Finished name conversions

Author: marktayl1

src/backend/agents/base_agent.py

@@ -21,6 +21,7 @@
     Step,
     StepStatus,
 )
+from models.messages_kernel import AgentType
 from src.backend.event_utils import track_event_if_configured
 
 
@@ -76,7 +77,7 @@ async def handle_action_request(
                 AssistantMessage(content=message.action, source="GroupChatManager"),
                 UserMessage(
                     content=f"{step.human_feedback}. Now make the function call",
-                    source="HumanAgent",
+                    source=AgentType.HUMAN.value,
                 ),
             ]
         )

src/backend/agents/group_chat_manager.py

@@ -21,7 +21,7 @@
     Step,
     StepStatus,
 )
-
+from models.messages_kernel import AgentType
 from src.backend.event_utils import track_event_if_configured
 
 
@@ -57,7 +57,7 @@ async def handle_input_task(
                 user_id=self._user_id,
                 plan_id="",
                 content=f"{message.description}",
-                source="HumanAgent",
+                source=AgentType.HUMAN.value,
                 step_id="",
             )
         )
@@ -68,7 +68,7 @@ async def handle_input_task(
                 "session_id": message.session_id,
                 "user_id": self._user_id,
                 "content": message.description,
-                "source": "HumanAgent",
+                "source": AgentType.HUMAN.value,
             },
         )
 

src/backend/agents/human.py

@@ -13,6 +13,7 @@
     Step,
 )
 from src.backend.event_utils import track_event_if_configured
+from models.messages_kernel import AgentType
 
 
 @default_subscription
@@ -52,7 +53,7 @@ async def handle_step_feedback(
                 user_id=self.user_id,
                 plan_id=step.plan_id,
                 content=f"Received feedback for step: {step.action}",
-                source="HumanAgent",
+                source=AgentType.HUMAN.value,
                 step_id=message.step_id,
             )
         )
@@ -64,7 +65,7 @@ async def handle_step_feedback(
                 "user_id": self.user_id,
                 "plan_id": step.plan_id,
                 "content": f"Received feedback for step: {step.action}",
-                "source": "HumanAgent",
+                "source": AgentType.HUMAN.value,
                 "step_id": message.step_id,
             },
         )

src/backend/agents/planner.py

@@ -25,7 +25,7 @@
     StepStatus,
     HumanFeedbackStatus,
 )
-
+from models.messages_kernel import AgentType
 from src.backend.event_utils import track_event_if_configured
 
 
@@ -133,7 +133,7 @@ async def handle_plan_clarification(
                 user_id=self._user_id,
                 plan_id="",
                 content=f"{message.human_clarification}",
-                source="HumanAgent",
+                source=AgentType.HUMAN.value,
                 step_id="",
             )
         )
@@ -144,7 +144,7 @@ async def handle_plan_clarification(
                 "session_id": message.session_id,
                 "user_id": self._user_id,
                 "content": f"{message.human_clarification}",
-                "source": "HumanAgent",
+                "source": AgentType.HUMAN.value,
             },
         )
 

src/backend/app_kernel.py

@@ -413,7 +413,7 @@ async def approve_step_endpoint(
     agents = await get_agents(human_feedback.session_id, user_id)
 
     # Send the approval to the group chat manager
-    group_chat_manager = agents["GroupChatManager"]
+    group_chat_manager = agents[AgentType.GROUP_CHAT_MANAGER.value]
 
     # Handle the approval
     human_feedback_json = human_feedback.json()

src/backend/models/messages.py

@@ -2,13 +2,7 @@
 from enum import Enum
 from typing import Literal, Optional
 
-from autogen_core.components.models import (
-    AssistantMessage,
-    FunctionExecutionResultMessage,
-    LLMMessage,
-    SystemMessage,
-    UserMessage,
-)
+from .messages_kernel import AgentType
 from pydantic import BaseModel, Field
 
 
@@ -23,15 +17,15 @@ class DataType(str, Enum):
 class BAgentType(str, Enum):
     """Enumeration of agent types."""
 
-    human_agent = "HumanAgent"
-    hr_agent = "HrAgent"
-    marketing_agent = "MarketingAgent"
-    procurement_agent = "ProcurementAgent"
-    product_agent = "ProductAgent"
-    generic_agent = "GenericAgent"
-    tech_support_agent = "TechSupportAgent"
-    group_chat_manager = "GroupChatManager"
-    planner_agent = "PlannerAgent"
+    AgentType.HUMAN.value = "HumanAgent"
+    AgentType.HR.value = "HrAgent"
+    AgentType.MARKETING.value = "MarketingAgent"
+    AgentType.PROCUREMENT.value = "ProcurementAgent"
+    AgentType.PRODUCT.value = "ProductAgent"
+    AgentType.GENERIC.value = "GenericAgent"
+    AgentType.TECH_SUPPORT.value = "TechSupportAgent"
+    AgentType.GROUP_CHAT_MANAGER.value = "GroupChatManager"
+    AgentType.PLANNER.value = "PlannerAgent"
 
     # Add other agents as needed
 

src/backend/tests/test_group_chat_manager_integration.py

@@ -222,9 +222,9 @@ async def initialize_group_chat_manager(self):
 
         # Create agent dictionary for the group chat manager
         available_agents = {
-            "PlannerAgent": planner_agent,
-            "HumanAgent": human_agent,
-            "GenericAgent": generic_agent
+            "planner_agent": planner_agent,
+            "human_agent": human_agent,
+            "generic_agent": generic_agent
         }
 
         # Create the group chat manager

src/backend/utils_kernel.py

@@ -95,7 +95,7 @@ async def get_agents(session_id: str, user_id: str) -> Dict[str, Any]:
         }
 
         # Convert to the agent name dictionary format used by the rest of the app
-        agents = {agent_classes[agent_type]: agent for agent_type, agent in raw_agents.items()}
+        agents = {agent_type.value: agent for agent_type, agent in raw_agents.items()}
 
         # Cache the agents
         agent_instances[cache_key] = agents