| import spacy | |
| import streamlit as st | |
| # Load your trained SpaCy NER model | |
| nlp = spacy.load('my_ner') | |
| # Define a function to perform NER on user input | |
| def predict_ner(text): | |
| doc = nlp(text) | |
| ents = [(ent.text, ent.label_) for ent in doc.ents] | |
| return ents | |
| # Create the Streamlit app | |
| def main(): | |
| st.title("SpaCy NER Demo") | |
| # Add a text input for users to input their text | |
| text = st.text_input("Enter some text:") | |
| # If the user has entered some text, show the NER predictions | |
| if text: | |
| st.write("Predictions:") | |
| ents = predict_ner(text) | |
| for ent in ents: | |
| st.write(ent) | |
| if __name__ == '__main__': | |
| main() | |