Update app.py

app.py

@@ -1,51 +1,56 @@
 import streamlit as st
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
 import torch
-import difflib
 
-# Load the grammar correction model
+# Load grammar correction model
 @st.cache_resource
-def load_model():
+def load_grammar_model():
     model_name = "prithivida/grammar_error_correcter_v1"
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
     return tokenizer, model
 
-tokenizer, model = load_model()
+# Load explanation model
+@st.cache_resource
+def load_explainer():
+    explainer = pipeline("text2text-generation", model="google/flan-t5-base", max_length=256)
+    return explainer
+
+grammar_tokenizer, grammar_model = load_grammar_model()
+explanation_model = load_explainer()
 
-# Function to correct grammar
+# Grammar correction function
 def correct_grammar(text):
     input_text = "gec: " + text
-    inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True)
-    outputs = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
-    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    inputs = grammar_tokenizer.encode(input_text, return_tensors="pt", truncation=True)
+    outputs = grammar_model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
+    corrected_text = grammar_tokenizer.decode(outputs[0], skip_special_tokens=True)
     return corrected_text
 
-# Function to show differences
-def show_differences(original, corrected):
-    diff = difflib.ndiff(original.split(), corrected.split())
-    changes = []
-    for d in diff:
-        if d.startswith("- "):
-            changes.append(f"❌ Removed: `{d[2:]}`")
-        elif d.startswith("+ "):
-            changes.append(f"✅ Added: `{d[2:]}`")
-    return "\n".join(changes) if changes else "No major changes found."
-
-# Streamlit UI
-st.title("📝 Grammar Correction App")
-st.write("Enter a sentence or paragraph below, and the AI will correct grammatical errors and highlight the changes.")
+# Explanation function using second model
+def explain_correction(original, corrected):
+    prompt = f"Explain the grammar improvements made from: \"{original}\" to: \"{corrected}\""
+    result = explanation_model(prompt)[0]['generated_text']
+    return result
+
+# Streamlit App UI
+st.title("📝 Smart Grammar Correction with Explanations")
+st.write("Enter your text below. The AI will correct grammar **and explain why** the changes were made using grammar principles.")
 
 user_input = st.text_area("Your Text", height=200, placeholder="Type or paste your text here...")
 
-if st.button("Correct Grammar"):
+if st.button("Correct and Explain"):
     if user_input.strip():
         with st.spinner("Correcting grammar..."):
             corrected = correct_grammar(user_input)
+
+        with st.spinner("Explaining corrections..."):
+            explanation = explain_correction(user_input, corrected)
+
         st.subheader("✅ Corrected Text")
         st.success(corrected)
 
-        st.subheader("🕵️ What Changed?")
-        st.markdown(show_differences(user_input, corrected))
+        st.subheader("📘 Explanation (Why it was changed)")
+        st.markdown(explanation)
     else:
         st.warning("Please enter some text to correct.")