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| import time | |
| import errant | |
| import streamlit as st | |
| from happytransformer import HappyTextToText, TTSettings | |
| from highlighter import show_edits, show_highlights | |
| checkpoints = [ | |
| "aseifert/t5-base-jfleg-wi", | |
| "aseifert/byt5-base-jfleg-wi", | |
| "prithivida/grammar_error_correcter_v2", | |
| "Modfiededition/t5-base-fine-tuned-on-jfleg", | |
| ] | |
| def get_model(model_name): | |
| return HappyTextToText("T5", model_name) | |
| def get_annotator(lang: str): | |
| return errant.load(lang) | |
| st.title("Check & Improve English Grammar") | |
| st.markdown("This writing assistant detects 🔍 and corrects ✍️ grammatical mistakes for you!") | |
| checkpoint = st.selectbox("Choose model", checkpoints) | |
| happy_tt = get_model(checkpoint) | |
| annotator = get_annotator("en") | |
| args = TTSettings(num_beams=5, min_length=1, max_length=1024) | |
| input_text = st.text_area( | |
| label="Original text", | |
| value="A dog is bigger then mouse.", | |
| placeholder="Enter your text here", | |
| ) | |
| button = st.button("✍️ Check") | |
| def output(input_text): | |
| with st.spinner("Checking for errors 🔍"): | |
| prefixed_input_text = "Grammar: " + input_text | |
| result = happy_tt.generate_text(prefixed_input_text, args=args).text | |
| try: | |
| st.success(result) | |
| show_highlights(annotator, input_text, result) | |
| # st.table(show_edits(annotator, input_text, result)) | |
| except Exception as e: | |
| st.error("Some error occured!" + str(e)) | |
| st.stop() | |
| start = time.time() | |
| output(input_text) | |
| st.write("---") | |
| st.text(f"Built by Team Writing Assistant ❤️ – prediction took {time.time() - start:.2f}s") | |