app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForTokenClassification
from pipeline import DiscoursePipeline  # ton code custom

model_id = "poyum/test_discut"
tokenizer = AutoTokenizer.from_pretrained(model_id)
pipe = DiscoursePipeline(model_id=model_id, tokenizer=tokenizer)

def predict(text):
    return pipe(text)

demo = gr.Interface(fn=predict, inputs="text", outputs="text")
demo.launch()