Updating doc strings for evaluate API

src/promptflow-evals/promptflow/evals/evaluate/_evaluate.py

@@ -269,12 +269,13 @@ def evaluate(
     target: Optional[Callable] = None,
     data: Optional[str] = None,
     evaluators: Optional[Dict[str, Callable]] = None,
-    evaluator_config: Optional[Dict[str, Dict[str, str]]] = {},
+    evaluator_config: Optional[Dict[str, Dict[str, str]]] = None,
     azure_ai_project: Optional[Dict] = None,
     output_path: Optional[str] = None,
     **kwargs,
 ):
-    """Evaluates target or data with built-in evaluation metrics
+    """Evaluates target or data with built-in or custom evaluators. If both target and data are provided,
+        data will be run through target function and then results will be evaluated.
 
     :keyword evaluation_name: Display name of the evaluation.
     :paramtype evaluation_name: Optional[str]
@@ -283,21 +284,35 @@ def evaluate(
     :keyword data: Path to the data to be evaluated or passed to target if target is set.
         Only .jsonl format files are supported.  `target` and `data` both cannot be None
     :paramtype data: Optional[str]
-    :keyword evaluator_config: Configuration for evaluators.
+    :keyword evaluators: Evaluators to be used for evaluation. It should be a dictionary with key as alias for evaluator
+        and value as the evaluator function.
+    :paramtype evaluators: Optional[Dict[str, Callable]
+    :keyword evaluator_config: Configuration for evaluators. The configuration should be a dictionary with evaluator
+        names as keys and a dictionary of column mappings as values. The column mappings should be a dictionary with
+        keys as the column names in the evaluator input and values as the column names in the input data or data
+        generated by target.
     :paramtype evaluator_config: Optional[Dict[str, Dict[str, str]]
-    :keyword output_path: The local folder path to save evaluation artifacts to if set
+    :keyword output_path: The local folder or file path to save evaluation results to if set. If folder path is provided
+          the results will be saved to a file named `evaluation_results.json` in the folder.
     :paramtype output_path: Optional[str]
     :keyword azure_ai_project: Logs evaluation results to AI Studio
+        Example: {
+                "subscription_id": "<subscription_id>",
+                "resource_group_name": "<resource_group_name>",
+                "project_name": "<project_name>"
+        }
     :paramtype azure_ai_project: Optional[Dict]
-    :return: A EvaluationResult object.
-    :rtype: ~azure.ai.generative.evaluate.EvaluationResult
+    :return: Evaluation results.
+    :rtype: dict
     """
 
     trace_destination = _trace_destination_from_project_scope(azure_ai_project) if azure_ai_project else None
 
     input_data_df = _validate_and_load_data(target, data, evaluators, output_path, azure_ai_project, evaluation_name)
 
     # Process evaluator config to replace ${target.} with ${data.}
+    if evaluator_config is None:
+        evaluator_config = {}
     evaluator_config = _process_evaluator_config(evaluator_config)
     _validate_columns(input_data_df, evaluators, target, evaluator_config)