readme update

README.md

@@ -1,6 +1,6 @@
 # AI Agent execution using Temporal
 
-Work in progress (very early!).
+Work in progress.
 
 This demo shows a multi-turn conversation with an AI agent running inside a Temporal workflow. The goal is to collect information towards a goal. There's a simple DSL input for collecting information (currently set up to use mock functions to search for events, book flights around those events then generate an invoice for those flights, see `send_message.py`). The AI will respond with clarifications and ask for any missing information to that goal. It uses a local LLM via Ollama.
 

workflows/tool_workflow.py

@@ -179,7 +179,7 @@ class ToolWorkflow:
                     "Chat ended. Conversation summary:\n"
                     + f"{self.conversation_summary}"
                 )
-                return f"{self.conversation_history}"
+                return f"{self.conversation_summary}"
 
     @workflow.signal
     async def user_prompt(self, prompt: str) -> None: