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| import time | |
| import streamlit as st | |
| import subprocess | |
| from highlighter import show_highlights | |
| from utils import ( | |
| download_quantized_model, | |
| download_spacy_model, | |
| errant_tokenize, | |
| get_annotator, | |
| load_model_and_tokenizer, | |
| ) | |
| model_names = [ | |
| "aseifert/t5-base-jfleg-wi", | |
| "aseifert/byt5-base-jfleg-wi", | |
| "team-writing-assistant/t5-base-c4jfleg", | |
| "Modfiededition/t5-base-fine-tuned-on-jfleg", | |
| "prithivida/grammar_error_correcter_v2", | |
| ] | |
| st.write("Output of `pip freeze`:") | |
| p = subprocess.Popen(["pip", "freeze"], stdout=subprocess.PIPE) | |
| output = p.communicate()[0] | |
| st.code(output.decode("utf-8")) | |
| def predict(model, args, text: str): | |
| return model.generate_text(text, args=args).text | |
| def main(): | |
| st.title("🤗 Writing Assistant") | |
| st.markdown( | |
| """This writing assistant will proofread any text for you! See my [GitHub repo](https://github.com/aseifert/hf-writing-assistant) for implementation details.""" | |
| ) | |
| model_name = st.selectbox("Choose model", model_names) | |
| download_quantized_model(model_name) | |
| model, tokenizer = load_model_and_tokenizer(model_name) | |
| download_spacy_model() | |
| annotator = get_annotator("en") | |
| default_text = "A dog is bigger then mouse." | |
| default_text = "it gives him many apprtunites in the life, and i think that being knowledge person is a very wouderful thing to have so we can spend our lives in a successful way and full of happenis." | |
| input_text = st.text_area( | |
| label="Original text", | |
| value=default_text, | |
| ) | |
| start = None | |
| if st.button("✍️ Check"): | |
| start = time.time() | |
| with st.spinner("Checking for errors 🔍"): | |
| output_text = predict(model, tokenizer, input_text) | |
| try: | |
| tokenized_input_text = errant_tokenize(input_text) | |
| tokenized_output_text = errant_tokenize(output_text) | |
| show_highlights(annotator, tokenized_input_text, tokenized_output_text) | |
| st.write("") | |
| st.success(output_text) | |
| except Exception as e: | |
| st.error("Some error occured!" + str(e)) | |
| st.stop() | |
| st.write("---") | |
| st.markdown( | |
| "Built by [@therealaseifert](https://twitter.com/therealaseifert) during the HF community event – 👨\u200d💻 [GitHub repo](https://github.com/aseifert/hf-writing-assistant) – 🤗 Team Writing Assistant" | |
| ) | |
| st.markdown( | |
| "_Highlighting code thanks to [Gramformer](https://github.com/PrithivirajDamodaran/Gramformer)_" | |
| ) | |
| if start is not None: | |
| st.text(f"prediction took {time.time() - start:.2f}s") | |
| if __name__ == "__main__": | |
| main() | |