Files
strix/strix/orchestration/hooks.py
T
0xallamandClaude Opus 4.7 5253332906 fix(telemetry): capture tool args in tool_executions for TUI renderers
The 19 tool renderers under strix/interface/tool_components/ all read
tool_data.get("args", {}) to render meaningful previews (URLs, methods,
note titles, vuln severities, etc.). After the SDK migration,
tracer.log_tool_start was only recording tool_name — every renderer
silently fell back to its empty-args path and the TUI lost its
per-call context.

Pull args from the SDK-native ToolContext (tool_input when parsed,
otherwise json-decode tool_arguments) and stash them on the
tool_executions entry. log_tool_start now takes an optional args dict;
existing callers pass nothing and get the empty-dict default.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-25 18:08:36 -07:00

267 lines
10 KiB
Python

"""``StrixOrchestrationHooks`` — RunHooks wiring bus + tracer + warnings."""
from __future__ import annotations
import json
import logging
from datetime import UTC, datetime
from typing import Any
from agents.items import ModelResponse
from agents.lifecycle import RunHooks
from agents.run_context import AgentHookContext, RunContextWrapper
from agents.tool_context import ToolContext
logger = logging.getLogger(__name__)
class StrixOrchestrationHooks(RunHooks[Any]):
"""Lifecycle hooks for Strix multi-agent runs.
Wires three concerns:
1. Turn-budget warnings injected into ``input_items`` at 85% and
``N - 3`` of ``max_turns``.
2. LLM usage recording into the bus + tracer, plus mirroring the
bus's agent tree into ``tracer.agents`` for the TUI.
3. Subagent crash detection: if ``on_agent_end`` fires without
``agent_finish_called`` being set, posts a crash message to the
parent's inbox so the parent learns on its next turn instead of
waiting forever.
"""
async def on_llm_start(
self,
context: RunContextWrapper[Any],
agent: Any,
system_prompt: str | None,
input_items: list[Any],
) -> None:
del agent, system_prompt
try:
ctx = context.context
if not isinstance(ctx, dict):
return
bus = ctx.get("bus")
agent_id = ctx.get("agent_id")
if bus is None or agent_id is None:
return
stats = bus.stats_live.get(agent_id)
if stats is None:
return
max_turns = int(ctx.get("max_turns", 300))
cur = int(stats.get("calls", 0))
if max_turns < 4:
return
# Once-flags live alongside ``calls`` on ``bus.stats_live`` so the
# warnings fire exactly once per agent lifetime — surviving
# ``run_with_continuation`` cycles, mirroring legacy
# ``state.max_iterations_warning_sent``.
#
# The flags are mutated lock-free below. Safe because the SDK
# serializes ``on_llm_start`` per agent (one in-flight LLM call
# per ``Runner.run`` instance), so this hook is the sole writer
# to ``warned_85`` / ``warned_final`` for this agent_id.
# ``record_usage`` (which acquires the lock) only writes
# ``in`` / ``out`` / ``cached`` / ``calls`` — disjoint keys.
if cur >= int(max_turns * 0.85) and not stats.get("warned_85"):
stats["warned_85"] = True
input_items.append(
{
"role": "user",
"content": (
"[System warning] You are at 85% of your iteration "
"budget. Begin consolidating findings."
),
},
)
if cur >= max_turns - 3 and not stats.get("warned_final"):
stats["warned_final"] = True
input_items.append(
{
"role": "user",
"content": (
"[System warning] You have 3 iterations left. Your "
"next tool call MUST be the finish tool."
),
},
)
except Exception:
logger.exception("on_llm_start failed")
async def on_llm_end(
self,
context: RunContextWrapper[Any],
agent: Any,
response: ModelResponse,
) -> None:
del agent
try:
ctx = context.context
if not isinstance(ctx, dict):
return
usage = getattr(response, "usage", None)
agent_id = ctx.get("agent_id")
bus = ctx.get("bus")
if bus is not None and agent_id is not None:
await bus.record_usage(agent_id, usage)
tracer = ctx.get("tracer")
if tracer is not None and usage is not None and hasattr(tracer, "record_llm_usage"):
cached = 0
details = getattr(usage, "input_tokens_details", None)
if details is not None:
cached = int(getattr(details, "cached_tokens", 0) or 0)
tracer.record_llm_usage(
input_tokens=int(getattr(usage, "input_tokens", 0) or 0),
output_tokens=int(getattr(usage, "output_tokens", 0) or 0),
cached_tokens=cached,
)
except Exception:
logger.exception("on_llm_end failed")
async def on_agent_start(
self,
context: AgentHookContext[Any],
agent: Any,
) -> None:
# The TUI reads ``tracer.agents`` to render the agent tree;
# mirror the bus state into the tracer here so the tree
# populates as agents come online.
del agent
try:
ctx = context.context
if not isinstance(ctx, dict):
return
tracer = ctx.get("tracer")
bus = ctx.get("bus")
me = ctx.get("agent_id")
if tracer is None or bus is None or me is None:
return
now = datetime.now(UTC).isoformat()
tracer.agents.setdefault(
me,
{
"id": me,
"name": bus.names.get(me, me),
"parent_id": bus.parent_of.get(me),
"status": bus.statuses.get(me, "running"),
"created_at": now,
"updated_at": now,
},
)
except Exception:
logger.exception("on_agent_start failed")
async def on_agent_end(
self,
context: AgentHookContext[Any],
agent: Any,
output: Any,
) -> None:
try:
ctx = context.context
if not isinstance(ctx, dict):
return
bus = ctx.get("bus")
me = ctx.get("agent_id")
if bus is None or me is None:
return
crashed = (output is None) or not ctx.get("agent_finish_called", False)
# Interactive agents (root and children) stay alive across
# ``Runner.run`` cycles — ``run_with_continuation`` re-invokes
# ``Runner.run`` whenever the agent receives a follow-up
# message, so we just park (status=waiting) instead of
# finalizing. Crashed runs always finalize so the parent
# learns to stop waiting.
stays_alive = bool(ctx.get("interactive", False)) and not crashed
final_status = "waiting" if stays_alive else ("crashed" if crashed else "completed")
tracer = ctx.get("tracer")
if tracer is not None and me in tracer.agents:
tracer.agents[me]["status"] = final_status
tracer.agents[me]["updated_at"] = datetime.now(UTC).isoformat()
parent = bus.parent_of.get(me)
if crashed and parent is not None:
await bus.send(
parent,
{
"from": me,
"content": (
f"[Agent crash] {bus.names.get(me, me)} ({me}) "
f"terminated without calling agent_finish. "
f"Stop waiting on this child."
),
"type": "crash",
},
)
if stays_alive:
await bus.park(me)
# Reset the finish flag so the next cycle can detect its own
# finish-tool call. The lifetime turn counter and warning
# flags live on ``bus.stats_live`` and persist across cycles.
ctx["agent_finish_called"] = False
else:
await bus.finalize(me, final_status)
except Exception:
logger.exception("on_agent_end failed")
async def on_tool_start(
self,
context: RunContextWrapper[Any],
agent: Any,
tool: Any,
) -> None:
del agent
try:
ctx = context.context
if not isinstance(ctx, dict):
return
tracer = ctx.get("tracer")
if tracer is None:
return
# ``context`` is a ``ToolContext`` for function-tool calls (per the
# SDK ``RunHooks.on_tool_start`` docstring) — that's where the
# per-call args live. ``tool_input`` is the parsed dict when the
# SDK has it; otherwise parse ``tool_arguments`` (raw JSON).
args: dict[str, Any] = {}
if isinstance(context, ToolContext):
tool_input = context.tool_input
if isinstance(tool_input, dict):
args = tool_input
else:
raw = context.tool_arguments
if raw:
try:
parsed = json.loads(raw)
except (ValueError, TypeError):
parsed = None
if isinstance(parsed, dict):
args = parsed
tracer.log_tool_start(ctx.get("agent_id", "?"), tool.name, args)
except Exception:
logger.exception("on_tool_start failed")
async def on_tool_end(
self,
context: RunContextWrapper[Any],
agent: Any,
tool: Any,
result: str,
) -> None:
del agent
try:
ctx = context.context
if not isinstance(ctx, dict):
return
if tool.name in ("agent_finish", "finish_scan"):
ctx["agent_finish_called"] = True
tracer = ctx.get("tracer")
if tracer is not None:
tracer.log_tool_end(ctx.get("agent_id", "?"), tool.name, result)
except Exception:
logger.exception("on_tool_end failed")