agent action handle fix

Author: Fr4nc3

src/backend/kernel_agents/agent_base.py

@@ -277,18 +277,27 @@ async def handle_action_request(self, action_request: ActionRequest) -> str:
             chat_history = self._chat_history.copy()
 
             # Call the agent to handle the action
-            agent_response = self._agent.invoke(
+            async_generator = self._agent.invoke(
                 self._kernel, f"{action_request.action}\n\nPlease perform this action"
             )
-            result = str(agent_response)
+
+            response_content = ""
+
+            # Collect the response from the async generator
+            async for chunk in async_generator:
+                if chunk is not None:
+                    response_content += str(chunk)
+
+            logging.info(f"Response content length: {len(response_content)}")
+            logging.info(f"Response content: {response_content}")
 
             # Store agent message in cosmos memory
             await self._memory_store.add_item(
                 AgentMessage(
                     session_id=action_request.session_id,
                     user_id=self._user_id,
                     plan_id=action_request.plan_id,
-                    content=f"{result}",
+                    content=f"{response_content}",
                     source=self._agent_name,
                     step_id=action_request.step_id,
                 )
@@ -301,7 +310,7 @@ async def handle_action_request(self, action_request: ActionRequest) -> str:
                     "session_id": action_request.session_id,
                     "user_id": self._user_id,
                     "plan_id": action_request.plan_id,
-                    "content": f"{result}",
+                    "content": f"{response_content}",
                     "source": self._agent_name,
                     "step_id": action_request.step_id,
                 },
@@ -333,11 +342,11 @@ async def handle_action_request(self, action_request: ActionRequest) -> str:
             )
             return response.json()
 
-        logging.info(f"Task completed: {result}")
+        logging.info(f"Task completed: {response_content}")
 
         # Update step status
         step.status = StepStatus.completed
-        step.agent_reply = result
+        step.agent_reply = response_content
         await self._memory_store.update_step(step)
 
         # Track step completion in telemetry
@@ -346,10 +355,10 @@ async def handle_action_request(self, action_request: ActionRequest) -> str:
             {
                 "status": StepStatus.completed,
                 "session_id": action_request.session_id,
-                "agent_reply": f"{result}",
+                "agent_reply": f"{response_content}",
                 "user_id": self._user_id,
                 "plan_id": action_request.plan_id,
-                "content": f"{result}",
+                "content": f"{response_content}",
                 "source": self._agent_name,
                 "step_id": action_request.step_id,
             },
@@ -360,7 +369,7 @@ async def handle_action_request(self, action_request: ActionRequest) -> str:
             step_id=step.id,
             plan_id=step.plan_id,
             session_id=action_request.session_id,
-            result=result,
+            result=response_content,
             status=StepStatus.completed,
         )
 

src/backend/kernel_agents/planner_agent.py

@@ -126,12 +126,12 @@ async def async_init(self) -> None:
                 instructions=instructions,  # Pass the formatted string, not an object
                 temperature=0.0,
                 response_format=ResponseFormatJsonSchemaType(
-                json_schema=ResponseFormatJsonSchema(
-                    name=PlannerResponsePlan.__name__,
-                    description=f"respond with {PlannerResponsePlan.__name__.lower()}",
-                    schema=PlannerResponsePlan.model_json_schema(),
-                )
-            ),
+                    json_schema=ResponseFormatJsonSchema(
+                        name=PlannerResponsePlan.__name__,
+                        description=f"respond with {PlannerResponsePlan.__name__.lower()}",
+                        schema=PlannerResponsePlan.model_json_schema(),
+                    )
+                ),
             )
             logging.info("Successfully created Azure AI Agent for PlannerAgent")
             return True
@@ -316,7 +316,6 @@ async def _create_structured_plan(
             logging.info(f"Kernel arguments: {kernel_args}")
 
             # Get the schema for our expected response format
-    
 
             # Ensure we're using the right pattern for Azure AI agents with semantic kernel
             # Properly handle async generation
@@ -336,9 +335,7 @@ async def _create_structured_plan(
                 if chunk is not None:
                     response_content += str(chunk)
 
-            logging.info(f"\n\n\n\n")
             logging.info(f"Response content length: {len(response_content)}")
-            logging.info(f"\n\n\n\n")
 
             # Check if response is empty or whitespace
             if not response_content or response_content.isspace():