Adding files

Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["sepsis", "serve", "--address", "0.0.0.0", "--port", "7860" , "--allow-websocket-origin" , "Henok21-Sepsis-Prediction-in-Docker.hf.space"]

app.py

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+# For app development
+from typing import Annotated
+from fastapi import FastAPI, Form, Depends
+import pandas as pd
+import uvicorn
+from pydantic import BaseModel
+# For data frame
+import pandas as pd
+# For loading pipeline
+import pickle
+# For controlling warnings
+import warnings
+warnings.filterwarnings('ignore')
+
+# Pieline loading
+with open("..\\notebook\\pipeline.pkl", "rb") as f:
+    pipe = pickle.load(f) 
+
+app = FastAPI( title = "The classification API for predicting Sepsis positve / negative") # instantiating fastAPI object
+
+@app.get("/")
+async def root():
+    return {
+        "Info" : "The classification API for predicting Sepsis positve / Negative"
+    }
+
+# Class inherits from BaseModel to be used as pydantic model
+class Sepssis(BaseModel):
+    # Input features
+    plasma_glucose : float
+    Blood_work_result_1 : float
+    Blood_pressure : float
+    Blood_work_result_2 : float
+    Blood_work_result_3 : float
+    Body_mass_index : float
+    Blood_work_result_4 : float
+    Age : int
+    Insurance : int
+
+    @classmethod
+    def as_form(
+        cls,
+        plasma_glucose: float = Form(...), # "..." means the form is required
+        Blood_work_result_1: float = Form(...),
+        Blood_pressure: float = Form(...),
+        Blood_work_result_2: float = Form(...),
+        Blood_work_result_3: float = Form(...),
+        Body_mass_index: float = Form(...),
+        Blood_work_result_4: float = Form(...),
+        Age: float = Form(...),
+        Insurance: float = Form(...)
+    ) -> "Sepssis":      # Forward reference
+        return cls(
+            plasma_glucose=plasma_glucose,
+            Blood_work_result_1=Blood_work_result_1,
+            Blood_pressure=Blood_pressure,
+            Blood_work_result_2=Blood_work_result_2,
+            Blood_work_result_3=Blood_work_result_3,
+            Body_mass_index=Body_mass_index,
+            Blood_work_result_4=Blood_work_result_4,
+            Age=Age,
+            Insurance=Insurance
+        )
+
+@app.post("/dataframe/") 
+async def create_dataframe(form_data: Sepssis = Depends(Sepssis.as_form)):
+    try:
+        # Convert the form data to a data frame
+        df = pd.DataFrame(form_data.dict(), index=[0])
+
+        # Predicting...
+        output = pipe.predict_proba(df)
+               
+        df["predicted_label"] = output.argmax(axis = -1)
+        mapping = {0: "Sepsis Negative", 1: "Sepsis Positive"}
+        df["predicted_label"] = [mapping[x] for x in df["predicted_label"]]
+
+        # Calculating confidence score
+        confidence_score = output.max(axis= -1)
+        df["confidence_score"] = f"{round( ( confidence_score[0] * 100 ) , 2) }%"
+        
+        # Creating a display output
+        msg = "execution went fine"
+        code = 1
+        pred = df.to_dict("records")
+
+        result = { "Execution Message " : msg , "Execution Code " : code , "Prediction" : pred }
+
+    except Exception as e:
+        # If there is an error...
+        msg = "execution went wrong"
+        code = 0
+        pred = None
+
+        result = { "Error" : str(e) , "Execution Message " : msg , "Execution Code " : code , "Prediction" : pred }
+
+    return result
+
+# Running automaticaly when there is a change
+if __name__ == "__main__":
+    uvicorn.run("app:app" , reload = True)

requirements.txt

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+fastapi
+pandas
+pickle