add comments to deploy-ml-model/app.py

deploy-ml-model/app.py

@@ -3,21 +3,26 @@
 import pandas as pd
 from fastapi import FastAPI
 
+# Load the pre-trained machine learning model
 model = joblib.load("iris_classifier.joblib")
 
+# Create a FastAPI app instance with custom configuration
 app = FastAPI(docs_url="/", root_path=os.getenv("TFY_SERVICE_ROOT_PATH", "/"))
 
-
+# Define an API endpoint for making predictions
 @app.post("/predict")
 def predict(
     sepal_length: float, sepal_width: float, petal_length: float, petal_width: float
 ):
+    # Create a dictionary with input data
     data = dict(
         sepal_length=sepal_length,
         sepal_width=sepal_width,
         petal_length=petal_length,
         petal_width=petal_width,
     )
+    # Make a prediction using the loaded model
     prediction = int(model.predict(pd.DataFrame([data]))[0])
+    # Return the prediction as a JSON response
     return {"prediction": prediction}