app.py

from transformers import pipeline
import gradio as gr
completion_pipeline=pipeline("ner", model="dslim/bert-base-NER")
def merge_tokens(tokens):
    merged_tokens = []
    for token in tokens:
        if merged_tokens and token['entity'].startswith('I-') and merged_tokens[-1]['entity'].endswith(token['entity'][2:]):
            # If current token continues the entity of the last one, merge them
            last_token = merged_tokens[-1]
            last_token['word'] += token['word'].replace('##', '')
            last_token['end'] = token['end']
            last_token['score'] = (last_token['score'] + token['score']) 
        else:
            # Otherwise, add the token to the list
            merged_tokens.append(token)

    return merged_tokens

def ner(input):
    output = completion_pipeline(input)
    merged_tokens = merge_tokens(output)
    return {"text": input, "entities": merged_tokens}

demo = gr.Interface(fn=ner,
                    inputs=[gr.Textbox(label="Text to find entities", lines=2)],
                    outputs=[gr.HighlightedText(label="Text with entities")],
                    title="Named Entity",
                    description="You can use this application for finding entities in your data.",
                    allow_flagging="never",
                    examples=["My name is Sakil Ansari, I'm watching movies", "Nepal is a beautiful country.",
                              "Batman is a great character.",
                              "Murphy was the first cast member to sign the film."])

demo.launch()