from __future__ import annotations from typing import Any from openai.types.responses.response_text_delta_event import ResponseTextDeltaEvent from .agent import Agent from .items import ItemHelpers, TResponseInputItem from .result import RunResultBase from .run import Runner from .stream_events import AgentUpdatedStreamEvent, RawResponsesStreamEvent, RunItemStreamEvent async def run_demo_loop(agent: Agent[Any], *, stream: bool = True) -> None: """Run a simple REPL loop with the given agent. This utility allows quick manual testing and debugging of an agent from the command line. Conversation state is preserved across turns. Enter ``exit`` or ``quit`` to stop the loop. Args: agent: The starting agent to run. stream: Whether to stream the agent output. """ current_agent = agent input_items: list[TResponseInputItem] = [] while True: try: user_input = input(" > ") except (EOFError, KeyboardInterrupt): print() break if user_input.strip().lower() in {"exit", "quit"}: break if not user_input: continue input_items.append({"role": "user", "content": user_input}) result: RunResultBase if stream: result = Runner.run_streamed(current_agent, input=input_items) async for event in result.stream_events(): if isinstance(event, RawResponsesStreamEvent): if isinstance(event.data, ResponseTextDeltaEvent): print(event.data.delta, end="", flush=True) elif isinstance(event, RunItemStreamEvent): if event.item.type == "tool_call_item": print("\n[tool called]", flush=True) elif event.item.type == "tool_call_output_item": print(f"\n[tool output: {event.item.output}]", flush=True) elif event.item.type == "message_output_item": message = ItemHelpers.text_message_output(event.item) print(message, end="", flush=True) elif isinstance(event, AgentUpdatedStreamEvent): print(f"\n[Agent updated: {event.new_agent.name}]", flush=True) print() else: result = await Runner.run(current_agent, input_items) if result.final_output is not None: print(result.final_output) current_agent = result.last_agent input_items = result.to_input_list()