format files

Author: Fr4nc3

src/backend/config_kernel.py

@@ -3,6 +3,7 @@
 import logging
 import semantic_kernel as sk
 from semantic_kernel.kernel import Kernel
+
 # Updated imports for compatibility
 try:
     # Try newer structure
@@ -15,6 +16,7 @@
 # Import AppConfig from app_config
 from app_config import config
 
+
 # This file is left as a lightweight wrapper around AppConfig for backward compatibility
 # All configuration is now handled by AppConfig in app_config.py
 class Config:
@@ -39,7 +41,9 @@ class Config:
     AZURE_AI_SUBSCRIPTION_ID = config.AZURE_AI_SUBSCRIPTION_ID
     AZURE_AI_RESOURCE_GROUP = config.AZURE_AI_RESOURCE_GROUP
     AZURE_AI_PROJECT_NAME = config.AZURE_AI_PROJECT_NAME
-    AZURE_AI_AGENT_PROJECT_CONNECTION_STRING = config.AZURE_AI_AGENT_PROJECT_CONNECTION_STRING
+    AZURE_AI_AGENT_PROJECT_CONNECTION_STRING = (
+        config.AZURE_AI_AGENT_PROJECT_CONNECTION_STRING
+    )
 
     @staticmethod
     def GetAzureCredentials():
@@ -55,7 +59,7 @@ def GetCosmosDatabaseClient():
     def CreateKernel():
         """Creates a new Semantic Kernel instance using the AppConfig implementation."""
         return config.create_kernel()
-    
+
     @staticmethod
     def GetAIProjectClient():
         """Get an AIProjectClient using the AppConfig implementation."""

src/backend/kernel_agents/agent_utils.py

@@ -13,6 +13,7 @@
 
 class FSMStateAndTransition(BaseModel):
     """Model for state and transition in a finite state machine."""
+
     identifiedTargetState: str
     identifiedTargetTransition: str
 
@@ -25,61 +26,65 @@ async def extract_and_update_transition_states(
     kernel: sk.Kernel,
 ) -> Optional[Step]:
     """
-    This function extracts the identified target state and transition from the LLM response and updates 
+    This function extracts the identified target state and transition from the LLM response and updates
     the step with the identified target state and transition. This is reliant on the agent_reply already being present.
-    
+
     Args:
         step: The step to update
         session_id: The current session ID
         user_id: The user ID
         planner_dynamic_or_workflow: Type of planner
         kernel: The semantic kernel instance
-        
+
     Returns:
         The updated step or None if extraction fails
     """
     planner_dynamic_or_workflow = "workflow"
     if planner_dynamic_or_workflow == "workflow":
         cosmos = CosmosMemoryContext(session_id=session_id, user_id=user_id)
-        
+
         # Create chat history for the semantic kernel completion
         messages = [
             {"role": "assistant", "content": step.action},
             {"role": "assistant", "content": step.agent_reply},
-            {"role": "assistant", "content": "Based on the above conversation between two agents, I need you to identify the identifiedTargetState and identifiedTargetTransition values. Only return these values. Do not make any function calls. If you are unable to work out the next transition state, return ERROR."}
+            {
+                "role": "assistant",
+                "content": "Based on the above conversation between two agents, I need you to identify the identifiedTargetState and identifiedTargetTransition values. Only return these values. Do not make any function calls. If you are unable to work out the next transition state, return ERROR.",
+            },
         ]
 
         # Get the LLM response using semantic kernel
         completion_service = kernel.get_service("completion")
-        
+
         try:
             completion_result = await completion_service.complete_chat_async(
                 messages=messages,
-                execution_settings={
-                    "response_format": {"type": "json_object"}
-                }
+                execution_settings={"response_format": {"type": "json_object"}},
             )
-            
+
             content = completion_result
-            
+
             # Parse the LLM response
             parsed_result = json.loads(content)
             structured_plan = FSMStateAndTransition(**parsed_result)
-            
+
             # Update the step
             step.identified_target_state = structured_plan.identifiedTargetState
-            step.identified_target_transition = structured_plan.identifiedTargetTransition
-            
+            step.identified_target_transition = (
+                structured_plan.identifiedTargetTransition
+            )
+
             await cosmos.update_step(step)
             return step
-            
+
         except Exception as e:
             print(f"Error extracting transition states: {e}")
             return None
 
+
 # The commented-out functions below would be implemented when needed
 # async def set_next_viable_step_to_runnable(session_id):
 #     pass
 
 # async def initiate_replanning(session_id):
-#     pass
+#     pass

src/backend/kernel_agents/generic_agent.py

@@ -8,6 +8,7 @@
 from context.cosmos_memory_kernel import CosmosMemoryContext
 from models.messages_kernel import AgentType
 
+
 class GenericAgent(BaseAgent):
     """Generic agent implementation using Semantic Kernel."""
 
@@ -25,7 +26,7 @@ def __init__(
         definition=None,
     ) -> None:
         """Initialize the Generic Agent.
-        
+
         Args:
             kernel: The semantic kernel instance
             session_id: The current session identifier
@@ -43,17 +44,19 @@ def __init__(
             # Load the generic tools configuration
             config = self.load_tools_config("generic", config_path)
             tools = self.get_tools_from_config(kernel, "generic", config_path)
-            
+
             # Use system message from config if not explicitly provided
             if not system_message:
-                system_message = config.get("system_message", 
+                system_message = config.get(
+                    "system_message",
                     "You are a generic agent. You are used to handle generic tasks that a general Large Language Model can assist with. "
                     "You are being called as a fallback, when no other agents are able to use their specialised functions in order to solve "
-                    "the user's task. Summarize back to the user what was done.")
-            
+                    "the user's task. Summarize back to the user what was done.",
+                )
+
             # Use agent name from config if available
             agent_name = AgentType.GENERIC.value
-        
+
         # Call the parent initializer
         super().__init__(
             agent_name=agent_name,
@@ -64,20 +67,20 @@ def __init__(
             tools=tools,
             system_message=system_message,
             client=client,
-            definition=definition
+            definition=definition,
         )
-    
+
     # Explicitly inherit handle_action_request from the parent class
     # This is not technically necessary but makes the inheritance explicit
     async def handle_action_request(self, action_request_json: str) -> str:
         """Handle an action request from another agent or the system.
-        
+
         This method is inherited from BaseAgent but explicitly included here for clarity.
-        
+
         Args:
             action_request_json: The action request as a JSON string
-            
+
         Returns:
             A JSON string containing the action response
         """
-        return await super().handle_action_request(action_request_json)
+        return await super().handle_action_request(action_request_json)

src/backend/kernel_agents/hr_agent.py

@@ -7,9 +7,10 @@
 from context.cosmos_memory_kernel import CosmosMemoryContext
 from models.messages_kernel import AgentType
 
+
 class HrAgent(BaseAgent):
     """HR agent implementation using Semantic Kernel.
-    
+
     This agent provides HR-related functions such as onboarding, benefits management,
     and employee administration. All tools are loaded from hr_tools.json.
     """
@@ -28,7 +29,7 @@ def __init__(
         definition=None,
     ) -> None:
         """Initialize the HR Agent.
-        
+
         Args:
             kernel: The semantic kernel instance
             session_id: The current session identifier
@@ -46,17 +47,17 @@ def __init__(
             # Load the HR tools configuration
             config = self.load_tools_config("hr", config_path)
             tools = self.get_tools_from_config(kernel, "hr", config_path)
-            
+
             # Use system message from config if not explicitly provided
             if not system_message:
                 system_message = config.get(
-                    "system_message", 
-                    "You are an AI Agent. You have knowledge about HR (e.g., human resources), policies, procedures, and onboarding guidelines."
+                    "system_message",
+                    "You are an AI Agent. You have knowledge about HR (e.g., human resources), policies, procedures, and onboarding guidelines.",
                 )
-            
+
             # Use agent name from config if available
             agent_name = AgentType.HR.value
-        
+
         super().__init__(
             agent_name=agent_name,
             kernel=kernel,
@@ -66,5 +67,5 @@ def __init__(
             tools=tools,
             system_message=system_message,
             client=client,
-            definition=definition
-        )
+            definition=definition,
+        )

src/backend/kernel_agents/marketing_agent.py

@@ -7,9 +7,10 @@
 from context.cosmos_memory_kernel import CosmosMemoryContext
 from models.messages_kernel import AgentType
 
+
 class MarketingAgent(BaseAgent):
     """Marketing agent implementation using Semantic Kernel.
-    
+
     This agent specializes in marketing strategies, campaign development,
     content creation, and market analysis. It can create effective marketing
     campaigns, analyze market trends, develop promotional content, and more.
@@ -30,7 +31,7 @@ def __init__(
         definition=None,
     ) -> None:
         """Initialize the Marketing Agent.
-        
+
         Args:
             kernel: The semantic kernel instance
             session_id: The current session identifier
@@ -48,17 +49,17 @@ def __init__(
             # Load the marketing tools configuration
             config = self.load_tools_config("marketing", config_path)
             tools = self.get_tools_from_config(kernel, "marketing", config_path)
-            
+
             # Use system message from config if not explicitly provided
             if not system_message:
                 system_message = config.get(
-                    "system_message", 
-                    "You are an AI Agent. You have knowledge about marketing, including campaigns, market research, and promotional activities."
+                    "system_message",
+                    "You are an AI Agent. You have knowledge about marketing, including campaigns, market research, and promotional activities.",
                 )
-            
+
             # Use agent name from config if available
             agent_name = AgentType.MARKETING.value
-        
+
         super().__init__(
             agent_name=agent_name,
             kernel=kernel,
@@ -68,5 +69,5 @@ def __init__(
             tools=tools,
             system_message=system_message,
             client=client,
-            definition=definition
-        )
+            definition=definition,
+        )

src/backend/kernel_agents/procurement_agent.py

@@ -7,9 +7,10 @@
 from context.cosmos_memory_kernel import CosmosMemoryContext
 from models.messages_kernel import AgentType
 
+
 class ProcurementAgent(BaseAgent):
     """Procurement agent implementation using Semantic Kernel.
-    
+
     This agent specializes in purchasing, vendor management, supply chain operations,
     and inventory control. It can create purchase orders, manage vendors, track orders,
     and ensure efficient procurement processes.
@@ -29,7 +30,7 @@ def __init__(
         definition=None,
     ) -> None:
         """Initialize the Procurement Agent.
-        
+
         Args:
             kernel: The semantic kernel instance
             session_id: The current session identifier
@@ -47,17 +48,17 @@ def __init__(
             # Load the procurement tools configuration
             config = self.load_tools_config("procurement", config_path)
             tools = self.get_tools_from_config(kernel, "procurement", config_path)
-            
+
             # Use system message from config if not explicitly provided
             if not system_message:
                 system_message = config.get(
-                    "system_message", 
-                    "You are an AI Agent. You are able to assist with procurement enquiries and order items. If you need additional information from the human user asking the question in order to complete a request, ask before calling a function."
+                    "system_message",
+                    "You are an AI Agent. You are able to assist with procurement enquiries and order items. If you need additional information from the human user asking the question in order to complete a request, ask before calling a function.",
                 )
-            
+
             # Use agent name from config if available
             agent_name = AgentType.PROCUREMENT.value
-        
+
         super().__init__(
             agent_name=agent_name,
             kernel=kernel,
@@ -67,5 +68,5 @@ def __init__(
             tools=tools,
             system_message=system_message,
             client=client,
-            definition=definition
-        )
+            definition=definition,
+        )