Upload 3 files

fast_api.py

@@ -0,0 +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)

model_pipeline.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:04706238f5c6f50ec5461057a6d9a12e7a8c90cdf86a084b0f496769a31094bd
+size 103024

requirements.txt

@@ -0,0 +1,7 @@
+fastapi
+uvicorn
+joblib
+numpy
+pandas
+scikit-learn
+xgboost