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from fastapi import FastAPI, Request |
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from pydantic import BaseModel |
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import joblib |
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import uvicorn |
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import numpy as np |
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import pandas as pd |
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app = FastAPI() |
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model = joblib.load("model_pipeline.pkl") |
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class CustomerInput(BaseModel): |
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credit_score: int |
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country: str |
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gender: str |
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age: int |
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tenure: int |
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balance: float |
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products_number: int |
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credit_card: int |
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active_member: int |
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estimated_salary: float |
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@app.get("/") |
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def read_root(): |
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return {"message": "Model REST API is up!"} |
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@app.post("/predict") |
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def predict_customer(input: CustomerInput): |
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data = input.dict() |
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df = pd.DataFrame([data]) |
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prediction = model.predict(df) |
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return {"prediction": int(prediction[0])} |
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if __name__ == "__main__": |
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uvicorn.run(app, host="0.0.0.0", port=7860) |