Update app.py

app.py

@@ -1,37 +1,17 @@
-import streamlit as st
-from transformers import pipeline
-import re
+# First, ensure the 'transformers' library is installed
+try:
+    from transformers import pipeline
+except ModuleNotFoundError:
+    import subprocess
+    subprocess.check_call(["pip", "install", "transformers"])
+    from transformers import pipeline
 
-# Load grammar correction model
-@st.cache_resource
-def load_corrector():
-    return pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
+# Example: Load a grammar correction pipeline (you can replace this with your preferred task/model)
+corrector = 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")
+# Sample sentence
+sentence = "She don't like going to the gym because it make her tired."
 
-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}")
+# Run correction
+result = corrector(sentence, max_length=100, clean_up_tokenization_spaces=True)
+print("Corrected Sentence:", result[0]['generated_text'])