aact moderator

examples/experimental/nodes/initial_message_node.py

@@ -18,6 +18,7 @@ def __init__(
         input_tick_channel: str,
         output_channels: list[str],
         env_scenario: str,
+        node_name: str,
         redis_url: str = "redis://localhost:6379/0",
     ):
         super().__init__(
@@ -26,6 +27,7 @@ def __init__(
                 (output_channel, Text) for output_channel in output_channels
             ],
             redis_url=redis_url,
+            node_name=node_name,
         )
         self.env_scenario = env_scenario
         self.output_channels = output_channels

examples/experimental/sotopia_original_replica/llm_agent_sotopia.py

@@ -0,0 +1,113 @@
+import logging
+import sys
+from rich.logging import RichHandler
+
+from aact import NodeFactory
+
+from sotopia.experimental.agents.base_agent import BaseAgent
+from sotopia.experimental.agents.datamodels import Observation, AgentAction
+
+from sotopia.generation_utils import agenerate
+from sotopia.generation_utils.generate import StrOutputParser
+
+# Check Python version
+if sys.version_info >= (3, 11):
+    pass
+else:
+    pass
+
+# Configure logging
+FORMAT = "%(asctime)s - %(levelname)s - %(name)s - %(message)s"
+logging.basicConfig(
+    level=logging.WARNING,
+    format=FORMAT,
+    datefmt="[%X]",
+    handlers=[RichHandler()],
+)
+
+
+@NodeFactory.register("llm_agent")
+class LLMAgent(BaseAgent[Observation, AgentAction]):
+    def __init__(
+        self,
+        input_channels: list[str],
+        output_channel: str,
+        query_interval: int,
+        agent_name: str,
+        node_name: str,
+        goal: str,
+        model_name: str,
+        redis_url: str,
+    ):
+        super().__init__(
+            [(input_channel, Observation) for input_channel in input_channels],
+            [(output_channel, AgentAction)],
+            redis_url,
+            node_name,
+        )
+        self.output_channel = output_channel
+        self.query_interval = query_interval
+        self.count_ticks = 0
+        self.message_history: list[Observation] = []
+        self.name = agent_name
+        self.model_name = model_name
+        self.goal = goal
+
+    def _format_message_history(self, message_history: list[Observation]) -> str:
+        ## TODO: akhatua Fix the mapping of action to be gramatically correct
+        return "\n".join(message.to_natural_language() for message in message_history)
+
+    async def aact(self, obs: Observation) -> AgentAction:
+        if obs.turn_number == -1:
+            return AgentAction(
+                agent_name=self.name,
+                output_channel=self.output_channel,
+                action_type="none",
+                argument=self.model_name,
+            )
+
+        self.message_history.append(obs)
+
+        if len(obs.available_actions) == 1 and "none" in obs.available_actions:
+            return AgentAction(
+                agent_name=self.name,
+                output_channel=self.output_channel,
+                action_type="none",
+                argument="",
+            )
+        elif len(obs.available_actions) == 1 and "leave" in obs.available_actions:
+            self.shutdown_event.set()
+            return AgentAction(
+                agent_name=self.name,
+                output_channel=self.output_channel,
+                action_type="leave",
+                argument="",
+            )
+        else:
+            history = self._format_message_history(self.message_history)
+            action: str = await agenerate(
+                model_name=self.model_name,
+                template="Imagine that you are a friend of the other persons. Here is the "
+                "conversation between you and them.\n"
+                "You are {agent_name} in the conversation.\n"
+                "{message_history}\n"
+                "and you plan to {goal}.\n"
+                "You can choose to interrupt the other person "
+                "by saying something or not to interrupt by outputting notiong. What would you say? "
+                "Please only output a sentence or not outputting anything."
+                "{format_instructions}",
+                input_values={
+                    "message_history": history,
+                    "goal": self.goal,
+                    "agent_name": self.name,
+                },
+                temperature=0.7,
+                output_parser=StrOutputParser(),
+            )
+
+            return AgentAction(
+                agent_name=self.name,
+                output_channel=self.output_channel,
+                action_type="speak",
+                argument=action,
+            )