import spacy_streamlit import streamlit as st import typer from scripts.torch_ner_model import build_torch_ner_model from scripts.torch_ner_pipe import make_torch_entity_recognizer def main(models: str = None, default_text: str = None): st.title('NER Predictor') models = "training/model-best,training_trf/model-best" default_text = "The patient had surgery." models = [name.strip() for name in models.split(",")] labels = ["person", "problem", "pronoun", "test", "treatment"] #if st.button('Predict entities'): spacy_streamlit.visualize(models, default_text, visualizers=["ner"], ner_labels=labels) if __name__ == "__main__": try: typer.run(main) except SystemExit: pass