Update app.py

app.py

@@ -1,19 +1,33 @@
 import streamlit as st
-import language_tool_python
-
-st.set_page_config(page_title="Grammar & Spell Corrector", page_icon="📝")
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import torch
 
+st.set_page_config(page_title="Grammar Corrector", page_icon="📝")
 st.title("📝 AI Grammar & Spell Corrector")
 
-text = st.text_area("Enter your text below:", height=200)
+@st.cache_resource
+def load_model():
+    model = AutoModelForSeq2SeqLM.from_pretrained("vennify/t5-base-grammar-correction")
+    tokenizer = AutoTokenizer.from_pretrained("vennify/t5-base-grammar-correction")
+    return model, tokenizer
+
+model, tokenizer = load_model()
+
+def correct_grammar(text):
+    input_text = "grammar: " + text
+    inputs = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
+    with torch.no_grad():
+        outputs = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
+    corrected = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return corrected
+
+text = st.text_area("Enter your text:", height=200)
 
 if st.button("Correct Text"):
     if text.strip():
-        tool = language_tool_python.LanguageTool('en-US')
-        matches = tool.check(text)
-        corrected_text = language_tool_python.utils.correct(text, matches)
-        
-        st.subheader("✅ Corrected Text")
-        st.write(corrected_text)
+        with st.spinner("Correcting..."):
+            corrected = correct_grammar(text)
+            st.subheader("✅ Corrected Text")
+            st.write(corrected)
     else:
         st.warning("Please enter some text.")