app.py

import gradio as gr
from transformers import pipeline

# Load the pre-trained BioBERT model for NER
nlp_ner = pipeline("ner", model="dmis-lab/biobert-base-cased-v1.1", tokenizer="dmis-lab/biobert-base-cased-v1.1")

def ner_micobiology(abstract):
    entities = nlp_ner(abstract)
    return entities

# Gradio Interface for NER
iface = gr.Interface(
    fn=ner_micobiology, 
    inputs=gr.Textbox(label="Enter Microbiology Abstract", placeholder="Paste or type your microbiology abstract here..."),
    outputs="json",
    live=True, 
    title="Microbiology Named Entity Recognition with BioBERT",
    description="Extract named entities from your microbiology abstract using BioBERT for NER."
)

# Launch the Gradio interface
if __name__ == "__main__":
    iface.launch()