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Author SHA1 Message Date
Ahmed Allam d97dc1b2ef docs(prompts): text-only turns no longer end an autonomous run 2026-08-01 22:16:00 +00:00
Ahmed Allam 8b464dae5d refactor(tools): split wait_for_message into respond_to_user + wait_for_agents
One tool was doing three jobs (wait on the user, wait on other agents, and
- wrongly - wait for a long-running command), so the driver had to guess which
one an agent meant and used parent_id as the proxy: the root waits for a human,
everyone else waits for agents. That proxy is wrong, since the user can message
any agent from the TUI's agent tree.

Tool identity now carries the intent, and the coordinator records it as a
wait_kind that survives snapshot/restore:

  respond_to_user  -> wait_kind="user",   never auto-resumed (root or not)
  wait_for_agents  -> wait_kind="agents", auto-resumed on a 300s timer
  recovery exhaust -> wait_kind="stalled"

respond_to_user fuses the message and the yield into one call, so there is no
way to answer and then forget to stop - the two-step that gpt-4o-mini skipped
2/2 in live testing. Plain text still renders as before.

Auto-resume is also bounded now: an agent that re-parks after every timeout
burned a model turn every 300s for the rest of the scan (and, since parked
children notify their parent, spammed the parent's inbox on the same cycle).
After _MAX_IDLE_AUTO_RESUMES it stays parked until a real message arrives.
2026-08-01 22:13:07 +00:00
Ahmed Allam b7bf52c468 docs(core): correct the rationale for notifying a stalled child's parent
The user can message any agent from the TUI, not only the root, so the
justification is that the parent is an agent with no other way to learn
the child parked - not that the child has no human resumer.
2026-08-01 21:36:54 +00:00
Ahmed Allam ceff3b5408 fix(core): tell the parent when an interactive subagent parks
Parking is self-service only for the root, which the user is watching.
A parked child owes its parent a report it can no longer send, so the
parent would wait out its full timeout for nothing.
2026-08-01 21:30:44 +00:00
Ahmed Allam 44bb3abdf8 fix(tools): halve the wait_for_message ceiling to 300s
A mutual wait between two agents resolves only when both hit their cap,
so the ceiling is the worst-case idle burn. Name the constants instead of
repeating the literal, and align the interactive auto-resume timeout.
2026-08-01 21:25:09 +00:00
Ahmed Allam 5726c2d4ef fix(core): persist the tool-call recovery counter across resumes
An exhausted agent parked in 'waiting' got a fresh nudge budget on every
600s auto-resume, so a wedged agent could nudge-park-nudge indefinitely.
Track the count on the coordinator, snapshot it, and reset it only on
real input or an explicit lifecycle tool.
2026-08-01 19:36:20 +00:00
Ahmed Allam 69a60f3b7a fix(core): stop interactive runs stalling on a missing tool call
Interactive turns ended by plain text left the agent parked in 'waiting'
forever. Require an explicit lifecycle tool in both modes and nudge a
text-only turn back into a tool call, bounded by a recovery limit.
2026-08-01 19:16:53 +00:00
devin-ai-integration[bot]andGitHub 5602bc23ca fix: pre-v1-style lifecycle resilience — mailbox delivery, uniform revival, unexitable runner, waiting timeout, broader retries, crash-safe identity (#923) 2026-08-01 11:17:08 -07:00
alex sandGitHub a9deb84260 fix(llm): surface structured provider refusals (#944)
* fix(llm): surface structured provider refusals

* fix(llm): settle refused autonomous agents
2026-07-31 10:57:42 -04:00
25 changed files with 1363 additions and 331 deletions
+11 -3
View File
@@ -23,7 +23,7 @@ from strix.tools.agents_graph.tools import (
send_message_to_agent,
stop_agent,
view_agent_graph,
wait_for_message,
wait_for_agents,
)
from strix.tools.finish.tool import finish_scan
from strix.tools.load_skill.tool import load_skill
@@ -49,6 +49,7 @@ from strix.tools.reporting.tool import (
get_report,
list_reports,
)
from strix.tools.respond.tool import respond_to_user
from strix.tools.thinking.tool import think
from strix.tools.todo.tools import (
create_todo,
@@ -345,6 +346,10 @@ def _make_shell_configurator(*, chat_completions: bool) -> Any:
return configure
# Tools that hand control away by parking the agent rather than ending the scan.
_PARKING_TOOLS: frozenset[str] = frozenset({"respond_to_user", "wait_for_agents"})
def _lifecycle_tool_completed(tool_name: str, output: Any) -> bool:
if tool_name == "agent_finish":
completion_key = "agent_completed"
@@ -363,7 +368,7 @@ def _lifecycle_tool_completed(tool_name: str, output: Any) -> bool:
def _wait_tool_parked(tool_name: str, output: Any) -> bool:
if tool_name != "wait_for_message" or not isinstance(output, str):
if tool_name not in _PARKING_TOOLS or not isinstance(output, str):
return False
try:
parsed = json.loads(output)
@@ -425,7 +430,7 @@ _BASE_TOOLS: tuple[Tool, ...] = (
scope_rules,
view_agent_graph,
send_message_to_agent,
wait_for_message,
wait_for_agents,
create_agent,
stop_agent,
)
@@ -509,6 +514,9 @@ def build_strix_agent(
)
agent_tools = [*_EXTRA_TOOLS, *(extra_tools or [])]
if interactive:
# Yielding to the user is only meaningful when one is attached.
agent_tools.append(respond_to_user)
if is_root:
tools: list[Tool] = [*_BASE_TOOLS, *agent_tools, finish_scan]
else:
+15 -17
View File
@@ -31,28 +31,26 @@ INTER-AGENT MESSAGES:
{% if interactive %}
INTERACTIVE BEHAVIOR:
- You are in an interactive conversation with a user
- CRITICAL: A message WITHOUT a tool call IMMEDIATELY STOPS your entire execution and waits for user input. This is a HARD SYSTEM CONSTRAINT, not a suggestion.
- Statements like "Planning the assessment..." or "I'll now scan..." or "Starting with..." WITHOUT a tool call will HALT YOUR WORK COMPLETELY. The system interprets no-tool-call as "I'm done, waiting for the user."
- If you want to plan, call the think tool. If you want to act, call the appropriate tool. There is NO valid reason to output text without a tool call while working on a task.
- The ONLY time you may send a message without a tool call is when you are genuinely DONE and presenting final results, or when you NEED the user to answer a question before continuing.
- EVERY message while working MUST contain exactly one tool call — this is what keeps execution moving. No tool call = execution stops.
- You may include brief explanatory text BEFORE the tool call
- Respond naturally when the user asks questions or gives instructions
- For simple conversation, acknowledgements, or direct questions that you can answer from current context, reply in plain text and stop. Do NOT call think just to prepare wording.
- If you use a tool to answer a user question (for example list_todos, view_agent_graph, or a file read), then after the tool result arrives, provide the answer in plain text and stop unless the user explicitly asked you to continue working.
- Never loop through think or other tools just to prepare, polish, confirm, or announce a final answer. Once you know the answer, say it.
- NEVER send empty messages — if you have nothing to do or say, call the wait_for_message tool
- If you catch yourself about to describe multiple steps without a tool call, STOP and call the think tool instead
- You are in an interactive conversation with a user.
- HOW EXECUTION ENDS: your turn ends ONLY when you make an explicit lifecycle tool call. Plain text NEVER ends your turn and NEVER hands control to the user — text is shown to the user, and then execution continues.
- To answer the user and hand control back, call respond_to_user. It delivers your message AND parks you for their reply in one call, so there is no way to answer and then forget to stop. This is the ONLY way to yield to the user.
- To wait on another AGENT (a child's report, a peer's reply), call wait_for_agents. That is not a way to reach the user.
- To end the whole engagement, call the lifecycle tool: finish_scan (root) or agent_finish (subagent).
- A turn that ends with plain text and no tool call does NOT stop you: the system nudges you to continue and will re-run you. Do not rely on going silent to pause — it will not pause you.
- Answering a user question: put the answer in respond_to_user's message. Do not write the answer as plain text and then fall silent — that does not reach a stopping point, it just triggers a continuation nudge.
- You may include brief explanatory text before a tool call, and you can narrate while you work — plain text is shown to the user as you go. Narrating is free; respond_to_user is specifically the act of WAITING for the user, so do not call it just to give a status update.
- Respond naturally when the user asks questions or gives instructions.
- While actively working on a task, every turn should carry exactly one tool call — use think to plan, the appropriate tool to act, and respond_to_user only when you genuinely need the user.
- Never loop through think or other tools just to prepare, polish, confirm, or announce an answer. Once you know the answer, send it with respond_to_user.
{% else %}
AUTONOMOUS BEHAVIOR:
- Work autonomously by default
- You should NOT ask for user input or confirmation - you should always proceed with your task autonomously.
- Minimize user messaging: avoid redundancy and repetition; consolidate updates into a single concise message
- NEVER send an empty or blank message. If you have no content to output or need to wait (for user input, subagent results, or any other reason), you MUST call the wait_for_message tool (or another appropriate tool) instead of emitting an empty response.
- If there is nothing to execute and no user query to answer any more: do NOT send filler/repetitive text — either call wait_for_message or finish your work (subagents: agent_finish; root: finish_scan)
- While the agent loop is running, almost every output MUST be a tool call. Do NOT send plain text messages; act via tools. If idle, use wait_for_message; when done, use agent_finish (subagents) or finish_scan (root)
- A text-only turn — even one — IMMEDIATELY ends the scan/run with no report written. The lifecycle tools (``finish_scan`` for root, ``agent_finish`` for subagents) are the ONLY valid way to terminate. If you find yourself wanting to say "Done!" or "Scan complete" without a tool call, call the lifecycle tool instead — the report and termination signal both flow through it.
- NEVER send an empty or blank message. If you have no content to output or need to wait for subagent results, you MUST call the wait_for_agents tool (or another appropriate tool) instead of emitting an empty response.
- There is no user attached to this run, so there is nobody to ask and nothing to yield to. If there is nothing left to execute: do NOT send filler/repetitive text — either call wait_for_agents (only if you are genuinely expecting another agent to message you) or finish your work (subagents: agent_finish; root: finish_scan)
- While the agent loop is running, almost every output MUST be a tool call. Do NOT send plain text messages; act via tools. If waiting on another agent, use wait_for_agents; when done, use agent_finish (subagents) or finish_scan (root)
- A text-only turn does nothing: it neither ends the run nor yields — it just wastes a turn and forces a retry. The lifecycle tools (``finish_scan`` for root, ``agent_finish`` for subagents) are the ONLY way to terminate, and the report flows through them. If you find yourself wanting to say "Done!" or "Scan complete" without a tool call, call the lifecycle tool instead.
{% endif %}
</communication_rules>
+126 -32
View File
@@ -24,6 +24,11 @@ logger = logging.getLogger(__name__)
Status = Literal["running", "waiting", "completed", "stopped", "crashed", "failed", "budget_paused"]
# Why an agent parked. The user can message any agent, so this - not the agent's
# position in the tree - decides whether waiting is bounded: only an agent waiting
# on other agents is re-checked on a timer.
WaitKind = Literal["user", "agents", "stalled"]
@dataclass(slots=True)
class AgentRuntime:
@@ -32,6 +37,8 @@ class AgentRuntime:
stream: Any | None = None
interrupt_on_message: bool = False
wake: asyncio.Event = field(default_factory=asyncio.Event)
mailbox: list[dict[str, Any]] = field(default_factory=list)
user_wake_required: bool = False
class AgentCoordinator:
@@ -44,6 +51,9 @@ class AgentCoordinator:
self.metadata: dict[str, dict[str, Any]] = {}
self.pending_counts: dict[str, int] = {}
self.errors: dict[str, str] = {}
self.recovery_counts: dict[str, int] = {}
self.idle_resume_counts: dict[str, int] = {}
self.wait_kinds: dict[str, WaitKind] = {}
self.runtimes: dict[str, AgentRuntime] = {}
self._lock = asyncio.Lock()
self._snapshot_path: Path | None = None
@@ -179,11 +189,58 @@ class AgentCoordinator:
if agent_id in self.statuses:
self.statuses[agent_id] = "running"
self.errors.pop(agent_id, None)
self.wait_kinds.pop(agent_id, None)
self.runtimes.setdefault(agent_id, AgentRuntime()).user_wake_required = False
await self._maybe_snapshot()
async def park_waiting(self, agent_id: str) -> None:
async def park_waiting(self, agent_id: str, *, wait_kind: WaitKind) -> None:
"""Park an agent, recording what it is waiting on so the driver can time it."""
async with self._lock:
if agent_id in self.statuses:
self.wait_kinds[agent_id] = wait_kind
await self.set_status(agent_id, "waiting")
async def wait_kind_of(self, agent_id: str) -> WaitKind | None:
async with self._lock:
return self.wait_kinds.get(agent_id)
async def record_recovery(self, agent_id: str) -> int:
"""Count a turn that ended without a lifecycle tool call; return the new total.
Persisted so a resumed agent cannot earn a fresh nudge budget on every
auto-resume and loop forever.
"""
async with self._lock:
count = self.recovery_counts.get(agent_id, 0) + 1
self.recovery_counts[agent_id] = count
await self._maybe_snapshot()
return count
async def reset_recovery(self, agent_id: str) -> None:
"""Clear the nudge budget after real progress (new message or a lifecycle tool)."""
async with self._lock:
if self.recovery_counts.pop(agent_id, None) is None:
return
await self._maybe_snapshot()
async def record_idle_resume(self, agent_id: str) -> int:
"""Count an auto-resume that no message triggered; return the new total.
An agent that parks again after every auto-resume would otherwise burn a
model turn per timeout for the rest of the scan.
"""
async with self._lock:
count = self.idle_resume_counts.get(agent_id, 0) + 1
self.idle_resume_counts[agent_id] = count
await self._maybe_snapshot()
return count
async def reset_idle_resumes(self, agent_id: str) -> None:
async with self._lock:
if self.idle_resume_counts.pop(agent_id, None) is None:
return
await self._maybe_snapshot()
async def set_status(
self, agent_id: str, status: Status | str, *, error: str | None = None
) -> None:
@@ -196,6 +253,7 @@ class AgentCoordinator:
elif status == "running":
self.errors.pop(agent_id, None)
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
runtime.user_wake_required = status in {"failed", "crashed"}
runtime.wake.set()
logger.info("agent.status %s=%s", agent_id, status)
await self._maybe_snapshot()
@@ -203,49 +261,47 @@ class AgentCoordinator:
async def send(
self, target_agent_id: str, message: dict[str, Any], *, interrupt: bool = True
) -> bool:
"""Deliver a user/peer message by appending it to the target SDK session."""
if message.get("from") == "user" and self._budget_paused:
"""Queue a user/peer message in the target's mailbox and wake it."""
from_user = message.get("from") == "user"
if from_user and self._budget_paused:
await self.resume_from_budget_pause(exclude=target_agent_id)
async with self._lock:
if target_agent_id not in self.statuses:
logger.debug("agent.send dropped unknown target=%s", target_agent_id)
return False
runtime = self.runtimes.setdefault(target_agent_id, AgentRuntime())
session = runtime.session
runtime.mailbox.append(dict(message))
self.pending_counts[target_agent_id] = self.pending_counts.get(target_agent_id, 0) + 1
if from_user:
runtime.user_wake_required = False
runtime.wake.set()
stream = runtime.stream
interrupt_on_message = runtime.interrupt_on_message
if session is None:
logger.warning(
"agent.send dropped target=%s because its SDK session is not attached",
target_agent_id,
)
return False
try:
async with session_write_lock(session):
await session.add_items([self._message_to_session_item(message)])
except Exception:
logger.exception(
"agent.send failed to append to SDK session target=%s",
target_agent_id,
)
return False
async with self._lock:
self.pending_counts[target_agent_id] = self.pending_counts.get(target_agent_id, 0) + 1
self.runtimes.setdefault(target_agent_id, AgentRuntime()).wake.set()
if stream is not None and interrupt and interrupt_on_message:
stream.cancel(mode="immediate")
await self._maybe_snapshot()
return True
async def wait_for_message(self, agent_id: str) -> None:
async def wait_for_message(self, agent_id: str, *, timeout: float | None = None) -> bool:
"""Wait until a message is ready for ``agent_id``; False on ``timeout``."""
while True:
async with self._lock:
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
reserve_exit = self._reserve_stopped and self.parent_of.get(agent_id) is not None
if self._budget_stopped or reserve_exit or self.pending_counts.get(agent_id, 0) > 0:
return
wake = self.runtimes.setdefault(agent_id, AgentRuntime()).wake
pending_ready = (
self.pending_counts.get(agent_id, 0) > 0 and not runtime.user_wake_required
)
if self._budget_stopped or reserve_exit or pending_ready:
return True
wake = runtime.wake
wake.clear()
await wake.wait()
if timeout is None:
await wake.wait()
else:
try:
await asyncio.wait_for(wake.wait(), timeout)
except TimeoutError:
return False
async def consume_pending(
self,
@@ -253,17 +309,38 @@ class AgentCoordinator:
*,
include_items: bool = False,
) -> tuple[int, list[Any]]:
"""Drain the agent's mailbox into its own SDK session."""
async with self._lock:
count = self.pending_counts.get(agent_id, 0)
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
queued = list(runtime.mailbox)
runtime.mailbox.clear()
count = max(self.pending_counts.get(agent_id, 0), len(queued))
self.pending_counts[agent_id] = 0
session = self.runtimes.get(agent_id, AgentRuntime()).session
session = runtime.session
if count <= 0:
return 0, []
items = [self._message_to_session_item(m) for m in queued]
if items:
if session is None:
logger.warning(
"agent %s has no SDK session attached; %d queued messages were not persisted",
agent_id,
len(items),
)
else:
try:
async with session_write_lock(session):
await session.add_items(items)
except Exception:
logger.exception(
"failed to append %d queued messages to the session of %s",
len(items),
agent_id,
)
await self._maybe_snapshot()
if not include_items or session is None:
if not include_items:
return count, []
items = await session.get_items()
return count, list(items[-count:])
return count, items
async def request_stop(self, agent_id: str) -> None:
async with self._lock:
@@ -374,6 +451,14 @@ class AgentCoordinator:
"names": dict(self.names),
"metadata": {aid: dict(md) for aid, md in self.metadata.items()},
"pending_counts": dict(self.pending_counts),
"recovery_counts": dict(self.recovery_counts),
"idle_resume_counts": dict(self.idle_resume_counts),
"wait_kinds": dict(self.wait_kinds),
"mailboxes": {
aid: [dict(m) for m in runtime.mailbox]
for aid, runtime in self.runtimes.items()
if runtime.mailbox
},
"errors": dict(self.errors),
"budget_stopped": self._budget_stopped,
"reserve_stopped": self._reserve_stopped,
@@ -388,6 +473,15 @@ class AgentCoordinator:
self.metadata = {aid: dict(md) for aid, md in snap.get("metadata", {}).items()}
self.pending_counts = dict(snap.get("pending_counts", {}))
self.errors = dict(snap.get("errors", {}))
self.recovery_counts = dict(snap.get("recovery_counts", {}))
self.idle_resume_counts = dict(snap.get("idle_resume_counts", {}))
self.wait_kinds = dict(snap.get("wait_kinds", {}))
mailboxes = snap.get("mailboxes", {})
if isinstance(mailboxes, dict):
for aid, msgs in mailboxes.items():
if isinstance(msgs, list):
runtime = self.runtimes.setdefault(aid, AgentRuntime())
runtime.mailbox = [dict(m) for m in msgs if isinstance(m, dict)]
self._budget_stopped = bool(snap.get("budget_stopped", False))
self._reserve_stopped = bool(snap.get("reserve_stopped", False))
self._budget_paused = bool(snap.get("budget_paused", False))
+308 -126
View File
@@ -9,6 +9,7 @@ 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
@@ -16,9 +17,7 @@ from docker import errors as docker_errors # type: ignore[import-untyped, unuse
from openai import (
APIConnectionError,
APIError,
APIStatusError,
APITimeoutError,
RateLimitError,
)
from strix.config import codex
@@ -31,6 +30,8 @@ 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
@@ -106,15 +107,9 @@ async def _compact_session(
)
_GUARDRAIL_PARK_ERROR = (
"Blocked by the model's content guardrail (flagged as a possible cybersecurity risk). "
"Set STRIX_LLM to a model that isn't blocked and resume the scan to continue."
)
_TRANSIENT_MODEL_STATUS_CODES = frozenset({408, 500, 502, 503, 504})
_MAX_TRANSIENT_MODEL_RETRIES = 4
_MAX_TRANSIENT_MODEL_RETRIES = 5
_TRANSIENT_MODEL_RETRY_BASE_DELAY_S = 2.0
_TRANSIENT_MODEL_RETRY_MAX_DELAY_S = 30.0
_TRANSIENT_MODEL_RETRY_MAX_DELAY_S = 90.0
def _model_error_status_code(exc: BaseException) -> int | None:
@@ -123,15 +118,16 @@ def _model_error_status_code(exc: BaseException) -> int | None:
def _is_transient_model_error(exc: BaseException) -> bool:
if isinstance(exc, RateLimitError):
if codex.is_content_guardrail_error(exc):
return False
if isinstance(exc, APITimeoutError | APIConnectionError):
if isinstance(
exc, APITimeoutError | APIConnectionError | TimeoutError | ConnectionError | OSError
):
return True
if isinstance(exc, APIStatusError):
return exc.status_code in _TRANSIENT_MODEL_STATUS_CODES
if isinstance(exc, APIError):
return _model_error_status_code(exc) is None
return False
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:
@@ -139,6 +135,40 @@ def _transient_model_retry_delay(attempt: int) -> float:
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,
@@ -161,6 +191,10 @@ async def run_agent_loop(
)
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:
@@ -174,31 +208,17 @@ async def run_agent_loop(
await coordinator.send(agent_id, _reserve_notice())
if not (start_parked and interactive):
if interactive:
with contextlib.suppress(BudgetPausedError):
result = await _run_cycle(
agent,
coordinator,
agent_id,
input_data=initial_input,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=interactive,
event_sink=event_sink,
hooks=hooks,
)
else:
result = await _run_noninteractive_until_lifecycle(
with contextlib.suppress(BudgetPausedError):
result = await _run_until_lifecycle(
agent,
coordinator,
agent_id,
initial_input=initial_input,
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,
)
@@ -207,8 +227,9 @@ async def run_agent_loop(
return result
while True:
timeout = await _plain_waiting_timeout(coordinator, agent_id)
try:
await coordinator.wait_for_message(agent_id)
woke = await coordinator.wait_for_message(agent_id, timeout=timeout)
except asyncio.CancelledError:
return result
@@ -220,18 +241,46 @@ async def run_agent_loop(
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_cycle(
result = await _run_until_lifecycle(
agent,
coordinator,
agent_id,
input_data=[],
initial_input=[],
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=interactive,
interactive=True,
event_sink=event_sink,
hooks=hooks,
)
@@ -327,7 +376,6 @@ async def respawn_subagents(
if coordinator.parent_of.get(aid) is None or aid == root_id:
continue
md["_restored_status"] = status
md["_restored_error"] = coordinator.errors.get(aid)
candidates.append(
(
aid,
@@ -340,8 +388,7 @@ async def respawn_subagents(
for child_id, name, parent_id, md in candidates:
try:
restored_status = str(md.get("_restored_status") or "running")
recoverable_park = restored_status == "waiting" and bool(md.get("_restored_error"))
start_parked = interactive and restored_status != "running" and not recoverable_park
start_parked = interactive and restored_status != "running"
if start_parked:
logger.warning(
@@ -384,7 +431,10 @@ async def respawn_subagents(
await coordinator.set_status(child_id, "crashed")
async def _run_noninteractive_until_lifecycle(
_INTERACTIVE_TOOL_RECOVERY_LIMIT = 3
async def _run_until_lifecycle(
agent: Any,
coordinator: AgentCoordinator,
agent_id: str,
@@ -394,14 +444,20 @@ async def _run_noninteractive_until_lifecycle(
context: dict[str, Any],
max_turns: int,
session: Session | None,
interactive: bool,
event_sink: StreamEventSink | None,
hooks: RunHooks[dict[str, Any]] | None,
) -> RunResultBase | None:
"""Non-chat mode keeps running until finish_scan / agent_finish settles status."""
"""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
invalid_final_outputs = 0
invalid_final_output_limit = max(1, max_turns)
recovery_limit = _INTERACTIVE_TOOL_RECOVERY_LIMIT if interactive else max(1, max_turns)
while True:
if coordinator.budget_stopped:
@@ -412,7 +468,143 @@ async def _run_noninteractive_until_lifecycle(
await coordinator.set_status(agent_id, "stopped")
raise SubagentBudgetReservedError("scan reached the sub-agent budget reserve")
result = await _run_cycle(
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,
@@ -421,39 +613,17 @@ async def _run_noninteractive_until_lifecycle(
context=context,
max_turns=max_turns,
session=session,
interactive=False,
interactive=True,
event_sink=event_sink,
hooks=hooks,
)
status = await _agent_status(coordinator, agent_id)
if status != "running":
return result
invalid_final_outputs += 1
logger.warning(
"agent %s produced non-lifecycle final output in non-interactive mode; "
"forcing tool continuation (%d/%d): %s",
agent_id,
invalid_final_outputs,
invalid_final_output_limit,
_final_output_preview(result),
)
if invalid_final_outputs >= invalid_final_output_limit:
await coordinator.set_status(agent_id, "crashed")
await _notify_parent_on_terminal(coordinator, agent_id, "crashed")
raise MaxTurnsExceeded(
"Agent exhausted non-interactive recovery attempts without calling "
"finish_scan or agent_finish."
)
input_data = await _append_noninteractive_tool_required_message(
session=session,
context=context,
attempt=invalid_final_outputs,
limit=invalid_final_output_limit,
)
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
@@ -474,6 +644,8 @@ async def _run_cycle( # noqa: PLR0912, PLR0915
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:
@@ -487,6 +659,8 @@ async def _run_cycle( # noqa: PLR0912, PLR0915
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,
@@ -599,10 +773,8 @@ async def _run_cycle( # noqa: PLR0912, PLR0915
if session is not None:
input_data = []
continue
if codex.is_content_guardrail_error(exc):
return await _handle_content_guardrail(
coordinator, agent_id, exc, interactive=interactive
)
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))
@@ -621,41 +793,7 @@ async def _run_cycle( # noqa: PLR0912, PLR0915
await _notify_parent_on_terminal(coordinator, agent_id, status)
return None
else:
await _settle_run_result(coordinator, agent_id, interactive)
return stream
async def _handle_content_guardrail(
coordinator: AgentCoordinator,
agent_id: str,
exc: BaseException,
*,
interactive: bool,
) -> RunResultBase | None:
logger.warning("agent %s blocked by the model's content guardrail: %s", agent_id, exc)
if interactive:
await coordinator.set_status(agent_id, "waiting", error=_GUARDRAIL_PARK_ERROR)
return None
await coordinator.set_status(agent_id, "failed", error=_GUARDRAIL_PARK_ERROR)
await _notify_parent_on_terminal(coordinator, agent_id, "failed")
return None
async def _settle_run_result(
coordinator: AgentCoordinator,
agent_id: str,
interactive: bool,
) -> None:
async with coordinator._lock:
current_status = coordinator.statuses.get(agent_id)
if current_status != "running":
return
if not interactive:
return
await coordinator.set_status(agent_id, "waiting")
return cast("RunResultBase | None", stream)
async def _agent_status(coordinator: AgentCoordinator, agent_id: str) -> Status | None:
@@ -673,23 +811,37 @@ def _final_output_preview(result: RunResultBase | None) -> str:
return text[:300]
async def _append_noninteractive_tool_required_message(
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"
message = (
"Your previous response ended the autonomous Strix 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_message. "
"Otherwise use the appropriate execution or planning tool. "
f"This is recovery attempt {attempt}/{limit}."
)
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 Strix 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]
@@ -716,6 +868,36 @@ _TERMINAL_NOTICE = {
}
_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,
+1 -7
View File
@@ -377,12 +377,6 @@ async def run_strix_scan(
async with coordinator._lock:
root_status = coordinator.statuses.get(root_id)
root_error = coordinator.errors.get(root_id)
root_recoverable_park = root_status == "waiting" and bool(root_error)
root_start_parked = bool(
interactive and is_resume and root_status != "running" and not root_recoverable_park
)
result = await run_agent_loop(
agent=root_agent,
@@ -394,7 +388,7 @@ async def run_strix_scan(
agent_id=root_id,
interactive=interactive,
session=root_session,
start_parked=root_start_parked,
start_parked=bool(interactive and is_resume and root_status != "running"),
event_sink=event_sink,
hooks=hooks,
)
+13
View File
@@ -7,6 +7,7 @@ import logging
from typing import TYPE_CHECKING, Any, cast
from weakref import WeakKeyDictionary
from agents.items import ItemHelpers
from agents.memory import SQLiteSession
@@ -26,6 +27,18 @@ def open_agent_session(agent_id: str, path: Path) -> SQLiteSession:
return SQLiteSession(session_id=agent_id, db_path=path)
async def seed_initial_input(session: Session, initial_input: Any) -> bool:
"""Commit an agent's opening identity/task input before its first run cycle."""
items = ItemHelpers.input_to_new_input_list(initial_input)
if not items:
return False
async with session_write_lock(session):
if await session.get_items():
return False
await session.add_items(items)
return True
_IMAGE_REJECTED_TEXT = "[image rejected by the model]"
_IMAGE_ELIDED_TEXT = "[older screenshot elided to bound context memory]"
_INHERITED_IMAGE_TEXT = "[screenshot omitted from inherited context]"
+6 -2
View File
@@ -1041,9 +1041,9 @@ class StrixTUIApp(App): # type: ignore[misc]
name=names.get(agent_id, agent_id),
parent_id=parent_of.get(agent_id),
status=status,
error_message=error,
error_message=error or "",
)
if status in {"failed", "crashed"} and error:
if error:
if agent_id not in self._error_noted_agents:
self._error_noted_agents.add(agent_id)
self.live_view.record_agent_error(agent_id, error)
@@ -1293,6 +1293,10 @@ class StrixTUIApp(App): # type: ignore[misc]
text.append("Send a message to continue", style="dim")
keymap = keymap_styled([("ctrl-q", "quit")])
else:
error_msg = agent_data.get("error_message") or ""
if error_msg:
text.append(error_msg, style="red")
text.append(" \u00b7 ", style="dim")
text.append("Send message to resume", style="dim")
return (text, keymap, False)
+1 -1
View File
@@ -82,7 +82,7 @@ class TuiLiveView:
current["parent_id"] = parent_id
if status is not None:
current["status"] = status
if error_message:
if error_message is not None:
current["error_message"] = error_message
current["updated_at"] = now
@@ -6,6 +6,7 @@ from . import (
notes_renderer,
proxy_renderer,
reporting_renderer,
respond_renderer,
shell_renderer,
thinking_renderer,
todo_renderer,
@@ -23,6 +24,7 @@ __all__ = [
"proxy_renderer",
"render_tool_widget",
"reporting_renderer",
"respond_renderer",
"shell_renderer",
"thinking_renderer",
"todo_renderer",
@@ -117,8 +117,8 @@ class AgentFinishRenderer(BaseToolRenderer):
@register_tool_renderer
class WaitForMessageRenderer(BaseToolRenderer):
tool_name: ClassVar[str] = "wait_for_message"
class WaitForAgentsRenderer(BaseToolRenderer):
tool_name: ClassVar[str] = "wait_for_agents"
css_classes: ClassVar[list[str]] = ["tool-call", "agents-graph-tool"]
@classmethod
@@ -0,0 +1,35 @@
from typing import Any, ClassVar
from rich.text import Text
from textual.widgets import Static
from .agent_message_renderer import AgentMessageRenderer
from .base_renderer import BaseToolRenderer
from .registry import register_tool_renderer
@register_tool_renderer
class RespondToUserRenderer(BaseToolRenderer):
"""Render a reply as the agent's own prose, not as a tool call.
``respond_to_user`` carries the message the user is meant to read, so it
gets the same markdown treatment as a plain assistant turn.
"""
tool_name: ClassVar[str] = "respond_to_user"
css_classes: ClassVar[list[str]] = ["tool-call", "respond-tool"]
@classmethod
def render(cls, tool_data: dict[str, Any]) -> Static:
args = tool_data.get("args", {})
message = args.get("message", "")
text = Text()
if message:
text.append_text(AgentMessageRenderer.render_simple(message))
text.append("\n\n")
text.append("", style="#6b7280")
text.append("waiting for your reply", style="dim")
css_classes = cls.get_css_classes(tool_data.get("status", "unknown"))
return Static(text, classes=css_classes)
@@ -54,7 +54,7 @@ export default function AgentCommsRenderer({ toolName, args }: ToolRendererProps
);
}
if (toolName === "wait_for_message") {
if (toolName === "wait_for_agents") {
const reason = (args.reason as string) ?? "";
return (
<div className="flex items-center gap-2">
@@ -0,0 +1,20 @@
"use client";
import type { ToolRendererProps } from "@/types/events";
import Markdown from "./Markdown";
/**
* `respond_to_user` carries the message the user is meant to read, so it renders
* as the agent's own prose rather than as a tool call.
*/
export default function RespondRenderer({ args }: ToolRendererProps) {
const message = (args.message as string) ?? "";
if (!message) return null;
return (
<div>
<Markdown text={message} />
<div className="mt-1.5 text-[#888] text-[13px]">waiting for your reply</div>
</div>
);
}
@@ -24,6 +24,7 @@ import NotesRenderer from "./NotesRenderer";
import TodoRenderer from "./TodoRenderer";
import FallbackRenderer from "./FallbackRenderer";
import LoadSkillRenderer from "./LoadSkillRenderer";
import RespondRenderer from "./RespondRenderer";
/**
* Tool-renderer mapping — data-driven, keyed by the engine's tool *family*.
@@ -104,10 +105,10 @@ const CATEGORY_TOOLS: Record<ToolCategory, readonly string[]> = {
proxy: ["list_requests", "view_request", "repeat_request", "list_sitemap", "view_sitemap_entry", "scope_rules", "send_request"],
reporting: ["create_vulnerability_report", "list_reports", "get_report"],
thinking: ["think"],
agents: ["create_agent", "agent_finish", "send_message_to_agent", "wait_for_message", "view_agent_graph", "stop_agent"],
agents: ["create_agent", "agent_finish", "send_message_to_agent", "wait_for_agents", "view_agent_graph", "stop_agent"],
search: ["web_search"],
// scan_start_info / subagent_start_info are strix-app synthetic events; finish_scan is the engine's
lifecycle: ["scan_start_info", "subagent_start_info", "finish_scan"],
lifecycle: ["scan_start_info", "subagent_start_info", "finish_scan", "respond_to_user"],
notes: ["create_note", "delete_note", "update_note", "list_notes", "get_note"],
skills: ["load_skill"],
todos: ["create_todo", "list_todos", "update_todo", "mark_todo_done", "mark_todo_pending", "delete_todo"],
@@ -127,6 +128,7 @@ const TOOL_CATEGORY: Record<string, ToolCategory> = Object.fromEntries(
*/
const RENDERER_OVERRIDES: Partial<Record<string, ComponentType<ToolRendererProps>>> = {
finish_scan: FinishRenderer,
respond_to_user: RespondRenderer,
apply_patch: ApplyPatchRenderer,
view_image: ViewImageRenderer,
list_reports: ReportListRenderer,
@@ -140,7 +142,8 @@ const RENDERER_OVERRIDES: Partial<Record<string, ComponentType<ToolRendererProps
const ICON_OVERRIDES: Partial<Record<string, ToolIconMeta>> = {
agent_finish: { icon: Flag, color: "text-cyan-400" },
send_message_to_agent: { icon: MessageCircle, color: "text-cyan-400" },
wait_for_message: { icon: MessageCircle, color: "text-cyan-400" },
wait_for_agents: { icon: MessageCircle, color: "text-cyan-400" },
respond_to_user: { icon: MessageCircle, color: "text-emerald-400" },
view_agent_graph: { icon: Eye, color: "text-cyan-400" },
stop_agent: { icon: Ban, color: "text-red-400" },
scan_start_info: { icon: Crosshair, color: "text-emerald-400" },
File diff suppressed because one or more lines are too long
+1 -1
View File
@@ -6,7 +6,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta name="color-scheme" content="dark" />
<title>Strix Results</title>
<script type="module" crossorigin src="./assets/index-DzvI_0HX.js"></script>
<script type="module" crossorigin src="./assets/index-CGvQq6oe.js"></script>
<link rel="stylesheet" crossorigin href="./assets/index-C3kQ5kk8.css">
</head>
<body>
+36 -19
View File
@@ -218,25 +218,43 @@ def _session_items_payload(items: list[Any]) -> list[dict[str, Any]]:
return payload
@function_tool(timeout=601)
async def wait_for_message( # noqa: PLR0911
_WAIT_DEFAULT_TIMEOUT_S = 300
# Enforced by the SDK around the whole tool call, so it caps an oversized
# ``timeout_seconds`` the model asks for. One second of headroom lets the
# tool's own timeout fire first and return a clean result.
_WAIT_HARD_CEILING_S = _WAIT_DEFAULT_TIMEOUT_S + 1
@function_tool(timeout=_WAIT_HARD_CEILING_S)
async def wait_for_agents( # noqa: PLR0911
ctx: RunContextWrapper,
reason: str = "Waiting for messages from other agents",
timeout_seconds: int = 600,
timeout_seconds: int = _WAIT_DEFAULT_TIMEOUT_S,
) -> str:
"""Pause this agent until a message lands in its inbox (or timeout).
"""Pause until another AGENT messages you (or the timeout elapses).
Use when you have nothing useful to do until a child/peer responds
— typically after spawning subagents and you want to wait for
their completion reports. The agent automatically resumes when any
message arrives, so pick a ``timeout_seconds`` proportional to the
work you're awaiting.
Use when you have nothing useful to do until a child or peer
responds — typically after spawning subagents and you want their
completion reports. You resume the instant any message arrives, so
size ``timeout_seconds`` to the work you're awaiting.
**This tool is only for waiting on other agents.** Two things it is
NOT for:
- **Talking to the user.** Use ``respond_to_user``, which delivers
your message and hands control back in one call.
- **Waiting for a long-running command.** This tool does not watch
processes at all — it sleeps until a *message* arrives, so it
burns the full timeout even if your command finished a second
later. Poll the process instead: ``exec_command`` returns a
session/process id, and ``write_stdin`` with ``chars=""`` returns
as soon as there is new output or the process exits.
**Critical caveats:**
- **Never** call this if you finished your own task and have **no**
child agents running — that's a permanent stall. Call
``finish_scan`` (root) or ``agent_finish`` (subagent) instead.
- **Never** call this if you have no agents left to hear from —
that just strands you until the timeout. Call ``finish_scan``
(root) or ``agent_finish`` (subagent) instead.
- If you're waiting on an agent that **isn't your child**, message
it first asking it to ping you when done — otherwise it has no
reason to send to your inbox and you'll wait the full timeout.
@@ -247,7 +265,8 @@ async def wait_for_message( # noqa: PLR0911
reason: One-line note shown in graph snapshots while you're
waiting (helps a human or sibling agent debug who's stuck
on what).
timeout_seconds: Max seconds to wait (default 600). This is only
timeout_seconds: Max seconds to wait (default 300, and values above
that are cut short by a hard ceiling). This is only
a cap — the tool returns the INSTANT a message arrives, so a
larger value never makes you wait longer when the reply does
come. Right-size it to what you're waiting on: a short wait
@@ -257,9 +276,7 @@ async def wait_for_message( # noqa: PLR0911
bites when the expected message never arrives — so an oversized
timeout on a trivial wait just strands you idle until it
elapses. On timeout the tool returns and you decide whether to
keep working or wait again. (Applies to autonomous multi-agent
runs; in interactive/chat sessions the agent instead parks until
a message arrives and this cap is not enforced.)
keep working or wait again.
"""
inner = _ctx(ctx)
coordinator = coordinator_from_context(inner)
@@ -302,7 +319,7 @@ async def wait_for_message( # noqa: PLR0911
)
if interactive:
await coordinator.park_waiting(me)
await coordinator.park_waiting(me, wait_kind="agents")
return json.dumps(
{
"success": True,
@@ -314,7 +331,7 @@ async def wait_for_message( # noqa: PLR0911
default=str,
)
await coordinator.park_waiting(me)
await coordinator.park_waiting(me, wait_kind="agents")
try:
await asyncio.wait_for(coordinator.wait_for_message(me), timeout_seconds)
except TimeoutError:
@@ -373,7 +390,7 @@ async def create_agent(
Decompose complex pentests by handing focused subtasks to dedicated
children. The child runs asynchronously — the parent continues
immediately and can ``wait_for_message`` later (or just keep
immediately and can ``wait_for_agents`` later (or just keep
working in parallel). When the child calls ``agent_finish``, its
completion report lands in the parent's inbox.
+2 -2
View File
@@ -101,7 +101,7 @@ async def finish_scan(
execution stops. There is no draft mode and no second chance: never
submit placeholder, provisional, or "checking if done" text in any
field, and never call ``finish_scan`` to poll whether subagents are
done (use ``view_agent_graph`` / ``wait_for_message`` for that).
done (use ``view_agent_graph`` / ``wait_for_agents`` for that).
Call it exactly ONCE, only when every field holds genuine, finished
assessment prose.
@@ -111,7 +111,7 @@ async def finish_scan(
summary. If ANY agent is in ``running`` / ``waiting`` state,
you MUST NOT call ``finish_scan`` yet —
wrap them up first via ``send_message_to_agent`` (ask them to
finish), ``wait_for_message`` (block until their report
finish), ``wait_for_agents`` (block until their report
arrives), or ``stop_agent`` (graceful cancel). Only ``completed``
/ ``crashed`` / ``stopped`` agents are safe to leave behind.
Calling ``finish_scan`` while children are alive orphans their
+6
View File
@@ -0,0 +1,6 @@
"""User-facing reply tool for interactive sessions."""
from strix.tools.respond.tool import respond_to_user
__all__ = ["respond_to_user"]
+110
View File
@@ -0,0 +1,110 @@
"""``respond_to_user`` — deliver a reply and hand control back to the user."""
from __future__ import annotations
import json
from typing import Any
from agents import RunContextWrapper, function_tool
from strix.core.agents import coordinator_from_context
def _ctx(ctx: RunContextWrapper) -> dict[str, Any]:
return ctx.context if isinstance(ctx.context, dict) else {}
@function_tool
async def respond_to_user(ctx: RunContextWrapper, message: str) -> str:
"""Answer the user and hand control back to them.
This is the ONLY way to yield to the user. Delivering the message and
yielding are the same call on purpose: there is no way to answer and
then forget to stop, and no way to stop without having answered.
Call it when you have something for the user and nothing to do until
they reply — you answered their question, you need a decision or a
credential only they can give, or you finished a chunk of work and
want direction. You resume exactly where you left off when they
reply, with everything you have done so far intact.
Do NOT call it to narrate progress or to think out loud. Plain text
is still shown to the user as you work, so say whatever you like
mid-task without stopping; ``respond_to_user`` is specifically the
act of *waiting* for them. Every call costs the user their attention.
Not for these:
- **Waiting on another agent** (a child's report, a peer's reply) —
use ``wait_for_agents``.
- **Ending the engagement** — use ``finish_scan`` (root) or
``agent_finish`` (subagent). Those are terminal; this is a pause.
Args:
message: What to say to the user. Self-contained: they may not
have followed the tool calls that led here. Lead with the
answer or the decision you need, and if you are blocked, say
exactly what you need from them.
"""
inner = _ctx(ctx)
coordinator = coordinator_from_context(inner)
me = inner.get("agent_id")
interactive = bool(inner.get("interactive", False))
if coordinator is None or me is None:
return json.dumps(
{"success": False, "error": "Agent coordinator or agent_id missing in context"},
ensure_ascii=False,
default=str,
)
if not interactive:
return json.dumps(
{
"success": False,
"error": (
"No user is attached to an autonomous run. Keep working, and call "
"finish_scan (root) or agent_finish (subagent) when the task is done."
),
},
ensure_ascii=False,
default=str,
)
async with coordinator._lock:
stopped = coordinator.statuses.get(me) == "stopped"
if stopped:
return json.dumps(
{"success": True, "wait_outcome": "stopped", "message": message},
ensure_ascii=False,
default=str,
)
# A message that arrived while this turn was running is the user already
# talking: take it now instead of parking for one they have sent.
pending, _ = await coordinator.consume_pending(me)
if pending > 0:
await coordinator.mark_running(me)
return json.dumps(
{
"success": True,
"wait_outcome": "message_arrived",
"pending_messages": pending,
"message": message,
"note": "Your reply was delivered; the user had already sent a new message.",
},
ensure_ascii=False,
default=str,
)
await coordinator.park_waiting(me, wait_kind="user")
return json.dumps(
{
"success": True,
"wait_outcome": "waiting",
"message": message,
"note": "Reply delivered; parked until the user responds.",
},
ensure_ascii=False,
default=str,
)
+27 -1
View File
@@ -2,18 +2,29 @@
from __future__ import annotations
from typing import TYPE_CHECKING, Any
import pytest
from agents.tool import FunctionTool
from strix.agents import factory
if TYPE_CHECKING:
from agents.tool_context import ToolContext
def _tool(name: str) -> FunctionTool:
# A per-tool closure keeps two same-named tools unequal, which is what the
# duplicate-name tests exercise.
async def invoke(_ctx: ToolContext[Any], _input: str) -> str:
return "ok"
return FunctionTool(
name=name,
description="test tool",
params_json_schema={"type": "object", "properties": {}, "additionalProperties": False},
on_invoke_tool=lambda _ctx, _inp: "ok",
on_invoke_tool=invoke,
)
@@ -86,3 +97,18 @@ def test_no_override_renders_builtin_prompt() -> None:
assert isinstance(agent.instructions, str)
assert agent.instructions != ""
def test_respond_to_user_is_interactive_only() -> None:
"""Yielding to the user is meaningless when no user is attached."""
interactive = factory.build_strix_agent(is_root=True, interactive=True)
autonomous = factory.build_strix_agent(is_root=True, interactive=False)
assert "respond_to_user" in [t.name for t in interactive.tools]
assert "respond_to_user" not in [t.name for t in autonomous.tools]
def test_wait_for_agents_is_available_in_both_modes() -> None:
for interactive in (True, False):
agent = factory.build_strix_agent(is_root=True, interactive=interactive)
assert "wait_for_agents" in [t.name for t in agent.tools]
+25 -10
View File
@@ -7,7 +7,7 @@ from unittest.mock import MagicMock, patch
import pytest
from strix.core import execution
from strix.core.agents import AgentCoordinator
from strix.core.agents import AgentCoordinator, WaitKind
from strix.core.execution import _start_child_runner, run_agent_loop
from strix.core.hooks import BudgetExceededError, ReportUsageHooks
from strix.core.sessions import open_agent_session
@@ -42,23 +42,32 @@ class _FakeStream:
hooks: ReportUsageHooks,
context: dict[str, Any],
agent: Any,
coordinator: AgentCoordinator,
) -> None:
self._ledger = ledger
self._hooks = hooks
self._context = context
self._agent = agent
self._coordinator = coordinator
self.run_loop_exception: BaseException | None = None
self.final_output = None
async def stream_events(self) -> AsyncIterator[Any]:
agent_id = str(self._context.get("agent_id"))
self._ledger.cost += COST_PER_CALL
self._ledger.calls.append(str(self._context.get("agent_id")))
self._ledger.calls.append(agent_id)
ctx_wrapper = MagicMock()
ctx_wrapper.context = self._context
try:
await self._hooks.on_llm_end(ctx_wrapper, self._agent, MagicMock())
except Exception as exc: # noqa: BLE001
self.run_loop_exception = exc
# Stand in for the explicit yield tool a real turn ends with. Without it
# every turn looks like a forgotten tool call and burns the recovery
# budget, which is a different scenario from the one under test here.
if self._coordinator.statuses.get(agent_id) == "running":
wait_kind: WaitKind = "user" if self._context.get("parent_id") is None else "agents"
await self._coordinator.park_waiting(agent_id, wait_kind=wait_kind)
items: tuple[Any, ...] = ()
for item in items:
yield item
@@ -67,7 +76,7 @@ class _FakeStream:
return
def _fake_runner(ledger: _FakeLedger) -> Any:
def _fake_runner(ledger: _FakeLedger, coordinator: AgentCoordinator) -> Any:
class _FakeRunner:
@staticmethod
def run_streamed(
@@ -80,7 +89,13 @@ def _fake_runner(ledger: _FakeLedger) -> Any:
session: Any, # noqa: ARG004
hooks: ReportUsageHooks,
) -> _FakeStream:
return _FakeStream(ledger=ledger, hooks=hooks, context=context, agent=agent)
return _FakeStream(
ledger=ledger,
hooks=hooks,
context=context,
agent=agent,
coordinator=coordinator,
)
return _FakeRunner
@@ -103,10 +118,10 @@ async def test_full_budget_lifecycle_reserve_then_cap( # noqa: PLR0915
) -> None:
ledger = _FakeLedger()
hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET)
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger))
coordinator = AgentCoordinator()
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, coordinator))
monkeypatch.setattr(execution, "_compact_session", _noop_compact)
coordinator = AgentCoordinator()
db_path = tmp_path / "agents.sqlite"
sessions: list[Any] = []
run_config = MagicMock()
@@ -218,7 +233,6 @@ async def test_respawned_children_after_reserve_never_spend(
ledger = _FakeLedger()
ledger.cost = 9.5
hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET)
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger))
monkeypatch.setattr(execution, "_compact_session", _noop_compact)
coordinator = AgentCoordinator()
@@ -230,6 +244,7 @@ async def test_respawned_children_after_reserve_never_spend(
restored = AgentCoordinator()
await restored.restore(snap)
assert restored.reserve_stopped is True
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, restored))
sessions: list[Any] = []
with patch("strix.core.hooks.get_global_report_state", return_value=ledger):
@@ -264,7 +279,6 @@ async def test_resumed_parked_root_after_reserve_is_renotified_and_finalizes(
ledger = _FakeLedger()
ledger.cost = 9.0
hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET)
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger))
monkeypatch.setattr(execution, "_compact_session", _noop_compact)
coordinator = AgentCoordinator()
@@ -276,6 +290,7 @@ async def test_resumed_parked_root_after_reserve_is_renotified_and_finalizes(
restored = AgentCoordinator()
await restored.restore(snap)
assert restored.reserve_stopped is True
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, restored))
root_session = open_agent_session("root", tmp_path / "agents.sqlite")
with patch("strix.core.hooks.get_global_report_state", return_value=ledger):
@@ -312,10 +327,10 @@ async def test_interactive_budget_pause_then_user_message_extends_and_resumes(
ledger = _FakeLedger()
ledger.cost = 9.0
hooks = ReportUsageHooks(model="test-model", max_budget_usd=MAX_BUDGET, interactive=True)
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger))
coordinator = AgentCoordinator()
monkeypatch.setattr(execution, "Runner", _fake_runner(ledger, coordinator))
monkeypatch.setattr(execution, "_compact_session", _noop_compact)
coordinator = AgentCoordinator()
coordinator.set_budget_extender(hooks.extend_budget)
await coordinator.register("root", "strix", parent_id=None)
root_session = open_agent_session("root", tmp_path / "agents.sqlite")
+474 -52
View File
@@ -5,27 +5,29 @@ from __future__ import annotations
import asyncio
import contextlib
import json
from typing import Any
from typing import Any, cast
from unittest.mock import MagicMock
import pytest
from agents.exceptions import MaxTurnsExceeded
from agents.items import MessageOutputItem
from agents.memory import SQLiteSession
from agents.tool_context import ToolContext
from openai.types.responses import ResponseOutputMessage, ResponseOutputRefusal
from strix.config import codex
from strix.core import execution
from strix.core.agents import AgentCoordinator
from strix.core.execution import (
_handle_content_guardrail,
_notify_parent_on_terminal,
_notify_root_on_budget_reserve,
respawn_subagents,
)
from strix.core.sessions import seed_initial_input
from strix.tools.finish.tool import finish_scan
_NO_STREAM_EVENTS: list[Any] = []
class _StructuredRefusalStream:
def __init__(self, refusal: str) -> None:
self.run_loop_exception: BaseException | None = None
@@ -43,8 +45,8 @@ class _StructuredRefusalStream:
]
async def stream_events(self) -> Any:
if False:
yield None
for event in _NO_STREAM_EVENTS:
yield event
def cancel(self, mode: str = "immediate") -> None: # noqa: ARG002
return
@@ -529,44 +531,152 @@ async def test_terminal_notice_does_not_cancel_parent_stream(tmp_path: Any) -> N
@pytest.mark.asyncio
async def test_guardrail_interactive_parks_agent_wakeable(tmp_path: Any) -> None:
async def test_send_queues_without_session_and_drains_on_consume(tmp_path: Any) -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.register("child", "recon", parent_id="root")
exc = codex.CodexContentGuardrailError("chatgpt/gpt-5.6-sol")
result = await _handle_content_guardrail(coordinator, "child", exc, interactive=True)
assert await coordinator.send("root", {"from": "user", "content": "hello"}) is True
assert coordinator.pending_counts["root"] == 1
assert result is None
assert coordinator.statuses["child"] == "waiting"
assert "STRIX_LLM" in coordinator.errors["child"]
session = SQLiteSession("root", tmp_path / "agents.db")
await coordinator.attach_runtime("root", session=session)
waiter = asyncio.create_task(coordinator.wait_for_message("child"))
await asyncio.sleep(0)
assert not waiter.done()
session = SQLiteSession("child", tmp_path / "agents.db")
await coordinator.attach_runtime("child", session=session)
await coordinator.send("child", {"from": "user", "content": "switched model, resume"})
await asyncio.wait_for(waiter, timeout=1.0)
count, items = await coordinator.consume_pending("root", include_items=True)
assert count == 1
assert items[0]["content"] == "hello"
stored = await session.get_items()
last = cast("dict[str, Any]", stored[-1])
assert last["content"] == "hello"
session.close()
@pytest.mark.asyncio
async def test_guardrail_noninteractive_fails_only_blocked_agent(tmp_path: Any) -> None:
async def test_error_parked_agent_only_released_by_user_message(tmp_path: Any) -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.register("child", "recon", parent_id="root")
session = SQLiteSession("root", tmp_path / "agents.db")
await coordinator.attach_runtime("root", session=session)
exc = codex.CodexContentGuardrailError("chatgpt/gpt-5.6-sol")
session = SQLiteSession("child", tmp_path / "agents.db")
await coordinator.attach_runtime("child", session=session)
await coordinator.set_status("child", "crashed", error="boom")
result = await _handle_content_guardrail(coordinator, "child", exc, interactive=False)
await coordinator.send("child", {"from": "root", "content": "peer nudge"})
waiter = asyncio.create_task(coordinator.wait_for_message("child"))
await asyncio.sleep(0.05)
assert not waiter.done()
await coordinator.send("child", {"from": "user", "content": "wake up"})
assert await asyncio.wait_for(waiter, timeout=1.0) is True
count, items = await coordinator.consume_pending("child", include_items=True)
assert count == 2
assert items[0]["content"].endswith("peer nudge")
assert items[1]["content"] == "wake up"
session.close()
@pytest.mark.asyncio
async def test_wait_for_message_timeout_returns_false() -> None:
coordinator = AgentCoordinator()
await coordinator.register("child", "recon", parent_id="root")
assert await coordinator.wait_for_message("child", timeout=0.05) is False
@pytest.mark.asyncio
async def test_snapshot_round_trip_preserves_mailboxes() -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.send("root", {"from": "user", "content": "queued"})
snap = await coordinator.snapshot()
restored = AgentCoordinator()
await restored.restore(snap)
assert restored.pending_counts["root"] == 1
assert restored.runtimes["root"].mailbox == [{"from": "user", "content": "queued"}]
@pytest.mark.asyncio
async def test_run_cycle_parked_parks_instead_of_raising(
monkeypatch: pytest.MonkeyPatch,
) -> None:
async def _boom(*_args: Any, **_kwargs: Any) -> Any:
raise RuntimeError("unexpected explosion")
monkeypatch.setattr(execution, "_run_cycle", _boom)
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
result = await execution._run_cycle_parked(
object(),
coordinator,
"root",
input_data=[],
run_config=None, # type: ignore[arg-type]
context={},
max_turns=5,
session=None,
event_sink=None,
hooks=None,
)
assert result is None
assert coordinator.statuses["child"] == "failed"
assert "STRIX_LLM" in coordinator.errors["child"]
assert coordinator.statuses["root"] == "running"
assert coordinator.pending_counts.get("root", 0) > 0
assert coordinator.statuses["root"] == "failed"
assert coordinator.errors["root"] == "unexpected explosion"
class _SalvageStream:
def __init__(self, replay: list[dict[str, Any]]) -> None:
self._replay = replay
def to_input_list(self) -> list[dict[str, Any]]:
return self._replay
@pytest.mark.asyncio
async def test_salvage_stream_to_session_preserves_full_history(tmp_path: Any) -> None:
session = SQLiteSession("child", tmp_path / "agents.db")
await session.add_items([{"role": "user", "content": "identity + task"}])
pre_run = list(await session.get_items())
# A crash mid-run: the stream produced two turns the SDK never committed.
stream = _SalvageStream(
[
{"role": "assistant", "content": "recon turn 1"},
{"role": "assistant", "content": "recon turn 2"},
]
)
await execution._salvage_stream_to_session(session, pre_run, stream, "child")
stored = [cast("dict[str, Any]", i) for i in await session.get_items()]
assert [i["content"] for i in stored] == [
"identity + task",
"recon turn 1",
"recon turn 2",
]
# A crash with nothing new to salvage leaves the session untouched.
await execution._salvage_stream_to_session(
session, list(await session.get_items()), _SalvageStream([]), "child"
)
assert len(await session.get_items()) == 3
session.close()
@pytest.mark.asyncio
async def test_seed_initial_input_persists_and_is_idempotent(tmp_path: Any) -> None:
session = SQLiteSession("child", tmp_path / "agents.db")
identity = [{"role": "user", "content": "You are agent recon (abc); do X."}]
assert await seed_initial_input(session, identity) is True
assert len(await session.get_items()) == 1
# A populated session is left untouched (no duplicate identity message).
assert await seed_initial_input(session, identity) is False
assert len(await session.get_items()) == 1
assert await seed_initial_input(session, []) is False
session.close()
@@ -576,7 +686,9 @@ async def test_structured_provider_refusal_fails_interactive_agent(
) -> None:
refusal = "This request was blocked under the provider's usage policy."
stream = _StructuredRefusalStream(refusal)
monkeypatch.setattr(execution.Runner, "run_streamed", lambda *_args, **_kwargs: stream)
monkeypatch.setattr(
"strix.core.execution.Runner.run_streamed", lambda *_args, **_kwargs: stream
)
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
@@ -606,7 +718,9 @@ async def test_structured_provider_refusal_fails_noninteractive_child(
) -> None:
refusal = "This request was blocked under the provider's usage policy."
stream = _StructuredRefusalStream(refusal)
monkeypatch.setattr(execution.Runner, "run_streamed", lambda *_args, **_kwargs: stream)
monkeypatch.setattr(
"strix.core.execution.Runner.run_streamed", lambda *_args, **_kwargs: stream
)
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.register("child", "recon", parent_id="root")
@@ -635,34 +749,342 @@ async def test_structured_provider_refusal_fails_noninteractive_child(
@pytest.mark.asyncio
async def test_resume_revives_guardrail_parked_child_but_not_plain_waiting(
async def test_run_agent_loop_seeds_identity_before_first_cycle(
tmp_path: Any, monkeypatch: pytest.MonkeyPatch
) -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.register("blocked", "recon", parent_id="root")
await coordinator.register("peer_waiter", "recon", parent_id="root")
await coordinator.set_status("blocked", "waiting", error="STRIX_LLM guardrail")
await coordinator.set_status("peer_waiter", "waiting")
await coordinator.register("child", "recon", parent_id="root")
session = SQLiteSession("child", tmp_path / "agents.db")
parked: dict[str, bool] = {}
captured: dict[str, Any] = {}
async def _fake_start_child_runner(**kwargs: Any) -> None:
parked[kwargs["child_id"]] = bool(kwargs["start_parked"])
async def _crash_first_turn(*_args: Any, **kwargs: Any) -> Any:
captured["input_data"] = kwargs.get("input_data")
captured["items_at_start"] = await session.get_items()
raise RuntimeError("first-turn crash")
monkeypatch.setattr(execution, "_start_child_runner", _fake_start_child_runner)
monkeypatch.setattr(execution, "_run_cycle", _crash_first_turn)
await respawn_subagents(
coordinator=coordinator,
factory=lambda **_kwargs: object(),
agents_db_path=tmp_path / "agents.db",
sessions_to_close=[],
identity = [{"role": "user", "content": "You are agent recon (abc); maintain your identity."}]
with pytest.raises(RuntimeError, match="first-turn crash"):
await execution.run_agent_loop(
agent=object(),
initial_input=identity,
run_config=None, # type: ignore[arg-type]
context={"agent_id": "child", "parent_id": "root"},
max_turns=5,
coordinator=coordinator,
agent_id="child",
interactive=False,
session=session,
)
# The first cycle ran with an empty input against the pre-seeded session.
assert captured["input_data"] == []
assert captured["items_at_start"]
# The identity/task survives the first-turn crash, so a revival can resume it.
stored = await session.get_items()
assert any("recon" in str(cast("dict[str, Any]", i).get("content", "")) for i in stored)
session.close()
def _scripted_cycle(
coordinator: AgentCoordinator,
agent_id: str,
statuses: list[str],
calls: list[Any],
) -> Any:
"""Fake run cycle that leaves ``agent_id`` in a scripted status per call."""
async def _cycle(*_args: Any, **kwargs: Any) -> Any:
calls.append(kwargs.get("input_data"))
status = statuses[min(len(calls) - 1, len(statuses) - 1)]
await coordinator.set_status(agent_id, status)
return MagicMock(final_output="plain text, no tool call")
return _cycle
async def _drive(
coordinator: AgentCoordinator,
agent_id: str,
*,
interactive: bool,
max_turns: int = 5,
) -> Any:
return await execution._run_until_lifecycle(
MagicMock(),
coordinator,
agent_id,
initial_input=[],
run_config=MagicMock(),
max_turns=10,
interactive=True,
parent_ctx={"agent_id": "root", "parent_id": None},
root_id="root",
context={"agent_id": agent_id, "parent_id": None},
max_turns=max_turns,
session=None,
interactive=interactive,
event_sink=None,
hooks=None,
)
assert parked["blocked"] is False
assert parked["peer_waiter"] is True
@pytest.mark.asyncio
async def test_interactive_text_only_turn_is_nudged_instead_of_parking(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""A no-tool-call turn must not silently hand control back to the user."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "root", ["running", "completed"], calls),
)
await _drive(coordinator, "root", interactive=True)
assert len(calls) == 2
# The retry carries an explicit "call a tool" nudge rather than empty input.
nudge = calls[1][0]["content"]
assert "without a tool call" in nudge
assert "respond_to_user" in nudge
assert coordinator.statuses["root"] == "completed"
@pytest.mark.asyncio
async def test_interactive_explicit_park_gets_no_nudge(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""``waiting`` is only reachable via respond_to_user / wait_for_agents."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "root", ["waiting"], calls),
)
await _drive(coordinator, "root", interactive=True)
assert len(calls) == 1
assert coordinator.statuses["root"] == "waiting"
@pytest.mark.asyncio
async def test_interactive_recovery_exhaustion_parks_instead_of_crashing(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""A human can resume an interactive scan, so exhaustion parks rather than dies."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "root", ["running"], calls),
)
await _drive(coordinator, "root", interactive=True)
assert len(calls) == execution._INTERACTIVE_TOOL_RECOVERY_LIMIT
assert coordinator.statuses["root"] == "waiting"
@pytest.mark.asyncio
async def test_interactive_subagent_exhaustion_tells_its_parent(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""A parked child must report up so its parent stops waiting on it.
The parent is an agent, not a watching human, so a parent blocked in
wait_for_agents otherwise burns its whole timeout on a completion
report the child can no longer send.
"""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.register("child", "recon", parent_id="root")
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "child", ["running"], calls),
)
await _drive(coordinator, "child", interactive=True)
assert coordinator.statuses["child"] == "waiting"
pending, items = await coordinator.consume_pending("root", include_items=True)
assert pending == 1
notice = str(items[0])
assert "child" in notice
assert "parked" in notice
@pytest.mark.asyncio
async def test_interactive_root_exhaustion_notifies_nobody(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""The root has no parent to report to, so parking stays silent."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "root", ["running"], []),
)
await _drive(coordinator, "root", interactive=True)
pending, _ = await coordinator.consume_pending("root")
assert pending == 0
@pytest.mark.asyncio
async def test_noninteractive_recovery_exhaustion_crashes(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""No user is present to resume an autonomous run, so it still fails loudly."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle",
_scripted_cycle(coordinator, "root", ["running"], calls),
)
with pytest.raises(MaxTurnsExceeded):
await _drive(coordinator, "root", interactive=False, max_turns=2)
assert len(calls) == 2
assert coordinator.statuses["root"] == "crashed"
@pytest.mark.asyncio
async def test_tool_required_message_is_persisted_to_the_session(tmp_path: Any) -> None:
session = SQLiteSession("root", tmp_path / "agents.db")
assert (
await execution._append_tool_required_message(
session=session,
context={"parent_id": None},
attempt=1,
limit=3,
interactive=True,
)
== []
)
stored = [cast("dict[str, Any]", i) for i in await session.get_items()]
assert "finish_scan" in stored[0]["content"]
assert "respond_to_user" in stored[0]["content"]
session.close()
@pytest.mark.asyncio
async def test_recovery_count_survives_a_snapshot_round_trip(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""A resumed agent must not earn a fresh nudge budget and loop forever."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "root", ["running"], calls),
)
await _drive(coordinator, "root", interactive=True)
assert coordinator.recovery_counts["root"] == execution._INTERACTIVE_TOOL_RECOVERY_LIMIT
restored = AgentCoordinator()
await restored.restore(await coordinator.snapshot())
assert restored.recovery_counts["root"] == execution._INTERACTIVE_TOOL_RECOVERY_LIMIT
# The restored agent is already at its cap, so it parks after a single
# further text-only cycle instead of starting the whole budget over.
resumed_calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(restored, "root", ["running"], resumed_calls),
)
await _drive(restored, "root", interactive=True)
assert len(resumed_calls) == 1
assert restored.statuses["root"] == "waiting"
@pytest.mark.asyncio
async def test_recovery_count_is_cleared_by_a_lifecycle_tool(
monkeypatch: pytest.MonkeyPatch,
) -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
calls: list[Any] = []
monkeypatch.setattr(
execution,
"_run_cycle_parked",
_scripted_cycle(coordinator, "root", ["running", "completed"], calls),
)
await _drive(coordinator, "root", interactive=True)
assert "root" not in coordinator.recovery_counts
@pytest.mark.asyncio
async def test_agent_awaiting_a_human_is_never_auto_resumed() -> None:
"""The user can message any agent, so parking for one is not root-only."""
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.register("child", "recon", parent_id="root")
for agent_id in ("root", "child"):
await coordinator.park_waiting(agent_id, wait_kind="user")
assert await execution._plain_waiting_timeout(coordinator, agent_id) is None
@pytest.mark.asyncio
async def test_agent_awaiting_other_agents_is_re_checked_on_a_timer() -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.park_waiting("root", wait_kind="agents")
timeout = await execution._plain_waiting_timeout(coordinator, "root")
assert timeout == execution._WAITING_AUTO_RESUME_TIMEOUT_S
@pytest.mark.asyncio
async def test_idle_auto_resumes_stop_after_their_budget() -> None:
"""A wedged agent must not burn a model turn per timeout for the whole scan."""
coordinator = AgentCoordinator()
await coordinator.register("child", "recon", parent_id="root")
await coordinator.park_waiting("child", wait_kind="agents")
for _ in range(execution._MAX_IDLE_AUTO_RESUMES):
assert await execution._plain_waiting_timeout(coordinator, "child") is not None
await coordinator.record_idle_resume("child")
assert await execution._plain_waiting_timeout(coordinator, "child") is None
# A real message is real progress, so the budget starts over.
await coordinator.reset_idle_resumes("child")
assert await execution._plain_waiting_timeout(coordinator, "child") is not None
@pytest.mark.asyncio
async def test_wait_kind_survives_a_snapshot_round_trip() -> None:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
await coordinator.park_waiting("root", wait_kind="user")
await coordinator.record_idle_resume("root")
restored = AgentCoordinator()
await restored.restore(await coordinator.snapshot())
assert restored.wait_kinds["root"] == "user"
assert restored.idle_resume_counts["root"] == 1
assert await execution._plain_waiting_timeout(restored, "root") is None
+19 -2
View File
@@ -15,6 +15,7 @@ from openai import (
RateLimitError,
)
from strix.config import codex
from strix.core import execution
from strix.core.agents import AgentCoordinator
@@ -55,11 +56,27 @@ def test_server_errors_are_transient() -> None:
assert execution._is_transient_model_error(_status_error(status)) is True
def test_rate_limit_is_not_retried_here() -> None:
def test_rate_limit_is_retried() -> None:
rate_limited = RateLimitError(
"slow down", response=httpx.Response(429, request=_request()), body=None
)
assert execution._is_transient_model_error(rate_limited) is False
assert execution._is_transient_model_error(rate_limited) is True
def test_dns_and_connection_errors_are_transient() -> None:
assert execution._is_transient_model_error(OSError("nodename nor servname provided")) is True
assert execution._is_transient_model_error(ConnectionError("reset")) is True
assert execution._is_transient_model_error(TimeoutError("timed out")) is True
def test_content_guardrail_is_not_retried() -> None:
guardrail = APIError(
"This content was flagged for possible cybersecurity risk",
_request(),
body=None,
)
assert codex.is_content_guardrail_error(guardrail) is True
assert execution._is_transient_model_error(guardrail) is False
def test_client_errors_are_not_transient() -> None:
+66
View File
@@ -0,0 +1,66 @@
"""Tests for the ``respond_to_user`` yield tool."""
from __future__ import annotations
import json
from typing import Any
import pytest
from agents.tool_context import ToolContext
from strix.core.agents import AgentCoordinator
from strix.tools.respond.tool import respond_to_user
async def _call(context: dict[str, Any], message: str = "here is what I found") -> dict[str, Any]:
ctx = ToolContext(
context=context,
tool_name="respond_to_user",
tool_call_id="call-1",
tool_arguments="{}",
)
raw = await respond_to_user.on_invoke_tool(ctx, json.dumps({"message": message}))
return json.loads(raw) # type: ignore[no-any-return]
async def _context(*, interactive: bool, agent_id: str = "root") -> dict[str, Any]:
coordinator = AgentCoordinator()
await coordinator.register("root", "strix", parent_id=None)
return {"coordinator": coordinator, "agent_id": agent_id, "interactive": interactive}
@pytest.mark.asyncio
async def test_parks_the_agent_and_carries_the_message() -> None:
context = await _context(interactive=True)
result = await _call(context)
coordinator = context["coordinator"]
assert result["success"] is True
assert result["wait_outcome"] == "waiting"
assert result["message"] == "here is what I found"
assert coordinator.statuses["root"] == "waiting"
# Recorded as a human wait, so the driver never auto-resumes it.
assert coordinator.wait_kinds["root"] == "user"
@pytest.mark.asyncio
async def test_rejected_in_an_autonomous_run() -> None:
context = await _context(interactive=False)
result = await _call(context)
assert result["success"] is False
assert "finish_scan" in result["error"]
assert context["coordinator"].statuses["root"] == "running"
@pytest.mark.asyncio
async def test_a_message_that_already_arrived_is_taken_instead_of_parking() -> None:
context = await _context(interactive=True)
coordinator = context["coordinator"]
await coordinator.send("root", {"from": "user", "content": "wait, one more thing"})
result = await _call(context)
assert result["wait_outcome"] == "message_arrived"
assert result["pending_messages"] == 1
assert coordinator.statuses["root"] == "running"