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| import streamlit as st | |
| from transformers import pipeline | |
| import re | |
| st.set_page_config(page_title="Grammar Agent - Grammarly Alternative", layout="wide") | |
| st.title("📝 Grammar Agent - English Text Corrector") | |
| # Load grammar correction model | |
| def load_model(): | |
| return pipeline("text2text-generation", model="vennify/t5-base-grammar-correction") | |
| grammar_corrector = load_model() | |
| # Utility functions | |
| def capitalize_sentences(text): | |
| sentences = re.split(r'(?<=[.!?]) +', text) | |
| return ' '.join(s[0].upper() + s[1:] if s else '' for s in sentences) | |
| def correct_text(text): | |
| corrected = grammar_corrector(text, max_length=512)[0]['generated_text'] | |
| corrected = capitalize_sentences(corrected) | |
| return corrected | |
| def word_by_word_diff(original, corrected): | |
| original_words = original.split() | |
| corrected_words = corrected.split() | |
| diffs = [] | |
| for i in range(min(len(original_words), len(corrected_words))): | |
| if original_words[i] != corrected_words[i]: | |
| diffs.append((original_words[i], corrected_words[i])) | |
| if len(original_words) != len(corrected_words): | |
| extra = corrected_words[len(original_words):] | |
| for word in extra: | |
| diffs.append(("", word)) | |
| return diffs | |
| def analyze_differences(original, corrected): | |
| diffs = word_by_word_diff(original, corrected) | |
| analysis = [] | |
| for orig, corr in diffs: | |
| reason = "Grammar, Spelling or Punctuation correction" | |
| if orig == "": | |
| reason = "Missing word" | |
| elif orig.lower() != corr.lower(): | |
| if orig.lower() == corr: | |
| reason = "Capitalization" | |
| elif re.sub(r'[.,!?;]', '', orig.lower()) == re.sub(r'[.,!?;]', '', corr.lower()): | |
| reason = "Punctuation" | |
| elif len(orig) <= 3 or len(corr) <= 3: | |
| reason = "Spelling" | |
| analysis.append({ | |
| "Original": orig, | |
| "Correction": corr, | |
| "Reason": reason | |
| }) | |
| return analysis | |
| # Input Area | |
| input_text = st.text_area("Enter your sentence, paragraph, or essay:", height=250) | |
| if st.button("Correct and Analyze") and input_text: | |
| with st.spinner("Analyzing and correcting text..."): | |
| corrected = correct_text(input_text) | |
| analysis = analyze_differences(input_text, corrected) | |
| st.subheader("✅ Corrected Text:") | |
| st.success(corrected) | |
| st.subheader("📊 Error Analysis:") | |
| if analysis: | |
| for item in analysis: | |
| st.markdown(f"**Original:** `{item['Original']}` → **Correction:** `{item['Correction']}`") | |
| st.markdown(f"_Reason_: {item['Reason']}") | |
| st.markdown("---") | |
| else: | |
| st.write("No major corrections found. Great job!") | |
| st.subheader("📃 Side-by-Side Comparison") | |
| st.columns(2)[0].markdown(f"**Original:**\n\n{input_text}") | |
| st.columns(2)[1].markdown(f"**Corrected:**\n\n{corrected}") | |
| else: | |
| st.info("Enter text above and click 'Correct and Analyze' to begin.") | |