Display System

Terminal output, TaskOutput objects, and global display callbacks

from praisonaiagents import Agent

agent = Agent(name="assistant", instructions="Be helpful.", output=True)
agent.start("Explain loop detection in one paragraph.")

The display system formats agent output in the terminal and exposes hooks for custom rendering.

The user runs the agent in a terminal; the display system renders Rich output and optional global callbacks.

How It Works

Quick Start

1. Default terminal output

   from praisonaiagents import Agent
   
   agent = Agent(
       name="assistant",
       instructions="Be helpful.",
       output=True,
   )
   agent.start("Explain display callbacks in one sentence.")

2. Custom interaction handler

   from praisonaiagents import Agent, register_display_callback
   
   def compact(message=None, response=None, **kwargs):
       name = kwargs.get("agent_name", "agent")
       print(f"[{name}] {response}")
   
   register_display_callback("interaction", compact)
   
   agent = Agent(name="writer", instructions="Keep answers short.")
   agent.start("One tip for readable logs.")

3. Inspect TaskOutput in a task callback

   from praisonaiagents import Agent, Task, TaskOutput, PraisonAIAgents
   
   def show_result(output: TaskOutput):
       print(output.raw)
       if output.metadata:
           print("meta:", output.metadata)
   
   agent = Agent(name="analyst", instructions="Analyse briefly.")
   task = Task(
       description="List three benefits of typed task output",
       expected_output="Bulleted list",
       agent=agent,
       callback=show_result,
   )
   PraisonAIAgents(agents=[agent], tasks=[task]).start()

Core Types

TaskOutput

ReflectionOutput

Import both from the top level: from praisonaiagents import TaskOutput, ReflectionOutput.

Global Registries

Built-in display helpers (display_interaction, display_tool_call, display_error, and others) call registered callbacks even when verbose output is off.

Best Practices

Related