Initial Iris inference API

handler.py

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+import joblib
+import numpy as np
+
+model = joblib.load("model.joblib")
+labels = ["setosa", "versicolor", "virginica"]
+
+def predict(inputs):
+    features = np.array([[
+        inputs["sepal_length"],
+        inputs["sepal_width"],
+        inputs["petal_length"],
+        inputs["petal_width"]
+    ]])
+
+    probs = model.predict_proba(features)[0]
+    idx = probs.argmax()
+
+    return {
+        "class": labels[idx],
+        "confidence": float(probs[idx])
+    }

model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0cdf06e4de7d0c545424af5b7df04989dcf05f4bcc2e295ef444193d82aee315
+size 186737

requirements.txt

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+scikit-learn
+joblib
+numpy