MAINT Remove v0.13.0 deprecated APIs: FoundryScenario alias and piece.role in conversation_analytics

pyrit/analytics/conversation_analytics.py

@@ -42,7 +42,7 @@ def get_prompt_entries_with_same_converted_content(
         return [
             ConversationMessageWithSimilarity(
                 score=1.0,
-                role=memory.role,
+                role=memory.api_role,
                 content=memory.converted_value,
                 metric="exact_match",  # Exact match
             )

pyrit/scenario/scenarios/foundry/__init__.py

@@ -4,13 +4,11 @@
 """Foundry scenario classes."""
 
 from pyrit.scenario.scenarios.foundry.red_team_agent import (
-    FoundryScenario,
     FoundryStrategy,
     RedTeamAgent,
 )
 
 __all__ = [
-    "FoundryScenario",
     "FoundryStrategy",
     "RedTeamAgent",
 ]

pyrit/scenario/scenarios/foundry/red_team_agent.py

@@ -17,7 +17,6 @@
 
 from pyrit.auth import get_azure_openai_auth
 from pyrit.common import apply_defaults
-from pyrit.common.deprecation import print_deprecation_message
 from pyrit.datasets import TextJailBreak
 from pyrit.executor.attack import (
     CrescendoAttack,
@@ -485,21 +484,3 @@ def _get_attack(
         # attack types. The caller is responsible for ensuring the attack type accepts
         # these constructor parameters.
         return attack_type(**kwargs)  # type: ignore[arg-type]
-
-
-class FoundryScenario(RedTeamAgent):
-    """
-    Deprecated alias for RedTeamAgent.
-
-    This class is deprecated and will be removed in version 0.13.0.
-    Use `RedTeamAgent` instead.
-    """
-
-    def __init__(self, **kwargs: Any) -> None:
-        """Initialize FoundryScenario with deprecation warning."""
-        print_deprecation_message(
-            old_item="FoundryScenario",
-            new_item="RedTeamAgent",
-            removed_in="0.13.0",
-        )
-        super().__init__(**kwargs)

tests/partner_integration/azure_ai_evaluation/test_foundry_scenario_contract.py

@@ -4,7 +4,7 @@
 """Contract tests for Foundry scenario APIs used by azure-ai-evaluation.
 
 The azure-ai-evaluation red team module uses the scenario framework for attack execution:
-- FoundryExecutionManager creates FoundryScenario instances per risk category
+- FoundryExecutionManager creates RedTeamAgent instances per risk category
 - StrategyMapper maps AttackStrategy enum → FoundryStrategy
 - DatasetConfigurationBuilder produces DatasetConfiguration from RAI objectives
 - ScenarioOrchestrator processes ScenarioResult and AttackResult
@@ -13,7 +13,7 @@
 
 from pyrit.executor.attack import AttackScoringConfig
 from pyrit.scenario import ScenarioStrategy
-from pyrit.scenario.foundry import FoundryStrategy
+from pyrit.scenario.foundry import FoundryStrategy, RedTeamAgent
 
 
 class TestRedTeamStrategyContract:
@@ -25,13 +25,11 @@ def test_foundry_strategy_is_scenario_strategy(self):
 
 
 class TestRedTeamScenarioContract:
-    """Validate FoundryScenario importability."""
+    """Validate RedTeamAgent importability."""
 
-    def test_foundry_scenario_importable(self):
-        """ScenarioOrchestrator creates FoundryScenario instances."""
-        from pyrit.scenario.foundry import FoundryScenario  # noqa: F811
-
-        assert FoundryScenario is not None
+    def test_red_team_agent_importable(self):
+        """ScenarioOrchestrator creates RedTeamAgent instances."""
+        assert RedTeamAgent is not None
 
 
 class TestDatasetConfigurationContract:

tests/unit/analytics/test_conversation_analytics.py

@@ -8,8 +8,9 @@
 
 from pyrit.analytics.conversation_analytics import ConversationAnalytics
 from pyrit.memory.memory_interface import MemoryInterface
-from pyrit.memory.memory_models import EmbeddingDataEntry, PromptMemoryEntry
-from unit.mocks import get_sample_conversation_entries
+from pyrit.memory.memory_models import EmbeddingDataEntry
+from pyrit.models import Message, MessagePiece
+from unit.mocks import get_sample_conversations
 
 
 @pytest.fixture
@@ -18,15 +19,16 @@ def mock_memory_interface():
 
 
 @pytest.fixture
-def sample_conversations_entries() -> Sequence[PromptMemoryEntry]:
-    return get_sample_conversation_entries()
+def sample_message_pieces() -> Sequence[MessagePiece]:
+    conversations = get_sample_conversations()
+    return Message.flatten_to_message_pieces(conversations)
 
 
-def test_get_similar_chat_messages_by_content(mock_memory_interface, sample_conversations_entries):
-    sample_conversations_entries[0].converted_value = "Hello, how are you?"
-    sample_conversations_entries[2].converted_value = "Hello, how are you?"
+def test_get_similar_chat_messages_by_content(mock_memory_interface, sample_message_pieces):
+    sample_message_pieces[0].converted_value = "Hello, how are you?"
+    sample_message_pieces[2].converted_value = "Hello, how are you?"
 
-    mock_memory_interface.get_message_pieces.return_value = sample_conversations_entries
+    mock_memory_interface.get_message_pieces.return_value = sample_message_pieces
 
     analytics = ConversationAnalytics(memory_interface=mock_memory_interface)
     similar_messages = analytics.get_prompt_entries_with_same_converted_content(
@@ -41,27 +43,23 @@ def test_get_similar_chat_messages_by_content(mock_memory_interface, sample_conv
         assert message.metric == "exact_match"
 
 
-def test_get_similar_chat_messages_by_embedding(mock_memory_interface, sample_conversations_entries):
-    sample_conversations_entries[0].converted_value = "Similar message"
-    sample_conversations_entries[1].converted_value = "Different message"
+def test_get_similar_chat_messages_by_embedding(mock_memory_interface, sample_message_pieces):
+    sample_message_pieces[0].converted_value = "Similar message"
+    sample_message_pieces[1].converted_value = "Different message"
 
     # Mock EmbeddingData entries linked to the ConversationData entries
     target_embedding = [0.1, 0.2, 0.3]
     similar_embedding = [0.1, 0.2, 0.31]  # Slightly different, but should be similar
     different_embedding = [0.9, 0.8, 0.7]
 
     mock_embeddings = [
-        EmbeddingDataEntry(
-            id=sample_conversations_entries[0].id, embedding=similar_embedding, embedding_type_name="model1"
-        ),
-        EmbeddingDataEntry(
-            id=sample_conversations_entries[1].id, embedding=different_embedding, embedding_type_name="model2"
-        ),
+        EmbeddingDataEntry(id=sample_message_pieces[0].id, embedding=similar_embedding, embedding_type_name="model1"),
+        EmbeddingDataEntry(id=sample_message_pieces[1].id, embedding=different_embedding, embedding_type_name="model2"),
     ]
 
-    # Mock the get_message_pieces method to return the mock EmbeddingData entries
+    # Mock the get_all_embeddings method to return the mock EmbeddingData entries
     mock_memory_interface.get_all_embeddings.return_value = mock_embeddings
-    mock_memory_interface.get_message_pieces.return_value = sample_conversations_entries
+    mock_memory_interface.get_message_pieces.return_value = sample_message_pieces
 
     analytics = ConversationAnalytics(memory_interface=mock_memory_interface)
     similar_messages = analytics.get_similar_chat_messages_by_embedding(