import gradio as gr
from acrobert import acronym_linker


def greet(sentence):
    results = acronym_linker(sentence, mode='acrobert')
    return results


sample_list = [
    "The LDA is an example of a topic model.",
    "Using a camera sensor, LDA judges the position of your vehicle in relation to the road markings below. This keeps the driver consistently aware of their situation, so that corrective action can be taken when needed.",
    "AI is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. ",
    "In the United States, the AI for potassium for adults is 4.7 grams",
    "A whistleblower like monologist Mike Daisey gets targeted as a scapegoat who must
    be discredited and diminished in the public eyes. More often than not, PR is
    a preemptive process. Celebrity publicists are paid lots of money to keep certain
    stories out of the news.",
    "This new genome assembly and the annotation are tagged as a RefSeq genome by NCBI and thus provide substantially enhanced genomic resources for future research involving S. scovelli.",
    "In this study, we found that miR-34a demonstrated greater expression in the lungs of patients with IPF and in mice with experimental pulmonary fibrosis , with its primary localization in lung fibroblasts.",
]

iface = gr.Interface(fn=greet, inputs="text", outputs="text", examples=sample_list, cache_examples=False)
iface.launch()