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| import gradio as gr | |
| import spacy | |
| from spacy import displacy | |
| from spacy.tokens import Span | |
| from random import randint | |
| from fastcoref import LingMessCoref | |
| model = LingMessCoref() | |
| nlp = spacy.blank("en") | |
| default = "Lionel Messi has won a record seven Ballon d'Or awards. He signed for Paris Saint-Germain in August 2021. “I would like to thank my family” said the Argentinian footballer. Messi holds the records for most goals in La Liga. Paris Saint-Germain hopes he will do the same in Ligue 1." | |
| def corefer(text): | |
| preds = model.predict(texts=[text]) | |
| clusters = preds[0].get_clusters(as_strings=False) | |
| doc = nlp(text) | |
| doc.spans["sc"] = [] | |
| colors = {"Cluster {}".format(i):'#%06X' % randint(0, 0xFFFFFF) for i in range(len(clusters))} | |
| for i, cluster in enumerate(clusters): | |
| for sp in cluster: | |
| doc.spans["sc"] += [doc.char_span(sp[0], sp[1], "Cluster {}".format(i))] | |
| return displacy.render(doc, style="span", options= {"colors":colors }, page=True ) | |
| iface = gr.Interface(fn=corefer, | |
| inputs=gr.Textbox(label="Enter Text To Corefer with FastCoref", lines=2, value=default), | |
| outputs="html") | |
| iface.launch() |