feat:超级屎山优化
This commit is contained in:
@@ -17,8 +17,8 @@ from loguru import logger
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from utils.plugin_base import PluginBase
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from utils.decorators import on_text_message, on_quote_message, on_image_message, on_emoji_message
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from utils.redis_cache import get_cache
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from utils.llm_tooling import ToolResult, collect_tools_with_plugins, collect_tools, get_tool_schema_map, validate_tool_arguments
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from utils.image_processor import ImageProcessor, MediaConfig
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from utils.tool_executor import ToolExecutor
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from utils.tool_registry import get_tool_registry
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import xml.etree.ElementTree as ET
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import base64
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@@ -472,25 +472,39 @@ class AIChat(PluginBase):
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return ""
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def _collect_tools_with_plugins(self) -> dict:
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"""收集所有插件的 LLM 工具，并保留来源插件名"""
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from utils.plugin_manager import PluginManager
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tools_config = self.config.get("tools", {})
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return collect_tools_with_plugins(tools_config, PluginManager().plugins)
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"""收集工具定义（来自 ToolRegistry）并保留来源插件名"""
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registry = get_tool_registry()
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tools_config = (self.config or {}).get("tools", {})
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mode = tools_config.get("mode", "all")
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whitelist = set(tools_config.get("whitelist", []))
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blacklist = set(tools_config.get("blacklist", []))
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tools_map = {}
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for name in registry.list_tools():
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tool_def = registry.get(name)
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if not tool_def:
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continue
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if mode == "whitelist" and name not in whitelist:
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continue
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if mode == "blacklist" and name in blacklist:
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continue
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tools_map[name] = (tool_def.plugin_name, tool_def.schema)
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return tools_map
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def _collect_tools(self):
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"""收集所有插件的LLM工具（支持白名单/黑名单过滤）"""
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from utils.plugin_manager import PluginManager
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tools_config = self.config.get("tools", {})
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return collect_tools(tools_config, PluginManager().plugins)
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tools_map = self._collect_tools_with_plugins()
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return [item[1] for item in tools_map.values()]
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def _get_tool_schema_map(self, tools_map: dict | None = None) -> dict:
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"""构建工具名到参数 schema 的映射"""
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tools_map = tools_map or self._collect_tools_with_plugins()
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return get_tool_schema_map(tools_map)
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def _validate_tool_arguments(self, tool_name: str, arguments: dict, schema: dict) -> tuple:
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"""轻量校验并补全默认参数"""
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return validate_tool_arguments(tool_name, arguments, schema)
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schema_map = {}
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for name, (_plugin_name, tool) in tools_map.items():
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fn = tool.get("function", {})
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schema_map[name] = fn.get("parameters", {}) or {}
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return schema_map
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async def _handle_list_prompts(self, bot, from_wxid: str):
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"""处理人设列表指令"""
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@@ -627,10 +641,12 @@ class AIChat(PluginBase):
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)
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cleaned = cleaned.replace("展开阅读下文", "")
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cleaned = re.sub(
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r"（已触发工具处理：[^）]{0,300}结果将发送到聊天中。）",
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r"[（(]已触发工具处理[^)）\r\n]{0,500}[)）]?",
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"",
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cleaned,
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)
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cleaned = re.sub(r"(?m)^.*已触发工具处理.*$", "", cleaned)
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cleaned = re.sub(r"(?m)^.*结果将发送到聊天中.*$", "", cleaned)
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# 过滤图片占位符/文件名，避免把日志占位符当成正文发出去
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cleaned = re.sub(
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r"\\[图片[^\\]]*\\]\\s*\\S+\\.(?:png|jpe?g|gif|webp)",
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@@ -2297,56 +2313,69 @@ class AIChat(PluginBase):
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await self.store.update_group_message_by_id(chat_id, record_id, new_content)
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async def _execute_tool_and_get_result(
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def _prepare_tool_calls_for_executor(
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self,
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tool_name: str,
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arguments: dict,
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bot,
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tool_calls_data: list,
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messages: list,
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*,
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user_wxid: str,
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from_wxid: str,
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user_wxid: str = None,
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is_group: bool = False,
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tools_map: dict | None = None,
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timeout: float = None,
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):
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"""
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执行工具调用并返回结果（使用 ToolRegistry）
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is_group: bool,
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image_base64: str | None = None,
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) -> list:
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prepared = []
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if not tool_calls_data:
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return prepared
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通过 ToolRegistry 实现 O(1) 工具查找和统一超时保护
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"""
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# 获取工具专属超时时间
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if timeout is None:
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tool_timeout_config = self.config.get("tools", {}).get("timeout", {})
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timeout = tool_timeout_config.get(tool_name, tool_timeout_config.get("default", 60))
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for tool_call in tool_calls_data:
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function = (tool_call or {}).get("function") or {}
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function_name = function.get("name", "")
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if not function_name:
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continue
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# 添加用户信息到 arguments
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arguments["user_wxid"] = user_wxid or from_wxid
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arguments["is_group"] = bool(is_group)
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tool_call_id = (tool_call or {}).get("id", "")
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if not tool_call_id:
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tool_call_id = f"call_{uuid.uuid4().hex[:8]}"
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tool_call["id"] = tool_call_id
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logger.info(f"开始执行工具: {tool_name} (超时: {timeout}s)")
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raw_arguments = function.get("arguments", "{}")
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try:
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arguments = json.loads(raw_arguments) if raw_arguments else {}
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if not isinstance(arguments, dict):
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arguments = {}
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except Exception:
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arguments = {}
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if "function" not in tool_call:
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tool_call["function"] = {}
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tool_call["function"]["arguments"] = "{}"
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# 使用 ToolRegistry 执行工具（O(1) 查找 + 统一超时保护）
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registry = get_tool_registry()
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result = await registry.execute(tool_name, arguments, bot, from_wxid, timeout_override=timeout)
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if function_name in ("tavily_web_search", "web_search") and not arguments.get("query"):
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fallback_query = self._extract_tool_intent_text(self._extract_last_user_text(messages))
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fallback_query = str(fallback_query or "").strip()
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if fallback_query:
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arguments["query"] = fallback_query[:400]
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if "function" not in tool_call:
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tool_call["function"] = {}
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tool_call["function"]["arguments"] = json.dumps(arguments, ensure_ascii=False)
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# 规范化结果
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if result is None:
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return {"success": False, "message": f"工具 {tool_name} 返回空结果"}
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exec_args = dict(arguments)
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exec_args["user_wxid"] = user_wxid or from_wxid
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exec_args["is_group"] = bool(is_group)
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if not isinstance(result, dict):
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result = {"success": True, "message": str(result)}
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else:
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result.setdefault("success", True)
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if image_base64 and function_name == "flow2_ai_image_generation":
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exec_args["image_base64"] = image_base64
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logger.info("[异步-图片] 图生图工具，已添加图片数据")
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# 记录执行结果
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tool_def = registry.get(tool_name)
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plugin_name = tool_def.plugin_name if tool_def else "unknown"
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prepared.append({
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"id": tool_call_id,
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"type": "function",
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"function": {
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"name": function_name,
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"arguments": json.dumps(exec_args, ensure_ascii=False),
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},
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})
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if result.get("success"):
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logger.success(f"工具执行成功: {tool_name} ({plugin_name})")
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else:
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logger.warning(f"工具执行失败: {tool_name} ({plugin_name})")
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return result
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return prepared
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async def _execute_tools_async(self, tool_calls_data: list, bot, from_wxid: str,
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chat_id: str, user_wxid: str, nickname: str, is_group: bool,
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@@ -2360,140 +2389,70 @@ class AIChat(PluginBase):
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try:
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logger.info(f"开始异步执行 {len(tool_calls_data)} 个工具调用")
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# 获取并发控制配置
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concurrency_config = self.config.get("tools", {}).get("concurrency", {})
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concurrency_config = (self.config or {}).get("tools", {}).get("concurrency", {})
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max_concurrent = concurrency_config.get("max_concurrent", 5)
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semaphore = asyncio.Semaphore(max_concurrent)
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timeout_config = (self.config or {}).get("tools", {}).get("timeout", {})
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default_timeout = timeout_config.get("default", 60)
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# 并行执行所有工具（带并发限制）
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tasks = []
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tool_info_list = [] # 保存工具信息用于后续处理
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tools_map = self._collect_tools_with_plugins()
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schema_map = self._get_tool_schema_map(tools_map)
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executor = ToolExecutor(default_timeout=default_timeout, max_parallel=max_concurrent)
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prepared_tool_calls = self._prepare_tool_calls_for_executor(
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tool_calls_data,
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messages,
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user_wxid=user_wxid,
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from_wxid=from_wxid,
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is_group=is_group,
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)
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for tool_call in tool_calls_data:
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function_name = tool_call.get("function", {}).get("name", "")
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arguments_str = tool_call.get("function", {}).get("arguments", "{}")
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tool_call_id = tool_call.get("id", "")
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if not prepared_tool_calls:
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logger.info("[异步] 没有可执行的工具调用")
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return
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if not function_name:
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logger.info(f"[异步] 开始并行执行 {len(prepared_tool_calls)} 个工具 (最大并发: {max_concurrent})")
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results = await executor.execute_batch(prepared_tool_calls, bot, from_wxid, parallel=True)
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need_ai_reply_results = []
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for result in results:
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function_name = result.name
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tool_call_id = result.id
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tool_message = self._sanitize_llm_output(result.message or "")
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if result.success:
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logger.success(f"[异步] 工具 {function_name} 执行成功")
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else:
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logger.warning(f"[异步] 工具 {function_name} 执行失败: {result.error or result.message}")
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if result.need_ai_reply:
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need_ai_reply_results.append({
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"tool_call_id": tool_call_id,
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"function_name": function_name,
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"result": tool_message
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})
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continue
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try:
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arguments = json.loads(arguments_str)
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except Exception:
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arguments = {}
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if result.success and not result.already_sent and tool_message and not result.no_reply:
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if result.send_result_text:
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if tool_message:
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await bot.send_text(from_wxid, tool_message)
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else:
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logger.warning(f"[异步] 工具 {function_name} 输出清洗后为空，已跳过发送")
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if function_name in ("tavily_web_search", "web_search") and not arguments.get("query"):
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fallback_query = self._extract_tool_intent_text(self._extract_last_user_text(messages))
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fallback_query = str(fallback_query or "").strip()
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if fallback_query:
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arguments["query"] = fallback_query[:400]
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schema = schema_map.get(function_name)
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ok, err, arguments = self._validate_tool_arguments(function_name, arguments, schema)
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if not ok:
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logger.warning(f"[异步] 工具 {function_name} 参数校验失败: {err}")
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if not result.success and not result.no_reply:
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try:
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await bot.send_text(from_wxid, f"❌ 工具 {function_name} 参数错误: {err}")
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if tool_message:
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await bot.send_text(from_wxid, f"? {tool_message}")
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else:
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await bot.send_text(from_wxid, f"? {function_name} 执行失败")
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except Exception:
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pass
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continue
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logger.info(f"[异步] 准备执行工具: {function_name}, 参数: {arguments}")
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if result.save_to_memory and chat_id and tool_message:
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self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_message}")
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# 创建带并发限制的异步任务
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async def execute_with_semaphore(fn, args, bot_ref, wxid, user_wxid_ref, is_grp, t_map, sem):
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async with sem:
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return await self._execute_tool_and_get_result(
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fn, args, bot_ref, wxid,
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user_wxid=user_wxid_ref, is_group=is_grp, tools_map=t_map
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)
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task = execute_with_semaphore(
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function_name, arguments, bot, from_wxid,
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user_wxid, is_group, tools_map, semaphore
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if need_ai_reply_results:
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await self._continue_with_tool_results(
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need_ai_reply_results, bot, from_wxid, user_wxid, chat_id,
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nickname, is_group, messages, tool_calls_data
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)
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tasks.append(task)
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tool_info_list.append({
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"tool_call_id": tool_call_id,
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"function_name": function_name,
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"arguments": arguments
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})
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# 并行执行所有工具（带并发限制，防止资源耗尽）
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if tasks:
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logger.info(f"[异步] 开始并行执行 {len(tasks)} 个工具 (最大并发: {max_concurrent})")
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results = await asyncio.gather(*tasks, return_exceptions=True)
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need_ai_reply_results = []
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# 处理每个工具的结果
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for i, result in enumerate(results):
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tool_info = tool_info_list[i]
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function_name = tool_info["function_name"]
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tool_call_id = tool_info["tool_call_id"]
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tool_call_id = tool_info["tool_call_id"]
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if isinstance(result, Exception):
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logger.error(f"[异步] 工具 {function_name} 执行异常: {result}")
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try:
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await bot.send_text(from_wxid, f"❌ {function_name} 执行失败: {result}")
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except Exception:
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pass
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continue
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tool_result = ToolResult.from_raw(result)
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if not tool_result:
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continue
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tool_message = self._sanitize_llm_output(tool_result.message) if tool_result.message is not None else ""
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# 工具文本统一做一次输出清洗，避免工具内部/下游LLM把“思维链”发出来
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tool_message = self._sanitize_llm_output(tool_result.message) if tool_result.message is not None else ""
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if tool_result.success:
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logger.success(f"[异步] 工具 {function_name} 执行成功")
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else:
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logger.warning(f"[异步] 工具 {function_name} 执行失败")
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# 需要 AI 继续处理的结果
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if tool_result.need_ai_reply:
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need_ai_reply_results.append({
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"tool_call_id": tool_call_id,
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"function_name": function_name,
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"result": tool_message
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})
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continue
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# 工具成功且需要回文本时发送
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if tool_result.success and not tool_result.already_sent and tool_result.message and not tool_result.no_reply:
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if tool_result.send_result_text:
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if tool_message:
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await bot.send_text(from_wxid, tool_message)
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else:
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logger.warning(f"[异步] 工具 {function_name} 输出清洗后为空，已跳过发送")
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# 工具失败默认回一条错误提示
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if not tool_result.success and tool_message and not tool_result.no_reply:
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try:
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if tool_message:
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await bot.send_text(from_wxid, f"❌ {tool_message}")
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else:
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await bot.send_text(from_wxid, f"❌ {function_name} 执行失败")
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except Exception:
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pass
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# 保存工具结果到记忆（可选）
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if tool_result.save_to_memory and chat_id:
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if tool_message:
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self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_message}")
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# 如果有需要 AI 回复的工具结果，调用 AI 继续对话
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if need_ai_reply_results:
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await self._continue_with_tool_results(
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need_ai_reply_results, bot, from_wxid, user_wxid, chat_id,
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nickname, is_group, messages, tool_calls_data
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)
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logger.info(f"[异步] 所有工具执行完成")
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@@ -2502,7 +2461,7 @@ class AIChat(PluginBase):
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import traceback
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logger.error(f"详细错误: {traceback.format_exc()}")
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try:
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await bot.send_text(from_wxid, "❌ 工具执行过程中出现错误")
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await bot.send_text(from_wxid, "? 工具执行过程中出现错误")
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except:
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pass
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@@ -2700,126 +2659,71 @@ class AIChat(PluginBase):
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try:
|
||||
logger.info(f"[异步-图片] 开始执行 {len(tool_calls_data)} 个工具调用")
|
||||
|
||||
# 并行执行所有工具
|
||||
tasks = []
|
||||
tool_info_list = []
|
||||
tools_map = self._collect_tools_with_plugins()
|
||||
schema_map = self._get_tool_schema_map(tools_map)
|
||||
concurrency_config = (self.config or {}).get("tools", {}).get("concurrency", {})
|
||||
max_concurrent = concurrency_config.get("max_concurrent", 5)
|
||||
timeout_config = (self.config or {}).get("tools", {}).get("timeout", {})
|
||||
default_timeout = timeout_config.get("default", 60)
|
||||
|
||||
for tool_call in tool_calls_data:
|
||||
function_name = tool_call.get("function", {}).get("name", "")
|
||||
arguments_str = tool_call.get("function", {}).get("arguments", "{}")
|
||||
tool_call_id = tool_call.get("id", "")
|
||||
executor = ToolExecutor(default_timeout=default_timeout, max_parallel=max_concurrent)
|
||||
prepared_tool_calls = self._prepare_tool_calls_for_executor(
|
||||
tool_calls_data,
|
||||
messages,
|
||||
user_wxid=user_wxid,
|
||||
from_wxid=from_wxid,
|
||||
is_group=is_group,
|
||||
image_base64=image_base64,
|
||||
)
|
||||
|
||||
if not function_name:
|
||||
if not prepared_tool_calls:
|
||||
logger.info("[异步-图片] 没有可执行的工具调用")
|
||||
return
|
||||
|
||||
logger.info(f"[异步-图片] 开始并行执行 {len(prepared_tool_calls)} 个工具 (最大并发: {max_concurrent})")
|
||||
results = await executor.execute_batch(prepared_tool_calls, bot, from_wxid, parallel=True)
|
||||
need_ai_reply_results = []
|
||||
|
||||
for result in results:
|
||||
function_name = result.name
|
||||
tool_call_id = result.id
|
||||
tool_message = self._sanitize_llm_output(result.message or "")
|
||||
|
||||
if result.success:
|
||||
logger.success(f"[异步-图片] 工具 {function_name} 执行成功")
|
||||
else:
|
||||
logger.warning(f"[异步-图片] 工具 {function_name} 执行失败: {result.error or result.message}")
|
||||
|
||||
if result.need_ai_reply:
|
||||
need_ai_reply_results.append({
|
||||
"tool_call_id": tool_call_id,
|
||||
"function_name": function_name,
|
||||
"result": tool_message
|
||||
})
|
||||
continue
|
||||
|
||||
try:
|
||||
arguments = json.loads(arguments_str)
|
||||
except Exception:
|
||||
arguments = {}
|
||||
if result.success and not result.already_sent and tool_message and not result.no_reply:
|
||||
if result.send_result_text:
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, tool_message)
|
||||
else:
|
||||
logger.warning(f"[异步-图片] 工具 {function_name} 输出清洗后为空，已跳过发送")
|
||||
|
||||
if function_name in ("tavily_web_search", "web_search") and not arguments.get("query"):
|
||||
fallback_query = self._extract_tool_intent_text(self._extract_last_user_text(messages))
|
||||
fallback_query = str(fallback_query or "").strip()
|
||||
if fallback_query:
|
||||
arguments["query"] = fallback_query[:400]
|
||||
|
||||
# 如果是图生图工具，添加图片 base64
|
||||
if function_name == "flow2_ai_image_generation" and image_base64:
|
||||
arguments["image_base64"] = image_base64
|
||||
logger.info(f"[异步-图片] 图生图工具，已添加图片数据")
|
||||
|
||||
schema = schema_map.get(function_name)
|
||||
ok, err, arguments = self._validate_tool_arguments(function_name, arguments, schema)
|
||||
if not ok:
|
||||
logger.warning(f"[异步-图片] 工具 {function_name} 参数校验失败: {err}")
|
||||
if not result.success and not result.no_reply:
|
||||
try:
|
||||
await bot.send_text(from_wxid, f"❌ 工具 {function_name} 参数错误: {err}")
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, f"? {tool_message}")
|
||||
else:
|
||||
await bot.send_text(from_wxid, f"? {function_name} 执行失败")
|
||||
except Exception:
|
||||
pass
|
||||
continue
|
||||
|
||||
logger.info(f"[异步-图片] 准备执行工具: {function_name}")
|
||||
if result.save_to_memory and chat_id and tool_message:
|
||||
self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_message}")
|
||||
|
||||
task = self._execute_tool_and_get_result(
|
||||
function_name,
|
||||
arguments,
|
||||
bot,
|
||||
from_wxid,
|
||||
user_wxid=user_wxid,
|
||||
is_group=is_group,
|
||||
tools_map=tools_map,
|
||||
if need_ai_reply_results:
|
||||
await self._continue_with_tool_results(
|
||||
need_ai_reply_results, bot, from_wxid, user_wxid, chat_id,
|
||||
nickname, is_group, messages, tool_calls_data
|
||||
)
|
||||
tasks.append(task)
|
||||
tool_info_list.append({
|
||||
"tool_call_id": tool_call_id,
|
||||
"function_name": function_name,
|
||||
"arguments": arguments
|
||||
})
|
||||
|
||||
# 并行执行所有工具
|
||||
if tasks:
|
||||
results = await asyncio.gather(*tasks, return_exceptions=True)
|
||||
need_ai_reply_results = []
|
||||
|
||||
for i, result in enumerate(results):
|
||||
tool_info = tool_info_list[i]
|
||||
function_name = tool_info["function_name"]
|
||||
tool_call_id = tool_info["tool_call_id"]
|
||||
|
||||
if isinstance(result, Exception):
|
||||
logger.error(f"[异步-图片] 工具 {function_name} 执行异常: {result}")
|
||||
try:
|
||||
await bot.send_text(from_wxid, f"❌ {function_name} 执行失败: {result}")
|
||||
except Exception:
|
||||
pass
|
||||
continue
|
||||
|
||||
tool_result = ToolResult.from_raw(result)
|
||||
if not tool_result:
|
||||
continue
|
||||
|
||||
tool_message = self._sanitize_llm_output(tool_result.message or "")
|
||||
|
||||
if tool_result.success:
|
||||
logger.success(f"[异步-图片] 工具 {function_name} 执行成功")
|
||||
else:
|
||||
logger.warning(f"[异步-图片] 工具 {function_name} 执行失败")
|
||||
|
||||
if tool_result.need_ai_reply:
|
||||
need_ai_reply_results.append({
|
||||
"tool_call_id": tool_call_id,
|
||||
"function_name": function_name,
|
||||
"result": tool_message
|
||||
})
|
||||
continue
|
||||
|
||||
if tool_result.success and not tool_result.already_sent and tool_message and not tool_result.no_reply:
|
||||
if tool_result.send_result_text:
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, tool_message)
|
||||
else:
|
||||
logger.warning(f"[异步-图片] 工具 {function_name} 输出清洗后为空，已跳过发送")
|
||||
|
||||
if not tool_result.success and tool_message and not tool_result.no_reply:
|
||||
try:
|
||||
if tool_message:
|
||||
await bot.send_text(from_wxid, f"❌ {tool_message}")
|
||||
else:
|
||||
await bot.send_text(from_wxid, f"❌ {function_name} 执行失败")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
if tool_result.save_to_memory and chat_id:
|
||||
if tool_message:
|
||||
self._add_to_memory(chat_id, "assistant", f"[工具 {function_name} 结果]: {tool_message}")
|
||||
|
||||
if need_ai_reply_results:
|
||||
await self._continue_with_tool_results(
|
||||
need_ai_reply_results, bot, from_wxid, user_wxid, chat_id,
|
||||
nickname, is_group, messages, tool_calls_data
|
||||
)
|
||||
|
||||
logger.info(f"[异步-图片] 所有工具执行完成")
|
||||
|
||||
@@ -2828,7 +2732,7 @@ class AIChat(PluginBase):
|
||||
import traceback
|
||||
logger.error(f"详细错误: {traceback.format_exc()}")
|
||||
try:
|
||||
await bot.send_text(from_wxid, "❌ 工具执行过程中出现错误")
|
||||
await bot.send_text(from_wxid, "? 工具执行过程中出现错误")
|
||||
except:
|
||||
pass
|
||||
|
||||
|
||||
Reference in New Issue
Block a user