Update how-to-use-mlflow-cli-runs.md

Author: santiagxf

articles/machine-learning/how-to-use-mlflow-cli-runs.md

@@ -240,27 +240,29 @@ Select the logged metrics to render charts on the right side. You can customize
 
 You can also access or __query metrics, parameters and artifacts programatically__ using the MLflow SDK. Use [mlflow.get_run()](https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.get_run) as explained bellow:
 
-> [!TIP]
-> For more details about how to retrieve information from experiments and runs in Azure Machine Learning using MLflow view [Query & compare experiments and runs with MLflow](how-to-track-experiments-mlflow.md).
-
 ```python
 import mlflow
 
 run = mlflow.get_run("<RUN_ID>")
 
 metrics = run.data.metrics
-tags = run.data.tags
 params = run.data.params
+tags = run.data.tags
 
-print(metrics,tags,params)
+print(metrics, params, tags)
 ```
 
+> [!TIP]
+> For metrics, the previous example will only return the last value of a given metric. If you want to retrieve all the values of a given metric, use `mlflow.get_metric_history` method as explained at [Getting params and metrics from a run](how-to-track-experiments-mlflow.md#getting-params-and-metrics-from-a-run).
+
 To download artifacts you have logged, like files and models, you can use [mlflow.artifacts.download_artifacts()](https://www.mlflow.org/docs/latest/python_api/mlflow.artifacts.html#mlflow.artifacts.download_artifacts)
 
 ```python
 mlflow.artifacts.download_artifacts(run_id="<RUN_ID>", artifact_path="helloworld.txt")
 ```
 
+For more details about how to __retrieve or compare__ information from experiments and runs in Azure Machine Learning using MLflow view [Query & compare experiments and runs with MLflow](how-to-track-experiments-mlflow.md)
+
 ## Example notebooks
 
 If you are looking for examples about how to use MLflow in Jupyter notebooks, please see our example's repository [Using MLflow (Jupyter Notebooks)](https://github.com/Azure/azureml-examples/tree/main/sdk/python/using-mlflow).