merged old agent goal in with keynote goal

workflows/workflow_helpers.py

@@ -5,7 +5,10 @@ from temporalio.exceptions import ActivityError
 from temporalio.common import RetryPolicy
 
 from models.data_types import ConversationHistory, ToolPromptInput
-from prompts.agent_prompt_generators import generate_missing_args_prompt, generate_tool_completion_prompt
+from prompts.agent_prompt_generators import (
+    generate_missing_args_prompt,
+    generate_tool_completion_prompt,
+)
 from shared.config import TEMPORAL_LEGACY_TASK_QUEUE
 
 # Constants from original file
@@ -14,12 +17,13 @@ TOOL_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT = timedelta(minutes=30)
 LLM_ACTIVITY_START_TO_CLOSE_TIMEOUT = timedelta(seconds=10)
 LLM_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT = timedelta(minutes=30)
 
+
 async def handle_tool_execution(
     current_tool: str,
     tool_data: Dict[str, Any],
     tool_results: list,
     add_message_callback: callable,
-    prompt_queue: Deque[str]
+    prompt_queue: Deque[str],
 ) -> None:
     """Execute a tool after confirmation and handle its result."""
     workflow.logger.info(f"Confirmed. Proceeding with tool: {current_tool}")
@@ -50,11 +54,12 @@ async def handle_tool_execution(
     add_message_callback("tool_result", dynamic_result)
     prompt_queue.append(generate_tool_completion_prompt(current_tool, dynamic_result))
 
+
 async def handle_missing_args(
     current_tool: str,
     args: Dict[str, Any],
     tool_data: Dict[str, Any],
-    prompt_queue: Deque[str]
+    prompt_queue: Deque[str],
 ) -> bool:
     """Check for missing arguments and handle them if found."""
     missing_args = [key for key, value in args.items() if value is None]
@@ -69,13 +74,15 @@ async def handle_missing_args(
         return True
     return False
 
+
 def format_history(conversation_history: ConversationHistory) -> str:
     """Format the conversation history into a single string."""
-    return " ".join(
-        str(msg["response"]) for msg in conversation_history["messages"]
-    )
+    return " ".join(str(msg["response"]) for msg in conversation_history["messages"])
 
-def prompt_with_history(conversation_history: ConversationHistory, prompt: str) -> tuple[str, str]:
+
+def prompt_with_history(
+    conversation_history: ConversationHistory, prompt: str
+) -> tuple[str, str]:
     """Generate a context-aware prompt with conversation history."""
     history_string = format_history(conversation_history)
     context_instructions = (
@@ -86,16 +93,19 @@ def prompt_with_history(conversation_history: ConversationHistory, prompt: str)
     )
     return (context_instructions, prompt)
 
+
 async def continue_as_new_if_needed(
     conversation_history: ConversationHistory,
     prompt_queue: Deque[str],
     agent_goal: Any,
     max_turns: int,
-    add_message_callback: callable
+    add_message_callback: callable,
 ) -> None:
     """Handle workflow continuation if message limit is reached."""
     if len(conversation_history["messages"]) >= max_turns:
-        summary_context, summary_prompt = prompt_summary_with_history(conversation_history)
+        summary_context, summary_prompt = prompt_summary_with_history(
+            conversation_history
+        )
         summary_input = ToolPromptInput(
             prompt=summary_prompt, context_instructions=summary_context
         )
@@ -104,21 +114,24 @@ async def continue_as_new_if_needed(
             summary_input,
             schedule_to_close_timeout=LLM_ACTIVITY_SCHEDULE_TO_CLOSE_TIMEOUT,
         )
-        workflow.logger.info(
-            f"Continuing as new after {max_turns} turns."
-        )
+        workflow.logger.info(f"Continuing as new after {max_turns} turns.")
         add_message_callback("conversation_summary", conversation_summary)
         workflow.continue_as_new(
-            args=[{
-                "tool_params": {
-                    "conversation_summary": conversation_summary,
-                    "prompt_queue": prompt_queue,
-                },
-                "agent_goal": agent_goal,
-            }]
+            args=[
+                {
+                    "tool_params": {
+                        "conversation_summary": conversation_summary,
+                        "prompt_queue": prompt_queue,
+                    },
+                    "agent_goal": agent_goal,
+                }
+            ]
         )
 
-def prompt_summary_with_history(conversation_history: ConversationHistory) -> tuple[str, str]:
+
+def prompt_summary_with_history(
+    conversation_history: ConversationHistory,
+) -> tuple[str, str]:
     """Generate a prompt for summarizing the conversation.
     Used only for continue as new of the workflow."""
     history_string = format_history(conversation_history)
@@ -127,4 +140,4 @@ def prompt_summary_with_history(conversation_history: ConversationHistory) -> tu
         "Please produce a two sentence summary of this conversation. "
         'Put the summary in the format { "summary": "<plain text>" }'
     )
-    return (context_instructions, actual_prompt) 
+    return (context_instructions, actual_prompt)