Simplify the "warm transfer" demo to use the new "function" action type in lieu of a bunch of custom code

Author: kompfner

examples/static/warm_transfer.py

@@ -148,14 +148,11 @@ async def pre_transferring_to_human_agent(action: dict, flow_manager: FlowManage
             }
         )
 
-async def queue_post_transferring_to_human_agent(action: dict, flow_manager: FlowManager):
-    task = flow_manager.task
-    await task.queue_frame(PostTransferringToHumanAgentFrame())
-
 # NOTE: this isn't a "real" post-action because it needs to run after the "transferring you to a
 # human agent" speech is actually spoken, not just after sending the LLM the instruction to do so.
-async def post_transferring_to_human_agent(transport: DailyTransport):
+async def post_transferring_to_human_agent(action: dict, flow_manager: FlowManager):
     """Post-action after starting transferring to the human agent."""
+    transport: DailyTransport = flow_manager.transport
     customer_participant_id = get_customer_participant_id(transport=transport)
 
     # Update the customer:
@@ -178,15 +175,12 @@ async def post_transferring_to_human_agent(transport: DailyTransport):
             }
         )
 
-async def queue_post_end_human_agent_conversation(action: dict, flow_manager: FlowManager):
-    task = flow_manager.task
-    await task.queue_frame(PostEndHumanAgentConversationFrame())
-
 # NOTE: this isn't a "real" post-action because it needs to run after the "I'm patching you through
 # to the customer" speech is actually spoken, not just after sending the LLM the instruction to do
 # so.
-async def post_end_human_agent_conversation(transport: DailyTransport):
+async def post_end_human_agent_conversation(action: dict, flow_manager: FlowManager):
     """Post-action after starting to end the conversation with the human agent, when the agent is being patched through to the customer."""
+    transport: DailyTransport = flow_manager.transport
     customer_participant_id = get_customer_participant_id(transport=transport)
     agent_participant_id = get_human_agent_participant_id(transport=transport)
 
@@ -368,15 +362,14 @@ def create_transferring_to_human_agent_node() -> NodeConfig:
         functions=[],
         pre_actions=[
             ActionConfig(
-                type="pre_transferring_to_human_agent",
+                type="function",
                 handler=pre_transferring_to_human_agent
-            )
+            ),
         ],
         post_actions=[
-            # NOTE: "real" post action (post_transferring_to_human_agent) is triggered by CustomControlProcessor
             ActionConfig(
-                type="queue_post_transferring_to_human_agent",
-                handler=queue_post_transferring_to_human_agent
+                type="function",
+                handler=post_transferring_to_human_agent
             )
         ]
     )
@@ -443,10 +436,9 @@ def create_end_human_agent_conversation_node() -> NodeConfig:
         ],
         functions=[],
         post_actions=[
-            # NOTE: "real" post action (post_end_human_agent_conversation) is triggered by CustomControlProcessor
             ActionConfig(
-                type="queue_post_end_human_agent_conversation",
-                handler=queue_post_end_human_agent_conversation
+                type="function",
+                handler=post_end_human_agent_conversation
             ),
             ActionConfig(type="end_conversation")
         ]
@@ -543,35 +535,6 @@ async def get_token(user_id: str, permissions: dict, daily_rest_helper: DailyRES
         ))
     )
 
-@dataclass
-class PostTransferringToHumanAgentFrame(ControlFrame):
-    """
-    Indicates that the bot has finished speaking the "transferring you to human agent" speech.
-    """
-    pass
-
-@dataclass
-class PostEndHumanAgentConversationFrame(ControlFrame):
-    """
-    Indicates that the bot has finished speaking the "I'm patching you through to the customer" speech.
-    """
-    pass
-
-class CustomControlProcessor(FrameProcessor):
-    def __init__(self, transport: DailyTransport):
-        super().__init__()
-        self.__transport = transport
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, PostTransferringToHumanAgentFrame):
-            await post_transferring_to_human_agent(transport=self.__transport)
-        elif isinstance(frame, PostEndHumanAgentConversationFrame):
-            await post_end_human_agent_conversation(transport=self.__transport)
-
-        await self.push_frame(frame, direction)
-
 async def main():
     """Main function to set up and run the bot."""
 
@@ -596,7 +559,6 @@ async def main():
             voice_id="820a3788-2b37-4d21-847a-b65d8a68c99a",  # Salesman
         )
         llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
-        custom_control_processor = CustomControlProcessor(transport=transport)
 
         # Initialize context
         context = OpenAILLMContext()
@@ -611,8 +573,7 @@ async def main():
                 llm,
                 tts,
                 transport.output(),
-                context_aggregator.assistant(),
-                custom_control_processor
+                context_aggregator.assistant()
             ]
         )
         task = PipelineTask(pipeline=pipeline, params=PipelineParams(allow_interruptions=True))