feat: Introduce unified tooling system for plugins and MCP
- Added a new `tooling` module to define a unified model for tool declarations, invocations, and execution results, facilitating compatibility between plugins, legacy actions, and MCP tools. - Implemented `ToolProvider` interface for various tool providers including built-in tools, MCP tools, and plugin runtime tools. - Enhanced `MCPManager` and `MCPConnection` to support unified tool invocation and execution results. - Updated `ComponentRegistry` and related classes to accommodate the new tool specifications and descriptions. - Refactored existing components to utilize the new tooling system, ensuring backward compatibility with legacy actions. - Improved error handling and logging for tool invocations across different providers.
This commit is contained in:
DrSmoothl
@@ -1,124 +1,163 @@
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"""
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MaiSaka built-in tool definitions.
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"""
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"""Maisaka 内置工具声明。"""
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from typing import List
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from copy import deepcopy
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from typing import Any, Dict, List
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from src.llm_models.payload_content.tool_option import ToolOption, ToolParamType
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from src.core.tooling import ToolSpec, build_tool_detailed_description
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from src.llm_models.payload_content.tool_option import ToolDefinitionInput
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def create_builtin_tools() -> List[ToolOption]:
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"""Create built-in tools exposed to the main chat-loop model."""
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from src.llm_models.payload_content.tool_option import ToolOptionBuilder
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def _build_tool_spec(
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name: str,
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brief_description: str,
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parameters_schema: Dict[str, Any] | None = None,
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detailed_description: str = "",
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) -> ToolSpec:
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"""构建单个内置工具声明。
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tools: List[ToolOption] = []
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Args:
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name: 工具名称。
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brief_description: 简要描述。
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parameters_schema: 参数 Schema。
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detailed_description: 详细描述；为空时自动根据参数生成。
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wait_builder = ToolOptionBuilder()
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wait_builder.set_name("wait")
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wait_builder.set_description("Pause speaking and wait for the user to provide more input.")
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wait_builder.add_param(
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name="seconds",
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param_type=ToolParamType.INTEGER,
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description="How many seconds to wait before timing out.",
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required=True,
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enum_values=None,
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Returns:
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ToolSpec: 构建完成的工具声明。
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"""
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normalized_schema = deepcopy(parameters_schema) if parameters_schema is not None else None
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return ToolSpec(
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name=name,
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brief_description=brief_description,
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detailed_description=(
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detailed_description.strip()
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or build_tool_detailed_description(normalized_schema)
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),
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parameters_schema=normalized_schema,
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provider_name="maisaka_builtin",
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provider_type="builtin",
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)
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tools.append(wait_builder.build())
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reply_builder = ToolOptionBuilder()
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reply_builder.set_name("reply")
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reply_builder.set_description(
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"Generate and emit a visible reply based on the current thought. "
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"You must specify the target user msg_id to reply to."
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)
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reply_builder.add_param(
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name="msg_id",
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param_type=ToolParamType.STRING,
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description="The msg_id of the specific user message that this reply should target.",
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required=True,
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enum_values=None,
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)
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reply_builder.add_param(
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name="quote",
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param_type=ToolParamType.BOOLEAN,
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description="Whether the visible reply should be sent as a quoted reply to the target msg_id.",
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required=False,
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enum_values=None,
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)
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reply_builder.add_param(
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name="unknown_words",
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param_type=ToolParamType.ARRAY,
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description="Optional list of words or phrases that may need jargon lookup before replying.",
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required=False,
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enum_values=None,
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items_schema={"type": "string"},
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)
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tools.append(reply_builder.build())
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query_jargon_builder = ToolOptionBuilder()
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query_jargon_builder.set_name("query_jargon")
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query_jargon_builder.set_description(
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"Query the meanings of one or more jargon words in the current chat context."
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)
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query_jargon_builder.add_param(
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name="words",
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param_type=ToolParamType.ARRAY,
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description="A list of words or phrases to query from the jargon store.",
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required=True,
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enum_values=None,
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items_schema={"type": "string"},
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)
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tools.append(query_jargon_builder.build())
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query_person_info_builder = ToolOptionBuilder()
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query_person_info_builder.set_name("query_person_info")
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query_person_info_builder.set_description(
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"Query profile and memory information about a specific person by person name, nickname, or user ID."
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)
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query_person_info_builder.add_param(
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name="person_name",
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param_type=ToolParamType.STRING,
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description="The person's name, nickname, or user ID to search for.",
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required=True,
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enum_values=None,
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)
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query_person_info_builder.add_param(
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name="limit",
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param_type=ToolParamType.INTEGER,
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description="Maximum number of matched person records to return. Defaults to 3.",
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required=False,
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enum_values=None,
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)
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tools.append(query_person_info_builder.build())
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no_reply_builder = ToolOptionBuilder()
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no_reply_builder.set_name("no_reply")
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no_reply_builder.set_description("Do not emit a visible reply this round and continue thinking.")
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tools.append(no_reply_builder.build())
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stop_builder = ToolOptionBuilder()
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stop_builder.set_name("stop")
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stop_builder.set_description("Stop the current inner loop and return control to the outer chat flow.")
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tools.append(stop_builder.build())
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send_emoji_builder = ToolOptionBuilder()
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send_emoji_builder.set_name("send_emoji")
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send_emoji_builder.set_description(
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"Send an emoji sticker to help express emotions. "
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"You should specify the emotion type to select an appropriate emoji."
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)
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send_emoji_builder.add_param(
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name="emotion",
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param_type=ToolParamType.STRING,
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description="The emotion type for selecting an appropriate emoji (e.g., 'happy', 'sad', 'angry', 'surprised', etc.).",
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required=False,
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enum_values=None,
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)
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tools.append(send_emoji_builder.build())
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return tools
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def get_builtin_tools() -> List[ToolOption]:
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"""Return built-in tools."""
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return create_builtin_tools()
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def create_builtin_tool_specs() -> List[ToolSpec]:
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"""创建 Maisaka 内置工具声明列表。
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Returns:
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List[ToolSpec]: 内置工具声明列表。
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"""
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return [
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_build_tool_spec(
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name="wait",
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brief_description="暂停当前对话并等待用户新的输入。",
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parameters_schema={
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"type": "object",
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"properties": {
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"seconds": {
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"type": "integer",
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"description": "等待的秒数。",
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},
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},
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"required": ["seconds"],
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},
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),
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_build_tool_spec(
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name="reply",
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brief_description="根据当前思考生成并发送一条可见回复。",
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parameters_schema={
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"type": "object",
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"properties": {
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"msg_id": {
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"type": "string",
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"description": "要回复的目标用户消息编号。",
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},
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"quote": {
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"type": "boolean",
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"description": "是否以引用回复的方式发送。",
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"default": True,
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},
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"unknown_words": {
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"type": "array",
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"description": "回复前可能需要查询的黑话或词条列表。",
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"items": {"type": "string"},
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},
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},
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"required": ["msg_id"],
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},
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),
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_build_tool_spec(
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name="query_jargon",
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brief_description="查询当前聊天上下文中的黑话或词条含义。",
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parameters_schema={
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"type": "object",
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"properties": {
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"words": {
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"type": "array",
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"description": "要查询的词条列表。",
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"items": {"type": "string"},
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},
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},
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"required": ["words"],
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},
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),
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_build_tool_spec(
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name="query_person_info",
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brief_description="查询某个人的档案和相关记忆信息。",
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parameters_schema={
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"type": "object",
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"properties": {
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"person_name": {
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"type": "string",
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"description": "人物名称、昵称或用户 ID。",
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},
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"limit": {
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"type": "integer",
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"description": "最多返回多少条匹配记录。",
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"default": 3,
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},
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},
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"required": ["person_name"],
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},
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),
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_build_tool_spec(
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name="no_reply",
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brief_description="本轮不发送可见回复，继续下一步思考。",
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),
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_build_tool_spec(
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name="stop",
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brief_description="暂停当前内部循环，等待新的外部消息。",
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),
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_build_tool_spec(
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name="send_emoji",
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brief_description="发送一个合适的表情包来辅助表达情绪。",
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parameters_schema={
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"type": "object",
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"properties": {
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"emotion": {
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"type": "string",
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"description": "希望表达的情绪，例如 happy、sad、angry 等。",
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},
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},
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},
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),
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]
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def get_builtin_tool_specs() -> List[ToolSpec]:
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"""获取 Maisaka 内置工具声明。
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Returns:
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List[ToolSpec]: 内置工具声明列表。
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"""
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return create_builtin_tool_specs()
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def get_builtin_tools() -> List[ToolDefinitionInput]:
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"""获取兼容旧模型层的内置工具定义。
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Returns:
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List[ToolDefinitionInput]: 可直接传给模型层的工具定义。
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"""
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return [tool_spec.to_llm_definition() for tool_spec in create_builtin_tool_specs()]
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