Hook clara to UI

app.py

@@ -1,7 +1,33 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load a text classification model
+# Replace with your model's path or Hugging Face model name
+model = pipeline(task="text-classification", model="adrienhongcs/clara-0")
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+def predict(input_text):
+    # Get predictions from the model
+    predictions = model(input_text)
+    
+    # Extract the label and score
+    label = predictions[0]["label"]
+    score = predictions[0]["score"]
+    
+    # Return the label and score
+    return label, score
+
+# Create the Gradio interface
+gradio_app = gr.Interface(
+    fn=predict,  # Function to call
+    inputs=gr.Textbox(label="Enter a deduction backup doc text"),  # Text input
+    outputs=[
+        gr.Textbox(label="Predicted Reason"),  # Output for the label
+        gr.Number(label="Confidence Score")   # Output for the score
+    ],
+    title="Clara the reason classifier",
+    description="Enter a deduction backup (as text) to classify it and get the predicted label and confidence score."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    gradio_app.launch()