Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Load grammar correction model
+corrector = pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
+explainer = pipeline("text2text-generation", model="google/flan-t5-base")
+
+st.title("🧠 English Sentence Helper")
+st.write("Improve your grammar, get feedback, and learn from your mistakes.")
+
+user_input = st.text_area("✍️ Enter a sentence you want to check:")
+
+if st.button("Analyze"):
+    if user_input:
+        with st.spinner("Analyzing your sentence..."):
+            corrected = corrector(user_input)[0]['generated_text']
+            explanation_prompt = f"Explain the grammatical errors in this sentence: {user_input}"
+            improvement_prompt = f"Suggest improvements in grammar, vocabulary, or structure: {user_input}"
+
+            explanation = explainer(explanation_prompt)[0]['generated_text']
+            improvements = explainer(improvement_prompt)[0]['generated_text']
+
+        st.success("✅ Analysis Complete!")
+
+        st.markdown(f"**Original Sentence:** {user_input}")
+        st.markdown(f"**Corrected Sentence:** {corrected}")
+        st.markdown(f"**Grammar Explanation:** {explanation}")
+        st.markdown(f"**Improvement Suggestions:** {improvements}")
+    else:
+        st.warning("Please enter a sentence.")