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from fastapi import FastAPI, HTTPException, Query
import pandas as pd
import joblib
app = FastAPI()
# Load the sepsis prediction model
model = joblib.load('XGB.joblib')
@app.get("/")
async def read_root():
return {"message": "Sepsis Prediction API using FastAPI"}
def classify(prediction):
if prediction == 0:
return "Patient does not have sepsis"
else:
return "Patient has sepsis"
@app.get("/predict/")
async def predict_sepsis(
prg: float = Query(..., description="Plasma glucose"),
pl: float = Query(..., description="Blood Work Result-1 (mu U/ml)"),
pr: float = Query(..., description="Blood Pressure (mm Hg)"),
sk: float = Query(..., description="Blood Work Result-2 (mm)"),
ts: float = Query(..., description="Blood Work Result-3 (mu U/ml)"),
m11: float = Query(..., description="Body mass index (weight in kg/(height in m)^2"),
bd2: float = Query(..., description="Blood Work Result-4 (mu U/ml)"),
age: int = Query(..., description="Patient's age (years)")
):
input_data = [prg, pl, pr, sk, ts, m11, bd2, age]
input_df = pd.DataFrame([input_data], columns=[
"Plasma glucose", "Blood Work Result-1", "Blood Pressure",
"Blood Work Result-2", "Blood Work Result-3",
"Body mass index", "Blood Work Result-4", "Age"
])
pred = model.predict(input_df)
output = classify(pred[0])
response = {
"prediction": output
}
return response
# Run the app using Uvicorn
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="127.0.0.1", port=7860) |