Files
nanobot/nanobot/agent/subagent.py
T
e804f2fddb fix(agent): align LLM wall timeout with sustained goals for main + subagents
Centralize runner_wall_llm_timeout_s in session goal_state metadata helpers so
spawned subagents inherit the same policy as AgentLoop without coupling to
long_task. Pass optional resolver into SubagentManager and add tests.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-16 16:33:49 +08:00

352 lines
14 KiB
Python

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