chengyongruandXubin Ren
043f0e67f7
This commit implements a progressive refactoring of the tool system to support plugin discovery, scoped loading, and protocol-driven runtime context injection. Key changes: - Add Tool ABC metadata (tool_name, _scopes) and ToolContext dataclass for dependency injection. - Introduce ToolLoader with pkgutil-based builtin discovery and entry_points-based third-party plugin loading. - Add scope filtering (core/subagent/memory) so different contexts load appropriate tool sets. - Introduce ContextAware protocol and RequestContext dataclass to replace hardcoded per-tool context injection in AgentLoop. - Add RuntimeState / MutableRuntimeState protocols to decouple MyTool from AgentLoop. - Migrate all built-in tools to declare scopes and implement create()/enabled() hooks. - Migrate MessageTool, SpawnTool, CronTool, and MyTool to ContextAware. - Refactor AgentLoop to use ToolLoader and protocol-driven context injection. - Refactor SubagentManager to use ToolLoader(scope="subagent") with per-run FileStates isolation. - Register all built-in tools via pyproject.toml entry_points. - Add comprehensive tests for loader scopes, entry_points, ContextAware, subagent tools, and runtime state sync.
340 lines
13 KiB
Python
340 lines
13 KiB
Python
"""Subagent manager for background task execution."""
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import asyncio
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import json
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import time
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import uuid
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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from loguru import logger
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from nanobot.agent.hook import AgentHook, AgentHookContext
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from nanobot.agent.runner import AgentRunner, AgentRunSpec
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from nanobot.agent.tools.context import ToolContext
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from nanobot.agent.tools.file_state import FileStates
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from nanobot.agent.tools.loader import ToolLoader
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from nanobot.agent.tools.registry import ToolRegistry
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from nanobot.bus.events import InboundMessage
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from nanobot.bus.queue import MessageBus
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from nanobot.config.schema import AgentDefaults, ToolsConfig
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from nanobot.providers.base import LLMProvider
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from nanobot.utils.prompt_templates import render_template
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@dataclass(slots=True)
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class SubagentStatus:
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"""Real-time status of a running subagent."""
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task_id: str
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label: str
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task_description: str
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started_at: float # time.monotonic()
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phase: str = "initializing" # initializing | awaiting_tools | tools_completed | final_response | done | error
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iteration: int = 0
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tool_events: list = field(default_factory=list) # [{name, status, detail}, ...]
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usage: dict = field(default_factory=dict) # token usage
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stop_reason: str | None = None
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error: str | None = None
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class _SubagentHook(AgentHook):
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"""Hook for subagent execution — logs tool calls and updates status."""
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def __init__(self, task_id: str, status: SubagentStatus | None = None) -> None:
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super().__init__()
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self._task_id = task_id
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self._status = status
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async def before_execute_tools(self, context: AgentHookContext) -> None:
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for tool_call in context.tool_calls:
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args_str = json.dumps(tool_call.arguments, ensure_ascii=False)
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logger.debug(
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"Subagent [{}] executing: {} with arguments: {}",
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self._task_id, tool_call.name, args_str,
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)
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async def after_iteration(self, context: AgentHookContext) -> None:
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if self._status is None:
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return
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self._status.iteration = context.iteration
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self._status.tool_events = list(context.tool_events)
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self._status.usage = dict(context.usage)
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if context.error:
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self._status.error = str(context.error)
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class SubagentManager:
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"""Manages background subagent execution."""
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def __init__(
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self,
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provider: LLMProvider,
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workspace: Path,
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bus: MessageBus,
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max_tool_result_chars: int,
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model: str | None = None,
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tools_config: ToolsConfig | None = None,
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restrict_to_workspace: bool = False,
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disabled_skills: list[str] | None = None,
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max_iterations: int | None = None,
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):
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defaults = AgentDefaults()
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self.provider = provider
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self.workspace = workspace
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self.bus = bus
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self.model = model or provider.get_default_model()
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self.tools_config = tools_config or ToolsConfig()
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self.max_tool_result_chars = max_tool_result_chars
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self.restrict_to_workspace = restrict_to_workspace
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self.disabled_skills = set(disabled_skills or [])
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self.max_iterations = (
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max_iterations
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if max_iterations is not None
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else defaults.max_tool_iterations
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)
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self.max_concurrent_subagents = defaults.max_concurrent_subagents
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self.runner = AgentRunner(provider)
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self._running_tasks: dict[str, asyncio.Task[None]] = {}
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self._task_statuses: dict[str, SubagentStatus] = {}
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self._session_tasks: dict[str, set[str]] = {} # session_key -> {task_id, ...}
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self._tools_cache: ToolRegistry | None = None
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def _subagent_tools_config(self) -> ToolsConfig:
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"""Build a ToolsConfig scoped for subagent use."""
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return ToolsConfig(
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exec=self.tools_config.exec,
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web=self.tools_config.web,
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restrict_to_workspace=self.restrict_to_workspace,
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)
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def _build_tools(self) -> ToolRegistry:
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"""Build the subagent tool registry via ToolLoader (cached)."""
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if self._tools_cache is not None:
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return self._tools_cache
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registry = ToolRegistry()
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ctx = ToolContext(
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config=self._subagent_tools_config(),
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workspace=str(self.workspace),
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file_state_store=FileStates(),
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)
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ToolLoader().load(ctx, registry, scope="subagent")
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self._tools_cache = registry
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return registry
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def set_provider(self, provider: LLMProvider, model: str) -> None:
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self.provider = provider
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self.model = model
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self.runner.provider = provider
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async def spawn(
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self,
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task: str,
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label: str | None = None,
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origin_channel: str = "cli",
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origin_chat_id: str = "direct",
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session_key: str | None = None,
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origin_message_id: str | None = None,
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) -> str:
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"""Spawn a subagent to execute a task in the background."""
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task_id = str(uuid.uuid4())[:8]
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display_label = label or task[:30] + ("..." if len(task) > 30 else "")
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origin = {"channel": origin_channel, "chat_id": origin_chat_id, "session_key": session_key}
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status = SubagentStatus(
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task_id=task_id,
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label=display_label,
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task_description=task,
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started_at=time.monotonic(),
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)
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self._task_statuses[task_id] = status
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bg_task = asyncio.create_task(
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self._run_subagent(task_id, task, display_label, origin, status, origin_message_id)
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)
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self._running_tasks[task_id] = bg_task
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if session_key:
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self._session_tasks.setdefault(session_key, set()).add(task_id)
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def _cleanup(_: asyncio.Task) -> None:
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self._running_tasks.pop(task_id, None)
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self._task_statuses.pop(task_id, None)
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if session_key and (ids := self._session_tasks.get(session_key)):
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ids.discard(task_id)
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if not ids:
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del self._session_tasks[session_key]
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bg_task.add_done_callback(_cleanup)
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logger.info("Spawned subagent [{}]: {}", task_id, display_label)
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return f"Subagent [{display_label}] started (id: {task_id}). I'll notify you when it completes."
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async def _run_subagent(
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self,
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task_id: str,
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task: str,
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label: str,
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origin: dict[str, str],
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status: SubagentStatus,
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origin_message_id: str | None = None,
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) -> None:
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"""Execute the subagent task and announce the result."""
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logger.info("Subagent [{}] starting task: {}", task_id, label)
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async def _on_checkpoint(payload: dict) -> None:
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status.phase = payload.get("phase", status.phase)
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status.iteration = payload.get("iteration", status.iteration)
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try:
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tools = self._build_tools()
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system_prompt = self._build_subagent_prompt()
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messages: list[dict[str, Any]] = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": task},
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]
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result = await self.runner.run(AgentRunSpec(
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initial_messages=messages,
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tools=tools,
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model=self.model,
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max_iterations=self.max_iterations,
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max_tool_result_chars=self.max_tool_result_chars,
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hook=_SubagentHook(task_id, status),
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max_iterations_message="Task completed but no final response was generated.",
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error_message=None,
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fail_on_tool_error=True,
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checkpoint_callback=_on_checkpoint,
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))
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status.phase = "done"
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status.stop_reason = result.stop_reason
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if result.stop_reason == "tool_error":
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status.tool_events = list(result.tool_events)
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await self._announce_result(
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task_id, label, task,
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self._format_partial_progress(result),
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origin, "error", origin_message_id,
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)
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elif result.stop_reason == "error":
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await self._announce_result(
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task_id, label, task,
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result.error or "Error: subagent execution failed.",
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origin, "error", origin_message_id,
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)
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else:
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final_result = result.final_content or "Task completed but no final response was generated."
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logger.info("Subagent [{}] completed successfully", task_id)
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await self._announce_result(task_id, label, task, final_result, origin, "ok", origin_message_id)
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except Exception as e:
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status.phase = "error"
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status.error = str(e)
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logger.exception("Subagent [{}] failed", task_id)
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await self._announce_result(task_id, label, task, f"Error: {e}", origin, "error", origin_message_id)
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async def _announce_result(
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self,
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task_id: str,
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label: str,
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task: str,
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result: str,
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origin: dict[str, str],
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status: str,
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origin_message_id: str | None = None,
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) -> None:
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"""Announce the subagent result to the main agent via the message bus."""
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status_text = "completed successfully" if status == "ok" else "failed"
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announce_content = render_template(
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"agent/subagent_announce.md",
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label=label,
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status_text=status_text,
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task=task,
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result=result,
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)
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# Inject as system message to trigger main agent.
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# Use session_key_override to align with the main agent's effective
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# session key (which accounts for unified sessions) so the result is
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# routed to the correct pending queue (mid-turn injection) instead of
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# being dispatched as a competing independent task.
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override = origin.get("session_key") or f"{origin['channel']}:{origin['chat_id']}"
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metadata: dict[str, Any] = {
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"injected_event": "subagent_result",
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"subagent_task_id": task_id,
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}
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if origin_message_id:
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metadata["origin_message_id"] = origin_message_id
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msg = InboundMessage(
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channel="system",
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sender_id="subagent",
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chat_id=f"{origin['channel']}:{origin['chat_id']}",
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content=announce_content,
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session_key_override=override,
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metadata=metadata,
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)
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await self.bus.publish_inbound(msg)
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logger.debug("Subagent [{}] announced result to {}:{}", task_id, origin['channel'], origin['chat_id'])
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@staticmethod
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def _format_partial_progress(result) -> str:
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completed = [e for e in result.tool_events if e["status"] == "ok"]
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failure = next((e for e in reversed(result.tool_events) if e["status"] == "error"), None)
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lines: list[str] = []
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if completed:
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lines.append("Completed steps:")
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for event in completed[-3:]:
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lines.append(f"- {event['name']}: {event['detail']}")
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if failure:
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if lines:
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lines.append("")
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lines.append("Failure:")
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lines.append(f"- {failure['name']}: {failure['detail']}")
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if result.error and not failure:
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if lines:
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lines.append("")
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lines.append("Failure:")
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lines.append(f"- {result.error}")
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return "\n".join(lines) or (result.error or "Error: subagent execution failed.")
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def _build_subagent_prompt(self) -> str:
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"""Build a focused system prompt for the subagent."""
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from nanobot.agent.context import ContextBuilder
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from nanobot.agent.skills import SkillsLoader
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time_ctx = ContextBuilder._build_runtime_context(None, None)
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skills_summary = SkillsLoader(
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self.workspace,
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disabled_skills=self.disabled_skills,
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).build_skills_summary()
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return render_template(
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"agent/subagent_system.md",
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time_ctx=time_ctx,
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workspace=str(self.workspace),
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skills_summary=skills_summary or "",
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)
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async def cancel_by_session(self, session_key: str) -> int:
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"""Cancel all subagents for the given session. Returns count cancelled."""
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tasks = [self._running_tasks[tid] for tid in self._session_tasks.get(session_key, [])
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if tid in self._running_tasks and not self._running_tasks[tid].done()]
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for t in tasks:
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t.cancel()
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if tasks:
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await asyncio.gather(*tasks, return_exceptions=True)
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return len(tasks)
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def get_running_count(self) -> int:
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"""Return the number of currently running subagents."""
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return len(self._running_tasks)
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def get_running_count_by_session(self, session_key: str) -> int:
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"""Return the number of currently running subagents for a session."""
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tids = self._session_tasks.get(session_key, set())
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return sum(
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1 for tid in tids
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if tid in self._running_tasks and not self._running_tasks[tid].done()
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)
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