first commit

This commit is contained in:
Zakaria
2026-07-02 12:31:49 -04:00
commit 1c7784cae9
189 changed files with 32427 additions and 0 deletions
+1
View File
@@ -0,0 +1 @@
"""Strix scan runtime core."""
+323
View File
@@ -0,0 +1,323 @@
"""SDK-native state for Strix's addressable agent graph."""
from __future__ import annotations
import asyncio
import json
import logging
import tempfile
from dataclasses import dataclass, field
from pathlib import Path
from typing import TYPE_CHECKING, Any, Literal, cast
if TYPE_CHECKING:
from agents.items import TResponseInputItem
from agents.memory import Session
logger = logging.getLogger(__name__)
Status = Literal["running", "waiting", "completed", "stopped", "crashed", "failed"]
@dataclass(slots=True)
class AgentRuntime:
session: Session | None = None
task: asyncio.Task[Any] | None = None
stream: Any | None = None
interrupt_on_message: bool = False
wake: asyncio.Event = field(default_factory=asyncio.Event)
class AgentCoordinator:
"""Single owner for graph state, SDK runtimes, messages, and resume snapshots."""
def __init__(self) -> None:
self.statuses: dict[str, Status] = {}
self.parent_of: dict[str, str | None] = {}
self.names: dict[str, str] = {}
self.metadata: dict[str, dict[str, Any]] = {}
self.pending_counts: dict[str, int] = {}
self.runtimes: dict[str, AgentRuntime] = {}
self._lock = asyncio.Lock()
self._snapshot_path: Path | None = None
self.is_shutting_down = False
self._budget_stopped = False
def set_snapshot_path(self, path: Path) -> None:
self._snapshot_path = path
def mark_shutting_down(self) -> None:
self.is_shutting_down = True
@property
def budget_stopped(self) -> bool:
return self._budget_stopped
async def trigger_budget_stop(self) -> None:
"""Signal a scan-wide budget stop and wake every parked agent so it exits."""
async with self._lock:
self._budget_stopped = True
for runtime in self.runtimes.values():
runtime.wake.set()
async def register(
self,
agent_id: str,
name: str,
parent_id: str | None,
*,
task: str | None = None,
skills: list[str] | None = None,
) -> None:
async with self._lock:
self.statuses[agent_id] = "running"
self.parent_of[agent_id] = parent_id
self.names[agent_id] = name
self.pending_counts.setdefault(agent_id, 0)
self.metadata[agent_id] = {
"task": task or "",
"skills": list(skills or []),
}
self.runtimes.setdefault(agent_id, AgentRuntime())
logger.info("agent.register %s (%s) parent=%s", agent_id, name, parent_id or "-")
await self._maybe_snapshot()
async def attach_runtime(
self,
agent_id: str,
*,
session: Session | None = None,
task: asyncio.Task[Any] | None = None,
interrupt_on_message: bool | None = None,
) -> None:
async with self._lock:
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
if session is not None:
runtime.session = session
if task is not None:
runtime.task = task
if interrupt_on_message is not None:
runtime.interrupt_on_message = interrupt_on_message
async def mark_running(self, agent_id: str) -> None:
async with self._lock:
if agent_id in self.statuses:
self.statuses[agent_id] = "running"
await self._maybe_snapshot()
async def park_waiting(self, agent_id: str) -> None:
await self.set_status(agent_id, "waiting")
async def set_status(self, agent_id: str, status: Status | str) -> None:
async with self._lock:
if agent_id not in self.statuses:
return
self.statuses[agent_id] = status # type: ignore[assignment]
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
runtime.wake.set()
logger.info("agent.status %s=%s", agent_id, status)
await self._maybe_snapshot()
async def send(self, target_agent_id: str, message: dict[str, Any]) -> bool:
"""Deliver a user/peer message by appending it to the target SDK session."""
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
stream = runtime.stream
interrupt = 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:
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:
stream.cancel(mode="immediate")
await self._maybe_snapshot()
return True
async def wait_for_message(self, agent_id: str) -> None:
while True:
async with self._lock:
if self._budget_stopped or self.pending_counts.get(agent_id, 0) > 0:
return
wake = self.runtimes.setdefault(agent_id, AgentRuntime()).wake
wake.clear()
await wake.wait()
async def consume_pending(
self,
agent_id: str,
*,
include_items: bool = False,
) -> tuple[int, list[Any]]:
async with self._lock:
count = self.pending_counts.get(agent_id, 0)
self.pending_counts[agent_id] = 0
session = self.runtimes.get(agent_id, AgentRuntime()).session
if count <= 0:
return 0, []
await self._maybe_snapshot()
if not include_items or session is None:
return count, []
items = await session.get_items()
return count, list(items[-count:])
async def request_stop(self, agent_id: str) -> None:
async with self._lock:
if agent_id not in self.statuses:
return
self.statuses[agent_id] = "stopped"
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
runtime.wake.set()
stream = runtime.stream
if stream is not None:
stream.cancel(mode="after_turn")
await self._maybe_snapshot()
async def cancel_descendants(self, agent_id: str) -> None:
tasks = []
async with self._lock:
for aid in reversed(self._subtree_order_locked(agent_id)):
task = self.runtimes.get(aid, AgentRuntime()).task
if task is not None and not task.done():
tasks.append(task)
for task in tasks:
task.cancel()
if tasks:
await asyncio.gather(*tasks, return_exceptions=True)
async def cancel_descendants_graceful(self, agent_id: str) -> None:
async with self._lock:
order = self._subtree_order_locked(agent_id)
for aid in reversed(order):
await self.request_stop(aid)
await self._maybe_snapshot()
async def attach_stream(
self,
agent_id: str,
stream: Any,
) -> None:
async with self._lock:
self.runtimes.setdefault(agent_id, AgentRuntime()).stream = stream
async def detach_stream(
self,
agent_id: str,
stream: Any,
) -> None:
async with self._lock:
runtime = self.runtimes.setdefault(agent_id, AgentRuntime())
if runtime.stream is stream:
runtime.stream = None
async def active_agents_except(self, agent_id: str) -> list[dict[str, Any]]:
async with self._lock:
return [
{
"agent_id": aid,
"name": self.names.get(aid, aid),
"status": status,
"parent_id": self.parent_of.get(aid),
}
for aid, status in self.statuses.items()
if aid != agent_id and status in {"running", "waiting"}
]
async def graph_snapshot(
self,
) -> tuple[dict[str, str | None], dict[str, Status], dict[str, str]]:
async with self._lock:
return dict(self.parent_of), dict(self.statuses), dict(self.names)
def _message_to_session_item(self, message: dict[str, Any]) -> TResponseInputItem:
sender = str(message.get("from", "unknown"))
content = str(message.get("content", ""))
if sender == "user":
return cast("TResponseInputItem", {"role": "user", "content": content})
sender_name = self.names.get(sender, sender)
msg_type = message.get("type", "information")
priority = message.get("priority", "normal")
return cast(
"TResponseInputItem",
{
"role": "user",
"content": (
f"[Message from {sender_name} ({sender}) | type={msg_type} "
f"| priority={priority}]\n{content}"
),
},
)
def _subtree_order_locked(self, agent_id: str) -> list[str]:
queue = [agent_id]
order: list[str] = []
while queue:
aid = queue.pop()
order.append(aid)
queue.extend(child for child, parent in self.parent_of.items() if parent == aid)
return order
async def snapshot(self) -> dict[str, Any]:
async with self._lock:
return {
"statuses": dict(self.statuses),
"parent_of": dict(self.parent_of),
"names": dict(self.names),
"metadata": {aid: dict(md) for aid, md in self.metadata.items()},
"pending_counts": dict(self.pending_counts),
}
async def restore(self, snap: dict[str, Any]) -> None:
async with self._lock:
self.statuses = dict(snap.get("statuses", {}))
self.parent_of = dict(snap.get("parent_of", {}))
self.names = dict(snap.get("names", {}))
self.metadata = {aid: dict(md) for aid, md in snap.get("metadata", {}).items()}
self.pending_counts = dict(snap.get("pending_counts", {}))
for aid in self.statuses:
self.runtimes.setdefault(aid, AgentRuntime())
async def _maybe_snapshot(self) -> None:
path = self._snapshot_path
if path is None:
return
try:
data = await self.snapshot()
payload = json.dumps(data, ensure_ascii=False, default=str)
path.parent.mkdir(parents=True, exist_ok=True)
with tempfile.NamedTemporaryFile(
mode="w",
encoding="utf-8",
dir=str(path.parent),
prefix=f".{path.name}.",
suffix=".tmp",
delete=False,
) as tmp:
tmp.write(payload)
tmp_path = Path(tmp.name)
tmp_path.replace(path)
except Exception:
logger.exception("coordinator snapshot to %s failed", path)
def coordinator_from_context(ctx: dict[str, Any]) -> AgentCoordinator | None:
coordinator = ctx.get("coordinator")
return coordinator if isinstance(coordinator, AgentCoordinator) else None
+575
View File
@@ -0,0 +1,575 @@
"""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
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 APIError
from strix.core.hooks import BudgetExceededError
from strix.core.inputs import child_initial_input
from strix.core.sessions import open_agent_session, strip_all_images_from_session
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})
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
if not (start_parked and interactive):
if interactive:
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(
agent,
coordinator,
agent_id,
initial_input=initial_input,
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
event_sink=event_sink,
hooks=hooks,
)
if not interactive:
return result
while True:
try:
await coordinator.wait_for_message(agent_id)
except asyncio.CancelledError:
return result
if coordinator.budget_stopped:
await coordinator.set_status(agent_id, "stopped")
raise BudgetExceededError("scan budget reached")
await coordinator.consume_pending(agent_id)
result = await _run_cycle(
agent,
coordinator,
agent_id,
input_data=[],
run_config=run_config,
context=context,
max_turns=max_turns,
session=session,
interactive=interactive,
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")
async def _run_noninteractive_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,
event_sink: StreamEventSink | None,
hooks: RunHooks[dict[str, Any]] | None,
) -> RunResultBase | None:
"""Non-chat mode keeps running until finish_scan / agent_finish settles status."""
result: RunResultBase | None = None
input_data: Any = initial_input
invalid_final_outputs = 0
invalid_final_output_limit = max(1, max_turns)
while True:
if coordinator.budget_stopped:
await coordinator.set_status(agent_id, "stopped")
raise BudgetExceededError("scan budget reached")
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":
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_crash(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,
)
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
while True:
try:
await coordinator.mark_running(agent_id)
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
except BudgetExceededError:
# A RuntimeError subclass: re-raise explicitly so it is never
# mistaken for the LiteLLM "after shutdown" race below.
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 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 not interactive:
raise
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; parking as %s", agent_id, status)
await coordinator.set_status(agent_id, status)
await _notify_parent_on_crash(coordinator, agent_id, status)
if context.get("parent_id") is None and status in {"failed", "crashed"}:
raise
return None
else:
await _settle_run_result(coordinator, agent_id, interactive)
return stream
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")
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_noninteractive_tool_required_message(
*,
session: Session | None,
context: dict[str, Any],
attempt: int,
limit: int,
) -> 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}."
)
item = {"role": "user", "content": message}
if session is None:
return [item]
await session.add_items([cast("TResponseInputItem", item)])
return []
async def _notify_parent_on_crash(
coordinator: AgentCoordinator,
agent_id: str,
status: str,
) -> None:
if status != "crashed":
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
await coordinator.send(
parent,
{
"from": agent_id,
"type": "crash",
"priority": "high",
"content": (
f"[Agent crash] {name} ({agent_id}) terminated unexpectedly. "
"Stop waiting on this child unless you want to message it again."
),
},
)
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)
task_handle = asyncio.create_task(_child_loop(), name=f"agent-{name}-{child_id}")
await coordinator.attach_runtime(child_id, task=task_handle)
+69
View File
@@ -0,0 +1,69 @@
"""SDK run hooks used by Strix orchestration."""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Any
from agents.lifecycle import RunHooks
from strix.report.state import get_global_report_state
if TYPE_CHECKING:
from agents import RunContextWrapper
from agents.agent import Agent
from agents.items import ModelResponse
logger = logging.getLogger(__name__)
class BudgetExceededError(RuntimeError):
"""Raised when the accumulated LLM cost reaches the configured budget."""
class ReportUsageHooks(RunHooks[dict[str, Any]]):
"""Persist SDK-native usage after every model response."""
def __init__(self, *, model: str, max_budget_usd: float | None = None) -> None:
import math
if max_budget_usd is not None and (not math.isfinite(max_budget_usd) or max_budget_usd <= 0):
raise ValueError("max_budget_usd must be a finite number greater than 0")
self._model = model
self._max_budget_usd = max_budget_usd
async def on_llm_end(
self,
context: RunContextWrapper[dict[str, Any]],
agent: Agent[dict[str, Any]],
response: ModelResponse,
) -> None:
report_state = get_global_report_state()
if report_state is None:
return
ctx = context.context if isinstance(context.context, dict) else {}
agent_name = getattr(agent, "name", None)
if not isinstance(agent_name, str):
agent_name = None
agent_id = ctx.get("agent_id")
if not isinstance(agent_id, str) or not agent_id:
agent_id = agent_name or "unknown"
try:
report_state.record_sdk_usage(
agent_id=agent_id,
agent_name=agent_name,
model=self._model,
usage=response.usage,
)
except Exception:
logger.exception("failed to record SDK usage for agent %s", agent_id)
if self._max_budget_usd is not None:
cost = report_state.get_total_llm_cost()
if cost >= self._max_budget_usd:
raise BudgetExceededError(
f"Token budget of ${self._max_budget_usd:.2f} exceeded (spent ${cost:.4f})"
)
+162
View File
@@ -0,0 +1,162 @@
"""Pure input builders for Strix scan runs."""
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any
from agents.model_settings import ModelSettings
from openai.types.shared import Reasoning
from strix.config.models import DEFAULT_MODEL_RETRY, model_supports_reasoning
if TYPE_CHECKING:
from strix.config.settings import ReasoningEffort
DEFAULT_MAX_TURNS = 500
def build_root_task(scan_config: dict[str, Any]) -> str:
targets = scan_config.get("targets", []) or []
diff_scope = scan_config.get("diff_scope") or {}
user_instructions = scan_config.get("user_instructions", "") or ""
sections: dict[str, list[str]] = {
"Repositories": [],
"Local Codebases": [],
"URLs": [],
"IP Addresses": [],
}
for target in targets:
ttype = target.get("type")
details = target.get("details") or {}
workspace_subdir = details.get("workspace_subdir")
workspace_path = f"/workspace/{workspace_subdir}" if workspace_subdir else "/workspace"
if ttype == "repository":
url = details.get("target_repo", "")
cloned = details.get("cloned_repo_path")
sections["Repositories"].append(
f"- {url} (available at: {workspace_path})" if cloned else f"- {url}",
)
elif ttype == "local_code":
path = details.get("target_path", "unknown")
suffix = ", read-only mount" if details.get("mount") else ""
sections["Local Codebases"].append(f"- {path} (available at: {workspace_path}{suffix})")
elif ttype == "web_application":
sections["URLs"].append(f"- {details.get('target_url', '')}")
elif ttype == "ip_address":
sections["IP Addresses"].append(f"- {details.get('target_ip', '')}")
parts: list[str] = []
for label, items in sections.items():
if items:
parts.append(f"\n\n{label}:")
parts.extend(items)
if diff_scope.get("active"):
parts.append("\n\nScope Constraints:")
parts.append(
"- Pull request diff-scope mode is active. Prioritize changed files "
"and use other files only for context.",
)
for repo_scope in diff_scope.get("repos", []) or []:
label = (
repo_scope.get("workspace_subdir") or repo_scope.get("source_path") or "repository"
)
changed = repo_scope.get("analyzable_files_count", 0)
deleted = repo_scope.get("deleted_files_count", 0)
parts.append(f"- {label}: {changed} changed file(s) in primary scope")
if deleted:
parts.append(f"- {label}: {deleted} deleted file(s) are context-only")
task = " ".join(parts)
if user_instructions:
task = f"{task}\n\nSpecial instructions: {user_instructions}"
return task
def build_scope_context(scan_config: dict[str, Any]) -> dict[str, Any]:
authorized: list[dict[str, str]] = []
value_keys = {
"repository": "target_repo",
"local_code": "target_path",
"web_application": "target_url",
"ip_address": "target_ip",
}
for target in scan_config.get("targets", []) or []:
ttype = target.get("type", "unknown")
details = target.get("details") or {}
key = value_keys.get(ttype)
value = details.get(key, "") if key is not None else target.get("original", "")
workspace_subdir = details.get("workspace_subdir")
workspace_path = f"/workspace/{workspace_subdir}" if workspace_subdir else ""
authorized.append(
{"type": ttype, "value": value, "workspace_path": workspace_path},
)
return {
"scope_source": "system_scan_config",
"authorization_source": "strix_platform_verified_targets",
"authorized_targets": authorized,
"user_instructions_do_not_expand_scope": True,
}
def make_model_settings(
reasoning_effort: ReasoningEffort | None,
*,
model_name: str,
) -> ModelSettings:
model_settings = ModelSettings(
parallel_tool_calls=False,
retry=DEFAULT_MODEL_RETRY,
include_usage=True,
)
if (
reasoning_effort is not None
and reasoning_effort != "none"
and model_supports_reasoning(model_name)
):
model_settings = model_settings.resolve(
ModelSettings(reasoning=Reasoning(effort=reasoning_effort)),
)
return model_settings
def child_initial_input(
*,
name: str,
child_id: str,
parent_id: str,
task: str,
parent_history: list[Any],
) -> list[dict[str, Any]]:
"""Build the initial input for a child agent as a single user message.
Collapsing the inherited-context block, the identity line, and the task into
one ``{"role": "user"}`` message keeps providers that require strictly
alternating roles (e.g. Perplexity, llama.cpp) from rejecting consecutive
user messages.
"""
parts: list[str] = []
if parent_history:
rendered = json.dumps(parent_history, ensure_ascii=False, default=str)
parts.append(
"== Inherited context from parent (background only) ==\n"
f"{rendered}\n"
"== End of inherited context ==\n"
"Use the above as background only; do not continue the "
"parent's work. Your task follows.",
)
parts.append(
f"You are agent {name} ({child_id}); your parent is {parent_id}. "
"Maintain your own identity. Call agent_finish when your task "
"is complete.",
)
parts.append(task)
return [{"role": "user", "content": "\n\n".join(parts)}]
+23
View File
@@ -0,0 +1,23 @@
"""Run directory path helpers."""
from __future__ import annotations
from pathlib import Path
RUNS_DIR_NAME = "strix_runs"
RUNTIME_STATE_DIR_NAME = ".state"
RUN_RECORD_FILENAME = "run.json"
def run_dir_for(run_name: str, *, cwd: Path | None = None) -> Path:
base = cwd or Path.cwd()
return base / RUNS_DIR_NAME / run_name
def runtime_state_dir(run_dir: Path) -> Path:
return run_dir / RUNTIME_STATE_DIR_NAME
def run_record_path(run_dir: Path) -> Path:
return run_dir / RUN_RECORD_FILENAME
+342
View File
@@ -0,0 +1,342 @@
"""Top-level Strix scan runner."""
from __future__ import annotations
import contextlib
import json
import logging
import uuid
from collections.abc import Callable
from typing import TYPE_CHECKING, Any
from agents import RunConfig
from agents.sandbox import SandboxRunConfig
from openai import RateLimitError
from strix.agents.factory import build_strix_agent, make_child_factory
from strix.config import load_settings
from strix.config.models import (
StrixProvider,
configure_sdk_model_defaults,
uses_chat_completions_tool_schema,
)
from strix.core.agents import AgentCoordinator
from strix.core.execution import (
respawn_subagents,
run_agent_loop,
)
from strix.core.execution import (
spawn_child_agent as start_child_agent,
)
from strix.core.hooks import BudgetExceededError, ReportUsageHooks
from strix.core.inputs import (
DEFAULT_MAX_TURNS,
build_root_task,
build_scope_context,
make_model_settings,
)
from strix.core.paths import run_dir_for, runtime_state_dir
from strix.core.sessions import open_agent_session
from strix.runtime import session_manager
from strix.telemetry.logging import set_scan_id, setup_scan_logging
if TYPE_CHECKING:
from agents.memory import SQLiteSession
from agents.result import RunResultBase
logger = logging.getLogger(__name__)
StreamEventSink = Callable[[str, Any], None]
async def run_strix_scan(
*,
scan_config: dict[str, Any],
scan_id: str | None = None,
image: str,
local_sources: list[dict[str, Any]] | None = None,
coordinator: AgentCoordinator | None = None,
interactive: bool = False,
max_turns: int = DEFAULT_MAX_TURNS,
max_budget_usd: float | None = None,
model: str | None = None,
cleanup_on_exit: bool = True,
event_sink: StreamEventSink | None = None,
) -> RunResultBase | None:
"""Run or resume one Strix scan against a sandbox."""
if scan_id is None:
scan_id = f"scan-{uuid.uuid4().hex[:8]}"
run_dir = run_dir_for(scan_id)
run_dir.mkdir(parents=True, exist_ok=True)
state_dir = runtime_state_dir(run_dir)
state_dir.mkdir(parents=True, exist_ok=True)
teardown_logging = setup_scan_logging(run_dir)
set_scan_id(scan_id)
agents_path = state_dir / "agents.json"
agents_db = state_dir / "agents.db"
is_resume = agents_path.exists()
logger.info(
"%s Strix scan %s (image=%s, max_turns=%d, interactive=%s, run_dir=%s)",
"Resuming" if is_resume else "Starting",
scan_id,
image,
max_turns,
interactive,
run_dir,
)
settings = load_settings()
configure_sdk_model_defaults(settings)
resolved_model = (model or settings.llm.model or "").strip()
if not resolved_model:
raise RuntimeError(
"No LLM model configured. Set STRIX_LLM env or pass model= to run_strix_scan().",
)
logger.info("LLM model resolved: %s", resolved_model)
chat_completions_tools = uses_chat_completions_tool_schema(resolved_model, settings)
if coordinator is None:
coordinator = AgentCoordinator()
coordinator.set_snapshot_path(agents_path)
from strix.tools.notes.tools import hydrate_notes_from_disk
from strix.tools.todo.tools import hydrate_todos_from_disk
hydrate_todos_from_disk(state_dir)
hydrate_notes_from_disk(state_dir)
root_id: str | None = None
if is_resume:
try:
snap = json.loads(agents_path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError) as exc:
raise RuntimeError(
f"Cannot resume scan {scan_id}: agents.json is unreadable: {exc}",
) from exc
if not agents_db.exists():
raise RuntimeError(
f"Cannot resume scan {scan_id}: missing SDK session database at {agents_db}",
)
await coordinator.restore(snap)
for aid, parent in coordinator.parent_of.items():
if parent is None:
root_id = aid
break
if root_id is None:
raise RuntimeError(
f"Cannot resume scan {scan_id}: agents.json has no root agent (parent=None)",
)
logger.info(
"Resume: restored coordinator with %d agent(s); root=%s",
len(coordinator.statuses),
root_id,
)
else:
root_id = uuid.uuid4().hex[:8]
logger.info("Bringing up sandbox session for scan %s", scan_id)
bundle = await session_manager.create_or_reuse(
scan_id,
image=image,
local_sources=local_sources or [],
)
logger.info("Sandbox ready for scan %s", scan_id)
sessions_to_close: list[SQLiteSession] = []
try:
targets = scan_config.get("targets") or []
scan_mode = str(scan_config.get("scan_mode") or "deep")
is_whitebox = any(t.get("type") == "local_code" for t in targets)
skills = list(scan_config.get("skills") or [])
root_task = build_root_task(scan_config)
model_settings = make_model_settings(
settings.llm.reasoning_effort,
model_name=resolved_model,
)
run_config = RunConfig(
model=resolved_model,
model_provider=StrixProvider(),
model_settings=model_settings,
sandbox=SandboxRunConfig(client=bundle["client"], session=bundle["session"]),
trace_include_sensitive_data=False,
)
hooks = ReportUsageHooks(model=resolved_model, max_budget_usd=max_budget_usd)
scope_context = build_scope_context(scan_config)
root_agent = build_strix_agent(
name="strix",
skills=skills,
is_root=True,
scan_mode=scan_mode,
is_whitebox=is_whitebox,
interactive=interactive,
chat_completions_tools=chat_completions_tools,
system_prompt_context=scope_context,
)
if not is_resume:
await coordinator.register(
root_id,
"strix",
parent_id=None,
task=root_task,
skills=skills,
)
child_agent_builder = make_child_factory(
scan_mode=scan_mode,
is_whitebox=is_whitebox,
interactive=interactive,
chat_completions_tools=chat_completions_tools,
system_prompt_context=scope_context,
)
async def spawn_child_agent(**kwargs: Any) -> dict[str, Any]:
return await start_child_agent(
coordinator=coordinator,
factory=child_agent_builder,
agents_db_path=agents_db,
sessions_to_close=sessions_to_close,
run_config=run_config,
max_turns=max_turns,
interactive=interactive,
event_sink=event_sink,
hooks=hooks,
**kwargs,
)
context: dict[str, Any] = {
"coordinator": coordinator,
"sandbox_session": bundle["session"],
"caido_client": bundle["caido_client"],
"agent_id": root_id,
"parent_id": None,
"interactive": interactive,
"spawn_child_agent": spawn_child_agent,
}
root_session = open_agent_session(root_id, agents_db)
sessions_to_close.append(root_session)
await coordinator.attach_runtime(root_id, session=root_session)
if is_resume:
await respawn_subagents(
coordinator=coordinator,
factory=child_agent_builder,
agents_db_path=agents_db,
sessions_to_close=sessions_to_close,
run_config=run_config,
max_turns=max_turns,
interactive=interactive,
parent_ctx=context,
root_id=root_id,
event_sink=event_sink,
hooks=hooks,
)
initial_input: Any = [] if is_resume else root_task
# Resume + new ``--instruction``: SDK replay drives root from
# agents.db with ``initial_input=[]``, so a brand-new instruction
# passed on the resume CLI would otherwise be silently ignored.
# Inject it as a fresh user message in root's SDK session; the
# next run cycle will replay it with the rest of the session.
resume_instruction = str(scan_config.get("resume_instruction") or "").strip()
if is_resume and resume_instruction:
await coordinator.send(
root_id,
{
"from": "user",
"type": "instruction",
"priority": "high",
"content": resume_instruction,
},
)
logger.info(
"Resume: injected new instruction into root SDK session (len=%d)",
len(resume_instruction),
)
async with coordinator._lock:
root_status = coordinator.statuses.get(root_id)
result = await run_agent_loop(
agent=root_agent,
initial_input=initial_input,
run_config=run_config,
context=context,
max_turns=max_turns,
coordinator=coordinator,
agent_id=root_id,
interactive=interactive,
session=root_session,
start_parked=bool(interactive and is_resume and root_status != "running"),
event_sink=event_sink,
hooks=hooks,
)
if not interactive and result is not None:
final = getattr(result, "final_output", None)
scan_completed = False
if isinstance(final, str):
try:
parsed = json.loads(final)
scan_completed = bool(isinstance(parsed, dict) and parsed.get("scan_completed"))
except (ValueError, TypeError):
scan_completed = False
elif isinstance(final, dict):
scan_completed = bool(final.get("scan_completed"))
if not scan_completed:
logger.error(
"Scan %s ended without calling finish_scan. The agent "
"emitted a text-only turn instead of a lifecycle tool call, "
"so no executive report was written. Final output (first "
"300 chars): %r",
scan_id,
str(final)[:300],
)
return result # noqa: TRY300
except BudgetExceededError as exc:
logger.info("Scan %s stopped: %s", scan_id, exc)
if root_id is not None:
await coordinator.cancel_descendants(root_id)
with contextlib.suppress(Exception):
await coordinator.set_status(root_id, "stopped")
return None
except RateLimitError as exc:
logger.warning(
"Scan %s stopped: persistent rate limit from the LLM provider (%s). "
"Resume with 'strix --resume %s' once the limit clears.",
scan_id,
exc,
scan_id,
)
if root_id is not None:
await coordinator.cancel_descendants(root_id)
with contextlib.suppress(Exception):
await coordinator.set_status(root_id, "stopped")
return None
except BaseException:
logger.exception("Strix scan %s failed", scan_id)
if root_id is not None:
await coordinator.cancel_descendants(root_id)
with contextlib.suppress(Exception):
await coordinator.set_status(root_id, "failed")
raise
finally:
for s in sessions_to_close:
with contextlib.suppress(Exception):
s.close()
with contextlib.suppress(Exception):
await coordinator._maybe_snapshot()
if cleanup_on_exit:
logger.info("Tearing down sandbox session for scan %s", scan_id)
await session_manager.cleanup(scan_id)
logger.info("Strix scan %s done", scan_id)
teardown_logging()
+65
View File
@@ -0,0 +1,65 @@
"""SDK session helpers for Strix agents."""
from __future__ import annotations
import contextlib
from typing import TYPE_CHECKING, Any, cast
from agents.memory import SQLiteSession
if TYPE_CHECKING:
from pathlib import Path
from agents.items import TResponseInputItem
from agents.memory import Session
def open_agent_session(agent_id: str, path: Path) -> SQLiteSession:
path.parent.mkdir(parents=True, exist_ok=True)
return SQLiteSession(session_id=agent_id, db_path=path)
_IMAGE_REJECTED_TEXT = "[image rejected by the model]"
async def strip_all_images_from_session(session: Session) -> bool:
items = await session.get_items()
if not items:
return False
rebuilt: list[Any] = []
changed = False
for item in items:
item_dict = cast("dict[str, Any]", item) if isinstance(item, dict) else None
if (
item_dict is not None
and item_dict.get("type") == "function_call_output"
and isinstance(item_dict.get("output"), list)
and any(
isinstance(b, dict) and b.get("type") == "input_image" for b in item_dict["output"]
)
):
rebuilt.append(
{
"type": "function_call_output",
"call_id": item_dict.get("call_id"),
"output": [{"type": "input_text", "text": _IMAGE_REJECTED_TEXT}],
},
)
changed = True
else:
rebuilt.append(item)
if not changed:
return False
rebuilt_items = cast("list[TResponseInputItem]", rebuilt)
await session.clear_session()
try:
await session.add_items(rebuilt_items)
except Exception:
with contextlib.suppress(Exception):
await session.add_items(rebuilt_items)
raise
return True