from abc import ABC, abstractmethod from typing import Any, AsyncGenerator, List, Optional, Union import openai from letta.schemas.enums import MessageStreamStatus from letta.schemas.letta_message import LegacyLettaMessage, LettaMessage from letta.schemas.letta_message_content import TextContent from letta.schemas.letta_response import LettaResponse from letta.schemas.message import MessageCreate from letta.schemas.user import User from letta.services.agent_manager import AgentManager from letta.services.message_manager import MessageManager class BaseAgent(ABC): """ Abstract base class for AI agents, handling message management, tool execution, and context tracking. """ def __init__( self, agent_id: str, # TODO: Make required once client refactor hits openai_client: Optional[openai.AsyncClient], message_manager: MessageManager, agent_manager: AgentManager, actor: User, ): self.agent_id = agent_id self.openai_client = openai_client self.message_manager = message_manager self.agent_manager = agent_manager self.actor = actor @abstractmethod async def step(self, input_messages: List[MessageCreate], max_steps: int = 10) -> LettaResponse: """ Main execution loop for the agent. """ raise NotImplementedError @abstractmethod async def step_stream( self, input_messages: List[MessageCreate], max_steps: int = 10 ) -> AsyncGenerator[Union[LettaMessage, LegacyLettaMessage, MessageStreamStatus], None]: """ Main streaming execution loop for the agent. """ raise NotImplementedError def pre_process_input_message(self, input_messages: List[MessageCreate]) -> Any: """ Pre-process function to run on the input_message. """ def get_content(message: MessageCreate) -> str: if isinstance(message.content, str): return message.content elif message.content and len(message.content) == 1 and isinstance(message.content[0], TextContent): return message.content[0].text else: return "" return [{"role": input_message.role.value, "content": get_content(input_message)} for input_message in input_messages]