upload files

.gitignore

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+myvenv

Dockerfile

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+FROM python:3.9-slim
+
+WORKDIR /app
+
+COPY ./models/sepssis_model_v1.pkl /app/models/sepssis_model_v1.pkl
+Copy ./requirements.txt /app/requirements.txt
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY ./app /app
+
+EXPOSE 8000
+
+CMD ["uvicorn", "main:app", "--host","0.0.0.0","--port","8000"]

app/main.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+import joblib 
+import numpy as np 
+
+
+class SepssisInput(BaseModel):
+    PRG:float
+    PL:float	
+    PR:float	
+    SK:float	
+    TS:float	
+    M11:float
+    Age:float	
+    Insurance:int
+
+
+model=joblib.load("models/sepssis_model_v1.pkl")
+
+app=FastAPI()
+
+
+@app.get("/")
+def home_page():
+    return "Welcome to the API "
+
+
+@app.post("/predict")
+def inference_sepssis(sepssis_features:SepssisInput):
+    input_data=np.array([[
+        sepssis_features.PRG,
+        sepssis_features.PL,
+        sepssis_features.PR,
+        sepssis_features.SK,
+        sepssis_features.TS,
+        sepssis_features.M11,
+        sepssis_features.Age,
+        sepssis_features.Insurance
+    ]])
+
+    label_predict=model.predict(input_data)
+
+    sepssis_mapping={
+        0:"Negative",
+        1:"Positive"
+    }
+    
+    clase_predict=sepssis_mapping[label_predict[0]]
+    return {"Predict_for_Sepssis":clase_predict}
+		

models/sepssis_model_v1.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4cd86d3763f4106af99664f1b62b7cde8eb857de037c0dbfde9f1bc142d511a7
+size 856265

requirements.txt

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+joblib==1.3.2
+scikit-learn==1.2.2
+fastapi
+uvicorn
+