c6136d946f
Behavior-neutral extraction of the 686-LOC concurrent executor and the 429-LOC sequential executor into focused helpers: - _ConcurrentBatch (run_worker / submit_all / await_completion / run) and _StartOrderGate replace the nested closures + nonlocal counters; _ToolOutcome replaces the 7-tuple result slots; _ParsedCall/_parse_tool_call replaces the 6-tuple parsed-call rows in both executors (-> 2 sites). - _append_skipped_tool_results unifies the four cancelled/skipped-result loops (concurrent pre-flight, sequential pre-tool interrupt, sequential KeyboardInterrupt, sequential post-tool interrupt) -> 4 sites; absorbs _append_cancelled_tool_results. - _observe_tool_result / _commit_tool_result / _finalize_tool_batch / _print_tool_completed / _tool_progress_enabled unify the post-execution guardrail-observe -> append+flush -> tool.completed -> budget -> /steer tail shared by the concurrent, sequential and segmented paths (-> 2-3 sites each). - _unfinished_tool_result, _blocked_tool_result, _abandoned_sequential_result collapse the duplicated synthesize-result + terminal post_tool_call blocks. - _registered_tool_worker / _interrupt_worker_tids unify worker tid tracking and interrupt fan-out between the two middleware runners (-> 2 / 3 sites). - _run_with_activity_heartbeat extracts the heartbeat thread wrapper. - _resolve_sequential_dispatch + _SequentialDispatch turn the 5-branch inline/delegate/context-engine/memory/registry if/elif into a resolver with per-branch spinner/error/KeyboardInterrupt policy, preserving branch order. - _cancelled_tool_result and _managed_values inlined (single caller each). Public signatures (execute_tool_calls_concurrent/sequential/segmented, both middleware runners, every symbol imported by run_agent.py/agent/tests) are unchanged; middleware/hook/persistence/progress-callback order is identical.
2366 lines
92 KiB
Python
2366 lines
92 KiB
Python
"""Tool-call execution: sequential and concurrent dispatch, extracted from AIAgent.
|
||
|
||
Functions take the parent ``AIAgent`` first; ``run_agent`` keeps thin wrappers, and
|
||
tests that patch ``run_agent._set_interrupt`` still work because we reach it via ``_ra()``.
|
||
"""
|
||
|
||
from __future__ import annotations
|
||
|
||
import concurrent.futures
|
||
import contextlib
|
||
import json
|
||
from pathlib import Path
|
||
import logging
|
||
import os
|
||
import random
|
||
import threading
|
||
import time
|
||
from dataclasses import dataclass
|
||
from typing import Any, Callable, Optional
|
||
|
||
from agent.display import (
|
||
KawaiiSpinner,
|
||
build_tool_preview as _build_tool_preview,
|
||
build_tool_label as _build_tool_label,
|
||
get_cute_tool_message as _get_cute_tool_message_impl,
|
||
get_tool_emoji as _get_tool_emoji,
|
||
redact_tool_args_for_display as _redact_tool_args_for_display,
|
||
_detect_tool_failure,
|
||
)
|
||
from agent.message_sanitization import coalesce_tool_call_id
|
||
from agent.inline_tool_executors import (
|
||
INLINE_TOOL_EXECUTORS,
|
||
InlineToolContext,
|
||
emit_terminal_post_tool_call,
|
||
tool_hook_ids,
|
||
)
|
||
from agent.tool_dispatch_helpers import (
|
||
_NEVER_PARALLEL_TOOLS,
|
||
_is_destructive_command,
|
||
_is_multimodal_tool_result,
|
||
_multimodal_text_summary,
|
||
_append_subdir_hint_to_multimodal,
|
||
_plan_tool_batch_segments,
|
||
make_tool_result_message,
|
||
)
|
||
from tools.terminal_tool import (
|
||
get_active_env,
|
||
)
|
||
from tools.thread_context import propagate_context_to_thread
|
||
from tools.tool_result_storage import (
|
||
maybe_persist_tool_result,
|
||
enforce_turn_budget,
|
||
extract_persisted_path,
|
||
)
|
||
from tools.budget_config import BudgetConfig, DEFAULT_BUDGET, budget_for_context_window
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
|
||
def _pairing_tool_call_id(tool_call: Any) -> str:
|
||
"""Return the canonical id used by the persisted assistant message."""
|
||
return coalesce_tool_call_id(tool_call)
|
||
|
||
|
||
def _tc_name(tool_call: Any) -> str:
|
||
return getattr(getattr(tool_call, "function", None), "name", "") or "tool"
|
||
|
||
|
||
def _record_persisted_path_for_stub(agent, tool_call_id: str, function_result) -> None:
|
||
"""Record the spillover file path so a later result-reference stub can't dangle.
|
||
|
||
Best-effort: bookkeeping never breaks tool execution.
|
||
"""
|
||
try:
|
||
if not isinstance(function_result, str):
|
||
return
|
||
path = extract_persisted_path(function_result)
|
||
if path:
|
||
agent._tool_guardrails.record_persisted_result(tool_call_id, path)
|
||
except Exception as exc:
|
||
logger.debug("persisted-path record for result stub failed: %s", exc)
|
||
|
||
|
||
def _ensure_file_checkpoint(
|
||
agent,
|
||
function_name: str,
|
||
function_args: dict,
|
||
effective_task_id: str,
|
||
) -> None:
|
||
"""Checkpoint the same workspace path that the file tool will mutate."""
|
||
file_path = function_args.get("path", "")
|
||
if not file_path:
|
||
return
|
||
|
||
# File tools resolve relative paths against the task's live cwd (differs from the
|
||
# process cwd in Docker); resolve the same way before locating the project root.
|
||
from tools.file_tools import _resolve_path_for_task
|
||
|
||
resolved_path = _resolve_path_for_task(file_path, effective_task_id or "default")
|
||
work_dir = agent._checkpoint_mgr.get_working_dir_for_path(str(resolved_path))
|
||
agent._checkpoint_mgr.ensure_checkpoint(work_dir, f"before {function_name}")
|
||
|
||
|
||
def _budget_for_agent(agent) -> BudgetConfig:
|
||
"""Resolve a tool-result BudgetConfig scaled to the agent's context window.
|
||
|
||
Small-context models get a proportional budget so one large result can't overflow
|
||
the request (#23767); falls back to the default when context length is unknown.
|
||
"""
|
||
try:
|
||
ctx = getattr(getattr(agent, "context_compressor", None), "context_length", None)
|
||
# budget_for_context_window(None), not DEFAULT_BUDGET, so the MCP threshold
|
||
# override still applies when the context length isn't resolvable.
|
||
return budget_for_context_window(int(ctx) if ctx else None)
|
||
except Exception:
|
||
return DEFAULT_BUDGET
|
||
|
||
# Maximum number of concurrent worker threads for parallel tool execution.
|
||
_MAX_TOOL_WORKERS = 8
|
||
_DEFAULT_IMAGE_PARALLEL_REQUESTS = 4
|
||
# Generous ceiling for slow-but-valid tool work (large page fetches, slow
|
||
# remote backends) so the batch guard does not preempt a legitimate attempt.
|
||
_DEFAULT_CONCURRENT_TOOL_TIMEOUT_S = 420.0
|
||
# Start-order gate wait bound: long enough for an approval round-trip, short enough
|
||
# that one wedged dispatch cannot starve the batch.
|
||
_START_ORDER_GATE_TIMEOUT_S = 120.0
|
||
# Fallback authorization-gate lock bound; the effective bound derives from
|
||
# approvals.timeout (see _authorization_gate_lock_timeout) since overstaying it means wedged.
|
||
_AUTHORIZATION_GATE_LOCK_TIMEOUT_S = 360.0
|
||
|
||
|
||
def _authorization_gate_lock_timeout() -> float:
|
||
"""Bound for the authorization serialization lock: approval timeout + margin.
|
||
|
||
Delegates to ``tools.approval.human_wait_ceiling`` so the two bounds can't drift:
|
||
never break serialization while an approval prompt is answerable, but never let a
|
||
wedged holder park other workers forever (#79719). Resolved once per batch.
|
||
"""
|
||
try:
|
||
from tools.approval import human_wait_ceiling
|
||
|
||
# Safety-capped so a huge approvals.timeout can't overflow Lock.acquire (#83220);
|
||
# deliberately NOT min()'d with the fallback so the gate never gives up early (#79719).
|
||
return human_wait_ceiling()
|
||
except Exception:
|
||
return _AUTHORIZATION_GATE_LOCK_TIMEOUT_S
|
||
|
||
|
||
class _BatchAbandoned(BaseException):
|
||
"""Raised inside a worker when the batch was abandoned before dispatch.
|
||
|
||
BaseException so ``except Exception`` handlers in the middleware chain can't swallow it.
|
||
"""
|
||
|
||
|
||
def _parse_tool_arguments(raw_arguments: Any) -> tuple[dict, Optional[str]]:
|
||
"""Parse model-emitted arguments without repairing or coercing them."""
|
||
try:
|
||
arguments = json.loads(raw_arguments)
|
||
except (json.JSONDecodeError, TypeError):
|
||
arguments = None
|
||
if isinstance(arguments, dict):
|
||
return arguments, None
|
||
return {}, json.dumps(
|
||
{
|
||
"error": "Invalid tool arguments",
|
||
"message": (
|
||
"Tool arguments must be a valid JSON object; tool was not executed."
|
||
),
|
||
},
|
||
ensure_ascii=False,
|
||
)
|
||
|
||
|
||
def _resolve_concurrent_tool_timeout() -> float | None:
|
||
"""Resolve the per-batch concurrent tool deadline via the unified resolver (#85125).
|
||
|
||
``timeouts.tools.concurrent_batch`` wins; ``HERMES_CONCURRENT_TOOL_TIMEOUT_S`` is the
|
||
legacy bridge; ``0``/negative disables the bound.
|
||
"""
|
||
from agent.deadline import resolve_timeout
|
||
|
||
return resolve_timeout(
|
||
"tools.concurrent_batch",
|
||
default=_DEFAULT_CONCURRENT_TOOL_TIMEOUT_S,
|
||
env_var="HERMES_CONCURRENT_TOOL_TIMEOUT_S",
|
||
)
|
||
|
||
|
||
def _flush_session_db_after_tool_progress(
|
||
agent,
|
||
messages: list,
|
||
*,
|
||
stage: str,
|
||
) -> bool:
|
||
"""Flush tool-call progress to the session DB before projecting it to any UI.
|
||
|
||
Tool side effects can kill/restart the process before turn-end persistence runs.
|
||
"""
|
||
try:
|
||
persisted = agent._flush_messages_to_session_db(messages) is not False
|
||
if not persisted:
|
||
agent._incremental_persistence_failed = True
|
||
# Flush recorded any classified cause at the catch site; only default
|
||
# to 'unknown' when nothing more specific exists.
|
||
if getattr(agent, "_last_persistence_error_cause", None) is None:
|
||
agent._last_persistence_error_cause = "unknown"
|
||
return persisted
|
||
except Exception as exc:
|
||
agent._incremental_persistence_failed = True
|
||
from hermes_state import classify_persistence_error
|
||
agent._last_persistence_error_cause = classify_persistence_error(exc)
|
||
logger.warning("Incremental tool-call persistence failed after %s: %s", stage, exc)
|
||
return False
|
||
|
||
|
||
def _image_generate_parallel_limit() -> int:
|
||
"""Return the configured image-generation parallelism cap (conservative default;
|
||
backend bursts hit TTFB/rate-limit failures).
|
||
"""
|
||
try:
|
||
from hermes_cli.config import load_config
|
||
|
||
cfg = load_config() or {}
|
||
image_gen = cfg.get("image_gen") if isinstance(cfg, dict) else None
|
||
value = (
|
||
image_gen.get("max_parallel_requests")
|
||
if isinstance(image_gen, dict)
|
||
else None
|
||
)
|
||
except Exception:
|
||
value = None
|
||
|
||
try:
|
||
limit = int(value)
|
||
except (TypeError, ValueError):
|
||
limit = _DEFAULT_IMAGE_PARALLEL_REQUESTS
|
||
return max(1, min(limit, _MAX_TOOL_WORKERS))
|
||
|
||
|
||
def _max_workers_for_tool_batch(runnable_calls) -> int:
|
||
"""Return the worker cap for a concurrent tool batch."""
|
||
if not runnable_calls:
|
||
return 0
|
||
max_workers = _MAX_TOOL_WORKERS
|
||
if any(
|
||
(call[2] if len(call) >= 3 else None) == "image_generate"
|
||
for call in runnable_calls
|
||
):
|
||
max_workers = min(max_workers, _image_generate_parallel_limit())
|
||
return min(len(runnable_calls), max_workers)
|
||
|
||
|
||
def _ra():
|
||
"""Lazy reference to ``run_agent`` so patches like ``run_agent._set_interrupt`` work."""
|
||
import run_agent
|
||
return run_agent
|
||
|
||
|
||
def _is_interpreter_shutdown_submit_error(exc: RuntimeError) -> bool:
|
||
"""Shutdown-race predicate; delegates to ``tools.interpreter_shutdown`` so every site
|
||
recognizes both CPython shutdown-message variants (#55924/#58720).
|
||
"""
|
||
from tools.interpreter_shutdown import interpreter_shutting_down
|
||
|
||
return interpreter_shutting_down(exc)
|
||
|
||
|
||
_emit_terminal_post_tool_call = emit_terminal_post_tool_call
|
||
|
||
|
||
def _emit_cancelled_terminal_post_tool_call(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
start_time: float,
|
||
reason: str = "user interrupt",
|
||
error_type: str = "keyboard_interrupt",
|
||
middleware_trace: Optional[list[dict[str, Any]]] = None,
|
||
) -> str:
|
||
result = json.dumps(
|
||
{
|
||
"error": f"Tool execution cancelled by {reason}",
|
||
"status": "cancelled",
|
||
},
|
||
ensure_ascii=False,
|
||
)
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
result=result,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
duration_ms=int((time.time() - start_time) * 1000),
|
||
status="cancelled",
|
||
error_type=error_type,
|
||
error_message=f"Tool execution cancelled by {reason}",
|
||
middleware_trace=list(middleware_trace or []),
|
||
)
|
||
return result
|
||
|
||
|
||
def _append_skipped_tool_results(
|
||
agent,
|
||
messages: list,
|
||
tool_calls,
|
||
effective_task_id: str,
|
||
*,
|
||
content: str,
|
||
hook_error_type: Optional[str] = None,
|
||
hook_id: Optional[Callable[[Any], str]] = None,
|
||
flush_stage: Optional[str] = None,
|
||
stop_on_flush_failure: bool = True,
|
||
) -> bool:
|
||
"""Append one ``tool`` result per unstarted call so the assistant tool-call turn never
|
||
lacks matching results (role-alternation violation).
|
||
|
||
``content`` is formatted with ``{name}``. ``hook_error_type`` also emits the terminal
|
||
``post_tool_call`` (status=cancelled) per call, ``hook_id`` overriding the hook's id.
|
||
``flush_stage`` flushes the session DB after each append; returns False on the first
|
||
failed flush when ``stop_on_flush_failure`` (the caller must stop the batch).
|
||
"""
|
||
for tc in tool_calls:
|
||
name = _tc_name(tc)
|
||
result = content.format(name=name)
|
||
messages.append(make_tool_result_message(
|
||
name,
|
||
result,
|
||
_pairing_tool_call_id(tc),
|
||
effect_disposition="none",
|
||
))
|
||
if hook_error_type is not None:
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=name,
|
||
function_args={},
|
||
result=result,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=(hook_id or _pairing_tool_call_id)(tc),
|
||
status="cancelled",
|
||
error_type=hook_error_type,
|
||
error_message="Tool execution skipped due to user interrupt",
|
||
)
|
||
if flush_stage is not None:
|
||
flushed = _flush_session_db_after_tool_progress(
|
||
agent, messages, stage=f"{flush_stage} {name}"
|
||
)
|
||
if not flushed and stop_on_flush_failure:
|
||
return False
|
||
return True
|
||
|
||
|
||
def _tool_search_scoped_names(agent) -> frozenset:
|
||
"""Return the deferrable tool names the session may invoke via tool_call.
|
||
|
||
The Tool Search unwrap bypasses the bridge's scope check in
|
||
``model_tools.handle_function_call``, so restricted sessions are validated against
|
||
this set. Cached on the agent; refreshed when the registry generation changes.
|
||
"""
|
||
try:
|
||
import model_tools
|
||
from tools import tool_search as _ts
|
||
from tools.registry import registry as _registry
|
||
except Exception:
|
||
return frozenset()
|
||
|
||
enabled = getattr(agent, "enabled_toolsets", None)
|
||
disabled = getattr(agent, "disabled_toolsets", None)
|
||
cache_key = (
|
||
_registry.current_scope_key(),
|
||
getattr(_registry, "_generation", 0),
|
||
frozenset(enabled) if enabled is not None else None,
|
||
frozenset(disabled) if disabled is not None else None,
|
||
)
|
||
cached = getattr(agent, "_tool_search_scope_cache", None)
|
||
if cached is not None and cached[0] == cache_key:
|
||
return cached[1]
|
||
try:
|
||
scoped_defs = model_tools.get_tool_definitions(
|
||
enabled_toolsets=enabled,
|
||
disabled_toolsets=disabled,
|
||
quiet_mode=True,
|
||
skip_tool_search_assembly=True,
|
||
) or []
|
||
names = _ts.scoped_deferrable_names(scoped_defs)
|
||
except Exception:
|
||
names = frozenset()
|
||
try:
|
||
agent._tool_search_scope_cache = (cache_key, names)
|
||
except Exception:
|
||
pass
|
||
return names
|
||
|
||
|
||
def _canonical_tool_name(function_name: str) -> str:
|
||
"""Map legacy tool-name aliases (2026-08 renames) BEFORE agent-loop dispatch."""
|
||
from model_tools import _LEGACY_TOOL_ALIASES as _lta
|
||
|
||
return _lta.get(function_name, function_name)
|
||
|
||
|
||
def _unwrap_tool_search_call(
|
||
agent, function_name: str, function_args: dict, *, flatten_probe: bool = False
|
||
) -> tuple[str, dict, Optional[str]]:
|
||
"""Peel the ``tool_call`` bridge so downstream hooks see the underlying tool.
|
||
|
||
Checkpointing, guardrails, plugin hooks and the activity feed must observe the real
|
||
tool name, not the bridge. ``tool_call.function`` stays untouched for the transcript
|
||
and tool_call_id pairing. The unwrap bypasses
|
||
handle_function_call's scope check, so session toolset scope is enforced HERE.
|
||
Returns ``(name, args, scope_block)``; ``scope_block`` is the block message when
|
||
the underlying tool is out of scope or its args fail the deferred-schema probe
|
||
(``flatten_probe`` collapses the probe's JSON payload to one plain string for
|
||
callers that wrap the message in ``{"error": ...}``).
|
||
"""
|
||
scope_block: Optional[str] = None
|
||
try:
|
||
from tools import tool_search as _ts
|
||
if function_name == _ts.TOOL_CALL_NAME:
|
||
underlying, underlying_args, err = _ts.resolve_underlying_call(function_args)
|
||
if not err and underlying:
|
||
if underlying in _tool_search_scoped_names(agent):
|
||
# Validate before unwrapping: the generic bridge hides the concrete
|
||
# parameter schema from provider-native tool-call validation.
|
||
probe_err = _ts.validate_deferred_call_args(underlying, underlying_args)
|
||
if probe_err is None:
|
||
return underlying, underlying_args, None
|
||
scope_block = probe_err
|
||
if flatten_probe:
|
||
try:
|
||
probe = json.loads(probe_err)
|
||
scope_block = (
|
||
f"{probe.get('error', '')} Parameters schema: "
|
||
f"{json.dumps(probe.get('parameters', {}), ensure_ascii=False)}. "
|
||
f"{probe.get('hint', '')}"
|
||
).strip()
|
||
except Exception:
|
||
scope_block = probe_err
|
||
else:
|
||
scope_block = (
|
||
f"'{underlying}' is not available in this session. "
|
||
"Use tool_search to find tools you can call."
|
||
)
|
||
except Exception:
|
||
pass
|
||
return function_name, function_args, scope_block
|
||
|
||
|
||
@dataclass
|
||
class _ParsedCall:
|
||
"""One model tool call after alias canonicalization, arg parsing and bridge unwrap."""
|
||
|
||
tool_call: Any
|
||
name: str
|
||
args: dict
|
||
middleware_trace: list
|
||
parse_error: Optional[str]
|
||
scope_block: Optional[str]
|
||
|
||
|
||
def _parse_tool_call(agent, tool_call, *, flatten_probe: bool = False) -> _ParsedCall:
|
||
name = _canonical_tool_name(tool_call.function.name)
|
||
args, parse_error = _parse_tool_arguments(tool_call.function.arguments)
|
||
if parse_error is not None:
|
||
return _ParsedCall(tool_call, name, args, [], parse_error, None)
|
||
name, args, scope_block = _unwrap_tool_search_call(
|
||
agent, name, args, flatten_probe=flatten_probe
|
||
)
|
||
return _ParsedCall(tool_call, name, args, [], None, scope_block)
|
||
|
||
|
||
@dataclass
|
||
class _ManagedToolResult:
|
||
result: Any
|
||
args: dict[str, Any]
|
||
middleware_trace: list[dict[str, Any]]
|
||
blocked: bool
|
||
dispatched: bool
|
||
|
||
|
||
class _ToolTimeoutResult(str):
|
||
"""Marker for a synthesized sequential-tool timeout result."""
|
||
|
||
|
||
class _ToolCancelledResult(str):
|
||
"""Marker for a synthesized sequential-tool user-interrupt result.
|
||
|
||
The terminal post_tool_call event was already emitted (status=cancelled), so a
|
||
late-finishing abandoned worker must not report success.
|
||
"""
|
||
|
||
|
||
class _ConcurrentToolAuthorizationGate:
|
||
"""Serialize policy prompts and exclude human approval waits from batch deadlines.
|
||
|
||
The acquire is BOUNDED: on expiry the worker prompts unserialized rather than
|
||
starving the batch behind a wedged plugin/approval client (#79705).
|
||
|
||
Deadline exclusion is measured at the SOURCE of the human wait
|
||
(``tools.approval.human_wait_seconds``), NOT as gate residency: residency-based
|
||
exclusion let a wedged plugin keep the deadline from ever firing (#79719).
|
||
"""
|
||
|
||
def __init__(
|
||
self,
|
||
*,
|
||
lock_timeout: float | None = None,
|
||
session_key: str | None = None,
|
||
) -> None:
|
||
self._serialization_lock = threading.Lock()
|
||
self._lock_timeout = (
|
||
_authorization_gate_lock_timeout()
|
||
if lock_timeout is None
|
||
else lock_timeout
|
||
)
|
||
self._session_key = session_key
|
||
if self._session_key is None:
|
||
try:
|
||
from tools.approval import get_current_session_key
|
||
|
||
# Snapshot on the SUBMITTING thread: excluded_seconds() is polled
|
||
# from the batch wait loop, whose context may differ from workers'.
|
||
self._session_key = get_current_session_key()
|
||
except Exception:
|
||
logger.debug(
|
||
"authorization gate could not snapshot the session key; "
|
||
"human-wait exclusion will re-resolve it at poll time",
|
||
exc_info=True,
|
||
)
|
||
self._baseline_wait_seconds = self._human_wait_seconds()
|
||
|
||
def _human_wait_seconds(self) -> float:
|
||
try:
|
||
from tools.approval import human_wait_seconds
|
||
|
||
return human_wait_seconds(self._session_key)
|
||
except Exception:
|
||
return 0.0
|
||
|
||
def run(self, callback):
|
||
acquired = self._serialization_lock.acquire(timeout=self._lock_timeout)
|
||
if not acquired:
|
||
logger.warning(
|
||
"authorization gate lock not acquired after %.1fs "
|
||
"(holder wedged in a pre_tool_call plugin or approval "
|
||
"round-trip?); running prompt unserialized",
|
||
self._lock_timeout,
|
||
)
|
||
return callback()
|
||
try:
|
||
return callback()
|
||
finally:
|
||
self._serialization_lock.release()
|
||
|
||
def excluded_seconds(self) -> float:
|
||
"""Return human-approval wait seconds accrued since the batch started."""
|
||
return max(0.0, self._human_wait_seconds() - self._baseline_wait_seconds)
|
||
|
||
|
||
@contextlib.contextmanager
|
||
def _registered_tool_worker(agent):
|
||
"""Track this worker tid for interrupt fan-out (``AIAgent.interrupt()``).
|
||
|
||
On exit (including BaseException, which bypasses ``except Exception``) the tid is
|
||
discarded and its interrupt bit cleared so a recycled tid starts clean.
|
||
"""
|
||
tid = threading.current_thread().ident
|
||
with agent._tool_worker_threads_lock:
|
||
agent._tool_worker_threads.add(tid)
|
||
try:
|
||
yield tid
|
||
finally:
|
||
with agent._tool_worker_threads_lock:
|
||
agent._tool_worker_threads.discard(tid)
|
||
try:
|
||
_ra()._set_interrupt(False, tid)
|
||
except Exception:
|
||
pass
|
||
|
||
|
||
_NO_REASON = object()
|
||
|
||
|
||
def _interrupt_worker_tids(agent, tids, *, reason=_NO_REASON) -> None:
|
||
"""Raise the interrupt bit on each worker tid (best-effort, via ``run_agent``)."""
|
||
kwargs = {} if reason is _NO_REASON else {"reason": reason}
|
||
for tid in tids:
|
||
try:
|
||
_ra()._set_interrupt(True, tid, **kwargs)
|
||
except Exception:
|
||
pass
|
||
|
||
|
||
# Heartbeat cadence; must stay far below the gateway turn-inactivity timeout
|
||
# (default 1800s) so a silent-but-healthy tool never looks idle.
|
||
_TOOL_ACTIVITY_HEARTBEAT_INTERVAL_S = 30.0
|
||
|
||
|
||
def _run_tool_activity_heartbeat(
|
||
agent,
|
||
stop_event: threading.Event,
|
||
label: str,
|
||
interval: float = _TOOL_ACTIVITY_HEARTBEAT_INTERVAL_S,
|
||
) -> None:
|
||
"""Daemon thread that stamps ``agent._touch_activity`` every ``interval`` seconds
|
||
until ``stop_event`` is set.
|
||
|
||
Keeps the gateway turn-inactivity watchdog (default 30 min) from abandoning a turn
|
||
whose tool runs silently. Wedged tools stay bounded by the tool layer's own timeouts.
|
||
"""
|
||
|
||
try:
|
||
while not stop_event.wait(interval):
|
||
agent._touch_activity(label)
|
||
except Exception:
|
||
# A heartbeat must never break the agent loop.
|
||
pass
|
||
|
||
|
||
def _run_with_activity_heartbeat(agent, function_name: str, fn):
|
||
"""Run ``fn()`` with a heartbeat so the gateway inactivity watchdog doesn't abandon a
|
||
silent-but-live turn (#84491); covers both executor paths.
|
||
"""
|
||
stop = threading.Event()
|
||
thread = threading.Thread(
|
||
target=_run_tool_activity_heartbeat,
|
||
args=(agent, stop, f"tool running: {function_name}"),
|
||
kwargs={"interval": _TOOL_ACTIVITY_HEARTBEAT_INTERVAL_S},
|
||
daemon=True,
|
||
name=f"tool-activity-hb-{function_name[:24]}",
|
||
)
|
||
thread.start()
|
||
try:
|
||
return fn()
|
||
finally:
|
||
stop.set()
|
||
thread.join(timeout=2.0)
|
||
|
||
|
||
def _blocked_tool_result(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
final_args: dict,
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
block_message: Optional[str],
|
||
block_error_type: str,
|
||
guardrail_decision,
|
||
trace: list,
|
||
) -> str:
|
||
"""Synthesize the result for a call blocked by scope/plugin (``block_message``) or by
|
||
guardrail policy (``guardrail_decision``) and emit its terminal post_tool_call."""
|
||
if block_message is not None:
|
||
result = json.dumps({"error": block_message}, ensure_ascii=False)
|
||
error_type = block_error_type
|
||
error_message = block_message
|
||
else:
|
||
result = agent._guardrail_block_result(guardrail_decision)
|
||
error_type = "guardrail_block"
|
||
error_message = (
|
||
getattr(guardrail_decision, "message", None)
|
||
or "Tool blocked by guardrail policy"
|
||
)
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=final_args,
|
||
result=result,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
status="blocked",
|
||
error_type=error_type,
|
||
error_message=error_message,
|
||
middleware_trace=list(trace),
|
||
)
|
||
return result
|
||
|
||
|
||
def _run_agent_tool_execution_middleware(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
execute,
|
||
scope_block: str | None = None,
|
||
display_index: int | None = None,
|
||
middleware_trace: list[dict[str, Any]] | None = None,
|
||
begin_execution=None,
|
||
authorization_gate: _ConcurrentToolAuthorizationGate | None = None,
|
||
) -> _ManagedToolResult:
|
||
"""Run Relay rewrites before Hermes policy and dispatch exactly once."""
|
||
from agent import relay_tools
|
||
from hermes_cli.middleware import (
|
||
apply_tool_request_middleware,
|
||
run_tool_execution_middleware,
|
||
)
|
||
|
||
trace = middleware_trace if middleware_trace is not None else []
|
||
state = {
|
||
"args": function_args,
|
||
"middleware_trace": trace,
|
||
"blocked": False,
|
||
"dispatched": False,
|
||
}
|
||
dispatch_lock = threading.Lock()
|
||
|
||
def _authorized_dispatch(final_args: dict[str, Any]) -> Any:
|
||
with dispatch_lock:
|
||
if state["dispatched"]:
|
||
raise RuntimeError(
|
||
"Hermes tool execution callback invoked more than once"
|
||
)
|
||
state["dispatched"] = True
|
||
state["blocked"] = False
|
||
state["args"] = final_args
|
||
|
||
def _begin() -> None:
|
||
_begin_tool_execution(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=final_args,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
display_index=display_index,
|
||
)
|
||
|
||
def _advance_start_order(callback=None) -> None:
|
||
if begin_execution is None:
|
||
if callback is not None:
|
||
callback()
|
||
return
|
||
begin_execution(callback)
|
||
|
||
block_message = scope_block
|
||
block_error_type = "tool_scope_block"
|
||
if block_message is None:
|
||
block_error_type = "plugin_block"
|
||
|
||
def _resolve_pre_tool_block():
|
||
nonlocal final_args
|
||
try:
|
||
from hermes_cli.plugins import _dispatch_pre_tool_call_hooks
|
||
|
||
block_msg, modified_args = _dispatch_pre_tool_call_hooks(
|
||
function_name,
|
||
final_args,
|
||
**tool_hook_ids(agent, effective_task_id, tool_call_id),
|
||
middleware_trace=list(state["middleware_trace"]),
|
||
)
|
||
if modified_args is not None:
|
||
final_args = modified_args
|
||
state["args"] = modified_args
|
||
return block_msg
|
||
except Exception:
|
||
return None
|
||
|
||
block_message = (
|
||
_resolve_pre_tool_block()
|
||
if authorization_gate is None
|
||
else authorization_gate.run(_resolve_pre_tool_block)
|
||
)
|
||
|
||
guardrail_decision = None
|
||
if block_message is None:
|
||
guardrail_decision = agent._tool_guardrails.before_call(
|
||
function_name, final_args
|
||
)
|
||
if guardrail_decision.allows_execution:
|
||
guardrail_decision = None
|
||
|
||
if block_message is not None or guardrail_decision is not None:
|
||
_advance_start_order()
|
||
state["blocked"] = True
|
||
return _blocked_tool_result(
|
||
agent,
|
||
function_name=function_name,
|
||
final_args=final_args,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
block_message=block_message,
|
||
block_error_type=block_error_type,
|
||
guardrail_decision=guardrail_decision,
|
||
trace=state["middleware_trace"],
|
||
)
|
||
|
||
if function_name == "memory":
|
||
agent._turns_since_memory = 0
|
||
elif function_name == "skill_manage":
|
||
agent._iters_since_skill = 0
|
||
|
||
_advance_start_order(_begin)
|
||
return _run_with_activity_heartbeat(
|
||
agent, function_name, lambda: execute(final_args)
|
||
)
|
||
|
||
def _hermes_pipeline(relay_args: dict[str, Any]) -> Any:
|
||
request_result = apply_tool_request_middleware(
|
||
function_name,
|
||
relay_args,
|
||
skip_relay=True,
|
||
**tool_hook_ids(agent, effective_task_id, tool_call_id),
|
||
)
|
||
request_args = (
|
||
request_result.payload
|
||
if isinstance(request_result.payload, dict)
|
||
else relay_args
|
||
)
|
||
trace.clear()
|
||
trace.extend(request_result.trace)
|
||
return run_tool_execution_middleware(
|
||
function_name,
|
||
request_args,
|
||
lambda next_args: _authorized_dispatch(
|
||
next_args if isinstance(next_args, dict) else request_args
|
||
),
|
||
original_args=function_args,
|
||
**tool_hook_ids(agent, effective_task_id, tool_call_id),
|
||
)
|
||
|
||
result, _relay_args = relay_tools.execute(
|
||
function_name,
|
||
function_args,
|
||
_hermes_pipeline,
|
||
session_id=str(getattr(agent, "session_id", "") or ""),
|
||
metadata={
|
||
"task_id": effective_task_id or "",
|
||
"turn_id": getattr(agent, "_current_turn_id", "") or "",
|
||
"api_request_id": getattr(agent, "_current_api_request_id", "") or "",
|
||
"tool_call_id": tool_call_id or "",
|
||
},
|
||
)
|
||
return _ManagedToolResult(
|
||
result=result,
|
||
args=state["args"],
|
||
middleware_trace=state["middleware_trace"],
|
||
blocked=bool(state["blocked"]),
|
||
dispatched=bool(state["dispatched"]),
|
||
)
|
||
|
||
|
||
# Sequential wait-loop interrupt poll cadence: /stop lands within ~1s even when
|
||
# the tool never polls is_interrupted().
|
||
_SEQUENTIAL_INTERRUPT_POLL_SECONDS = 1.0
|
||
|
||
|
||
def _resolve_sequential_tool_timeout() -> float | None:
|
||
"""Deadline for one sequential tool call (#85125 Phase 2a).
|
||
|
||
``timeouts.tools.sequential_call`` wins; unset inherits the concurrent batch deadline
|
||
so the two paths can't drift. ``0``/negative disables the bound.
|
||
|
||
Deliberately NOT ``agent.deadline.run_bounded_sync``: both executors extend their
|
||
deadline while an approval prompt is open (MUST-preserve), which the fixed-deadline
|
||
primitive can't express.
|
||
"""
|
||
from agent.deadline import resolve_timeout
|
||
|
||
return resolve_timeout(
|
||
"tools.sequential_call",
|
||
default=_resolve_concurrent_tool_timeout(),
|
||
)
|
||
|
||
|
||
def _abandoned_sequential_result(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
middleware_trace: Optional[list],
|
||
message: str,
|
||
duration_ms: int,
|
||
status: str,
|
||
error_type: str,
|
||
error_message: str,
|
||
result_cls,
|
||
) -> _ManagedToolResult:
|
||
"""Emit the terminal post_tool_call for a worker the sequential runner gave up on
|
||
(timeout / interrupt) and wrap ``message`` in its marker ``result_cls``."""
|
||
trace = middleware_trace if middleware_trace is not None else []
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
result=message,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
duration_ms=duration_ms,
|
||
status=status,
|
||
error_type=error_type,
|
||
error_message=error_message,
|
||
middleware_trace=list(trace),
|
||
)
|
||
return _ManagedToolResult(
|
||
result=result_cls(message),
|
||
args=function_args,
|
||
middleware_trace=trace,
|
||
blocked=False,
|
||
dispatched=True,
|
||
)
|
||
|
||
|
||
def _run_sequential_tool_execution_middleware(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
execute,
|
||
scope_block: str | None = None,
|
||
display_index: int | None = None,
|
||
middleware_trace: list[dict[str, Any]] | None = None,
|
||
) -> _ManagedToolResult:
|
||
"""Run one sequential call with the concurrent executor's deadline.
|
||
|
||
Interactive tools (``clarify``) own their wait via ``agent.clarify_timeout``; the
|
||
generic deadline would report ``tool_timeout`` while the prompt is still live.
|
||
"""
|
||
timeout_s = _resolve_sequential_tool_timeout()
|
||
kwargs = {
|
||
"function_name": function_name,
|
||
"function_args": function_args,
|
||
"effective_task_id": effective_task_id,
|
||
"tool_call_id": tool_call_id,
|
||
"execute": execute,
|
||
"scope_block": scope_block,
|
||
"display_index": display_index,
|
||
"middleware_trace": middleware_trace,
|
||
}
|
||
if function_name in _NEVER_PARALLEL_TOOLS:
|
||
return _run_agent_tool_execution_middleware(agent, **kwargs)
|
||
|
||
from tools.daemon_pool import DaemonThreadPoolExecutor
|
||
|
||
authorization_gate = _ConcurrentToolAuthorizationGate()
|
||
worker_tid: list[int] = []
|
||
|
||
def _run() -> _ManagedToolResult:
|
||
with _registered_tool_worker(agent) as tid:
|
||
worker_tid.append(tid)
|
||
return _run_agent_tool_execution_middleware(
|
||
agent, authorization_gate=authorization_gate, **kwargs
|
||
)
|
||
|
||
executor = DaemonThreadPoolExecutor(max_workers=1)
|
||
future = executor.submit(propagate_context_to_thread(_run))
|
||
# Disabled timeout still runs on the worker: this wait loop is what makes a
|
||
# non-cooperative tool interruptible, so no deadline must not mean no interrupt checks.
|
||
deadline = time.monotonic() + timeout_s if timeout_s is not None else None
|
||
started = time.monotonic()
|
||
timed_out = False
|
||
interrupted = False
|
||
_last_heartbeat = 0
|
||
try:
|
||
while True:
|
||
wait_slice = _SEQUENTIAL_INTERRUPT_POLL_SECONDS
|
||
if deadline is not None:
|
||
remaining = (
|
||
deadline + authorization_gate.excluded_seconds() - time.monotonic()
|
||
)
|
||
if remaining <= 0:
|
||
timed_out = True
|
||
break
|
||
wait_slice = min(wait_slice, remaining)
|
||
try:
|
||
return future.result(timeout=wait_slice)
|
||
except concurrent.futures.TimeoutError:
|
||
if agent._interrupt_requested:
|
||
interrupted = True
|
||
break
|
||
elapsed = int(time.monotonic() - started)
|
||
if elapsed - _last_heartbeat >= 30:
|
||
_last_heartbeat = elapsed
|
||
agent._touch_activity(
|
||
f"sequential tool running ({elapsed}s): {function_name}"
|
||
)
|
||
|
||
if interrupted:
|
||
# Belt-and-braces: interrupt() already fans out to tracked worker
|
||
# tids, but the worker may have registered after the fan-out ran.
|
||
_interrupt_worker_tids(
|
||
agent, worker_tid, reason=getattr(agent, "_tool_interrupt_reason", None)
|
||
)
|
||
# Grace for a cooperative tool to notice its interrupt bit (mirrors the
|
||
# concurrent path's 3s).
|
||
concurrent.futures.wait([future], timeout=3.0)
|
||
if future.done() and not future.cancelled():
|
||
return future.result()
|
||
timed_out = True # reuse the abandon-shutdown path in finally
|
||
future.cancel()
|
||
interrupt_reason = (
|
||
getattr(agent, "_tool_interrupt_reason", None)
|
||
or "interrupt requested"
|
||
)
|
||
message = (
|
||
f"[Tool execution cancelled — {function_name} was abandoned: "
|
||
f"{interrupt_reason}]"
|
||
)
|
||
logger.info(
|
||
"sequential tool %s abandoned due to %s (%.1fs elapsed)",
|
||
function_name, interrupt_reason, time.monotonic() - started,
|
||
)
|
||
return _abandoned_sequential_result(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
middleware_trace=middleware_trace,
|
||
message=message,
|
||
duration_ms=int((time.monotonic() - started) * 1000),
|
||
status="cancelled",
|
||
error_type="tool_interrupted",
|
||
error_message=f"Tool execution cancelled: {interrupt_reason}",
|
||
result_cls=_ToolCancelledResult,
|
||
)
|
||
|
||
# Only reachable when a deadline exists (interrupted returns above).
|
||
assert timeout_s is not None
|
||
message = (
|
||
f"Error executing tool '{function_name}': "
|
||
f"timed out after {timeout_s:.1f}s"
|
||
)
|
||
logger.warning(
|
||
"sequential tool %s timed out after %.1fs", function_name, timeout_s
|
||
)
|
||
future.cancel()
|
||
_interrupt_worker_tids(agent, worker_tid)
|
||
return _abandoned_sequential_result(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
middleware_trace=middleware_trace,
|
||
message=message,
|
||
duration_ms=int(timeout_s * 1000),
|
||
status="timeout",
|
||
error_type="tool_timeout",
|
||
error_message=message,
|
||
result_cls=_ToolTimeoutResult,
|
||
)
|
||
finally:
|
||
# Never join a wedged worker. DaemonThreadPoolExecutor also keeps it out
|
||
# of the stdlib atexit join, matching the concurrent timeout path.
|
||
executor.shutdown(wait=not timed_out, cancel_futures=timed_out)
|
||
|
||
|
||
def _begin_tool_execution(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict[str, Any],
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
display_index: int | None,
|
||
) -> None:
|
||
"""Run user-visible and checkpoint preflight on final tool arguments."""
|
||
display_args = _redact_tool_args_for_display(function_name, function_args) or function_args
|
||
if _tool_progress_enabled(agent):
|
||
args_str = json.dumps(display_args, ensure_ascii=False)
|
||
prefix = f"Tool {display_index}" if display_index is not None else "Tool"
|
||
if agent.verbose_logging:
|
||
print(f" 📞 {prefix}: {function_name}({list(display_args.keys())})")
|
||
print(
|
||
agent._wrap_verbose(
|
||
"Args: ", json.dumps(display_args, indent=2, ensure_ascii=False)
|
||
)
|
||
)
|
||
else:
|
||
args_preview = (
|
||
args_str[: agent.log_prefix_chars] + "..."
|
||
if len(args_str) > agent.log_prefix_chars
|
||
else args_str
|
||
)
|
||
print(
|
||
f" 📞 {prefix}: {function_name}({list(function_args.keys())}) - "
|
||
f"{args_preview}"
|
||
)
|
||
|
||
agent._current_tool = function_name
|
||
agent._touch_activity(f"executing tool: {function_name}")
|
||
try:
|
||
from tools.environments.base import set_activity_callback
|
||
|
||
set_activity_callback(agent._touch_activity)
|
||
except Exception:
|
||
pass
|
||
|
||
if agent.tool_progress_callback:
|
||
try:
|
||
preview = _build_tool_preview(function_name, display_args)
|
||
agent.tool_progress_callback(
|
||
"tool.started", function_name, preview, display_args
|
||
)
|
||
except Exception as callback_error:
|
||
logging.debug("Tool progress callback error: %s", callback_error)
|
||
|
||
if agent.tool_start_callback:
|
||
try:
|
||
agent.tool_start_callback(
|
||
tool_call_id, function_name, display_args
|
||
)
|
||
except Exception as callback_error:
|
||
logging.debug("Tool start callback error: %s", callback_error)
|
||
|
||
if not agent._checkpoint_mgr.enabled:
|
||
return
|
||
if function_name in {"write_file", "patch"}:
|
||
try:
|
||
_ensure_file_checkpoint(
|
||
agent,
|
||
function_name,
|
||
function_args,
|
||
effective_task_id,
|
||
)
|
||
except Exception:
|
||
pass
|
||
elif function_name == "terminal":
|
||
try:
|
||
command = function_args.get("command", "")
|
||
if _is_destructive_command(command):
|
||
cwd = function_args.get("workdir") or os.getenv(
|
||
"TERMINAL_CWD", os.getcwd()
|
||
)
|
||
agent._checkpoint_mgr.ensure_checkpoint(
|
||
cwd, f"before terminal: {command[:60]}"
|
||
)
|
||
except Exception:
|
||
pass
|
||
|
||
|
||
def _append_finalized_tool_result(
|
||
agent,
|
||
messages: list,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
function_result,
|
||
tool_call_id: str,
|
||
effective_task_id: str,
|
||
budget: BudgetConfig,
|
||
effect_disposition=None,
|
||
):
|
||
"""Persist/spill, hint, wrap and append one tool result; flush the session DB.
|
||
|
||
Returns ``(function_result, tool_message, risk_metadata)`` — ``function_result`` is the
|
||
persisted/hinted content — or ``None`` when the incremental flush failed (the caller
|
||
must stop the batch).
|
||
"""
|
||
if not _is_multimodal_tool_result(function_result):
|
||
function_result = maybe_persist_tool_result(
|
||
content=function_result,
|
||
tool_name=function_name,
|
||
tool_use_id=tool_call_id,
|
||
env=get_active_env(effective_task_id),
|
||
config=budget,
|
||
)
|
||
_record_persisted_path_for_stub(agent, tool_call_id, function_result)
|
||
|
||
subdir_hints = agent._subdirectory_hints.check_tool_call(function_name, function_args)
|
||
if subdir_hints:
|
||
if _is_multimodal_tool_result(function_result):
|
||
# Append the hint to the text summary part so the model still sees it;
|
||
# don't touch the image blocks.
|
||
_append_subdir_hint_to_multimodal(function_result, subdir_hints)
|
||
else:
|
||
function_result += subdir_hints
|
||
|
||
# Unwrap _multimodal dicts to an OpenAI-style content list; text-only servers
|
||
# get a string-safe fallback so a rejected image result never poisons history.
|
||
_tool_content = agent._tool_result_content_for_active_model(function_name, function_result)
|
||
tool_message = make_tool_result_message(
|
||
function_name,
|
||
_tool_content,
|
||
tool_call_id,
|
||
effect_disposition=effect_disposition,
|
||
)
|
||
messages.append(tool_message)
|
||
if not _flush_session_db_after_tool_progress(
|
||
agent,
|
||
messages,
|
||
stage=f"tool result {function_name}",
|
||
):
|
||
return None
|
||
return function_result, tool_message, tool_message.get("_tool_output_risk")
|
||
|
||
|
||
def _emit_tool_completed_progress(agent, function_name: str, *, duration: float, is_error: bool, result) -> None:
|
||
"""``tool.completed`` UI projection; downstream of the canonical append so resume
|
||
can reconstruct the result even if the UI bridge dies mid-projection."""
|
||
if not agent.tool_progress_callback:
|
||
return
|
||
try:
|
||
agent.tool_progress_callback(
|
||
"tool.completed", function_name, None, None,
|
||
duration=duration, is_error=is_error, result=result,
|
||
)
|
||
except Exception as cb_err:
|
||
logging.debug("Tool progress callback error: %s", cb_err)
|
||
|
||
|
||
def _emit_tool_complete_and_risk(
|
||
agent, *, function_name: str, function_args: dict, tool_call_id: str, result, risk_metadata, blocked: bool
|
||
) -> None:
|
||
"""Fire ``tool_complete_callback`` (unless blocked) then the ``tool.output_risk`` projection."""
|
||
if not blocked and agent.tool_complete_callback:
|
||
try:
|
||
display_args = _redact_tool_args_for_display(function_name, function_args) or function_args
|
||
agent.tool_complete_callback(tool_call_id, function_name, display_args, result)
|
||
except Exception as cb_err:
|
||
logging.debug("Tool complete callback error: %s", cb_err)
|
||
|
||
if (
|
||
risk_metadata is not None
|
||
and risk_metadata.get("risk") != "low"
|
||
and agent.tool_progress_callback
|
||
):
|
||
try:
|
||
agent.tool_progress_callback(
|
||
"tool.output_risk",
|
||
function_name,
|
||
None,
|
||
None,
|
||
tool_call_id=tool_call_id,
|
||
risk_metadata=risk_metadata,
|
||
)
|
||
except Exception as cb_err:
|
||
logging.debug("Tool output risk callback error: %s", cb_err)
|
||
|
||
|
||
def _observe_tool_result(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
function_result,
|
||
tool_call_id: str,
|
||
tool_duration: float,
|
||
is_error: bool,
|
||
blocked: bool,
|
||
error_preview: Callable[[Any], Any],
|
||
success_log_chars: Optional[int] = None,
|
||
):
|
||
"""Guardrail-observe a result that actually ran, log its outcome, and feed the
|
||
turn-end file-mutation verifier. Blocked calls never ran, so they count as neither
|
||
failure nor success and are not observed. ``success_log_chars`` (sequential path)
|
||
also logs the completion line. Returns the (possibly annotated) result."""
|
||
if not blocked:
|
||
function_result = agent._append_guardrail_observation(
|
||
function_name,
|
||
function_args,
|
||
function_result,
|
||
failed=is_error,
|
||
tool_call_id=tool_call_id,
|
||
)
|
||
if is_error:
|
||
logger.warning(
|
||
"Tool %s returned error (%.2fs): %s",
|
||
function_name, tool_duration, error_preview(function_result),
|
||
)
|
||
elif success_log_chars is not None:
|
||
logger.info("tool %s completed (%.2fs, %d chars)", function_name, tool_duration, success_log_chars)
|
||
if not blocked:
|
||
try:
|
||
agent._record_file_mutation_result(
|
||
function_name, function_args, function_result, is_error,
|
||
)
|
||
except Exception as _ver_err:
|
||
logging.debug("file-mutation verifier record failed: %s", _ver_err)
|
||
return function_result
|
||
|
||
|
||
def _commit_tool_result(
|
||
agent,
|
||
messages: list,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
function_result,
|
||
tool_call_id: str,
|
||
effective_task_id: str,
|
||
budget: BudgetConfig,
|
||
tool_duration: float,
|
||
is_error: bool,
|
||
blocked: bool,
|
||
effect_disposition,
|
||
):
|
||
"""Mark the tool done, append + flush its result, then project ``tool.completed``.
|
||
|
||
Returns ``(persisted_result, display_result, risk_metadata)`` — ``display_result`` is
|
||
the pre-persist content for UI previews — or ``None`` when the flush failed.
|
||
"""
|
||
agent._current_tool = None
|
||
_status_suffix = " (error)" if is_error else ""
|
||
agent._touch_activity(f"tool completed: {function_name} ({tool_duration:.1f}s){_status_suffix}")
|
||
|
||
finalized = _append_finalized_tool_result(
|
||
agent,
|
||
messages,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
function_result=function_result,
|
||
tool_call_id=tool_call_id,
|
||
effective_task_id=effective_task_id,
|
||
budget=budget,
|
||
effect_disposition=effect_disposition,
|
||
)
|
||
if finalized is None:
|
||
return None
|
||
persisted_result, _tool_message, risk_metadata = finalized
|
||
|
||
if not blocked:
|
||
_emit_tool_completed_progress(
|
||
agent, function_name,
|
||
duration=tool_duration, is_error=is_error, result=function_result,
|
||
)
|
||
return persisted_result, function_result, risk_metadata
|
||
|
||
|
||
def _finalize_tool_batch(agent, messages: list, effective_task_id: str, num_tools: int, budget: BudgetConfig) -> None:
|
||
"""Per-turn aggregate budget enforcement, then /steer injection.
|
||
|
||
/steer stays pending until AFTER budget enforcement so the steer marker is never
|
||
truncated or discarded when enforcement replaces a tool result; see ``steer()``.
|
||
"""
|
||
if num_tools <= 0:
|
||
return
|
||
enforce_turn_budget(messages[-num_tools:], env=get_active_env(effective_task_id), config=budget)
|
||
agent._apply_pending_steer_to_tool_results(messages, num_tools)
|
||
|
||
|
||
def _tool_progress_enabled(agent) -> bool:
|
||
return not agent.quiet_mode and getattr(agent, "tool_progress_mode", "all") != "off"
|
||
|
||
|
||
def _print_tool_completed(agent, index: int, tool_duration: float, result) -> None:
|
||
"""Non-quiet ``✅ Tool N completed`` line (full result under verbose logging)."""
|
||
if agent.verbose_logging:
|
||
print(f" ✅ Tool {index} completed in {tool_duration:.2f}s")
|
||
print(agent._wrap_verbose("Result: ", result))
|
||
else:
|
||
preview = result if isinstance(result, str) else str(result)
|
||
response_preview = preview[:agent.log_prefix_chars] + "..." if len(preview) > agent.log_prefix_chars else preview
|
||
print(f" ✅ Tool {index} completed in {tool_duration:.2f}s - {response_preview}")
|
||
|
||
|
||
# ── Concurrent batch machinery ──────────────────────────────────────────────
|
||
|
||
|
||
@dataclass
|
||
class _ToolOutcome:
|
||
"""One finished worker slot of a concurrent batch."""
|
||
|
||
name: str
|
||
args: dict
|
||
result: Any
|
||
duration: float
|
||
is_error: bool
|
||
blocked: bool
|
||
middleware_trace: list
|
||
|
||
|
||
def _start_order_gate_timeout(batch_timeout: float | None) -> float:
|
||
"""The gate bound must sit UNDER the batch deadline, else parked workers are falsely
|
||
reported timed out without starting. A disabled deadline keeps the stock bound."""
|
||
if batch_timeout is None:
|
||
return _START_ORDER_GATE_TIMEOUT_S
|
||
return min(_START_ORDER_GATE_TIMEOUT_S, batch_timeout / 2)
|
||
|
||
|
||
class _StartOrderGate:
|
||
"""Serialize worker dispatch by submit order (prompts appear in call order).
|
||
|
||
``abandon()`` releases every parked worker so none dispatches a tool the turn
|
||
already reported as timed out / interrupted.
|
||
"""
|
||
|
||
def __init__(self, timeout: float) -> None:
|
||
self._condition = threading.Condition()
|
||
self._next_order = 0
|
||
self._timeout = timeout
|
||
self.abandoned = threading.Event()
|
||
|
||
def abandon(self) -> None:
|
||
self.abandoned.set()
|
||
with self._condition:
|
||
self._condition.notify_all()
|
||
|
||
def begin_in_order(self, order: int, callback=None, *, tool_name: str = "") -> bool:
|
||
"""Wait for ``order``, run ``callback``, advance. Returns False if abandoned."""
|
||
with self._condition:
|
||
# Bounded wait so one wedged dispatch can't starve/leak later-ordered workers;
|
||
# on expiry proceed out of order (interleaved prompts beat starvation).
|
||
# >= (not ==) releases every skipped worker at once; abandoned short-circuits.
|
||
in_order = self._condition.wait_for(
|
||
lambda: self._next_order >= order or self.abandoned.is_set(),
|
||
timeout=self._timeout,
|
||
)
|
||
if self.abandoned.is_set():
|
||
# Do not run the callback or advance the counter: the turn has
|
||
# already synthesized this tool's result and moved on.
|
||
return False
|
||
if not in_order:
|
||
logger.warning(
|
||
"start-order gate timed out for %s (order=%d next=%d); "
|
||
"proceeding out of order",
|
||
tool_name or "tool",
|
||
order,
|
||
self._next_order,
|
||
)
|
||
try:
|
||
if callback is not None:
|
||
callback()
|
||
finally:
|
||
self._next_order = max(self._next_order, order + 1)
|
||
self._condition.notify_all()
|
||
return True
|
||
|
||
|
||
class _ConcurrentBatch:
|
||
"""Shared state of one concurrent tool batch: per-slot results, the start-order and
|
||
authorization gates, and the deadline bookkeeping the wait loop needs."""
|
||
|
||
def __init__(self, agent, messages: list, effective_task_id: str, parsed_calls: list[_ParsedCall], timeout_s: float | None) -> None:
|
||
self.agent = agent
|
||
self.messages = messages
|
||
self.effective_task_id = effective_task_id
|
||
self.parsed_calls = parsed_calls
|
||
self.timeout_s = timeout_s
|
||
self.results: list[Optional[_ToolOutcome]] = [None] * len(parsed_calls)
|
||
for i, pc in enumerate(parsed_calls):
|
||
if pc.parse_error is not None:
|
||
self.results[i] = _ToolOutcome(pc.name, pc.args, pc.parse_error, 0.0, True, True, pc.middleware_trace)
|
||
self.gate = _StartOrderGate(_start_order_gate_timeout(timeout_s))
|
||
self.authorization_gate = _ConcurrentToolAuthorizationGate()
|
||
self.timed_out_indices: set[int] = set()
|
||
|
||
def run_worker(
|
||
self,
|
||
index,
|
||
tool_call,
|
||
function_name,
|
||
function_args,
|
||
middleware_trace,
|
||
scope_block,
|
||
start_order,
|
||
):
|
||
"""Worker function executed in a thread."""
|
||
agent = self.agent
|
||
with _registered_tool_worker(agent) as _worker_tid:
|
||
# Race: interrupt may have fanned out before our registration; apply it
|
||
# to our own tid now.
|
||
if agent._interrupt_requested:
|
||
_interrupt_worker_tids(
|
||
agent, [_worker_tid], reason=getattr(agent, "_tool_interrupt_reason", None)
|
||
)
|
||
# Activity callback is thread-local; set it on THIS worker so
|
||
# _wait_for_process heartbeats fire.
|
||
try:
|
||
from tools.environments.base import set_activity_callback
|
||
set_activity_callback(agent._touch_activity)
|
||
except Exception:
|
||
pass
|
||
# Approval/sudo callbacks and turn ContextVars are propagated by
|
||
# propagate_context_to_thread() at submit (GHSA-qg5c-hvr5-hjgr, #13617).
|
||
start = time.time()
|
||
tool_call_id = _pairing_tool_call_id(tool_call)
|
||
blocked = False
|
||
dispatched = False
|
||
start_advanced = False
|
||
|
||
def _advance_start(callback=None) -> None:
|
||
nonlocal start_advanced
|
||
if start_advanced:
|
||
return
|
||
try:
|
||
proceed = self.gate.begin_in_order(start_order, callback, tool_name=function_name)
|
||
finally:
|
||
start_advanced = True
|
||
if not proceed:
|
||
# Batch already abandoned: the turn synthesized this tool's
|
||
# result and moved on. Abort instead of dispatching late.
|
||
raise _BatchAbandoned(function_name)
|
||
|
||
try:
|
||
try:
|
||
def _execute(next_args: dict[str, Any]) -> Any:
|
||
return agent._invoke_tool(
|
||
function_name,
|
||
next_args,
|
||
self.effective_task_id,
|
||
tool_call_id,
|
||
messages=self.messages,
|
||
pre_tool_block_checked=True,
|
||
skip_tool_request_middleware=True,
|
||
skip_tool_execution_middleware=True,
|
||
tool_request_middleware_trace=list(middleware_trace),
|
||
)
|
||
|
||
managed = _run_agent_tool_execution_middleware(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
effective_task_id=self.effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
execute=_execute,
|
||
scope_block=scope_block,
|
||
display_index=index + 1,
|
||
middleware_trace=middleware_trace,
|
||
begin_execution=_advance_start,
|
||
authorization_gate=self.authorization_gate,
|
||
)
|
||
result = managed.result
|
||
function_args = managed.args
|
||
middleware_trace = managed.middleware_trace
|
||
blocked = managed.blocked
|
||
dispatched = managed.dispatched
|
||
except _BatchAbandoned:
|
||
# Abandoned at the start-order gate: the main thread already synthesized
|
||
# this result, so write/emit nothing (would double-report the tool_call_id).
|
||
logger.info(
|
||
"tool %s abandoned at start-order gate; skipping dispatch",
|
||
function_name,
|
||
)
|
||
return
|
||
except KeyboardInterrupt:
|
||
try:
|
||
agent.interrupt("keyboard interrupt")
|
||
except Exception:
|
||
pass
|
||
result = _emit_cancelled_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
effective_task_id=self.effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
start_time=start,
|
||
middleware_trace=list(middleware_trace),
|
||
)
|
||
duration = time.time() - start
|
||
logger.info("tool %s cancelled (%.2fs)", function_name, duration)
|
||
self.results[index] = _ToolOutcome(
|
||
function_name, function_args, result, duration, True, False, middleware_trace,
|
||
)
|
||
return
|
||
except Exception as tool_error:
|
||
result = f"Error executing tool '{function_name}': {tool_error}"
|
||
logger.error("_invoke_tool raised for %s: %s", function_name, tool_error, exc_info=True)
|
||
duration = time.time() - start
|
||
if not blocked and not dispatched:
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
result=result,
|
||
effective_task_id=self.effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
duration_ms=int(duration * 1000),
|
||
middleware_trace=list(middleware_trace),
|
||
)
|
||
is_error, _ = _detect_tool_failure(function_name, result)
|
||
if is_error:
|
||
logger.info("tool %s failed (%.2fs): %s", function_name, duration, result[:200])
|
||
else:
|
||
logger.info("tool %s completed (%.2fs, %d chars)", function_name, duration, len(result))
|
||
self.results[index] = _ToolOutcome(
|
||
function_name, function_args, result, duration, is_error, blocked, middleware_trace,
|
||
)
|
||
finally:
|
||
# Teardown advance keeps later-ordered workers moving; never let the
|
||
# abandonment signal escape here.
|
||
try:
|
||
_advance_start()
|
||
except _BatchAbandoned:
|
||
pass
|
||
|
||
def submit_all(self, executor, runnable_calls) -> tuple[list, dict]:
|
||
"""Submit every runnable call; on interpreter shutdown, synthesize error results
|
||
for the unsubmitted remainder instead of raising."""
|
||
futures = []
|
||
future_to_index = {}
|
||
for submit_index, (i, tc, name, args, scope_block) in enumerate(runnable_calls):
|
||
# Propagate turn ContextVars and thread-local approval/sudo
|
||
# callbacks into the worker; clears callbacks on exit.
|
||
try:
|
||
f = executor.submit(
|
||
propagate_context_to_thread(self.run_worker),
|
||
i,
|
||
tc,
|
||
name,
|
||
args,
|
||
self.parsed_calls[i].middleware_trace,
|
||
scope_block,
|
||
submit_index,
|
||
)
|
||
except RuntimeError as submit_error:
|
||
if not _is_interpreter_shutdown_submit_error(submit_error):
|
||
raise
|
||
skipped_calls = runnable_calls[submit_index:]
|
||
logger.warning(
|
||
"interpreter shutdown while scheduling concurrent tools; "
|
||
"skipping %d unsubmitted tool(s)",
|
||
len(skipped_calls),
|
||
)
|
||
for skipped_i, _tc, skipped_name, skipped_args, _scope_block in skipped_calls:
|
||
if self.results[skipped_i] is None:
|
||
result = (
|
||
f"Error executing tool '{skipped_name}': "
|
||
"Python interpreter is shutting down; tool was not started"
|
||
)
|
||
self.results[skipped_i] = _ToolOutcome(
|
||
skipped_name, skipped_args, result, 0.0, True, False,
|
||
self.parsed_calls[skipped_i].middleware_trace,
|
||
)
|
||
break
|
||
futures.append(f)
|
||
future_to_index[f] = i
|
||
return futures, future_to_index
|
||
|
||
def _running_names(self, not_done, future_to_index) -> list[str]:
|
||
return [
|
||
self.parsed_calls[future_to_index[f]].name
|
||
for f in not_done
|
||
if f in future_to_index
|
||
]
|
||
|
||
def await_completion(self, futures, future_to_index, deadline: float | None) -> bool:
|
||
"""Wait with periodic heartbeats (gateway inactivity monitor) and interrupt checks
|
||
(/stop or a new message). Returns True when the batch was abandoned (deadline or
|
||
interrupt) and the executor must not join its workers."""
|
||
agent = self.agent
|
||
_conc_start = time.time()
|
||
while True:
|
||
wait_timeout = 5.0
|
||
if deadline is not None:
|
||
effective_deadline = deadline + self.authorization_gate.excluded_seconds()
|
||
remaining = effective_deadline - time.monotonic()
|
||
if remaining <= 0:
|
||
done, not_done = set(), {f for f in futures if not f.done()}
|
||
else:
|
||
wait_timeout = min(wait_timeout, remaining)
|
||
done, not_done = concurrent.futures.wait(futures, timeout=wait_timeout)
|
||
else:
|
||
done, not_done = concurrent.futures.wait(futures, timeout=wait_timeout)
|
||
if not not_done:
|
||
return False
|
||
|
||
if (
|
||
deadline is not None
|
||
and time.monotonic() >= deadline + self.authorization_gate.excluded_seconds()
|
||
):
|
||
self.timed_out_indices = {
|
||
future_to_index[f] for f in not_done if f in future_to_index
|
||
}
|
||
logger.warning(
|
||
"concurrent tool batch timed out after %.1fs; "
|
||
"%d tool(s) still running: %s",
|
||
self.timeout_s,
|
||
len(self.timed_out_indices),
|
||
", ".join(self._running_names(not_done, future_to_index)[:5]),
|
||
)
|
||
for f in not_done:
|
||
f.cancel()
|
||
# Release gate-parked workers before interrupt fan-out so none
|
||
# later dispatches a tool just reported as timed out.
|
||
self.gate.abandon()
|
||
with agent._tool_worker_threads_lock:
|
||
worker_tids = list(agent._tool_worker_threads)
|
||
_interrupt_worker_tids(agent, worker_tids)
|
||
return True
|
||
|
||
# Tools without interrupt checks (web_search, read_file) run to
|
||
# completion; cancel unstarted futures so we don't block on them.
|
||
if agent._interrupt_requested:
|
||
agent._vprint(
|
||
f"{agent.log_prefix}⚡ Interrupt: cancelling "
|
||
f"{len(not_done)} pending concurrent tool(s)",
|
||
force=True,
|
||
)
|
||
for f in not_done:
|
||
f.cancel()
|
||
# Release gate-parked workers so they abort instead of
|
||
# dispatching after the turn was already interrupted.
|
||
self.gate.abandon()
|
||
# Give already-running tools a moment to notice the
|
||
# per-thread interrupt signal and exit gracefully.
|
||
concurrent.futures.wait(not_done, timeout=3.0)
|
||
return True
|
||
|
||
_conc_elapsed = int(time.time() - _conc_start)
|
||
# Heartbeat every ~30s (6 × 5s poll intervals)
|
||
if _conc_elapsed > 0 and _conc_elapsed % 30 < 6:
|
||
_still_running = self._running_names(not_done, future_to_index)
|
||
agent._touch_activity(
|
||
f"concurrent tools running ({_conc_elapsed}s, "
|
||
f"{len(not_done)} remaining: {', '.join(_still_running[:3])})"
|
||
)
|
||
|
||
def run(self) -> None:
|
||
"""Dispatch the runnable calls on a daemon pool and wait for the batch."""
|
||
runnable_calls = [
|
||
(i, pc.tool_call, pc.name, pc.args, pc.scope_block)
|
||
for i, pc in enumerate(self.parsed_calls)
|
||
if pc.parse_error is None
|
||
]
|
||
if not runnable_calls:
|
||
return
|
||
deadline = time.monotonic() + self.timeout_s if self.timeout_s is not None else None
|
||
max_workers = _max_workers_for_tool_batch(runnable_calls)
|
||
# Daemon workers: stdlib ThreadPoolExecutor's atexit join would let one
|
||
# wedged tool thread block interpreter exit forever.
|
||
from tools.daemon_pool import DaemonThreadPoolExecutor
|
||
executor = DaemonThreadPoolExecutor(max_workers=max_workers)
|
||
abandon_executor = False
|
||
try:
|
||
futures, future_to_index = self.submit_all(executor, runnable_calls)
|
||
abandon_executor = self.await_completion(futures, future_to_index, deadline)
|
||
finally:
|
||
# Any abandoning exit from the wait loop (including the exception
|
||
# path) must release gate-parked workers.
|
||
if abandon_executor:
|
||
self.gate.abandon()
|
||
# On abandon do NOT join hung workers: a wedged thread is left detached
|
||
# rather than deadlocking the batch. Normal completion joins.
|
||
executor.shutdown(
|
||
wait=not abandon_executor,
|
||
cancel_futures=abandon_executor,
|
||
)
|
||
|
||
|
||
def _unfinished_tool_result(
|
||
agent,
|
||
pc: _ParsedCall,
|
||
*,
|
||
tool_call_id: str,
|
||
effective_task_id: str,
|
||
timed_out: bool,
|
||
timeout_s: float | None,
|
||
) -> tuple[str, float, Optional[str]]:
|
||
"""Synthesize the result for a slot no worker filled (deadline, interrupt, or a
|
||
thread that never returned) and emit its terminal post_tool_call.
|
||
|
||
Returns ``(function_result, tool_duration, effect_disposition)``.
|
||
"""
|
||
def _emit(result: str, *, status: str, error_type: str, error_message: str, duration_ms: int = 0) -> None:
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=pc.name,
|
||
function_args=pc.args,
|
||
result=result,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
duration_ms=duration_ms,
|
||
status=status,
|
||
error_type=error_type,
|
||
error_message=error_message,
|
||
middleware_trace=list(pc.middleware_trace),
|
||
)
|
||
|
||
if timed_out:
|
||
suffix = f"{timeout_s:.1f}s" if timeout_s is not None else "the configured timeout"
|
||
function_result = f"Error executing tool '{pc.name}': timed out after {suffix}"
|
||
_emit(
|
||
function_result,
|
||
duration_ms=int((timeout_s or 0.0) * 1000),
|
||
status="timeout",
|
||
error_type="tool_timeout",
|
||
error_message=function_result,
|
||
)
|
||
return function_result, float(timeout_s or 0.0), "unknown"
|
||
if agent._interrupt_requested:
|
||
function_result = f"[Tool execution cancelled — {pc.name} was skipped due to user interrupt]"
|
||
_emit(
|
||
function_result,
|
||
status="cancelled",
|
||
error_type="keyboard_interrupt",
|
||
error_message="Tool execution cancelled by user interrupt",
|
||
)
|
||
else:
|
||
function_result = f"Error executing tool '{pc.name}': thread did not return a result"
|
||
_emit(
|
||
function_result,
|
||
status="error",
|
||
error_type="thread_missing_result",
|
||
error_message=function_result,
|
||
)
|
||
return function_result, 0.0, None
|
||
|
||
|
||
def _append_batch_results(agent, messages: list, effective_task_id: str, batch: _ConcurrentBatch, budget: BudgetConfig) -> bool:
|
||
"""Append every slot's result in original call order; returns False at the first
|
||
failed flush (the caller must stop the batch)."""
|
||
for i, pc in enumerate(batch.parsed_calls):
|
||
r = batch.results[i]
|
||
tool_call_id = _pairing_tool_call_id(pc.tool_call)
|
||
# A worker may finish between the deadline snapshot and this loop;
|
||
# prefer its real result over a fabricated timeout.
|
||
if r is None:
|
||
name, args, middleware_trace, is_error, blocked = pc.name, pc.args, pc.middleware_trace, True, False
|
||
function_result, tool_duration, effect_disposition = _unfinished_tool_result(
|
||
agent, pc,
|
||
tool_call_id=tool_call_id,
|
||
effective_task_id=effective_task_id,
|
||
timed_out=i in batch.timed_out_indices,
|
||
timeout_s=batch.timeout_s,
|
||
)
|
||
else:
|
||
name, args, function_result, tool_duration, is_error, blocked, middleware_trace = (
|
||
r.name, r.args, r.result, r.duration, r.is_error, r.blocked, r.middleware_trace,
|
||
)
|
||
if pc.parse_error is not None:
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=name,
|
||
function_args=args,
|
||
result=function_result,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
status="error",
|
||
error_type="invalid_tool_arguments",
|
||
error_message="Tool arguments must be a valid JSON object",
|
||
middleware_trace=list(middleware_trace),
|
||
)
|
||
effect_disposition = "none" if blocked else None
|
||
function_result = _observe_tool_result(
|
||
agent,
|
||
function_name=name,
|
||
function_args=args,
|
||
function_result=function_result,
|
||
tool_call_id=tool_call_id,
|
||
tool_duration=tool_duration,
|
||
is_error=is_error,
|
||
blocked=blocked,
|
||
error_preview=lambda res: _multimodal_text_summary(res)[:200],
|
||
)
|
||
if agent.verbose_logging:
|
||
logging.debug("Tool %s completed in %.2fs", name, tool_duration)
|
||
logging.debug("Tool result (%d chars): %s", len(function_result), function_result)
|
||
|
||
committed = _commit_tool_result(
|
||
agent,
|
||
messages,
|
||
function_name=name,
|
||
function_args=args,
|
||
function_result=function_result,
|
||
tool_call_id=tool_call_id,
|
||
effective_task_id=effective_task_id,
|
||
budget=budget,
|
||
tool_duration=tool_duration,
|
||
is_error=is_error,
|
||
blocked=blocked,
|
||
effect_disposition=effect_disposition,
|
||
)
|
||
if committed is None:
|
||
return False
|
||
_persisted, display_function_result, risk_metadata = committed
|
||
|
||
if agent._should_emit_quiet_tool_messages():
|
||
cute_msg = _get_cute_tool_message_impl(
|
||
name, args, tool_duration, result=display_function_result,
|
||
)
|
||
agent._safe_print(f" {cute_msg}")
|
||
elif _tool_progress_enabled(agent):
|
||
_print_tool_completed(agent, i + 1, tool_duration, _multimodal_text_summary(display_function_result))
|
||
|
||
_emit_tool_complete_and_risk(
|
||
agent,
|
||
function_name=name,
|
||
function_args=args,
|
||
tool_call_id=tool_call_id,
|
||
result=display_function_result,
|
||
risk_metadata=risk_metadata,
|
||
blocked=blocked,
|
||
)
|
||
return True
|
||
|
||
|
||
def execute_tool_calls_concurrent(agent, assistant_message, messages: list, effective_task_id: str, api_call_count: int = 0, *, finalize: bool = True) -> None:
|
||
"""Execute tool calls concurrently; results are appended in original call order.
|
||
|
||
``finalize=False`` skips end-of-batch budget enforcement and /steer injection (the
|
||
segmented dispatcher owns turn-end work).
|
||
"""
|
||
tool_calls = assistant_message.tool_calls
|
||
num_tools = len(tool_calls)
|
||
|
||
# Resolve the context-scaled tool-output budget once per turn, not per result.
|
||
_tool_budget = _budget_for_agent(agent)
|
||
|
||
# ── Pre-flight: interrupt check ──────────────────────────────────
|
||
if agent._interrupt_requested:
|
||
print(f"{agent.log_prefix}⚡ Interrupt: skipping {num_tools} tool call(s)")
|
||
_append_skipped_tool_results(
|
||
agent, messages, tool_calls, effective_task_id,
|
||
content="[Tool execution cancelled — {name} was skipped due to user interrupt]",
|
||
hook_error_type="user_interrupt",
|
||
flush_stage="cancelled tool result",
|
||
stop_on_flush_failure=False,
|
||
)
|
||
return
|
||
|
||
parsed_calls = [_parse_tool_call(agent, tc) for tc in tool_calls]
|
||
|
||
tool_names_str = ", ".join(pc.name for pc in parsed_calls)
|
||
if _tool_progress_enabled(agent):
|
||
print(f" ⚡ Concurrent: {num_tools} tool calls — {tool_names_str}")
|
||
|
||
# Resolved before the batch is built so the start-order gate can clamp
|
||
# its own bound against the batch deadline it must stay under.
|
||
timeout_s = _resolve_concurrent_tool_timeout()
|
||
batch = _ConcurrentBatch(agent, messages, effective_task_id, parsed_calls, timeout_s)
|
||
|
||
# Touch activity before launching workers so the gateway knows
|
||
# we're executing tools (not stuck).
|
||
agent._current_tool = tool_names_str
|
||
agent._touch_activity(f"executing {num_tools} tools concurrently: {tool_names_str}")
|
||
|
||
# Start spinner for CLI mode (skip when TUI handles tool progress)
|
||
spinner = None
|
||
if agent._should_emit_quiet_tool_messages() and agent._should_start_quiet_spinner():
|
||
face = random.choice(KawaiiSpinner.get_waiting_faces())
|
||
spinner = KawaiiSpinner(f"{face} ⚡ running {num_tools} tools concurrently", spinner_type='dots', print_fn=agent._print_fn)
|
||
spinner.start()
|
||
|
||
try:
|
||
batch.run()
|
||
finally:
|
||
if spinner:
|
||
finished = [r for r in batch.results if r is not None]
|
||
total_dur = sum(r.duration for r in finished)
|
||
spinner.stop(f"⚡ {len(finished)}/{num_tools} tools completed in {total_dur:.1f}s total")
|
||
|
||
if not _append_batch_results(agent, messages, effective_task_id, batch, _tool_budget):
|
||
return
|
||
if finalize:
|
||
_finalize_tool_batch(agent, messages, effective_task_id, len(parsed_calls), _tool_budget)
|
||
|
||
|
||
# ── Sequential dispatch ─────────────────────────────────────────────────────
|
||
|
||
|
||
def _start_quiet_tool_spinner(agent, function_name: str, function_args: dict, *, gate: bool = True, label: Optional[str] = None):
|
||
"""Start the quiet-mode kawaii spinner for one tool call, or return None.
|
||
|
||
``gate=False`` skips ``_should_start_quiet_spinner`` (context-engine tools always spin).
|
||
"""
|
||
if not agent._should_emit_quiet_tool_messages():
|
||
return None
|
||
if gate and not agent._should_start_quiet_spinner():
|
||
return None
|
||
face = random.choice(KawaiiSpinner.get_waiting_faces())
|
||
if label is None:
|
||
emoji = _get_tool_emoji(function_name)
|
||
display_args = _redact_tool_args_for_display(function_name, function_args) or function_args
|
||
label = f"{emoji} {_build_tool_label(function_name, display_args) or function_name}"
|
||
spinner = KawaiiSpinner(f"{face} {label}", spinner_type='dots', print_fn=agent._print_fn)
|
||
spinner.start()
|
||
return spinner
|
||
|
||
|
||
def _finish_quiet_tool_spinner(agent, spinner, function_name: str, function_args: dict, tool_duration: float, result) -> None:
|
||
"""Stop the spinner with the cute completion line, or print it when no spinner ran."""
|
||
if spinner:
|
||
spinner.stop(_get_cute_tool_message_impl(function_name, function_args, tool_duration, result=result))
|
||
elif agent._should_emit_quiet_tool_messages():
|
||
agent._vprint(f" {_get_cute_tool_message_impl(function_name, function_args, tool_duration, result=result)}")
|
||
|
||
|
||
def _delegate_spinner_label(function_args: dict) -> str:
|
||
_action_arg = str(function_args.get("action") or "").strip().lower()
|
||
tasks_arg = function_args.get("tasks")
|
||
if _action_arg in ("list", "steer", "stop"):
|
||
return f"🔀 subagent {_action_arg}"
|
||
if tasks_arg and isinstance(tasks_arg, list):
|
||
return f"🔀 delegating {len(tasks_arg)} tasks · (/agents to monitor)"
|
||
goal_preview = (function_args.get("goal") or "")[:30]
|
||
return (
|
||
f"🔀 {goal_preview} · (/agents to monitor)"
|
||
if goal_preview
|
||
else "🔀 delegating · (/agents to monitor)"
|
||
)
|
||
|
||
|
||
@dataclass
|
||
class _SequentialDispatch:
|
||
"""How one sequential call executes: the callable plus its spinner/error policy."""
|
||
|
||
execute: Callable[[dict], Any]
|
||
spinner: Any = None
|
||
# Passed through to the middleware runner; the registry closure reads this list.
|
||
middleware_trace_arg: Optional[list] = None
|
||
# None → exceptions propagate (inline / delegate tools own their failures).
|
||
error_result: Optional[Callable[[Exception], str]] = None
|
||
error_log: str = ""
|
||
handles_keyboard_interrupt: bool = False
|
||
is_delegate: bool = False
|
||
finish_spinner: bool = True
|
||
# Inline tools print their completion line only on success (no try/finally).
|
||
finish_in_finally: bool = True
|
||
|
||
|
||
def _resolve_sequential_dispatch(
|
||
agent,
|
||
*,
|
||
function_name: str,
|
||
function_args: dict,
|
||
messages: list,
|
||
effective_task_id: str,
|
||
tool_call_id: str,
|
||
middleware_trace: list,
|
||
) -> _SequentialDispatch:
|
||
"""Pick the execute callable for one sequential call and start its spinner.
|
||
|
||
Precedence is the historical if/elif order: inline agent-level tools, delegate_task,
|
||
context-engine tools, memory-provider tools, then the registry.
|
||
"""
|
||
if function_name != "delegate_task" and function_name in INLINE_TOOL_EXECUTORS:
|
||
# Agent-level tools that need live AIAgent state; table shared with invoke_tool.
|
||
inline_executor = INLINE_TOOL_EXECUTORS[function_name]
|
||
inline_ctx = InlineToolContext(
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
messages=messages,
|
||
)
|
||
return _SequentialDispatch(
|
||
execute=lambda next_args: inline_executor(agent, next_args, inline_ctx),
|
||
finish_in_finally=False,
|
||
)
|
||
if function_name == "delegate_task":
|
||
spinner = _start_quiet_tool_spinner(
|
||
agent, function_name, function_args, label=_delegate_spinner_label(function_args)
|
||
)
|
||
agent._delegate_spinner = spinner
|
||
return _SequentialDispatch(
|
||
execute=lambda next_args: agent._dispatch_delegate_task(next_args),
|
||
spinner=spinner,
|
||
is_delegate=True,
|
||
)
|
||
if agent._context_engine_tool_names and function_name in agent._context_engine_tool_names:
|
||
# Context engine tools (lcm_grep, lcm_describe, lcm_expand, etc.)
|
||
return _SequentialDispatch(
|
||
execute=lambda next_args: agent.context_compressor.handle_tool_call(function_name, next_args, messages=messages),
|
||
spinner=_start_quiet_tool_spinner(agent, function_name, function_args, gate=False),
|
||
error_result=lambda e: json.dumps({"error": f"Context engine tool '{function_name}' failed: {e}"}),
|
||
error_log="context_engine.handle_tool_call raised for %s: %s",
|
||
)
|
||
if agent._memory_manager and agent._memory_manager.has_tool(function_name):
|
||
# Memory provider tools (hindsight_retain, honcho_search, etc.) are not in the
|
||
# tool registry — route through MemoryManager.
|
||
return _SequentialDispatch(
|
||
execute=lambda next_args: agent._memory_manager.handle_tool_call(function_name, next_args),
|
||
spinner=_start_quiet_tool_spinner(agent, function_name, function_args),
|
||
error_result=lambda e: json.dumps({"error": f"Memory tool '{function_name}' failed: {e}"}),
|
||
error_log="memory_manager.handle_tool_call raised for %s: %s",
|
||
)
|
||
|
||
# Registry tools: post hook is owned by this executor (inner observer suppressed).
|
||
def _execute(next_args: dict) -> Any:
|
||
from model_tools import suppress_post_tool_call_hook
|
||
|
||
with suppress_post_tool_call_hook():
|
||
return _ra().handle_function_call(
|
||
function_name,
|
||
next_args,
|
||
effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
session_id=agent.session_id or "",
|
||
turn_id=getattr(agent, "_current_turn_id", "") or "",
|
||
api_request_id=getattr(agent, "_current_api_request_id", "")
|
||
or "",
|
||
enabled_tools=(
|
||
list(agent.valid_tool_names)
|
||
if agent.valid_tool_names
|
||
else None
|
||
),
|
||
skip_pre_tool_call_hook=True,
|
||
skip_tool_request_middleware=True,
|
||
skip_tool_execution_middleware=True,
|
||
tool_request_middleware_trace=list(middleware_trace),
|
||
enabled_toolsets=getattr(agent, "enabled_toolsets", None),
|
||
disabled_toolsets=getattr(agent, "disabled_toolsets", None),
|
||
)
|
||
|
||
return _SequentialDispatch(
|
||
execute=_execute,
|
||
spinner=_start_quiet_tool_spinner(agent, function_name, function_args) if agent.quiet_mode else None,
|
||
middleware_trace_arg=middleware_trace,
|
||
error_result=lambda e: f"Error executing tool '{function_name}': {e}",
|
||
error_log="handle_function_call raised for %s: %s",
|
||
handles_keyboard_interrupt=True,
|
||
finish_spinner=bool(agent.quiet_mode),
|
||
)
|
||
|
||
|
||
def execute_tool_calls_sequential(agent, assistant_message, messages: list, effective_task_id: str, api_call_count: int = 0, *, finalize: bool = True) -> None:
|
||
"""Execute tool calls sequentially (single calls or interactive tools).
|
||
|
||
``finalize=False`` skips end-of-batch budget enforcement and /steer injection (the
|
||
segmented dispatcher owns turn-end work).
|
||
"""
|
||
# Resolve the context-scaled tool-output budget once per turn, not per result.
|
||
_tool_budget = _budget_for_agent(agent)
|
||
tool_calls = assistant_message.tool_calls
|
||
|
||
for i, tool_call in enumerate(tool_calls, 1):
|
||
tool_call_id = _pairing_tool_call_id(tool_call)
|
||
if getattr(agent, "_incremental_persistence_failed", False):
|
||
return
|
||
# SAFETY: check interrupt BEFORE each tool so a "stop" during the previous
|
||
# tool skips all remaining ones.
|
||
if agent._interrupt_requested:
|
||
remaining_calls = tool_calls[i-1:]
|
||
if remaining_calls:
|
||
agent._vprint(f"{agent.log_prefix}⚡ Interrupt: skipping {len(remaining_calls)} tool call(s)", force=True)
|
||
if not _append_skipped_tool_results(
|
||
agent, messages, remaining_calls, effective_task_id,
|
||
content="[Tool execution cancelled — {name} was skipped due to user interrupt]",
|
||
hook_error_type="user_interrupt",
|
||
hook_id=lambda tc: getattr(tc, "id", "") or "",
|
||
flush_stage="cancelled tool result",
|
||
):
|
||
return
|
||
break
|
||
|
||
pc = _parse_tool_call(agent, tool_call, flatten_probe=True)
|
||
function_name, function_args = pc.name, pc.args
|
||
if pc.parse_error is not None:
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
result=pc.parse_error,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
status="error",
|
||
error_type="invalid_tool_arguments",
|
||
error_message="Tool arguments must be a valid JSON object",
|
||
)
|
||
messages.append(
|
||
make_tool_result_message(
|
||
function_name,
|
||
pc.parse_error,
|
||
tool_call_id,
|
||
)
|
||
)
|
||
if not _flush_session_db_after_tool_progress(
|
||
agent,
|
||
messages,
|
||
stage=f"invalid tool arguments {function_name}",
|
||
):
|
||
return
|
||
continue
|
||
|
||
middleware_trace: list[dict[str, Any]] = pc.middleware_trace
|
||
_execution_blocked = False
|
||
_execution_dispatched = False
|
||
|
||
tool_start_time = time.time()
|
||
|
||
# One bounded execution funnel for every runtime-tool branch; no duplicated
|
||
# timeout policy in the callbacks.
|
||
dispatch = _resolve_sequential_dispatch(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
messages=messages,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
middleware_trace=middleware_trace,
|
||
)
|
||
_spinner_result = None
|
||
try:
|
||
managed = _run_sequential_tool_execution_middleware(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
execute=dispatch.execute,
|
||
scope_block=pc.scope_block,
|
||
display_index=i,
|
||
middleware_trace=dispatch.middleware_trace_arg,
|
||
)
|
||
function_result = managed.result
|
||
function_args = managed.args
|
||
middleware_trace = managed.middleware_trace
|
||
_execution_blocked = managed.blocked
|
||
_execution_dispatched = managed.dispatched
|
||
_spinner_result = function_result
|
||
except KeyboardInterrupt:
|
||
if not dispatch.handles_keyboard_interrupt:
|
||
raise
|
||
function_result = _emit_cancelled_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
start_time=tool_start_time,
|
||
middleware_trace=list(middleware_trace),
|
||
)
|
||
_spinner_result = function_result
|
||
try:
|
||
agent.interrupt("keyboard interrupt")
|
||
except Exception:
|
||
pass
|
||
# Emit results for THIS and every remaining call before re-raising so
|
||
# the tool-call turn keeps matching results (alternation).
|
||
_append_skipped_tool_results(
|
||
agent, messages, tool_calls[i - 1:], effective_task_id,
|
||
content="[Tool execution cancelled — {name} was skipped due to keyboard interrupt]",
|
||
)
|
||
raise
|
||
except Exception as tool_error:
|
||
if dispatch.error_result is None:
|
||
raise
|
||
function_result = dispatch.error_result(tool_error)
|
||
logger.error(dispatch.error_log, function_name, tool_error, exc_info=True)
|
||
finally:
|
||
if dispatch.is_delegate:
|
||
agent._delegate_spinner = None
|
||
tool_duration = time.time() - tool_start_time
|
||
if dispatch.finish_spinner and dispatch.finish_in_finally:
|
||
_finish_quiet_tool_spinner(agent, dispatch.spinner, function_name, function_args, tool_duration, _spinner_result)
|
||
if dispatch.finish_spinner and not dispatch.finish_in_finally:
|
||
_finish_quiet_tool_spinner(agent, dispatch.spinner, function_name, function_args, tool_duration, _spinner_result)
|
||
|
||
_execution_timed_out = isinstance(
|
||
function_result, (_ToolTimeoutResult, _ToolCancelledResult)
|
||
)
|
||
# Multimodal dict results (_multimodal=True) are not sliceable as strings.
|
||
_result_len = len(function_result) if isinstance(function_result, str) else len(str(function_result))
|
||
|
||
# Log tool errors to the persistent error log so [error] tags
|
||
# in the UI always have a corresponding detailed entry on disk.
|
||
_is_error_result, _ = _detect_tool_failure(function_name, function_result)
|
||
# Inline-dispatched runtime tools never reach handle_function_call, so the
|
||
# executor owns the one terminal post_tool_call per tool_call_id (the inner
|
||
# observer is suppressed); also stops an abandoned timeout worker reporting late.
|
||
if not _execution_blocked and not _execution_timed_out:
|
||
_emit_terminal_post_tool_call(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
result=function_result,
|
||
effective_task_id=effective_task_id,
|
||
tool_call_id=tool_call_id,
|
||
duration_ms=int(tool_duration * 1000),
|
||
middleware_trace=list(middleware_trace),
|
||
)
|
||
function_result = _observe_tool_result(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
function_result=function_result,
|
||
tool_call_id=tool_call_id,
|
||
tool_duration=tool_duration,
|
||
is_error=_is_error_result,
|
||
blocked=_execution_blocked,
|
||
error_preview=lambda res: (
|
||
res if agent.verbose_logging or not isinstance(res, str)
|
||
else (res[:200] if len(res) > 200 else res)
|
||
),
|
||
success_log_chars=_result_len,
|
||
)
|
||
|
||
if agent.verbose_logging:
|
||
logging.debug("Tool %s completed in %.2fs", function_name, tool_duration)
|
||
_log_result = _multimodal_text_summary(function_result)
|
||
logging.debug("Tool result (%d chars): %s", len(_log_result), _log_result)
|
||
|
||
committed = _commit_tool_result(
|
||
agent,
|
||
messages,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
function_result=function_result,
|
||
tool_call_id=tool_call_id,
|
||
effective_task_id=effective_task_id,
|
||
budget=_tool_budget,
|
||
tool_duration=tool_duration,
|
||
is_error=_is_error_result,
|
||
blocked=_execution_blocked,
|
||
effect_disposition="unknown" if _execution_timed_out else None,
|
||
)
|
||
if committed is None:
|
||
return
|
||
function_result, display_function_result, risk_metadata = committed
|
||
|
||
_emit_tool_complete_and_risk(
|
||
agent,
|
||
function_name=function_name,
|
||
function_args=function_args,
|
||
tool_call_id=tool_call_id,
|
||
result=display_function_result,
|
||
risk_metadata=risk_metadata,
|
||
blocked=_execution_blocked,
|
||
)
|
||
|
||
if _tool_progress_enabled(agent):
|
||
_print_tool_completed(agent, i, tool_duration, function_result)
|
||
|
||
if agent._interrupt_requested and i < len(tool_calls):
|
||
remaining = len(tool_calls) - i
|
||
agent._vprint(f"{agent.log_prefix}⚡ Interrupt: skipping {remaining} remaining tool call(s)", force=True)
|
||
if not _append_skipped_tool_results(
|
||
agent, messages, tool_calls[i:], effective_task_id,
|
||
content="[Tool execution skipped — {name} was not started. User sent a new message]",
|
||
flush_stage="skipped tool result",
|
||
):
|
||
return
|
||
break
|
||
|
||
if finalize:
|
||
_finalize_tool_batch(agent, messages, effective_task_id, len(tool_calls), _tool_budget)
|
||
|
||
|
||
def execute_tool_calls_segmented(agent, assistant_message, messages: list, effective_task_id: str, api_call_count: int = 0, segments=None) -> None:
|
||
"""Execute a mixed batch as ordered parallel/sequential segments.
|
||
|
||
``segments`` is the ``(kind, calls)`` plan from ``_plan_tool_batch_segments``;
|
||
contiguous segments preserve per-call result order and barrier boundaries exactly
|
||
as fully-sequential execution. Turn-end work (budget + /steer) runs once here;
|
||
segment executors run with ``finalize=False``. Each segment executor checks the
|
||
interrupt flag up front, so an interrupt drains later segments with one result per call.
|
||
"""
|
||
from types import SimpleNamespace
|
||
|
||
if segments is None:
|
||
_active_env = get_active_env(effective_task_id)
|
||
_exec_cwd = Path(_active_env.cwd) if _active_env is not None and _active_env.cwd else None
|
||
segments = _plan_tool_batch_segments(assistant_message.tool_calls, execution_cwd=_exec_cwd)
|
||
|
||
for kind, calls in segments:
|
||
if getattr(agent, "_incremental_persistence_failed", False):
|
||
return
|
||
segment_message = SimpleNamespace(tool_calls=list(calls))
|
||
run_segment = execute_tool_calls_concurrent if kind == "parallel" else execute_tool_calls_sequential
|
||
run_segment(
|
||
agent, segment_message, messages, effective_task_id, api_call_count,
|
||
finalize=False,
|
||
)
|
||
if getattr(agent, "_incremental_persistence_failed", False):
|
||
return
|
||
|
||
total_tools = len(assistant_message.tool_calls)
|
||
if total_tools > 0:
|
||
_finalize_tool_batch(agent, messages, effective_task_id, total_tools, _budget_for_agent(agent))
|
||
|
||
|
||
__all__ = [
|
||
"execute_tool_calls_concurrent",
|
||
"execute_tool_calls_sequential",
|
||
"execute_tool_calls_segmented",
|
||
]
|