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import gradio as gr
from transformers import pipeline
from utils import *
pipe = pipeline(model="raminass/scotus-v10", top_k=13, padding=True, truncation=True)
max_textboxes = 100
# https://www.gradio.app/guides/controlling-layout
def greet(opinion):
chunks = chunk_data(remove_citations(opinion))["text"].to_list()
result = average_text(chunks, pipe)
k = len(chunks)
wrt_boxes = []
for i in range(k):
wrt_boxes.append(gr.Textbox(chunks[i], visible=True))
wrt_boxes.append(gr.Label(value=result[1][i], visible=True))
return (
[result[0]]
+ wrt_boxes
+ [gr.Textbox(visible=False), gr.Label(visible=False)] * (max_textboxes - k)
)
with gr.Blocks() as demo:
opinion = gr.Textbox(label="Opinion")
op_level = gr.outputs.Label(num_top_classes=13, label="Overall")
greet_btn = gr.Button("Predict")
textboxes = []
for i in range(max_textboxes):
t = gr.Textbox(f"Textbox {i}", visible=False, label=f"Paragraph {i+1} Text")
par_level = gr.Label(
num_top_classes=5, label=f"Paragraph {i+1} Prediction", visible=False
)
textboxes.append(t)
textboxes.append(par_level)
greet_btn.click(
fn=greet,
inputs=opinion,
outputs=[op_level] + textboxes,
)
if __name__ == "__main__":
demo.launch()
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