Remove ModelConfig type as a temporary solution.

src/promptflow-evals/promptflow/evals/evaluators/chat/__init__.py

@@ -11,15 +11,14 @@
 
 import numpy as np
 
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.evals.evaluators import CoherenceEvaluator, FluencyEvaluator, GroundednessEvaluator, RelevanceEvaluator
 
 logger = logging.getLogger(__name__)
 
 
 class ChatEvaluator:
     def __init__(
-        self, model_config: AzureOpenAIModelConfiguration, eval_last_turn: bool = False, parallel: bool = True
+        self, model_config, eval_last_turn: bool = False, parallel: bool = True
     ):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
@@ -64,7 +63,7 @@ def __init__(
             FluencyEvaluator(model_config),
         ]
 
-    def __call__(self, *, conversation: List[Dict], **kwargs):
+    def __call__(self, *, conversation, **kwargs):
         """Evaluates chat scenario.
 
         :param conversation: The conversation to be evaluated. Each turn should have "role" and "content" keys.

src/promptflow-evals/promptflow/evals/evaluators/coherence/__init__.py

@@ -7,12 +7,11 @@
 from pathlib import Path
 
 from promptflow.client import load_flow
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.core._prompty_utils import convert_model_configuration_to_connection
 
 
 class CoherenceEvaluator:
-    def __init__(self, model_config: AzureOpenAIModelConfiguration):
+    def __init__(self, model_config):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
 

src/promptflow-evals/promptflow/evals/evaluators/content_safety/hate_unfairness.py

@@ -1,12 +1,10 @@
 from promptflow.client import load_flow
 from pathlib import Path
-from azure.core.credentials import TokenCredential
 from promptflow.evals._constants import EvaluationMetrics
-from typing import Optional
 
 
 class HateUnfairnessEvaluator:
-    def __init__(self, project_scope: dict, credential: Optional[TokenCredential] = None):
+    def __init__(self, project_scope: dict, credential=None):
         """
         Initialize an evaluator for hate unfairness score.
 

src/promptflow-evals/promptflow/evals/evaluators/content_safety/self_harm.py

@@ -1,12 +1,10 @@
 from promptflow.client import load_flow
 from pathlib import Path
-from azure.core.credentials import TokenCredential
 from promptflow.evals._constants import EvaluationMetrics
-from typing import Optional
 
 
 class SelfHarmEvaluator:
-    def __init__(self, project_scope: dict, credential: Optional[TokenCredential] = None):
+    def __init__(self, project_scope: dict, credential=None):
         """
         Initialize an evaluator for self harm score.
 

src/promptflow-evals/promptflow/evals/evaluators/content_safety/sexual.py

@@ -1,12 +1,10 @@
 from promptflow.client import load_flow
 from pathlib import Path
-from azure.core.credentials import TokenCredential
 from promptflow.evals._constants import EvaluationMetrics
-from typing import Optional
 
 
 class SexualEvaluator:
-    def __init__(self, project_scope: dict, credential: Optional[TokenCredential] = None):
+    def __init__(self, project_scope: dict, credential=None):
         """
         Initialize an evaluator for sexual score.
 

src/promptflow-evals/promptflow/evals/evaluators/content_safety/violence.py

@@ -1,12 +1,10 @@
 from promptflow.client import load_flow
 from pathlib import Path
-from azure.core.credentials import TokenCredential
 from promptflow.evals._constants import EvaluationMetrics
-from typing import Optional
 
 
 class ViolenceEvaluator:
-    def __init__(self, project_scope: dict, credential: Optional[TokenCredential] = None):
+    def __init__(self, project_scope: dict, credential=None):
         """
         Initialize an evaluator for violence score.
 

src/promptflow-evals/promptflow/evals/evaluators/fluency/__init__.py

@@ -7,12 +7,11 @@
 from pathlib import Path
 
 from promptflow.client import load_flow
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.core._prompty_utils import convert_model_configuration_to_connection
 
 
 class FluencyEvaluator:
-    def __init__(self, model_config: AzureOpenAIModelConfiguration):
+    def __init__(self, model_config):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
 

src/promptflow-evals/promptflow/evals/evaluators/groundedness/__init__.py

@@ -7,12 +7,11 @@
 from pathlib import Path
 
 from promptflow.client import load_flow
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.core._prompty_utils import convert_model_configuration_to_connection
 
 
 class GroundednessEvaluator:
-    def __init__(self, model_config: AzureOpenAIModelConfiguration):
+    def __init__(self, model_config):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
 

src/promptflow-evals/promptflow/evals/evaluators/qa/__init__.py

@@ -4,7 +4,6 @@
 
 __path__ = __import__("pkgutil").extend_path(__path__, __name__)  # type: ignore
 
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.evals.evaluators import (
     CoherenceEvaluator,
     F1ScoreEvaluator,
@@ -16,7 +15,7 @@
 
 
 class QAEvaluator:
-    def __init__(self, model_config: AzureOpenAIModelConfiguration):
+    def __init__(self, model_config):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
 

src/promptflow-evals/promptflow/evals/evaluators/relevance/__init__.py

@@ -7,12 +7,11 @@
 from pathlib import Path
 
 from promptflow.client import load_flow
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.core._prompty_utils import convert_model_configuration_to_connection
 
 
 class RelevanceEvaluator:
-    def __init__(self, model_config: AzureOpenAIModelConfiguration):
+    def __init__(self, model_config):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
 

src/promptflow-evals/promptflow/evals/evaluators/similarity/__init__.py

@@ -7,12 +7,11 @@
 from pathlib import Path
 
 from promptflow.client import load_flow
-from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.core._prompty_utils import convert_model_configuration_to_connection
 
 
 class SimilarityEvaluator:
-    def __init__(self, model_config: AzureOpenAIModelConfiguration):
+    def __init__(self, model_config):
         """
         Initialize an evaluator configured for a specific Azure OpenAI model.
 

src/promptflow-evals/tests/evals/conftest.py

@@ -6,6 +6,7 @@
 import pytest
 from pytest_mock import MockerFixture
 
+from promptflow.client import PFClient
 from promptflow.core import AzureOpenAIModelConfiguration
 from promptflow.executor._line_execution_process_pool import _process_wrapper
 from promptflow.executor._process_manager import create_spawned_fork_process_manager
@@ -72,6 +73,12 @@ def model_config() -> dict:
     return model_config
 
 
+@pytest.fixture
+def pf_client() -> PFClient:
+    """The fixture, returning PRClient"""
+    return PFClient()
+
+
 # ==================== Recording injection ====================
 # To inject patches in subprocesses, add new mock method in setup_recording_injection_if_enabled
 # in fork mode, this is automatically enabled.

src/promptflow-evals/tests/evals/unittests/test_save_eval.py

@@ -0,0 +1,38 @@
+from typing import Any, List, Optional, Type
+
+import inspect
+import os
+import pytest
+
+from promptflow.evals import evaluators
+from promptflow.evals.evaluators import content_safety
+
+
+def get_evaluators_from_module(namespace: Any, exceptions: Optional[List[str]] = None) -> List[Type]:
+    evaluators = []
+    for name, obj in inspect.getmembers(namespace):
+        if inspect.isclass(obj):
+            if exceptions and name in exceptions:
+                continue
+            evaluators.append(obj)
+    return evaluators
+
+
+@pytest.mark.unittest
+class TestSaveEval:
+    """Test saving evaluators."""
+
+    EVALUATORS = get_evaluators_from_module(evaluators)
+    RAI_EVALUATORS = get_evaluators_from_module(content_safety)
+
+    @pytest.mark.parametrize('evaluator', EVALUATORS)
+    def test_save_evaluators(self, tmpdir, pf_client, evaluator) -> None:
+        """Test regular evaluator saving."""
+        pf_client.flows.save(evaluator, path=tmpdir)
+        assert os.path.isfile(os.path.join(tmpdir, 'flow.flex.yaml'))
+
+    @pytest.mark.parametrize('rai_evaluator', RAI_EVALUATORS)
+    def test_save_rai_evaluators(self, tmpdir, pf_client, rai_evaluator):
+        """Test saving of RAI evaluators"""
+        pf_client.flows.save(rai_evaluator, path=tmpdir)
+        assert os.path.isfile(os.path.join(tmpdir, 'flow.flex.yaml'))