Create app.py

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import joblib
+import numpy as np
+import json
+from huggingface_hub import hf_hub_download
+
+# Download model artifacts from the model repo
+MODEL_REPO = "shahviransh/fraud-detection"
+MODEL_FILE = "fraud_detection_model.pkl"
+
+model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILE)
+model = joblib.load(model_path)
+
+
+def predict(input_json):
+    """
+    input_json expected format:
+    {
+      "features": [f1, f2, f3, ...]
+    }
+    """
+
+    try:
+        data = json.loads(input_json)
+        features = np.array(data["features"]).reshape(1, -1)
+
+        pred = model.predict(features)[0]
+        prob = model.predict_proba(features)[0].tolist()
+
+        return {
+            "prediction": int(pred),
+            "probabilities": prob
+        }
+    except Exception as e:
+        return {"error": str(e)}
+
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(label="JSON Input"),
+    outputs="json",
+    title="Fraud Detection API",
+    description="Submit JSON payload containing numerical features."
+)
+
+if __name__ == "__main__":
+    iface.launch()