Update app.py

app.py

@@ -1,39 +1,39 @@
-from fastapi import FastAPI, Request
-from pydantic import BaseModel
-import joblib
-import uvicorn
-import numpy as np
-import pandas as pd
-
-app = FastAPI()
-
-# Load model (ganti dengan path model kamu)
-model = joblib.load("model_pipeline.pkl")
-
-# Define input format
-class CustomerInput(BaseModel):
-    credit_score: int
-    country: str
-    gender: str
-    age: int
-    tenure: int
-    balance: float
-    products_number: int
-    credit_card: int
-    active_member: int
-    estimated_salary: float
-
-@app.get("/")
-def read_root():
-    return {"message": "Model REST API is up!"}
-
-@app.post("/predict")
-def predict_customer(input: CustomerInput):
-    data = input.dict()
-    df = pd.DataFrame([data])  # bentuk tabular
-    prediction = model.predict(df)
-    return {"prediction": int(prediction[0])}
-
-# Only needed for local testing
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+from fastapi import FastAPI, Request
+from pydantic import BaseModel
+import joblib
+import uvicorn
+import numpy as np
+import pandas as pd
+
+app = FastAPI()
+
+# Load model (ganti dengan path model kamu)
+model = joblib.load("model_pipeline.pkl")
+
+# Define input format
+class CustomerInput(BaseModel):
+    credit_score: int
+    country: str
+    gender: str
+    age: int
+    tenure: int
+    balance: float
+    products_number: int
+    credit_card: int
+    active_member: int
+    estimated_salary: float
+
+@app.get("/")
+def read_root():
+    return {"message": "Model REST API is up!"}
+
+@app.post("/predict")
+def predict_customer(input: CustomerInput):
+    data = input.dict()
+    df = pd.DataFrame([data])  # bentuk tabular
+    prediction = model.predict(df)
+    return {"prediction": int(prediction[0])}
+
+# Only needed for local testing
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)