Create app.py

app.py

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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="pszemraj/flan-t5-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("---")