`agentsociety.cityagent.societyagent`¶

Module Contents¶

Classes¶

Data¶

ENVIRONMENT_REFLECTION_PROMPT

API¶

agentsociety.cityagent.societyagent.ENVIRONMENT_REFLECTION_PROMPT = <Multiline-String>¶

class agentsociety.cityagent.societyagent.SocietyAgent(id: int, name: str, toolbox: agentsociety.agent.AgentToolbox, memory: agentsociety.memory.Memory, agent_params: Optional[agentsociety.cityagent.sharing_params.SocietyAgentConfig] = None, blocks: Optional[list[agentsociety.agent.Block]] = None)¶

Bases: agentsociety.agent.CitizenAgentBase

Initialization

Initialize agent with core components and configuration.

ParamsType¶: None

BlockOutputType¶: None

Context¶: None

StatusAttributes¶: None

description: str = <Multiline-String>¶: Agent implementation with configurable cognitive/behavioral modules and social interaction capabilities.

async status_summary()¶: Status summary

async before_forward()¶: Before forward

async reset()¶: Reset the agent.

async plan_generation()¶: Generate a new plan if no current plan exists in memory.

async reflect_to_environment()¶: Reflect to the environment

async forward()¶: Main agent loop coordinating status updates, plan execution, and cognition.

async check_and_update_step()¶: Check if the previous step has been completed

async do_chat(message: agentsociety.message.Message) → str¶: Process incoming social/economic messages and generate responses.

async react_to_intervention(intervention_message: str)¶: React to an intervention

async reset_position()¶: Reset the position of the agent.

async step_execution()¶: Execute the current step in the active plan based on step type.