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