ai-agent-book/chapter9/gaia-experience/AWorld/aworld/runner.py

# coding: utf-8
# Copyright (c) 2025 inclusionAI.
import asyncio
import logging
from concurrent.futures.process import ProcessPoolExecutor
from typing import List, Dict, Union

from aworld.config import RunConfig
from aworld.config.conf import TaskConfig
from aworld.agents.llm_agent import Agent
from aworld.core.agent.swarm import Swarm
from aworld.core.common import Config
from aworld.core.task import Task, TaskResponse, Runner
from aworld.output import StreamingOutputs
from aworld.utils.common import sync_exec
from aworld.utils.run_util import exec_tasks


class Runners:
    """Unified entrance to the utility class of the runnable task of execution."""

    @staticmethod
    def streamed_run_task(task: Task) -> StreamingOutputs:
        """Run the task in stream output."""
        if not task.conf:
            task.conf = TaskConfig()

        streamed_result = StreamingOutputs(
            input=task.input,
            usage={},
            is_complete=False
        )
        task.outputs = streamed_result
        streamed_result.task_id = task.id

        logging.info(f"[Runners]streamed_run_task start task_id={task.id}, agent={task.agent}, swarm = {task.swarm} ")

        streamed_result._run_impl_task = asyncio.create_task(
            Runners.run_task(task)
        )
        return streamed_result

    @staticmethod
    async def run_task(task: Union[Task, List[Task]], run_conf: RunConfig = None) -> Dict[str, TaskResponse]:
        """Run tasks for some complex scenarios where agents cannot be directly used.

        Args:
            task: User task define.
            run_conf:
        """
        if isinstance(task, Task):
            task = [task]

        logging.debug(f"[Runners]run_task start task_id={task[0].id} start")
        result = await exec_tasks(task, run_conf)
        logging.debug(f"[Runners]run_task end task_id={task[0].id} end")
        return result

    @staticmethod
    def sync_run_task(task: Union[Task, List[Task]], run_conf: Config = None) -> Dict[str, TaskResponse]:
        return sync_exec(Runners.run_task, task=task, run_conf=run_conf)

    @staticmethod
    def sync_run(
            input: str,
            agent: Agent = None,
            swarm: Swarm = None,
            tool_names: List[str] = [],
            session_id: str = None,
            run_conf: RunConfig = None
    ) -> TaskResponse:
        return sync_exec(
            Runners.run,
            input=input,
            agent=agent,
            swarm=swarm,
            tool_names=tool_names,
            session_id=session_id,
            run_conf=run_conf
        )

    @staticmethod
    async def run(
            input: str,
            agent: Agent = None,
            swarm: Swarm = None,
            tool_names: List[str] = [],
            session_id: str = None,
            run_conf: RunConfig = None
    ) -> TaskResponse:
        """Run agent directly with input and tool names.

        Args:
            input: User query.
            agent: An agent with AI model configured, prompts, tools, mcp servers and other agents.
            swarm: Multi-agent topo.
            tool_names: Tool name list.
            session_id: Session id.

        Returns:
            TaskResponse: Task response.
        """
        if agent and swarm:
            raise ValueError("`agent` and `swarm` only choose one.")

        if not input:
            raise ValueError('`input` is empty.')

        if agent:
            agent.task = input
            swarm = Swarm(agent)

        task = Task(input=input, swarm=swarm, tool_names=tool_names,
                    event_driven=swarm.event_driven, session_id=session_id)
        res = await Runners.run_task(task, run_conf=run_conf)
        return res.get(task.id)