app.py

from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
import gradio as gr

# Load pre-trained model and tokenizer
model_name = "ferrazzipaulo/biobert-drug-interactions"
pipe = pipeline("text-classification", model=model_name)

def predict_drug_interaction(text):
    result = pipe(text)
    return result[0]['label'], result[0]['score']

demo = gr.Interface(
    fn=predict_drug_interaction,
    inputs=gr.Textbox(label="Enter a biomedical sentence"),
    outputs=[
        gr.Label(label="Prediction"),
        gr.Number(label="Confidence Score")
    ],
    title="Drug Interaction Predictor",
    description="Detects whether two drugs are likely to interact based on biomedical text."
)

demo.launch()