Create app.py

app.py

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+import gradio as gr
+from setfit import SetFitModel
+
+try:
+    transactional_model = SetFitModel.from_pretrained("edugargar/risk_model")
+except Exception as e:
+    raise RuntimeError("Failed to load model: " + str(e))
+
+def predict_and_score(text):
+    preds = transactional_model([text])
+    predicted_class = preds[0]
+    probs = transactional_model.predict_proba([text])
+    probability_distribution = probs[0]
+    probability_str = ", ".join(f"{p:.4f}" for p in probability_distribution)
+    return predicted_class, probability_str
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Risk Model Prediction")
+    text_input = gr.Textbox(label="Enter your text here:")
+    predict_button = gr.Button("Predict")
+    prediction_output = gr.Textbox(label="Predicted Class:")
+    score_output = gr.Textbox(label="Score (Probability Distribution):")
+
+    predict_button.click(fn=predict_and_score, 
+                         inputs=[text_input], 
+                         outputs=[prediction_output, score_output])
+
+
+demo.launch()