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import gradio as gr
from gradio_client import Client
client = Client("Iker/FactChecking-Backend")
def fact_checking(
article_topic: str,
):
result = client.predict(article_topic=article_topic, api_name="/partial")
return result
if __name__ == "__main__":
theme = gr.themes.Soft(
primary_hue="green",
secondary_hue="gray",
neutral_hue="neutral",
font=[
gr.themes.GoogleFont("Poppins"),
gr.themes.GoogleFont("Poppins"),
gr.themes.GoogleFont("Poppins"),
gr.themes.GoogleFont("Poppins"),
],
font_mono=[
gr.themes.GoogleFont("Poppins"),
gr.themes.GoogleFont("Poppins"),
gr.themes.GoogleFont("Poppins"),
gr.themes.GoogleFont("Poppins"),
],
).set(
body_text_color="*secondary_600",
button_border_width="*block_label_border_width",
button_primary_background_fill="*primary_600",
button_secondary_background_fill="*primary_500",
button_secondary_background_fill_hover="*primary_400",
button_secondary_border_color="*primary_500",
)
with gr.Blocks(
theme=theme,
title="🤖 Automated Fact-Checking Engine",
analytics_enabled=False,
) as demo:
gr_text = gr.Textbox(
label="Fact-Checking Statement",
# info="Write here the statement you want to fact-check",
show_label=False,
lines=1,
interactive=True,
placeholder="Electric cars produce more contamination than petrol cars",
)
gr_play = gr.Button("Fact-Checking")
gr_output = gr.Markdown(
label="Fact-Checking Results",
visible=True,
)
gr_ft = gr.Textbox(
label="fact_checking",
info="String with fact checking text",
lines=1,
interactive=False,
visible=False,
)
gr_qa = gr.Textbox(
label="qa",
info="Questions and answers, first line is the question, second line is the answer, and so on",
lines=1,
interactive=False,
visible=False,
)
gr_citations = gr.Textbox(
label="citations",
info="Here you will see the citations, first line is the citation id, second line is the url, and so on",
lines=1,
interactive=False,
visible=False,
)
gr_image = gr.Textbox(
label="image",
info="Contains the image url",
interactive=False,
visible=False,
)
gr_play.click(
fact_checking,
inputs=[gr_text],
outputs=[gr_output, gr_ft, gr_qa, gr_citations, gr_image],
)
demo.queue(default_concurrency_limit=1)
demo.launch()
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