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import streamlit as st
from transformers import pipeline
from diff_match_patch import diff_match_patch
from langdetect import detect
import time
# Load models
@st.cache_resource
def load_grammar_model():
return pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
@st.cache_resource
def load_explainer_model():
return pipeline("text2text-generation", model="google/flan-t5-large")
@st.cache_resource
def load_translation_ur_to_en():
return pipeline("translation", model="Helsinki-NLP/opus-mt-ur-en")
@st.cache_resource
def load_translation_en_to_ur():
return pipeline("translation", model="Helsinki-NLP/opus-mt-en-ur")
# Initialize models
grammar_model = load_grammar_model()
explainer_model = load_explainer_model()
translate_ur_en = load_translation_ur_to_en()
translate_en_ur = load_translation_en_to_ur()
dmp = diff_match_patch()
st.title("📝 AI Grammar & Writing Assistant (Multilingual)")
st.markdown("Supports English & Urdu inputs. Fix grammar, punctuation, spelling, tenses — with explanations and writing tips.")
# Initialize session state
if "corrected_text" not in st.session_state:
st.session_state.corrected_text = ""
if "detected_lang" not in st.session_state:
st.session_state.detected_lang = ""
if "history" not in st.session_state:
st.session_state.history = []
user_input = st.text_area("✍️ Enter your sentence, paragraph, or essay:", height=200)
# Detect & Translate Urdu if needed
def detect_and_translate_input(text):
lang = detect(text)
if lang == "ur":
st.info("🔄 Detected Urdu input. Translating to English for grammar correction...")
translated = translate_ur_en(text)[0]['translation_text']
return translated, lang
return text, lang
# Button: Grammar Correction
if st.button("✅ Correct Grammar"):
if user_input.strip():
translated_input, lang = detect_and_translate_input(user_input)
st.session_state.detected_lang = lang
corrected = grammar_model(f"grammar: {translated_input}", max_length=512, do_sample=False)[0]["generated_text"]
st.session_state.corrected_text = corrected
# Show corrected text
st.subheader("✅ Corrected Text (in English)")
st.success(corrected)
# Highlight changes
st.subheader("🔍 Changes Highlighted")
diffs = dmp.diff_main(translated_input, corrected)
dmp.diff_cleanupSemantic(diffs)
html_diff = ""
for (op, data) in diffs:
if op == -1:
html_diff += f'<span style="background-color:#fbb;">{data}</span>'
elif op == 1:
html_diff += f'<span style="background-color:#bfb;">{data}</span>'
else:
html_diff += data
st.markdown(f"<div style='font-family:monospace;'>{html_diff}</div>", unsafe_allow_html=True)
# Optional Urdu output
if lang == "ur":
urdu_back = translate_en_ur(corrected)[0]['translation_text']
st.subheader("🔄 Corrected Text (Back in Urdu)")
st.success(urdu_back)
# Save to history
st.session_state.history.append({
"timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
"original": user_input,
"corrected": corrected,
"lang": lang
})
# Button: Explanation
if st.button("🧠 Explain Corrections"):
if st.session_state.corrected_text:
st.subheader("Line-by-Line Explanation")
original_lines = user_input.split(".")
for line in original_lines:
if line.strip():
prompt = f"Explain and fix issues in this sentence:\n'{line.strip()}.'"
explanation = explainer_model(prompt, max_length=100)[0]["generated_text"]
st.markdown(f"**🔸 {line.strip()}**")
st.info(explanation)
else:
st.warning("Please correct the grammar first.")
# Button: Suggest Improvements
if st.button("💡 Suggest Writing Improvements"):
if st.session_state.corrected_text:
prompt = f"Suggest improvements to make this text clearer and more professional:\n\n{st.session_state.corrected_text}"
suggestion = explainer_model(prompt, max_length=150)[0]["generated_text"]
st.subheader("Improvement Suggestions")
st.warning(suggestion)
else:
st.warning("Please correct the grammar first.")
# Download corrected text
if st.session_state.corrected_text:
st.download_button("⬇️ Download Corrected Text", st.session_state.corrected_text, file_name="corrected_text.txt")
# History viewer
if st.checkbox("📜 Show My Correction History"):
st.subheader("Correction History")
for record in st.session_state.history:
st.markdown(f"🕒 **{record['timestamp']}** | Language: `{record['lang']}`")
st.markdown(f"**Original:** {record['original']}")
st.markdown(f"**Corrected:** {record['corrected']}")
st.markdown("---")
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