438 lines
15 KiB
Python
438 lines
15 KiB
Python
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# -*- coding: utf-8 -*-
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"""A2A call tool: send a message to a remote A2A Agent.
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Supports resolution by alias (reading from per-agent a2a_config.json)
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or by direct URL. When using alias, auth config is automatically
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applied from the stored registration.
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The tool is an ``AsyncGenerator`` that yields intermediate
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``ToolChunk(state=RUNNING, is_last=False)`` chunks as SSE events
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arrive from the remote agent, so the QwenPaw frontend can render
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incremental progress in real time via the tool renderer. The final
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chunk carries ``state=SUCCESS, is_last=True``.
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"""
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import json
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import logging
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from collections.abc import AsyncGenerator
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from agentscope.message import TextBlock, ToolResultState
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from agentscope.tool import ToolChunk
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logger = logging.getLogger("qwenpaw").getChild(
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__name__.replace("plugin_cloudpaw.", ""),
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)
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async def a2a_call( # pylint: disable=too-many-branches,too-many-statements
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message: str,
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agent_alias: str = "",
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agent_url: str = "",
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context_id: str = "",
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) -> AsyncGenerator[ToolChunk, None]:
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"""向远程 A2A Agent 发送消息并获取响应。
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通过 ``agent_alias``（已注册的别名）或 ``agent_url``（URL）指定目标 Agent。
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使用别名时自动应用已注册的认证配置。
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Args:
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message: 发送给远程 Agent 的文本消息
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agent_alias: 已注册的远程 Agent 别名（优先使用，通过 a2a_list 查看可用别名）
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agent_url: 远程 A2A Agent 的基础 URL（alias 为空时使用）
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context_id: 可选，会话上下文 ID（多轮对话时传入上次返回的 contextId）
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Yields:
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ToolChunk: 远程 Agent 的流式响应，包含：
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- response_text: Agent 回复的文本内容（累积）
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- task_id: 任务 ID（如有）
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- context_id: 会话上下文 ID（用于多轮对话）
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- task_state: 任务最终状态
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- event_count: 收到的事件总数
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"""
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from modules.a2a.client_manager import get_a2a_manager
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try:
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from modules.a2a.call_stream import (
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finish_stream,
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get_stream,
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start_stream,
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)
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stream_queue = get_stream()
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if stream_queue is None:
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stream_queue = start_stream()
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_has_call_stream = True
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except ImportError:
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stream_queue = None
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_has_call_stream = False
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manager = get_a2a_manager()
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resolved_url = agent_url
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auth_type = ""
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auth_token = ""
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def _error_response(error_msg: str) -> ToolChunk:
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return ToolChunk(
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state=ToolResultState.SUCCESS,
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is_last=True,
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content=[
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TextBlock(
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type="text",
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text=json.dumps(
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{"error": error_msg, "task_state": "error"},
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ensure_ascii=False,
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),
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),
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],
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)
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if agent_alias:
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from .a2a_config_helper import resolve_agent_by_alias
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reg = resolve_agent_by_alias(agent_alias)
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if not reg:
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if _has_call_stream:
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finish_stream()
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yield _error_response(
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f"未找到别名为 '{agent_alias}' 的已注册 A2A Agent。"
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f"请先通过 a2a_list 查看可用的 Agent。",
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)
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return
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resolved_url = reg["url"]
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auth_type = reg.get("auth_type", "")
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auth_token = reg.get("auth_token", "")
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gateway_config = reg.get("gateway_config")
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card_info = await manager.get_card_info(resolved_url)
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if not card_info or card_info.get("status") != "connected":
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try:
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await manager.connect(
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agent_url=resolved_url,
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auth_type=auth_type,
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auth_token=auth_token,
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gateway_config=gateway_config,
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)
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except Exception as e:
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if _has_call_stream:
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finish_stream()
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yield _error_response(
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f"连接 '{agent_alias}' ({resolved_url}) 失败: {e}",
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)
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return
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if not resolved_url:
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if _has_call_stream:
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finish_stream()
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yield _error_response("必须提供 agent_alias 或 agent_url 之一。")
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return
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events: list[dict] = []
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try:
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logger.info(
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"A2A call started: alias=%s, url=%s, message=%s",
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agent_alias or "(direct)",
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resolved_url,
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message[:100],
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)
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tracker = _StepTracker()
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last_snapshot = ""
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async for event in manager.send_message(
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agent_url=resolved_url,
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message=message,
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context_id=context_id,
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streaming=True,
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):
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events.append(event)
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tracker.process(event)
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snapshot = json.dumps(
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tracker.snapshot(),
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ensure_ascii=False,
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)
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if snapshot != last_snapshot:
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last_snapshot = snapshot
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payload = {
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"steps": tracker.snapshot(),
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"task_state": "working",
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"event_count": len(events),
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}
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if stream_queue is not None:
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_push(stream_queue, payload)
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yield ToolChunk(
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state=ToolResultState.RUNNING,
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is_last=False,
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content=[
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TextBlock(
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type="text",
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text=json.dumps(payload, ensure_ascii=False),
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),
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],
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)
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result = _build_result(events, context_id)
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result["steps"] = tracker.snapshot()
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logger.info(
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"A2A call completed: events=%d, state=%s, text_len=%d",
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len(events),
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result.get("task_state"),
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len(result.get("response_text", "")),
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)
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if stream_queue is not None:
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_push(stream_queue, {**result, "final": True})
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except Exception as e:
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logger.exception("A2A call failed: %s — %s", resolved_url, e)
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result = {
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"response_text": "",
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"error": str(e),
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"task_id": "",
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"context_id": context_id,
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"task_state": "error",
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"event_count": len(events),
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}
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if stream_queue is not None:
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_push(stream_queue, {**result, "final": True})
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finally:
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if _has_call_stream:
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finish_stream()
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yield ToolChunk(
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state=ToolResultState.SUCCESS,
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is_last=True,
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content=[
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TextBlock(
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type="text",
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text=json.dumps(result, ensure_ascii=False),
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),
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],
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)
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def _push(queue, data: dict) -> None:
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"""Push data to the stream queue (non-blocking)."""
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try:
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queue.put_nowait(data)
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except Exception:
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pass
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class _StepTracker:
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"""Accumulates A2A SSE events into a structured list of UI steps.
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Step types:
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- thinking: LLM thinking tokens, accumulated into a single text block.
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Finalized (done=True) once a non-thinking event arrives.
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- tool_call: Remote agent tool invocation.
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status cycles: running → done / error.
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- text: Agent response text (artifact / message).
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"""
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def __init__(self) -> None:
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self._steps: list[dict] = []
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self._thinking_buf: list[str] = []
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self._active_tools: dict[str, int] = {}
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def process( # pylint: disable=too-many-branches
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self,
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event: dict,
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) -> None:
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ev_type = event.get("type", "")
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if ev_type == "status_update":
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su = event.get("statusUpdate", {})
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meta = su.get("metadata", {})
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msg_type = meta.get("message_type", "")
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if msg_type == "thinking":
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self._thinking_buf.append(meta.get("thinking", ""))
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self._ensure_thinking_step()
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return
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self._finalize_thinking()
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if msg_type == "tool_use":
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tool_id = meta.get("tool_use_id", "")
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name = meta.get("tool_name", "?")
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desc = (meta.get("tool_input") or {}).get("description", "")
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step = {
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"type": "tool_call",
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"name": name,
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"status": "running",
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"desc": desc,
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}
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self._steps.append(step)
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if tool_id:
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self._active_tools[tool_id] = len(self._steps) - 1
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elif msg_type == "tool_result":
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tool_id = meta.get("tool_use_id", "")
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is_error = meta.get("is_error", False)
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idx = self._active_tools.pop(tool_id, None)
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if idx is not None and idx < len(self._steps):
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self._steps[idx]["status"] = (
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"error" if is_error else "done"
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)
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else:
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name = meta.get("tool_name", "?")
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self._steps.append(
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{
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"type": "tool_call",
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"name": name,
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"status": "error" if is_error else "done",
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},
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)
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else:
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text = _extract_text_from_parts(
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su.get("status", {}).get("message", {}).get("parts", []),
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)
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if text:
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self._append_text(text)
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elif ev_type == "artifact_update":
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self._finalize_thinking()
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artifact = event.get("artifactUpdate", {}).get("artifact", {})
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text = _extract_text_from_parts(artifact.get("parts", []))
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if text:
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self._append_text(text)
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elif ev_type == "task":
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self._finalize_thinking()
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task_data = event.get("task", {})
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for artifact in task_data.get("artifacts", []):
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text = _extract_text_from_parts(artifact.get("parts", []))
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if text:
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self._append_text(text)
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elif ev_type == "message":
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self._finalize_thinking()
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text = _extract_text_from_parts(
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event.get("message", {}).get("parts", []),
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)
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if text:
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self._append_text(text)
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def snapshot(self) -> list[dict]:
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steps = [s.copy() for s in self._steps]
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if self._thinking_buf:
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for s in steps:
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if s.get("type") == "thinking" and not s.get("done"):
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s["text"] = "".join(self._thinking_buf)
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break
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return steps
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def _ensure_thinking_step(self) -> None:
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if (
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not self._steps
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or self._steps[-1].get("type") != "thinking"
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or self._steps[-1].get("done")
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):
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self._steps.append({"type": "thinking", "text": "", "done": False})
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def _finalize_thinking(self) -> None:
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if not self._thinking_buf:
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return
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text = "".join(self._thinking_buf)
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self._thinking_buf.clear()
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for s in reversed(self._steps):
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if s.get("type") == "thinking" and not s.get("done"):
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s["text"] = text
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s["done"] = True
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return
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def _append_text(self, text: str) -> None:
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if self._steps and self._steps[-1].get("type") == "text":
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self._steps[-1]["text"] += text
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else:
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self._steps.append({"type": "text", "text": text})
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def _build_result( # pylint: disable=too-many-branches,too-many-statements
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events: list[dict],
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initial_context_id: str,
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) -> dict:
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"""Build final result dict from all collected events."""
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artifact_texts: list[str] = []
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status_texts: list[str] = []
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final_task_id = ""
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final_context_id = initial_context_id
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final_state = ""
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for ev in events:
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ev_type = ev.get("type", "")
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|
|||
|
|
if ev_type == "task":
|
|||
|
|
task_data = ev.get("task", {})
|
|||
|
|
if "id" in task_data:
|
|||
|
|
final_task_id = task_data["id"]
|
|||
|
|
if "contextId" in task_data:
|
|||
|
|
final_context_id = task_data["contextId"]
|
|||
|
|
status = task_data.get("status", {})
|
|||
|
|
if "state" in status:
|
|||
|
|
final_state = status["state"]
|
|||
|
|
msg = status.get("message", {})
|
|||
|
|
text = _extract_text_from_parts(msg.get("parts", []))
|
|||
|
|
if text:
|
|||
|
|
status_texts.append(text)
|
|||
|
|
for artifact in task_data.get("artifacts", []):
|
|||
|
|
text = _extract_text_from_parts(artifact.get("parts", []))
|
|||
|
|
if text:
|
|||
|
|
artifact_texts.append(text)
|
|||
|
|
|
|||
|
|
elif ev_type == "status_update":
|
|||
|
|
su = ev.get("statusUpdate", {})
|
|||
|
|
if "taskId" in su:
|
|||
|
|
final_task_id = su["taskId"]
|
|||
|
|
if "contextId" in su:
|
|||
|
|
final_context_id = su["contextId"]
|
|||
|
|
status = su.get("status", {})
|
|||
|
|
if "state" in status:
|
|||
|
|
final_state = status["state"]
|
|||
|
|
msg = status.get("message", {})
|
|||
|
|
text = _extract_text_from_parts(msg.get("parts", []))
|
|||
|
|
if text:
|
|||
|
|
status_texts.append(text)
|
|||
|
|
|
|||
|
|
elif ev_type == "artifact_update":
|
|||
|
|
au = ev.get("artifactUpdate", {})
|
|||
|
|
if "taskId" in au:
|
|||
|
|
final_task_id = au["taskId"]
|
|||
|
|
if "contextId" in au:
|
|||
|
|
final_context_id = au["contextId"]
|
|||
|
|
artifact = au.get("artifact", {})
|
|||
|
|
text = _extract_text_from_parts(artifact.get("parts", []))
|
|||
|
|
if text:
|
|||
|
|
artifact_texts.append(text)
|
|||
|
|
|
|||
|
|
elif ev_type == "message":
|
|||
|
|
msg = ev.get("message", {})
|
|||
|
|
text = _extract_text_from_parts(msg.get("parts", []))
|
|||
|
|
if text:
|
|||
|
|
artifact_texts.append(text)
|
|||
|
|
|
|||
|
|
response_text = "".join(artifact_texts)
|
|||
|
|
if not response_text and status_texts:
|
|||
|
|
response_text = "\n".join(status_texts)
|
|||
|
|
if not response_text and final_state:
|
|||
|
|
response_text = f"[任务状态: {final_state}]"
|
|||
|
|
|
|||
|
|
return {
|
|||
|
|
"response_text": response_text,
|
|||
|
|
"task_id": final_task_id,
|
|||
|
|
"context_id": final_context_id,
|
|||
|
|
"task_state": final_state,
|
|||
|
|
"event_count": len(events),
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
|
|||
|
|
def _extract_text_from_parts(parts: list) -> str:
|
|||
|
|
"""Extract concatenated text from a list of A2A message parts."""
|
|||
|
|
texts = []
|
|||
|
|
for part in parts or []:
|
|||
|
|
if isinstance(part, dict) and "text" in part:
|
|||
|
|
texts.append(part["text"])
|
|||
|
|
return "".join(texts)
|