app.py

import gradio as gr

from interfaces.cap import demo as cap_demo
from interfaces.manifesto import demo as manifesto_demo
from interfaces.sentiment import demo as sentiment_demo
from interfaces.emotion import demo as emotion_demo

with gr.Blocks() as demo:
 gr.Markdown(
 """
 <div style="display: block; text-align: left; padding:0; margin:0;">
 <h1 style="text-align: center">Babel Machine Demo</h1>
 <p>This is a demo for text classification using language models finetuned on data labeled by <a href="https://www.comparativeagendas.net/">CAP</a>, <a href="https://manifesto-project.wzb.eu/">Manifesto Project</a>, sentiment, and emotion coding systems.<br>
 For the coding of complete datasets, please visit the official <a href="https://babel.poltextlab.com/">Babel Machine</a> site.</p>
 </div>
 """)

 gr.TabbedInterface(
 interface_list=[cap_demo, manifesto_demo, sentiment_demo, emotion_demo],
 tab_names=["CAP", "Manifesto", "Sentiment (3)", "Emotions (8)"],
 )

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

# TODO: add all languages & domains