chore: import upstream snapshot with attribution

examples/pyfunc/model_as_code_driver.py

@@ -0,0 +1,28 @@
+# This is an example for logging a Python model from code using the
+# mlflow.pyfunc.log_model API. When a path to a valid Python script is submitted to the
+# python_model argument, the model code itself is serialized instead of the model object.
+# Within the targeted script, the model implementation must be defined and set by
+# using the mlflow.models.set_model API.
+
+import pandas as pd
+
+import mlflow
+
+input_example = ["What is the weather like today?"]
+
+# Specify the path to the model notebook
+model_path = "model_as_code.py"
+print(f"Model path: {model_path}")
+
+print("Logging model as code using Pyfunc log model API")
+with mlflow.start_run():
+    model_info = mlflow.pyfunc.log_model(
+        python_model=model_path,
+        name="ai-model",
+        input_example=input_example,
+    )
+
+print("Loading model using Pyfunc load model API")
+pyfunc_model = mlflow.pyfunc.load_model(model_info.model_uri)
+output = pyfunc_model.predict(pd.DataFrame(input_example, columns=["input"]))
+print(f"Output: {output}")