Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load your trained model
+model_path = "./excuse_nonexcuse_classifier_model"
+classifier = pipeline("text-classification", model=model_path)
+
+# Map numeric labels to readable form
+id2label = {"LABEL_0": "not_excuse", "LABEL_1": "excuse"}
+
+# Inference function
+def classify_user_input(user_message):
+    result = classifier(user_message)[0]
+    label = id2label.get(result["label"], result["label"])
+    confidence = round(result["score"] * 100, 2)
+    return f"Prediction: {label}\nConfidence: {confidence}%"
+
+# Gradio interface
+demo = gr.Interface(
+    fn=classify_user_input,
+    inputs=gr.Textbox(
+        lines=4, 
+        placeholder="Type your excuse or message here...",
+        label="Your Message"
+    ),
+    outputs=gr.Textbox(label="Classification Result"),
+    title="🧠 Excuse Classifier",
+    description="Type any message below and see if it's classified as an excuse or not.",
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()