Fix content safety unit tests

src/promptflow-evals/promptflow/evals/evaluators/_coherence/_coherence.py

@@ -4,7 +4,6 @@
 
 import os
 import re
-from typing import Dict
 
 import numpy as np
 
@@ -24,9 +23,7 @@ def __init__(self, model_config: AzureOpenAIModelConfiguration):
 
         prompty_model_config = {"configuration": model_config}
         if USER_AGENT and isinstance(model_config, AzureOpenAIModelConfiguration):
-            prompty_model_config.update(
-                {"parameters": {"extra_headers": {"x-ms-useragent": USER_AGENT}}}
-            )
+            prompty_model_config.update({"parameters": {"extra_headers": {"x-ms-useragent": USER_AGENT}}})
         current_dir = os.path.dirname(__file__)
         prompty_path = os.path.join(current_dir, "coherence.prompty")
         self._flow = AsyncPrompty.load(source=prompty_path, model=prompty_model_config)
@@ -79,7 +76,7 @@ class CoherenceEvaluator:
     def __init__(self, model_config: AzureOpenAIModelConfiguration):
         self._async_evaluator = _AsyncCoherenceEvaluator(model_config)
 
-    def __call__(self, *, question: str, answer: str, **kwargs) -> Dict[str, float]:
+    def __call__(self, *, question: str, answer: str, **kwargs):
         """
         Evaluate coherence.
 

src/promptflow-evals/promptflow/evals/evaluators/_content_safety/_content_safety_sub_evaluator_base.py

@@ -2,7 +2,6 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # ---------------------------------------------------------
 from abc import ABC
-from typing import Dict, List
 
 try:
     from .common.constants import EvaluationMetrics
@@ -24,7 +23,7 @@ class ContentSafetySubEvaluatorBase(ABC):
     :type metric: ~promptflow.evals.evaluators._content_safety.flow.constants.EvaluationMetrics
     :param project_scope: The scope of the Azure AI project.
         It contains subscription id, resource group, and project name.
-    :type project_scope: dict
+    :type project_scope: Dict
     :param credential: The credential for connecting to Azure AI project.
     :type credential: TokenCredential
     """
@@ -34,7 +33,7 @@ def __init__(self, metric: EvaluationMetrics, project_scope: dict, credential=No
         self._project_scope = project_scope
         self._credential = credential
 
-    def __call__(self, *, question: str, answer: str, **kwargs) -> List[List[Dict]]:
+    def __call__(self, *, question: str, answer: str, **kwargs):
         """
         Evaluates content according to this evaluator's metric.
 
@@ -43,13 +42,12 @@ def __call__(self, *, question: str, answer: str, **kwargs) -> List[List[Dict]]:
         :keyword answer: The answer to be evaluated.
         :paramtype answer: str
         :return: The evaluation score computation based on the Content Safety metric (self.metric).
-        :rtype: List[List[Dict]]
+        :rtype: Any
         """
         # Validate inputs
         # Raises value error if failed, so execution alone signifies success.
         _ = validate_inputs(question=question, answer=answer)
 
-        # question: str, answer: str, metric_name: str, project_scope: dict, credential: TokenCredential
         # Run score computation based on supplied metric.
         result = evaluate_with_rai_service(
             metric_name=self._metric,

src/promptflow-evals/promptflow/evals/evaluators/_content_safety/_hate_unfairness.py

@@ -1,9 +1,6 @@
 # ---------------------------------------------------------
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # ---------------------------------------------------------
-from typing import Dict, Union
-
-from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
 
 try:
     from ._content_safety_sub_evaluator_base import ContentSafetySubEvaluatorBase
@@ -46,9 +43,7 @@ class HateUnfairnessEvaluator(ContentSafetySubEvaluatorBase):
         }
     """
 
-    def __init__(
-        self, project_scope: Dict, credential: Union[DefaultAzureCredential, ManagedIdentityCredential] = None
-    ) -> None:
+    def __init__(self, project_scope: dict, credential=None) -> None:
         # Hate_fairness is the actual backend metric name. Which, uh, doesn't sound great.
         # so invert the name.
         super().__init__(

src/promptflow-evals/promptflow/evals/evaluators/_content_safety/common/evaluate_with_rai_service.py

@@ -215,7 +215,7 @@ def parse_response(  # pylint: disable=too-many-branches,too-many-statements
     return result
 
 
-def _get_service_discovery_url(azure_ai_project: Dict, token: str) -> str:
+def _get_service_discovery_url(azure_ai_project: dict, token: str) -> str:
     """Get the discovery service URL for the Azure AI project
 
     :param azure_ai_project: The Azure AI project details.
@@ -240,7 +240,7 @@ def _get_service_discovery_url(azure_ai_project: Dict, token: str) -> str:
     return f"{base_url.scheme}://{base_url.netloc}"
 
 
-def get_rai_svc_url(project_scope: Dict, token: str) -> str:
+def get_rai_svc_url(project_scope: dict, token: str) -> str:
     """Get the Responsible AI service URL
 
     :param project_scope: The Azure AI project scope details.
@@ -294,8 +294,8 @@ def fetch_or_reuse_token(credential: TokenCredential, token: str = None) -> str:
 
 
 def evaluate_with_rai_service(
-    question: str, answer: str, metric_name: str, project_scope: Dict, credential: TokenCredential
-) -> List[List[Dict]]:
+    question: str, answer: str, metric_name: str, project_scope: dict, credential: TokenCredential
+):
     """ "Evaluate the content safety of the answer using Responsible AI service
 
     :param question: The question to evaluate.