app.py

import gradio as gr
from transformers import pipeline
from transformers import SummarizationPipeline

#summarizer = SummarizationPipeline(model="hamzamalik11/Biobart_radiology_summarization", task="summarization", tokenizer="hamzamalik11/Biobart_radiology_summarization")

pipeline = pipeline(task="summarization", model="hamzamalik11/Biobart_radiology_summarization")

def greet(RADIOLOGY_REPORT):
     summary_output= pipeline(RADIOLOGY_REPORT)
     return summary_output

findings_examples = [
    "prevoid bladder volume cc postvoid bladder volume cc bladder grossly normal appearance",
    "heart mediastinal contours normal left sided subclavian line position tip distal svc lungs remain clear active disease effusions",
    '''heart size normal mediastinal hilar contours remain stable small right pneumothorax remains unchanged surgical lung staples overlying
    left upper lobe seen linear pattern consistent prior upper lobe resection soft tissue osseous structures appear unremarkable nasogastric
    endotracheal tubes remain satisfactory position atelectatic changes right lower lung field remain unchanged prior study''',
]

radiology_demo = gr.Interface(fn=greet, inputs="text", outputs="text",
    examples=findings_examples,
    description="""                                                                -------------RADIOLOGY REPORT SUMMARIZATION----------------
                                                    ENTER YOUR FINDINGS IN RADIOLOGY REPORT SECTION  &  MODEL WILL PROVIDE YOU IMPRESSIONS AS AN OUTPUT""",

)

demo = gr.TabbedInterface([radiology_demo])

if __name__ == "__main__":
    demo.launch( share = True)