315 lines
15 KiB
Python
315 lines
15 KiB
Python
import logging
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from langchain.tools import BaseTool
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from deerflow.config import get_app_config
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from deerflow.config.app_config import AppConfig
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from deerflow.reflection import resolve_variable
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from deerflow.sandbox.security import is_host_bash_allowed
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from deerflow.tools.builtins import agent_orchestration_tool, ask_clarification_tool, memory_tool, present_file_tool, scheduled_task_tool, task_tool, view_image_tool
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from deerflow.tools.builtins.tool_search import reset_deferred_registry
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logger = logging.getLogger(__name__)
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BROWSER_CONTEXT_TOOL_USE = "deerflow.tools.builtins.browser_context_tool:browser_fetch_page_tool"
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BROWSER_ACT_TOOL_USE = "deerflow.tools.builtins.browser_act_tool:browser_act_tool"
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BROWSER_CONTEXT_TOOL_USES = {BROWSER_CONTEXT_TOOL_USE, BROWSER_ACT_TOOL_USE}
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BROWSER_CONTEXT_TOOL_NAMES = {"browser_fetch_page", "browser_act"}
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BUILTIN_TOOLS = [
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present_file_tool,
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ask_clarification_tool,
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]
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SUBAGENT_TOOLS = [
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task_tool,
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# task_status_tool is no longer exposed to LLM (backend handles polling internally)
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]
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def _is_host_bash_tool(tool: object) -> bool:
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"""Return True if the tool config represents a host-bash execution surface."""
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group = getattr(tool, "group", None)
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use = getattr(tool, "use", None)
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if group == "bash":
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return True
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if use == "deerflow.sandbox.tools:bash_tool":
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return True
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return False
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def _is_browser_context_tool(tool: object) -> bool:
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"""Return True if the tool config represents the browser extension bridge."""
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use = getattr(tool, "use", None)
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name = getattr(tool, "name", None)
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return use in BROWSER_CONTEXT_TOOL_USES or name in BROWSER_CONTEXT_TOOL_NAMES
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def _enforce_agent_orchestration_scope(
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tools: list[BaseTool],
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*,
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allow_agent_orchestration: bool,
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) -> list[BaseTool]:
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"""Fail closed: only an explicitly authorized coordinator may receive orchestration."""
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if allow_agent_orchestration:
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return tools
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return [tool for tool in tools if tool.name != "agent_orchestration"]
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def get_available_tools(
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groups: list[str] | None = None,
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include_mcp: bool = True,
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model_name: str | None = None,
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subagent_enabled: bool = False,
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is_scheduled_run: bool = False,
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excluded_tools: list[str] | None = None,
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*,
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allow_agent_orchestration: bool = False,
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app_config: AppConfig | None = None,
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) -> list[BaseTool]:
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"""Get all available tools from config.
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Note: MCP tools should be initialized at application startup using
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`initialize_mcp_tools()` from deerflow.mcp module.
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Args:
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groups: Optional list of tool groups to filter by.
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include_mcp: Whether to include tools from MCP servers (default: True).
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model_name: Optional model name to determine if vision tools should be included.
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subagent_enabled: Whether to include subagent tools (task, task_status).
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excluded_tools: Optional list of tool names to exclude from the result
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(applied AFTER all other resolution). Takes precedence over
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``app_config.excluded_tools``.
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allow_agent_orchestration: Explicit coordinator-only capability gate. Defaults to
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``False`` so ordinary agents and all indirect callers fail closed.
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Returns:
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List of available tools.
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"""
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config = app_config or get_app_config()
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selected_tool_configs = [tool for tool in config.tools if groups is None or tool.group in groups]
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disabled_tool_names = [tool.name for tool in selected_tool_configs if not tool.enabled]
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if disabled_tool_names:
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logger.info("Skipping disabled configured tool(s): %s", disabled_tool_names)
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tool_configs = [tool for tool in selected_tool_configs if tool.enabled]
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browser_context_config = getattr(config, "browser_context", None)
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if not getattr(browser_context_config, "enabled", False):
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tool_configs = [tool for tool in tool_configs if not _is_browser_context_tool(tool)]
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elif not getattr(browser_context_config, "actions_enabled", True):
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# browser_context is on, but interactive page actions are disabled — keep
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# the read-only browser_fetch_page tool, drop only browser_act.
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tool_configs = [
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tool
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for tool in tool_configs
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if getattr(tool, "use", None) != BROWSER_ACT_TOOL_USE and getattr(tool, "name", None) != "browser_act"
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]
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# Do not expose host bash by default when LocalSandboxProvider is active.
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if not is_host_bash_allowed(config):
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tool_configs = [tool for tool in tool_configs if not _is_host_bash_tool(tool)]
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loaded_tools_raw = [(cfg, resolve_variable(cfg.use, BaseTool)) for cfg in tool_configs]
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# Warn when the config ``name`` field and the tool object's ``.name``
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# attribute diverge — this mismatch is the root cause of issue #1803 where
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# the LLM receives one name in its tool schema but the runtime router
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# recognises a different name, producing "not a valid tool" errors.
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for cfg, loaded in loaded_tools_raw:
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if cfg.name != loaded.name:
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logger.warning(
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"Tool name mismatch: config name %r does not match tool .name %r (use: %s). The tool's own .name will be used for binding.",
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cfg.name,
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loaded.name,
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cfg.use,
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)
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loaded_tools = [t for _, t in loaded_tools_raw]
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# Conditionally add tools based on config
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builtin_tools = BUILTIN_TOOLS.copy()
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if allow_agent_orchestration:
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builtin_tools.append(agent_orchestration_tool)
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if not is_scheduled_run:
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builtin_tools.append(scheduled_task_tool)
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# Memory V2:记忆与 builtin provider 都启用时,暴露 memory 工具给 LLM 主动写入
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memory_config = getattr(config, "memory", None)
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if memory_config is not None and getattr(memory_config, "enabled", False):
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builtin_config = getattr(memory_config, "builtin", None)
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if builtin_config is not None and getattr(builtin_config, "enabled", False):
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builtin_tools.append(memory_tool)
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logger.info("Including memory tool (Memory V2 builtin provider enabled)")
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# Hindsight 在 tools / hybrid 模式下,额外暴露 3 个 Hindsight 工具
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if getattr(memory_config, "provider", "builtin") == "hindsight":
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hindsight_config = getattr(memory_config, "hindsight", None)
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memory_mode = getattr(hindsight_config, "memory_mode", "context") if hindsight_config else "context"
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if memory_mode in ("tools", "hybrid"):
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from deerflow.tools.builtins.hindsight_tools import HINDSIGHT_TOOLS
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builtin_tools.extend(HINDSIGHT_TOOLS)
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logger.info("Including Hindsight tools (memory_mode=%s)", memory_mode)
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skill_evolution_config = getattr(config, "skill_evolution", None)
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# skill_list / skill_view 是只读工具(发现、查看技能),与"自我进化"写能力无关,
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# 始终提供给 agent。
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from deerflow.tools.builtins.skill_tools import skill_list_tool, skill_view_tool
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builtin_tools.extend([skill_list_tool, skill_view_tool])
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# search_skills —— 仅当管理员开启"技能压缩"时提供。压缩开启后,非常驻技能不再
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# 全文注入系统提示词,agent 通过该关键词检索工具按需调出(纯关键词、离线、确定性)。
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try:
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from deerflow.config.system_settings import get_skill_compression_settings
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if get_skill_compression_settings().enabled:
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from deerflow.tools.builtins.skill_tools import search_skills_tool
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builtin_tools.append(search_skills_tool)
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except Exception: # noqa: BLE001 - 读取设置失败不能阻断 agent 构建
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logger.debug("Failed to evaluate skill compression setting for search_skills tool", exc_info=True)
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# read_peer_delivery —— 圆桌席位「按需读取前序席位完整交付」的只读工具(从 run context
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# 取网关注入的全文,非圆桌场景为空 → 工具自述「无」)。始终提供(只读、无副作用);圆桌
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# 总控/报告角色由 run policy 显式排除,避免干扰它们。
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from deerflow.tools.builtins.roundtable_peers_tool import read_peer_delivery_tool
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builtin_tools.append(read_peer_delivery_tool)
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# Conditional LLMWiki mode: the tool is absent when no effective WeKnora
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# address is configured, keeping legacy deployments behavior-identical.
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try:
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from deerflow.integrations.weknora.runtime import get_resolved_llmwiki_runtime
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if get_resolved_llmwiki_runtime(config).weknora_enabled:
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from deerflow.tools.builtins.llmwiki_search_tool import llmwiki_search_tool
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builtin_tools.append(llmwiki_search_tool)
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except Exception: # noqa: BLE001 - configuration/store failures must not block agent creation
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logger.debug("Failed to evaluate the conditional LLMWiki search tool", exc_info=True)
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# skill_manage 能创建/修改/删除技能,属于"自我进化"写能力,按 skill_evolution.enabled
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# 门控。该开关用户可在 per-user 配置里覆盖,所以按"生效配置(含 per-user 覆盖)"判断 ——
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# Gateway 每次 run 重建 agent,用户改了配置下次 run 即生效;解析失败退回全局 config.yaml。
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try:
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from deerflow.config.skill_evolution_runtime import load_skill_evolution_config_for_user
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from deerflow.runtime.user_context import get_effective_user_id
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skill_evolution_config = load_skill_evolution_config_for_user(get_effective_user_id())
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except Exception: # noqa: BLE001 - 解析失败不能阻断 agent 构建
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skill_evolution_config = getattr(config, "skill_evolution", None)
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if getattr(skill_evolution_config, "enabled", False):
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from deerflow.tools.skill_manage_tool import skill_manage_tool
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builtin_tools.append(skill_manage_tool)
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# Add subagent tools only if enabled via runtime parameter
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if subagent_enabled:
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builtin_tools.extend(SUBAGENT_TOOLS)
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logger.info("Including subagent tools (task)")
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# If no model_name specified, use the first model (default)
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if model_name is None and config.models:
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model_name = config.models[0].name
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# Add view_image_tool when vision is available — either the main model
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# supports vision natively, or a dedicated vision model is configured
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# (vision.model_name) so recognition can be delegated to it.
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from deerflow.models.vision import vision_enabled
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if vision_enabled(model_name, app_config=config):
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builtin_tools.append(view_image_tool)
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logger.info(f"Including view_image_tool for model '{model_name}' (vision available)")
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# Get cached MCP tools if enabled
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# NOTE: We use ExtensionsConfig.from_file() instead of config.extensions
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# to always read the latest configuration from disk. This ensures that changes
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# made through the Gateway API (which runs in a separate process) are immediately
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# reflected when loading MCP tools.
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mcp_tools = []
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# Reset deferred registry upfront to prevent stale state from previous calls
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reset_deferred_registry()
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if include_mcp:
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try:
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from deerflow.config.extensions_config import ExtensionsConfig
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from deerflow.mcp.cache import get_cached_mcp_tools
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extensions_config = ExtensionsConfig.from_file()
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if extensions_config.get_enabled_mcp_servers():
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mcp_tools = get_cached_mcp_tools()
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if mcp_tools:
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logger.info(f"Using {len(mcp_tools)} cached MCP tool(s)")
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# When tool_search is enabled, register MCP tools in the
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# deferred registry and add tool_search to builtin tools.
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if config.tool_search.enabled:
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from deerflow.tools.builtins.tool_search import DeferredToolRegistry, set_deferred_registry
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from deerflow.tools.builtins.tool_search import tool_search as tool_search_tool
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registry = DeferredToolRegistry()
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for t in mcp_tools:
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registry.register(t)
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set_deferred_registry(registry)
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builtin_tools.append(tool_search_tool)
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logger.info(f"Tool search active: {len(mcp_tools)} tools deferred")
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except ImportError:
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logger.warning("MCP module not available. Install 'langchain-mcp-adapters' package to enable MCP tools.")
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except Exception as e:
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logger.error(f"Failed to get cached MCP tools: {e}")
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# Add invoke_acp_agent tool if any ACP agents are configured
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acp_tools: list[BaseTool] = []
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try:
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from deerflow.tools.builtins.invoke_acp_agent_tool import build_invoke_acp_agent_tool
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if app_config is None:
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from deerflow.config.acp_config import get_acp_agents
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acp_agents = get_acp_agents()
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else:
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acp_agents = getattr(config, "acp_agents", {}) or {}
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if acp_agents:
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acp_tools.append(build_invoke_acp_agent_tool(acp_agents))
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logger.info(f"Including invoke_acp_agent tool ({len(acp_agents)} agent(s): {list(acp_agents.keys())})")
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except Exception as e:
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logger.warning(f"Failed to load ACP tool: {e}")
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logger.info(f"Total tools loaded: {len(loaded_tools)}, built-in tools: {len(builtin_tools)}, MCP tools: {len(mcp_tools)}, ACP tools: {len(acp_tools)}")
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# Deduplicate by tool name — config-loaded tools take priority, followed by
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# built-ins, MCP tools, and ACP tools. Duplicate names cause the LLM to
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# receive ambiguous or concatenated function schemas (issue #1803).
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all_tools = loaded_tools + builtin_tools + mcp_tools + acp_tools
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seen_names: set[str] = set()
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unique_tools: list[BaseTool] = []
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for t in all_tools:
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if t.name not in seen_names:
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unique_tools.append(t)
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seen_names.add(t.name)
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else:
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logger.warning(
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"Duplicate tool name %r detected and skipped — check your config.yaml and MCP server registrations (issue #1803).",
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t.name,
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)
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# Drop tools the caller (or config) wants excluded. Request-level
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# ``excluded_tools`` wins; the config-level list is the static fallback.
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effective_excluded = excluded_tools if excluded_tools else getattr(config, "excluded_tools", None) or []
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if effective_excluded:
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excluded_set = set(effective_excluded)
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filtered_tools = [t for t in unique_tools if t.name not in excluded_set]
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if len(filtered_tools) < len(unique_tools):
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logger.info(
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"Excluded %d tool(s) by request/config: %s",
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len(unique_tools) - len(filtered_tools),
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effective_excluded,
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)
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unique_tools = filtered_tools
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# Defense in depth: a config/MCP tool with the reserved name must not bypass the builtin gate.
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return _enforce_agent_orchestration_scope(
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unique_tools,
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allow_agent_orchestration=allow_agent_orchestration,
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)
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