- image_routing: capability probes -> _VISION_PROBES ordered table; magic-byte sniffing -> _MAGIC signature table; bool tokens -> dict; shared code-span / file-existence helpers for extract_image_refs. Fixture-corpus diff base vs new identical. - inline_tool_executors: 11 hand-written executor bodies -> _tool/_callback_tool arg-spec factories (kwargs mapping unchanged; corpus of calls identical). - file_safety: unify _is_under/_under_any, _resolve_target/_resolve_each, _mirror_info; deny-list tables compacted; drop retired get_cross_profile_warning stub (+ its tests). Every rule preserved (corpus). - image_gen_provider: drop _images_cache_dir (test-only wrapper), compact. - estop/delegation_context/kanban_stop/image_gen_registry: defensive-layer collapse and docstring compaction. Tool schema dump byte-identical to base.
221 lines
9.2 KiB
Python
221 lines
9.2 KiB
Python
"""Agent-level ("inline") tool executors shared by the sequential and concurrent tool paths.
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These tools need live ``AIAgent`` state (stores, callbacks, session DB) and therefore
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bypass the tool registry. Each executor is ``fn(agent, args, ctx) -> result``; the
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table replaces two hand-maintained if/elif chains (``invoke_tool`` and
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``execute_tool_calls_sequential``) that had drifted apart. Tool modules are imported
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lazily at call time so ``patch("tools.x.y")`` in tests keeps working.
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"""
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from __future__ import annotations
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import json
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from dataclasses import dataclass
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from importlib import import_module
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from typing import Any, Callable, Dict, Optional, Tuple
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def tool_hook_ids(agent, effective_task_id: str, tool_call_id: Optional[str]) -> Dict[str, str]:
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"""Identity kwargs every tool hook/middleware call carries (all coerced to ``""``)."""
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return {
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"task_id": effective_task_id or "",
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"session_id": getattr(agent, "session_id", "") or "",
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"tool_call_id": tool_call_id or "",
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"turn_id": getattr(agent, "_current_turn_id", "") or "",
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"api_request_id": getattr(agent, "_current_api_request_id", "") or "",
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}
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def emit_terminal_post_tool_call(
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agent,
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*,
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function_name: str,
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function_args: dict,
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result: Any,
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effective_task_id: str,
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tool_call_id: Optional[str],
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duration_ms: int = 0,
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status: Optional[str] = None,
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error_type: Optional[str] = None,
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error_message: Optional[str] = None,
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middleware_trace: Optional[list] = None,
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) -> None:
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"""Emit the one terminal ``post_tool_call`` hook for a tool_call_id (best-effort)."""
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try:
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from model_tools import _emit_post_tool_call_hook
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_emit_post_tool_call_hook(
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function_name=function_name,
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function_args=function_args,
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result=result,
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**tool_hook_ids(agent, effective_task_id, tool_call_id),
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duration_ms=duration_ms,
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status=status,
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error_type=error_type,
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error_message=error_message,
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middleware_trace=list(middleware_trace or []),
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)
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except Exception:
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pass
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@dataclass
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class InlineToolContext:
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"""Per-call state an inline executor may need beyond its arguments."""
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effective_task_id: str
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tool_call_id: Optional[str] = None
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messages: Optional[list] = None
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InlineToolExecutor = Callable[[Any, dict, InlineToolContext], Any]
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# ``(kwarg, args_key)`` → ``args.get(key)``; ``(kwarg, args_key, default)`` → ``args.get(key, default)``.
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_ArgSpec = Tuple[Any, ...]
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def _call_tool(module: str, func: str, args: dict, arg_specs: Tuple[_ArgSpec, ...], **fixed: Any) -> Any:
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"""Import ``module.func`` lazily and call it with args mapped per ``arg_specs`` plus ``fixed``."""
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fn = getattr(import_module(module), func)
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return fn(**{spec[0]: args.get(*spec[1:]) for spec in arg_specs}, **fixed)
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def _tool(
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module: str, func: str, *arg_specs: _ArgSpec, **fixed: Callable[[Any, InlineToolContext], Any],
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) -> InlineToolExecutor:
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"""Executor calling ``module.func`` with mapped args plus ``fixed`` kwargs computed from ``(agent, ctx)``."""
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def _exec(agent, args: dict, ctx: InlineToolContext) -> Any:
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return _call_tool(module, func, args, arg_specs, **{k: f(agent, ctx) for k, f in fixed.items()})
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return _exec
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def _callback_tool(module: str, func: str, callback_attr: str, *arg_specs: _ArgSpec) -> InlineToolExecutor:
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"""Executor for a GUI-callback tool: mapped args plus ``callback=getattr(agent, callback_attr, None)``."""
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return _tool(module, func, *arg_specs, callback=lambda agent, ctx: getattr(agent, callback_attr, None))
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def _session_search(agent, args: dict, ctx: InlineToolContext) -> Any:
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session_db = agent._get_session_db_for_recall()
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if not session_db:
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from hermes_state import format_session_db_unavailable
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return json.dumps({"success": False, "error": format_session_db_unavailable()})
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return _call_tool(
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"tools.session_search_tool", "session_search", args,
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(
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("query", "query", ""), ("role_filter", "role_filter"), ("limit", "limit", 3),
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("session_id", "session_id"), ("around_message_id", "around_message_id"),
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("window", "window", 5), ("sort", "sort"), ("detail", "detail", "adaptive"),
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),
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db=session_db, current_session_id=agent.session_id,
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)
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def _memory(agent, args: dict, ctx: InlineToolContext) -> Any:
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result = _call_tool(
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"tools.memory_tool", "memory_tool", args,
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(
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("action", "action"), ("target", "target", "memory"), ("content", "content"),
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("old_text", "old_text"), ("operations", "operations"),
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),
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store=agent._memory_store,
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)
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# Mirror built-in memory writes to external providers; gating lives in
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# MemoryManager.notify_memory_tool_write.
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if agent._memory_manager:
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agent._memory_manager.notify_memory_tool_write(
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result,
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args,
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build_metadata=lambda: agent._build_memory_write_metadata(
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task_id=ctx.effective_task_id,
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tool_call_id=ctx.tool_call_id,
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),
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)
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return result
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_read_preview = _callback_tool(
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"tools.read_preview_tool", "read_preview_tool", "read_preview_callback",
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("start", "start"), ("count", "count"),
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)
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def _desktop_preview(agent, args: dict, ctx: InlineToolContext) -> Any:
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# action=read needs the GUI callback (agent-level); open/close go through the
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# registry handler like any other tool.
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if (args.get("action") or "").strip() == "read":
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return _read_preview(agent, args, ctx)
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from tools.preview_tool import _handle_preview
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return _handle_preview(args)
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# Order is the historical if/elif order of ``execute_tool_calls_sequential``.
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INLINE_TOOL_EXECUTORS: Dict[str, InlineToolExecutor] = {
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"todo_list": _tool(
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"tools.todo_tool", "todo_tool", ("todos", "todos"), ("merge", "merge", False),
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store=lambda agent, ctx: agent._todo_store,
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),
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# Bot Mode teammate DM is injected, not registered: only a canonical Bot
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# Chat session carries the schema, and the tool re-gates on the title.
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"message_agent": _tool(
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"tools.bot_mode_dm", "message_agent_tool", ("target", "target", ""), ("message", "message", ""),
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task_id=lambda agent, ctx: ctx.effective_task_id, agent=lambda agent, ctx: agent,
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),
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"session_search": _session_search,
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"memory": _memory,
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"clarify": _tool(
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"tools.clarify_tool", "clarify_tool",
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("question", "question", ""), ("choices", "choices"), ("multi_select", "multi_select", False),
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("questions", "questions"),
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callback=lambda agent, ctx: agent.clarify_callback,
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),
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"read_terminal": _callback_tool(
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"tools.read_terminal_tool", "read_terminal_tool", "read_terminal_callback",
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("start_line", "start_line"), ("count", "count"),
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),
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"desktop_preview": _desktop_preview,
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"drive_preview": _callback_tool(
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"tools.drive_preview_tool", "drive_preview_tool", "drive_preview_callback",
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("action", "action", ""), ("ref", "ref"), ("selector", "selector"), ("text", "text"),
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("key", "key"), ("submit", "submit"), ("amount", "amount"), ("to", "to"), ("limit", "max"),
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),
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"annotate_preview": _callback_tool(
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"tools.annotate_preview_tool", "annotate_preview_tool", "drive_preview_callback",
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("action", "action", "add"), ("ref", "ref"), ("selector", "selector"), ("label", "label"),
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),
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"read_window_below": _callback_tool(
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"tools.read_window_tool", "read_window_below_tool", "read_window_below_callback",
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),
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"gui_tour": _callback_tool(
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"tools.tour_tool", "tour_tool", "tour_callback",
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("action", "action", ""), ("surface", "surface"), ("selector", "selector"), ("title", "title"),
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("text", "text"), ("side", "side"), ("steps", "steps"), ("step_index", "step_index"),
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),
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"setup_mcp": _callback_tool(
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"tools.setup_mcp_tool", "setup_mcp_tool", "setup_mcp_callback",
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("server", "server", ""), ("action", "action", "install"), ("reason", "reason", ""),
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),
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"delegate_task": lambda agent, args, ctx: agent._dispatch_delegate_task(args),
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}
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# ``invoke_tool`` (concurrent path) consults the memory manager right after these three
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# names and before the remaining inline tools; ``message_agent`` falls through to the
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# registry there (Bot Mode DM is only injected into the sequential path's schema).
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INVOKE_TOOL_PRE_MEMORY_MANAGER_NAMES = frozenset({"todo_list", "session_search", "memory"})
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def resolve_invoke_tool_executor(agent, function_name: str) -> Optional[InlineToolExecutor]:
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"""Inline executor for ``invoke_tool`` (concurrent path), or None for registry dispatch.
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Precedence: todo_list/session_search/memory, then memory-manager tools, then the
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remaining inline tools (``message_agent`` excluded).
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"""
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if function_name in INVOKE_TOOL_PRE_MEMORY_MANAGER_NAMES:
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return INLINE_TOOL_EXECUTORS[function_name]
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memory_manager = agent._memory_manager
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if memory_manager and memory_manager.has_tool(function_name):
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return lambda agent, args, ctx: agent._memory_manager.handle_tool_call(function_name, args)
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if function_name == "message_agent":
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return None
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return INLINE_TOOL_EXECUTORS.get(function_name)
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