Change agent goal to be an element of the workflow, including query

api/main.py

@@ -20,7 +20,7 @@ temporal_client: Optional[Client] = None
 load_dotenv()
 
 
-def get_agent_goal():
+def get_initial_agent_goal():
     """Get the agent goal from environment variables."""
     goals = {
         "goal_match_train_invoice": goal_match_train_invoice,
@@ -121,6 +121,27 @@ async def get_conversation_history():
         raise HTTPException(
             status_code=500, detail="Internal server error while querying workflow."
         )
+    
+@app.get("/agent-goal")
+async def get_agent_goal():
+    """Calls the workflow's 'get_agent_goal' query."""
+    try:
+        # Get workflow handle
+        handle = temporal_client.get_workflow_handle("agent-workflow")
+
+        # Check if the workflow is completed
+        workflow_status = await handle.describe()
+        if workflow_status.status == 2:
+            # Workflow is completed; return an empty response
+            return {}
+
+        # Query the workflow
+        agent_goal = await handle.query("get_agent_goal")
+        return agent_goal
+    except TemporalError as e:
+        # Workflow not found; return an empty response
+        print(e)
+        return {}
 
 
 @app.post("/send-prompt")
@@ -128,7 +149,8 @@ async def send_prompt(prompt: str):
     # Create combined input with goal from environment
     combined_input = CombinedInput(
         tool_params=AgentGoalWorkflowParams(None, None),
-        agent_goal=get_agent_goal(),
+        agent_goal=get_initial_agent_goal(),
+        #change to get from workflow query
     )
 
     workflow_id = "agent-workflow"
@@ -172,13 +194,13 @@ async def end_chat():
 
 @app.post("/start-workflow")
 async def start_workflow():
-    # Get the configured goal
-    agent_goal = get_agent_goal()
+    # Get the initial goal as set in shared/config or env or just...always should be "pick a goal?"
+    initial_agent_goal = get_initial_agent_goal()
 
     # Create combined input
     combined_input = CombinedInput(
         tool_params=AgentGoalWorkflowParams(None, None),
-        agent_goal=agent_goal,
+        agent_goal=initial_agent_goal,
     )
 
     workflow_id = "agent-workflow"
@@ -190,9 +212,9 @@ async def start_workflow():
         id=workflow_id,
         task_queue=TEMPORAL_TASK_QUEUE,
         start_signal="user_prompt",
-        start_signal_args=["### " + agent_goal.starter_prompt],
+        start_signal_args=["### " + initial_agent_goal.starter_prompt],
     )
 
     return {
-        "message": f"Workflow started with goal's starter prompt: {agent_goal.starter_prompt}."
+        "message": f"Workflow started with goal's starter prompt: {initial_agent_goal.starter_prompt}."
     }

shared/config.py

@@ -18,6 +18,7 @@ TEMPORAL_API_KEY = os.getenv("TEMPORAL_API_KEY", "")
 
 #Starting agent goal - 1st goal is always to help user pick a next goal
 AGENT_GOAL = "goal_choose_agent_type"
+#AGENT_GOAL = "goal_event_flight_invoice"
 
 
 async def get_temporal_client() -> Client:

tools/change_goal.py

@@ -1,6 +1,13 @@
-# can this just call the API endpoint to set the goal, if that changes to allow a param?
+# can this just call the API endpoint to set the goal, if that changes to allow a param? 
+#   if this functions, it could work to both send a signal and also circumvent the UI -> API thing. Maybe?
+
 # --- OR ---
+
 # end this workflow and start a new one with the new goal
+
+# --- OR ---
+
+# send a signal to the workflow from here?
 import shared.config
 
 def change_goal(args: dict) -> dict:

workflows/agent_goal_workflow.py

@@ -7,6 +7,7 @@ from temporalio.common import RetryPolicy
 from temporalio import workflow
 
 from models.data_types import ConversationHistory, NextStep, ValidationInput
+from models.tool_definitions import AgentGoal
 from workflows.workflow_helpers import LLM_ACTIVITY_START_TO_CLOSE_TIMEOUT, \
     LLM_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT
 from workflows import workflow_helpers as helpers
@@ -49,6 +50,8 @@ class AgentGoalWorkflow:
         self.tool_data: Optional[ToolData] = None
         self.confirm: bool = False
         self.tool_results: List[Dict[str, Any]] = []
+        #set initial goal of "pick an agent" here??
+        self.goal: AgentGoal = {"tools": []}
 
     # see ../api/main.py#temporal_client.start_workflow() for how these parameters are set
     @workflow.run
@@ -56,7 +59,7 @@ class AgentGoalWorkflow:
         """Main workflow execution method."""
         # setup phase, starts with blank tool_params and agent_goal prompt as defined in tools/goal_registry.py
         params = combined_input.tool_params
-        agent_goal = combined_input.agent_goal
+        self.goal = combined_input.agent_goal
 
         # add message from sample conversation provided in tools/goal_registry.py, if it exists
         if params and params.conversation_summary:
@@ -77,15 +80,15 @@ class AgentGoalWorkflow:
             )
 
             #update the goal, in case it's changed - doesn't help
-            goals = {
-                "goal_match_train_invoice": goal_match_train_invoice,
-                "goal_event_flight_invoice": goal_event_flight_invoice,
-                "goal_choose_agent_type": goal_choose_agent_type,
-            }
+            #goals = {
+             #   "goal_match_train_invoice": goal_match_train_invoice,
+              #  "goal_event_flight_invoice": goal_event_flight_invoice,
+               # "goal_choose_agent_type": goal_choose_agent_type,
+            #}
 
-            if shared.config.AGENT_GOAL is not None:
-                agent_goal = goals.get(shared.config.AGENT_GOAL)
-            workflow.logger.warning("AGENT_GOAL: " + shared.config.AGENT_GOAL)
+            #if shared.config.AGENT_GOAL is not None:
+             #   agent_goal = goals.get(shared.config.AGENT_GOAL)
+            #workflow.logger.warning("AGENT_GOAL: " + shared.config.AGENT_GOAL)
            # workflow.logger.warning("agent_goal", agent_goal)
 
             #process signals of various kinds
@@ -112,6 +115,9 @@ class AgentGoalWorkflow:
                     self.add_message,
                     self.prompt_queue
                 )
+               # workflow.logger.warning("last tool_data tool: ", self.tool_data[-1].tool)
+                #workflow.logger.warning("last tool_data args: ", self.tool_data[-1].args)
+               # workflow.logger.warning("last tool_results [args]: ", self.tool_results[-1]["args"])
                 continue
 
             if self.prompt_queue:
@@ -123,7 +129,7 @@ class AgentGoalWorkflow:
                     validation_input = ValidationInput(
                         prompt=prompt,
                         conversation_history=self.conversation_history,
-                        agent_goal=agent_goal,
+                        agent_goal=self.goal,
                     )
                     validation_result = await workflow.execute_activity(
                         ToolActivities.agent_validatePrompt,
@@ -147,7 +153,7 @@ class AgentGoalWorkflow:
 
                 # Proceed with generating the context and prompt
                 context_instructions = generate_genai_prompt(
-                    agent_goal, self.conversation_history, self.tool_data
+                    self.goal, self.conversation_history, self.tool_data
                 )
 
                 prompt_input = ToolPromptInput(
@@ -189,7 +195,7 @@ class AgentGoalWorkflow:
                 await helpers.continue_as_new_if_needed(
                     self.conversation_history,
                     self.prompt_queue,
-                    agent_goal,
+                    self.goal,
                     MAX_TURNS_BEFORE_CONTINUE,
                     self.add_message
                 )
@@ -220,6 +226,11 @@ class AgentGoalWorkflow:
     def get_conversation_history(self) -> ConversationHistory:
         """Query handler to retrieve the full conversation history."""
         return self.conversation_history
+    
+    @workflow.query
+    def get_agent_goal(self) -> AgentGoal:
+        """Query handler to retrieve the current goal of the agent."""
+        return self.goal
 
     @workflow.query
     def get_summary_from_history(self) -> Optional[str]: