Change instructions to AI to handle switching back to ListAgents when done with tool chain

api/main.py

@@ -194,7 +194,6 @@ async def end_chat():
 
 @app.post("/start-workflow")
 async def start_workflow():
-    # 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

prompts/agent_prompt_generators.py

@@ -81,9 +81,8 @@ def generate_genai_prompt(
         "1) If any required argument is missing, set next='question' and ask the user.\n"
         "2) If all required arguments are known, set next='confirm' and specify the tool.\n"
         "   The user will confirm before the tool is run.\n"
-        "3) If no more tools are needed (user_confirmed_tool_run has been run for all), set next='done' and tool=null.\n"
+        "3) If no more tools are needed (user_confirmed_tool_run has been run for all), set next='confirm' and tool='ListAgents'.\n"
         "4) response should be short and user-friendly.\n"
-        "5) Don't set next='done' until the final tool has returned user_confirmed_tool_run.\n"
     )
 
     # Validation Task (If raw_json is provided)
@@ -126,9 +125,7 @@ def generate_tool_completion_prompt(current_tool: str, dynamic_result: dict) ->
         "You will need to use the tool_results to auto-fill arguments for subsequent tools and also to figure out if all tools have been run."
         '{"next": "<question|confirm|done>", "tool": "<tool_name or null>", "args": {"<arg1>": "<value1 or null>", "<arg2>": "<value2 or null>}, "response": "<plain text (can include \\n line breaks)>"}'
         "ONLY return those json keys (next, tool, args, response), nothing else."
-        'Next should only be "done" if all tools have been run (use the system prompt to figure that out).'
-        'Next should be "question" if the tool is not the last one in the sequence.'
-        'Next should NOT be "confirm" at this point.'
+        'Next should be "question".'
     )
 
 def generate_missing_args_prompt(current_tool: str, tool_data: dict, missing_args: list[str]) -> str:

workflows/agent_goal_workflow.py

@@ -12,9 +12,6 @@ from workflows.workflow_helpers import LLM_ACTIVITY_START_TO_CLOSE_TIMEOUT, \
     LLM_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT
 from workflows import workflow_helpers as helpers
 
-
-#importlib.reload(my_module)
-
 with workflow.unsafe.imports_passed_through():
     from activities.tool_activities import ToolActivities
     from prompts.agent_prompt_generators import (
@@ -24,9 +21,6 @@ with workflow.unsafe.imports_passed_through():
         CombinedInput,
         ToolPromptInput,
     )
-    import shared.config
-    importlib.reload(shared.config)
-    #from shared.config import AGENT_GOAL
     from tools.goal_registry import goal_match_train_invoice, goal_event_flight_invoice, goal_choose_agent_type
 
 # Constants
@@ -50,7 +44,6 @@ 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
@@ -108,16 +101,8 @@ class AgentGoalWorkflow:
                 if len(self.tool_results) > 0 and "new_goal" in self.tool_results[-1].keys() and "ChangeGoal" in self.tool_results[-1].values():
                     
                     new_goal = self.tool_results[-1].get("new_goal")
-                    workflow.logger.info(f"Booya new goal!: {new_goal}")
-                    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 new_goal is not None:
-                        self.goal = goals.get(new_goal)
-                    #todo reset goal or tools if this doesn't work or whatever
+                    workflow.logger.warning(f"Booya new goal!: {new_goal}")
+                    self.change_goal(new_goal)
                 continue
 
             if self.prompt_queue:
@@ -161,7 +146,6 @@ class AgentGoalWorkflow:
                     context_instructions=context_instructions,
                 )
 
-                # connect to LLM and get...its feedback? which tool to run? ??
                 tool_data = await workflow.execute_activity(
                     ToolActivities.agent_toolPlanner,
                     prompt_input,
@@ -259,3 +243,15 @@ class AgentGoalWorkflow:
         self.conversation_history["messages"].append(
             {"actor": actor, "response": response}
         )
+
+    def change_goal(self, goal: str) -> None:
+        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 goal is not None:
+            self.goal = goals.get(goal)
+            workflow.logger.warning("Changed goal to " + goal)
+        #todo reset goal or tools if this doesn't work or whatever