return

app/main.py

@@ -1,10 +1,9 @@
-from fastapi import FastAPI, Request
+from fastapi import FastAPI
 from pydantic import BaseModel
 import pickle
 import pandas as pd
 import numpy as np
 import uvicorn
-import json
 
 # call the app
 app = FastAPI(title="API")
@@ -64,42 +63,24 @@ class Patients(BaseModel):
 # Endpoints
 # Root Endpoint
 @app.get("/")
-def root(request: Request):
-    content = await request.json()
-    response = {}
-
-    if "endpoint" in content:
-        endpoint = content["endpoint"]
-
-        if endpoint == "predict":
-            if "patient" in content:
-                patient_data = content["patient"]
-                patient = Patient(**patient_data)
-                prediction = predict_sepsis(patient)
-                response["prediction"] = prediction
-
-        elif endpoint == "predict_multiple":
-            if "patients" in content:
-                patients_data = content["patients"]
-                patients = Patients(**patients_data)
-                prediction = predict_sepsis_for_multiple_patients(patients)
-                response["prediction"] = prediction
-
-    return response
+def root():
+    return {"Welcome to the Sepsis Prediction API! This API provides endpoints for predicting sepsis based on patient data."}    
 
 # Prediction endpoint
+@app.post("/predict")
 def predict_sepsis(patient: Patient):
     # Make prediction
     data = pd.DataFrame(patient.dict(), index=[0])
     parsed = predict(df=data)
-    return parsed
+    return {"output": parsed}
 
 # Multiple Prediction Endpoint
+@app.post("/predict_multiple")
 def predict_sepsis_for_multiple_patients(patients: Patients):
     """Make prediction with the passed data"""
     data = pd.DataFrame(Patients.return_list_of_dict(patients))
     parsed = predict(df=data, endpoint="multi")
-    return parsed
+    return {"output": parsed}
 
 if __name__ == "__main__":
-    uvicorn.run("main:app", reload=True)
+    uvicorn.run("main:app", reload=True)