ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/gaia-experience/AWorld/aworld/runner.py

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+# 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)