Files
strix/strix/core/execution.py
T
2026-08-06 15:39:43 +03:00

1033 lines
36 KiB
Python

"""Execution loop for addressable SDK-backed Strix agents."""
from __future__ import annotations
import asyncio
import contextlib
import logging
import uuid
from collections.abc import Callable
from typing import TYPE_CHECKING, Any, cast
import litellm
from agents import RunConfig, Runner
from agents.exceptions import AgentsException, MaxTurnsExceeded, UserError
from agents.sandbox.errors import ExecTransportError
from docker import errors as docker_errors # type: ignore[import-untyped, unused-ignore]
from openai import (
APIConnectionError,
APIError,
APITimeoutError,
)
from strix.config import codex
from strix.core.hooks import (
BudgetExceededError,
BudgetPausedError,
SubagentBudgetReservedError,
)
from strix.core.inputs import child_initial_input
from strix.core.sessions import (
enforce_image_budget,
open_agent_session,
replace_session_items,
seed_initial_input,
strip_all_images_from_session,
)
from strix.llm.compaction import is_context_overflow, maybe_compact
if TYPE_CHECKING:
from pathlib import Path
from agents.items import TResponseInputItem
from agents.lifecycle import RunHooks
from agents.memory import Session, SQLiteSession
from agents.result import RunResultBase
from strix.core.agents import AgentCoordinator, Status
logger = logging.getLogger(__name__)
StreamEventSink = Callable[[str, Any], None]
_INPUT_REJECTION_CODES = frozenset({400, 404, 422})
_MAX_COMPACTIONS_PER_CYCLE = 2
class ProviderRefusalError(AgentsException):
"""Raised when a provider returns a structured refusal instead of an exception."""
def _structured_provider_refusal(result: Any) -> str | None:
for item in getattr(result, "new_items", ()) or ():
raw_item = getattr(item, "raw_item", None)
for content in getattr(raw_item, "content", ()) or ():
if getattr(content, "type", None) != "refusal":
continue
refusal = getattr(content, "refusal", None)
if isinstance(refusal, str) and refusal.strip():
return refusal.strip()
return "The model provider refused this request."
return None
def _run_config_model(run_config: RunConfig) -> str | None:
return run_config.model if isinstance(run_config.model, str) else None
def _agent_instructions(agent: Any) -> str:
instructions = getattr(agent, "instructions", None)
return instructions if isinstance(instructions, str) else ""
def _agent_tools_text(agent: Any) -> str:
parts: list[str] = []
for tool in getattr(agent, "tools", []) or []:
name = getattr(tool, "name", "")
description = getattr(tool, "description", "") or ""
schema = getattr(tool, "params_json_schema", "") or ""
parts.append(f"{name} {description} {schema}")
return "\n".join(parts)
async def _compact_session(
agent: Any, session: Session, run_config: RunConfig, *, force: bool
) -> bool:
model = _run_config_model(run_config)
if session is None or model is None:
return False
return await maybe_compact(
session,
model=model,
instructions=_agent_instructions(agent),
tools_text=_agent_tools_text(agent),
force=force,
)
_MAX_TRANSIENT_MODEL_RETRIES = 5
_TRANSIENT_MODEL_RETRY_BASE_DELAY_S = 2.0
_TRANSIENT_MODEL_RETRY_MAX_DELAY_S = 90.0
def _model_error_status_code(exc: BaseException) -> int | None:
code = getattr(exc, "status_code", None)
return code if isinstance(code, int) else None
def _is_transient_model_error(exc: BaseException) -> bool:
if codex.is_content_guardrail_error(exc):
return False
if isinstance(
exc, APITimeoutError | APIConnectionError | TimeoutError | ConnectionError | OSError
):
return True
code = _model_error_status_code(exc)
if code is not None:
return bool(litellm._should_retry(code))
return isinstance(exc, APIError)
def _transient_model_retry_delay(attempt: int) -> float:
delay = _TRANSIENT_MODEL_RETRY_BASE_DELAY_S * float(2 ** (attempt - 1))
return min(delay, _TRANSIENT_MODEL_RETRY_MAX_DELAY_S)
async def _salvage_stream_to_session(
session: Session,
pre_run_items: list[Any],
stream: Any,
agent_id: str,
) -> None:
"""Persist a crashed run's full history so a revived agent loses no context."""
if stream is None:
return
try:
replay = list(stream.to_input_list())
except Exception:
logger.exception("could not build salvage history for %s", agent_id)
return
desired = list(pre_run_items) + replay
if len(desired) <= len(pre_run_items):
return
try:
await replace_session_items(session, desired)
except Exception:
logger.exception("salvaging crashed run history failed for %s", agent_id)
async def _seed_and_prepare_first_input(
session: Session | None, initial_input: Any, *, start_parked: bool
) -> Any:
"""Persist the opening input up front so it survives a first-turn crash."""
if initial_input and session is not None and not start_parked:
with contextlib.suppress(Exception):
if await seed_initial_input(session, initial_input):
return []
return initial_input
async def run_agent_loop(
*,
agent: Any,
initial_input: Any,
run_config: RunConfig,
context: dict[str, Any],
max_turns: int,
coordinator: AgentCoordinator,
agent_id: str,
interactive: bool,
session: Session | None = None,
start_parked: bool = False,
event_sink: StreamEventSink | None = None,
hooks: RunHooks[dict[str, Any]] | None = None,
) -> RunResultBase | None:
await coordinator.attach_runtime(
agent_id,
session=session,
interrupt_on_message=interactive,
)
result: RunResultBase | None = None
first_cycle_input = await _seed_and_prepare_first_input(
session, initial_input, start_parked=start_parked
)
budget_stopped = coordinator.budget_stopped
reserve_stopped = coordinator.reserve_stopped
if budget_stopped:
await coordinator.set_status(agent_id, "stopped")
raise BudgetExceededError("scan budget reached")
if reserve_stopped and context.get("parent_id") is not None:
await coordinator.set_status(agent_id, "stopped")
raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
if reserve_stopped and start_parked and interactive and context.get("parent_id") is None:
await coordinator.send(agent_id, _reserve_notice())
if not (start_parked and interactive):
with contextlib.suppress(BudgetPausedError):
result = await _run_until_lifecycle(
agent,
coordinator,
agent_id,
initial_input=first_cycle_input,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=interactive,
event_sink=event_sink,
hooks=hooks,
)
if not interactive:
return result
while True:
timeout = await _plain_waiting_timeout(coordinator, agent_id)
try:
woke = await coordinator.wait_for_message(agent_id, timeout=timeout)
except asyncio.CancelledError:
return result
if coordinator.budget_stopped:
await coordinator.set_status(agent_id, "stopped")
raise BudgetExceededError("scan budget reached")
if coordinator.reserve_stopped and context.get("parent_id") is not None:
await coordinator.set_status(agent_id, "stopped")
raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
if woke:
# Real input is real progress, so the nudge budget starts over. A bare
# auto-resume is not: it must not hand a wedged agent a fresh budget.
await coordinator.reset_recovery(agent_id)
await coordinator.reset_idle_resumes(agent_id)
else:
idle_resumes = await coordinator.record_idle_resume(agent_id)
if idle_resumes >= _MAX_IDLE_AUTO_RESUMES:
logger.warning(
"agent %s auto-resumed %d times without hearing from anyone; "
"leaving it parked until a real message arrives",
agent_id,
idle_resumes,
)
await coordinator.park_waiting(agent_id, wait_kind="stalled")
await _notify_parent_on_stall(coordinator, agent_id)
continue
logger.info("agent %s reached its waiting timeout; auto-resuming", agent_id)
await coordinator.send(
agent_id,
{
"from": "system",
"type": "auto_resume",
"content": "Waiting timeout reached. Resuming execution.",
},
interrupt=False,
)
await coordinator.consume_pending(agent_id)
with contextlib.suppress(BudgetPausedError):
result = await _run_until_lifecycle(
agent,
coordinator,
agent_id,
initial_input=[],
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=True,
event_sink=event_sink,
hooks=hooks,
)
async def spawn_child_agent(
*,
coordinator: AgentCoordinator,
factory: Any,
agents_db_path: Path,
sessions_to_close: list[SQLiteSession],
run_config: RunConfig,
max_turns: int,
interactive: bool,
parent_ctx: dict[str, Any],
name: str,
task: str,
skills: list[str],
parent_history: list[Any],
event_sink: StreamEventSink | None = None,
hooks: RunHooks[dict[str, Any]] | None = None,
) -> dict[str, Any]:
parent_id = parent_ctx.get("agent_id")
if not isinstance(parent_id, str):
raise TypeError("Parent agent_id missing from context")
child_id = uuid.uuid4().hex[:8]
child_agent = factory(name=name, skills=skills)
await coordinator.register(
child_id,
name,
parent_id,
task=task,
skills=skills,
)
await _start_child_runner(
parent_ctx=parent_ctx,
coordinator=coordinator,
agents_db_path=agents_db_path,
sessions_to_close=sessions_to_close,
run_config=run_config,
max_turns=max_turns,
interactive=interactive,
child_agent=child_agent,
child_id=child_id,
name=name,
parent_id=parent_id,
task=task,
initial_input=child_initial_input(
name=name,
child_id=child_id,
parent_id=parent_id,
task=task,
parent_history=parent_history,
),
event_sink=event_sink,
hooks=hooks,
)
return {
"success": True,
"agent_id": child_id,
"name": name,
"parent_id": parent_id,
"message": f"Spawned '{name}' ({child_id}) running in parallel.",
}
async def respawn_subagents(
*,
coordinator: AgentCoordinator,
factory: Any,
agents_db_path: Path,
sessions_to_close: list[SQLiteSession],
run_config: RunConfig,
max_turns: int,
interactive: bool,
parent_ctx: dict[str, Any],
root_id: str,
event_sink: StreamEventSink | None = None,
hooks: RunHooks[dict[str, Any]] | None = None,
) -> None:
async with coordinator._lock:
agents_snapshot = [
(aid, status, dict(coordinator.metadata.get(aid, {})))
for aid, status in coordinator.statuses.items()
]
candidates: list[tuple[str, str, str | None, dict[str, Any]]] = []
for aid, status, md in agents_snapshot:
if not interactive and status not in {"running", "waiting"}:
continue
if coordinator.parent_of.get(aid) is None or aid == root_id:
continue
md["_restored_status"] = status
candidates.append(
(
aid,
coordinator.names.get(aid, aid),
coordinator.parent_of.get(aid),
md,
)
)
for child_id, name, parent_id, md in candidates:
try:
restored_status = str(md.get("_restored_status") or "running")
start_parked = interactive and restored_status != "running"
if start_parked:
logger.warning(
"respawn %s (%s): starting parked from status=%s",
child_id,
name,
restored_status,
)
child_skills = list(md.get("skills") or [])
child_agent = factory(name=name, skills=child_skills)
await _start_child_runner(
parent_ctx=parent_ctx,
coordinator=coordinator,
agents_db_path=agents_db_path,
sessions_to_close=sessions_to_close,
run_config=run_config,
max_turns=max_turns,
interactive=interactive,
child_agent=child_agent,
child_id=child_id,
name=name,
parent_id=parent_id,
task=str(md.get("task", "")),
initial_input=[],
start_parked=start_parked,
event_sink=event_sink,
hooks=hooks,
)
logger.info(
"respawned %s (%s) parent=%s task_len=%d",
child_id,
name,
parent_id or "-",
len(md.get("task", "")),
)
except Exception:
logger.exception("respawn %s failed; marking crashed", child_id)
with contextlib.suppress(Exception):
await coordinator.set_status(child_id, "crashed")
_INTERACTIVE_TOOL_RECOVERY_LIMIT = 3
async def _run_until_lifecycle(
agent: Any,
coordinator: AgentCoordinator,
agent_id: str,
*,
initial_input: Any,
run_config: RunConfig,
context: dict[str, Any],
max_turns: int,
session: Session | None,
interactive: bool,
event_sink: StreamEventSink | None,
hooks: RunHooks[dict[str, Any]] | None,
) -> RunResultBase | None:
"""Drive an agent until an explicit lifecycle tool settles its status.
A turn that ends without ``finish_scan``, ``agent_finish``,
``respond_to_user``, or ``wait_for_agents`` leaves the agent ``running``:
plain text never terminates a run and never yields to the user. Such a turn
is nudged back into a tool call, bounded by a recovery limit.
"""
result: RunResultBase | None = None
input_data: Any = initial_input
recovery_limit = _INTERACTIVE_TOOL_RECOVERY_LIMIT if interactive else max(1, max_turns)
while True:
if coordinator.budget_stopped:
await coordinator.set_status(agent_id, "stopped")
raise BudgetExceededError("scan budget reached")
if coordinator.reserve_stopped and context.get("parent_id") is not None:
await coordinator.set_status(agent_id, "stopped")
raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
if interactive:
result = await _run_cycle_parked(
agent,
coordinator,
agent_id,
input_data=input_data,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
event_sink=event_sink,
hooks=hooks,
)
else:
result = await _run_cycle(
agent,
coordinator,
agent_id,
input_data=input_data,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=False,
event_sink=event_sink,
hooks=hooks,
)
status = await _agent_status(coordinator, agent_id)
if status != "running":
await coordinator.reset_recovery(agent_id)
return result
recoveries = await coordinator.record_recovery(agent_id)
logger.warning(
"agent %s ended a turn without a lifecycle tool call (interactive=%s); "
"forcing tool continuation (%d/%d): %s",
agent_id,
interactive,
recoveries,
recovery_limit,
_final_output_preview(result),
)
if recoveries >= recovery_limit:
return await _exhausted_recovery(coordinator, agent_id, result, interactive=interactive)
input_data = await _append_tool_required_message(
session=session,
context=context,
attempt=recoveries,
limit=recovery_limit,
interactive=interactive,
)
async def _exhausted_recovery(
coordinator: AgentCoordinator,
agent_id: str,
result: RunResultBase | None,
*,
interactive: bool,
) -> RunResultBase | None:
"""Settle an agent that never recovered into a tool call.
Interactive runs park instead of dying: a human is attached and can message
any agent, so the scan stays resumable. Autonomous runs have nobody to
resume them, so they fail loudly.
"""
if not interactive:
await coordinator.set_status(agent_id, "crashed")
await notify_parent_on_terminal(coordinator, agent_id, "crashed")
raise MaxTurnsExceeded(
"Agent exhausted recovery attempts without calling finish_scan or agent_finish."
)
logger.warning(
"agent %s exhausted tool-call recovery attempts; parking until a message arrives",
agent_id,
)
await coordinator.park_waiting(agent_id, wait_kind="stalled")
# A parked child owes its parent a completion report it can no longer send. The
# parent is an agent, not a watching human, so nothing else tells it to stop
# waiting and it burns its full timeout on a message that is never coming.
await _notify_parent_on_stall(coordinator, agent_id)
return result
_WAITING_AUTO_RESUME_TIMEOUT_S = 300.0
# An agent that parks again after every auto-resume makes no progress, so stop
# spending a model turn per timeout and leave it parked for a real message.
_MAX_IDLE_AUTO_RESUMES = 3
async def _plain_waiting_timeout(
coordinator: AgentCoordinator,
agent_id: str,
) -> float | None:
"""Auto-resume timeout for a parked agent; None waits until a message arrives.
Driven by what the agent is waiting on, not by where it sits in the graph:
the user can message any agent, so an agent awaiting a human parks
indefinitely whether or not it is the root. Only an agent awaiting other
agents is re-checked on a timer, and only until it has spent its idle
budget re-parking without hearing anything.
"""
async with coordinator._lock:
status = coordinator.statuses.get(agent_id)
has_error = agent_id in coordinator.errors
runtime = coordinator.runtimes.get(agent_id)
gated = runtime.user_wake_required if runtime is not None else False
wait_kind = coordinator.wait_kinds.get(agent_id)
idle_resumes = coordinator.idle_resume_counts.get(agent_id, 0)
if status != "waiting" or has_error or gated:
return None
if wait_kind != "agents" or idle_resumes >= _MAX_IDLE_AUTO_RESUMES:
return None
return _WAITING_AUTO_RESUME_TIMEOUT_S
async def _run_cycle_parked(
agent: Any,
coordinator: AgentCoordinator,
agent_id: str,
*,
input_data: Any,
run_config: RunConfig,
context: dict[str, Any],
max_turns: int,
session: Session | None,
event_sink: StreamEventSink | None,
hooks: RunHooks[dict[str, Any]] | None,
) -> RunResultBase | None:
"""Interactive run cycle that parks on any error instead of killing the runner."""
try:
return await _run_cycle(
agent,
coordinator,
agent_id,
input_data=input_data,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=True,
event_sink=event_sink,
hooks=hooks,
)
except (BudgetExceededError, BudgetPausedError, SubagentBudgetReservedError):
raise
except Exception as exc:
logger.exception("error escaped the run cycle for %s; parking as failed", agent_id)
await coordinator.set_status(agent_id, "failed", error=str(exc) or type(exc).__name__)
await notify_parent_on_terminal(coordinator, agent_id, "failed")
return None
async def _run_cycle( # noqa: PLR0912, PLR0915
agent: Any,
coordinator: AgentCoordinator,
agent_id: str,
*,
input_data: Any,
run_config: RunConfig,
context: dict[str, Any],
max_turns: int,
session: Session | None,
interactive: bool,
event_sink: StreamEventSink | None,
hooks: RunHooks[dict[str, Any]] | None,
) -> RunResultBase | None:
image_strips = 0
compactions = 0
model_retries = 0
while True:
stream: Any = None
pre_run_items: list[Any] = []
try:
await coordinator.mark_running(agent_id)
if session is not None:
max_images = context.get("max_context_images")
if isinstance(max_images, int):
try:
await enforce_image_budget(session, max_images)
except Exception:
logger.exception("image-budget enforcement failed for %s", agent_id)
try:
await _compact_session(agent, session, run_config, force=False)
except Exception:
logger.exception("proactive compaction failed for %s", agent_id)
with contextlib.suppress(Exception):
pre_run_items = list(await session.get_items())
stream = Runner.run_streamed(
agent,
input=input_data,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
hooks=hooks,
)
await coordinator.attach_stream(agent_id, stream)
try:
try:
async for event in stream.stream_events():
if event_sink is not None:
try:
event_sink(agent_id, event)
except Exception:
logger.exception("stream event sink failed for %s", agent_id)
if stream.run_loop_exception is not None:
raise stream.run_loop_exception
if refusal := _structured_provider_refusal(stream):
raise ProviderRefusalError(refusal)
except (BudgetExceededError, BudgetPausedError, SubagentBudgetReservedError):
raise
except RuntimeError as stream_exc:
if "after shutdown" not in str(stream_exc):
raise
logger.warning(
"Ignoring LiteLLM end-of-stream shutdown race for %s",
agent_id,
)
except (ExecTransportError, docker_errors.NotFound):
if not coordinator.is_shutting_down:
raise
logger.warning(
"Ignoring sandbox container error during teardown for %s",
agent_id,
exc_info=True,
)
finally:
await coordinator.detach_stream(agent_id, stream)
except BudgetPausedError as exc:
logger.info("agent %s paused at the scan budget limit: %s", agent_id, exc)
await coordinator.pause_for_budget(agent_id)
raise
except SubagentBudgetReservedError as exc:
logger.info("sub-agent %s stopped at the budget reserve: %s", agent_id, exc)
await coordinator.set_status(agent_id, "stopped")
await _notify_root_on_budget_reserve(coordinator)
raise
except BudgetExceededError as exc:
logger.info(
"agent %s reached the scan budget limit; stopping the scan: %s", agent_id, exc
)
await coordinator.set_status(agent_id, "stopped")
await coordinator.trigger_budget_stop()
raise
except Exception as exc:
if (
image_strips < 3
and session is not None
and getattr(exc, "status_code", None) in _INPUT_REJECTION_CODES
):
try:
stripped = await strip_all_images_from_session(session)
except Exception:
logger.exception("image-strip recovery failed for %s", agent_id)
stripped = False
if stripped:
image_strips += 1
logger.info(
"Stripped images from %s session after rejection; retrying (%d)",
agent_id,
image_strips,
)
input_data = []
continue
if (
compactions < _MAX_COMPACTIONS_PER_CYCLE
and session is not None
and is_context_overflow(exc)
):
try:
compacted = await _compact_session(agent, session, run_config, force=True)
except Exception:
logger.exception("overflow compaction recovery failed for %s", agent_id)
compacted = False
if compacted:
compactions += 1
logger.info(
"Compacted %s session after context overflow; retrying (%d)",
agent_id,
compactions,
)
input_data = []
continue
if model_retries < _MAX_TRANSIENT_MODEL_RETRIES and _is_transient_model_error(exc):
model_retries += 1
delay = _transient_model_retry_delay(model_retries)
logger.warning(
"transient model/provider error for %s; replaying turn "
"(attempt %d/%d, backoff %.1fs): %r",
agent_id,
model_retries,
_MAX_TRANSIENT_MODEL_RETRIES,
delay,
exc,
)
await asyncio.sleep(delay)
if session is not None:
input_data = []
continue
if session is not None:
await _salvage_stream_to_session(session, pre_run_items, stream, agent_id)
if isinstance(exc, ProviderRefusalError):
logger.warning("agent %s refused by the model provider: %s", agent_id, exc)
await coordinator.set_status(agent_id, "failed", error=str(exc))
await notify_parent_on_terminal(coordinator, agent_id, "failed")
return None
if isinstance(exc, MaxTurnsExceeded):
status: Status = "stopped"
elif isinstance(exc, UserError | AgentsException | APIError):
status = "failed"
else:
status = "crashed"
logger.exception("agent run failed for %s; marking %s", agent_id, status)
# Settle the status and wake the parent before the exception unwinds a
# non-interactive agent's task: a child that dies still owes its parent a
# report, and the parent would otherwise wait out its timeout on a message
# the dead child can no longer send.
await coordinator.set_status(agent_id, status, error=str(exc) or type(exc).__name__)
await notify_parent_on_terminal(coordinator, agent_id, status)
if not interactive:
raise
return None
else:
return cast("RunResultBase | None", stream)
async def _agent_status(coordinator: AgentCoordinator, agent_id: str) -> Status | None:
async with coordinator._lock:
return coordinator.statuses.get(agent_id)
def _final_output_preview(result: RunResultBase | None) -> str:
final_output = getattr(result, "final_output", None)
if final_output is None:
return "<none>"
text = str(final_output).replace("\n", " ").strip()
if not text:
return "<empty>"
return text[:300]
async def _append_tool_required_message(
*,
session: Session | None,
context: dict[str, Any],
attempt: int,
limit: int,
interactive: bool,
) -> list[dict[str, str]]:
finish_tool = "finish_scan" if context.get("parent_id") is None else "agent_finish"
if interactive:
message = (
"Your previous message ended a turn without a tool call. Plain text never ends "
"execution and never hands control to the user: it is shown to the user, and the "
"run continues. Continue immediately and call exactly one tool. "
"If you have something to tell the user and nothing to do until they reply, "
"call respond_to_user. "
"If you are blocked waiting for another agent, call wait_for_agents. "
f"If the whole engagement is complete, call {finish_tool}. "
"Otherwise use the appropriate execution or planning tool. "
f"This is recovery attempt {attempt}/{limit}."
)
else:
message = (
"Your previous response ended the autonomous run without a lifecycle tool "
"call. That is invalid in non-interactive mode; plain text final answers are "
"ignored. Continue immediately and call exactly one tool. "
f"If your work is complete, call {finish_tool}. "
"If you are blocked waiting for another agent, call wait_for_agents. "
"Otherwise use the appropriate execution or planning tool. "
f"This is recovery attempt {attempt}/{limit}."
)
item = {"role": "user", "content": message}
if session is None:
return [item]
await session.add_items([cast("TResponseInputItem", item)])
return []
_TERMINAL_NOTICE = {
"completed": (
"[Agent completed] {name} ({agent_id}) finished and is no longer running, but it "
"sent no completion report. Stop waiting on this child; ask it directly if you "
"need its results."
),
"crashed": (
"[Agent crash] {name} ({agent_id}) terminated unexpectedly. "
"Stop waiting on this child unless you want to message it again."
),
"failed": (
"[Agent failed] {name} ({agent_id}) stopped with an error and will not "
"send a completion report. Stop waiting on this child unless you want to "
"message it again."
),
"stopped": (
"[Agent stopped] {name} ({agent_id}) was stopped before finishing (turn limit "
"or an explicit stop). It will not send a completion report, so stop waiting "
"on this child; account for its unfinished subtask and continue."
),
}
_STALL_NOTICE = (
"[Agent stalled] {name} ({agent_id}) kept ending turns without a tool call and is "
"parked until it receives a message. It will not send a completion report on its "
"own: either message it with a concrete next step to unblock it, or stop waiting on "
"it and account for its unfinished subtask."
)
async def _notify_parent_on_stall(
coordinator: AgentCoordinator,
agent_id: str,
) -> None:
"""Tell the parent that a child parked mid-task, so it stops waiting blindly."""
async with coordinator._lock:
parent = coordinator.parent_of.get(agent_id)
name = coordinator.names.get(agent_id, agent_id)
if parent is None:
return
await coordinator.send(
parent,
{
"from": agent_id,
"type": "stalled",
"priority": "high",
"content": _STALL_NOTICE.format(name=name, agent_id=agent_id),
},
interrupt=False,
)
async def notify_parent_on_terminal(
coordinator: AgentCoordinator,
agent_id: str,
status: str,
) -> None:
template = _TERMINAL_NOTICE.get(status)
if template is None:
return
async with coordinator._lock:
parent = coordinator.parent_of.get(agent_id)
name = coordinator.names.get(agent_id, agent_id)
if parent is None:
return
if not await coordinator.claim_parent_notice(agent_id):
return
await coordinator.send(
parent,
{
"from": agent_id,
"type": status,
"priority": "high",
"content": template.format(name=name, agent_id=agent_id),
},
interrupt=False,
)
def _reserve_notice() -> dict[str, Any]:
return {
"from": "system",
"type": "budget_reserve_stop",
"priority": "high",
"content": (
"[Budget reserve] The scan has reached the sub-agent budget reserve: every "
"sub-agent is being force-stopped as soon as its in-flight turn completes, and "
"none will send a completion report. Their confirmed vulnerabilities are "
"already filed as they were found. Do not wait on any sub-agents and do not "
"spawn new ones — wrap up now and call finish_scan."
),
}
async def _notify_root_on_budget_reserve(coordinator: AgentCoordinator) -> None:
root = await coordinator.claim_reserve_notification()
if root is None:
return
await coordinator.send(root, _reserve_notice())
async def _notify_parent_on_exit(
coordinator: AgentCoordinator,
agent_id: str,
) -> None:
"""Backstop for a child whose loop ended without telling its parent.
Every terminal state counts, including ``completed``: a child that skips its
completion report leaves the parent waiting on a message nobody will send.
"""
status = await _agent_status(coordinator, agent_id)
if status is None:
return
await notify_parent_on_terminal(coordinator, agent_id, status)
async def _start_child_runner(
*,
parent_ctx: dict[str, Any],
coordinator: AgentCoordinator,
agents_db_path: Path,
sessions_to_close: list[SQLiteSession],
run_config: RunConfig,
max_turns: int,
interactive: bool,
child_agent: Any,
child_id: str,
name: str,
parent_id: str | None,
task: str,
initial_input: Any,
start_parked: bool = False,
event_sink: StreamEventSink | None = None,
hooks: RunHooks[dict[str, Any]] | None = None,
) -> None:
session = open_agent_session(child_id, agents_db_path)
sessions_to_close.append(session)
await coordinator.attach_runtime(child_id, session=session)
child_ctx: dict[str, Any] = dict(parent_ctx)
child_ctx["agent_id"] = child_id
child_ctx["parent_id"] = parent_id
child_ctx["task"] = task
async def _child_loop() -> None:
# A budget stop is a clean scan-wide shutdown, not a child failure: the
# child's status and parent notification are already settled in
# ``_run_cycle``. Swallow it here so the detached task does not surface a
# spurious "Task exception was never retrieved" warning. The root agent
# hits the same limit on its next call and tears the scan down.
try:
await run_agent_loop(
agent=child_agent,
initial_input=initial_input,
run_config=run_config,
context=child_ctx,
max_turns=max_turns,
coordinator=coordinator,
agent_id=child_id,
interactive=interactive,
session=session,
start_parked=start_parked,
event_sink=event_sink,
hooks=hooks,
)
except BudgetExceededError:
logger.info("child %s stopped after reaching the scan budget limit", child_id)
except SubagentBudgetReservedError:
logger.info("child %s stopped at the sub-agent budget reserve", child_id)
finally:
if not coordinator.is_shutting_down:
await _notify_parent_on_exit(coordinator, child_id)
task_handle = asyncio.create_task(_child_loop(), name=f"agent-{name}-{child_id}")
await coordinator.attach_runtime(child_id, task=task_handle)