Create app.py

app.py

@@ -0,0 +1,55 @@
+import gradio as gr
+import torch
+import numpy as np
+import json
+from huggingface_hub import hf_hub_download
+
+REPO = "gabrielnkl/model-fraud-detect"
+MODEL = "model.pt"
+
+model_path = hf_hub_download(repo_id=REPO, filename=MODEL)
+model = torch.jit.load(model_path)
+model.eval()
+
+TYPE_MAP = {
+    "PAYMENT": 0,
+    "TRANSFER": 1,
+    "CASH_OUT": 2,
+    "DEBIT": 3,
+    "CASH_IN": 4
+}
+
+def predict(json_input):
+
+    try:
+        d = json.loads(json_input)
+
+        amount = float(d["amount"])
+        old = float(d["oldbalanceOrg"])
+        new = float(d["newbalanceOrig"])
+        t = TYPE_MAP[d["type"]]
+
+        x = np.array([[amount, old, new, t]], dtype=np.float32)
+        tensor = torch.from_numpy(x)
+
+        prob = float(model(tensor).item())
+        pred = int(prob > 0.5)
+
+        return {
+            "prediction": pred,
+            "fraud_probability": round(prob, 4)
+        }
+
+    except Exception as e:
+        return {"error": str(e)}
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(lines=8, label="JSON Input"),
+    outputs="json",
+    title="Fraud Detection API"
+)
+
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)
+