.strip() == "":
+        st.warning("Please enter a sentence.")
+    else:
+        # Step 1: Grammar correction
+        corrected = grammar_corrector(user_input, max_length=128, do_sample=False)[0]['generated_text']
+        
+        # Step 2: Explanation prompt
+        explanation_prompt = f"Original: {user_input}\nCorrected: {corrected}\nExplain the changes simply with grammar rules and examples."
+        explanation = explainer(explanation_prompt, max_length=200, do_sample=False)[0]['generated_text']
+        
+        # Output
+        st.markdown(f"**Correction:** {corrected}")
+        st.markdown(f"**Explanation:** {explanation}")