7b6bd19781
变更项： 1. 新增 llm.scenes 场景路由层，支持 scene->backend 统一映射，并补充默认场景配置。 2. 扩展 LLMRegistry，新增 scene 解析逻辑；当声明 scene 时强制按场景路由结果生效，保持旧 backend 配置兼容。 3. 扩展后台 /api/system/llm_config 读写能力，支持 scenes 配置保存；新增插件 LLM 依赖扫描与拓扑数据输出。 4. 升级 system_llm 页面：新增场景路由管理区、插件依赖拓扑表，支持可视化查看 插件->scene->backend->provider。 5. 迁移核心插件配置到 scene 模式（保留兼容字段）：dify/global_news/game_task/message_summary/ai_auto_response/member_context/douyu。 6. 调整部分插件初始化默认 llm_config，补充 scene 字段，确保后台场景切换可直接生效。
229 lines
8.4 KiB
Python
229 lines
8.4 KiB
Python
import asyncio
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import threading
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import time # 添加这一行
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from typing import Dict, Any, List, Optional, Tuple
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from base.plugin_common.message_plugin_interface import MessagePluginInterface
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from base.plugin_common.plugin_interface import PluginStatus
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from utils.decorator.plugin_decorators import plugin_stats_decorator
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from utils.robot_cmd.robot_command import Feature, PermissionStatus, GroupBotManager
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from utils.decorator.points_decorator import plugin_points_cost
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from utils.markdown_to_image import convert_md_str_to_image
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from utils.ai.unified_llm import UnifiedLLMClient
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from wechat_ipad import WechatAPIClient
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# 导入新闻抓取函数
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from .news_crawler import nbc, cnn, abc, fox, bbc
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class GlobalNewsPlugin(MessagePluginInterface):
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"""全球新闻插件"""
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# 功能权限常量
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FEATURE_KEY = "GLOBAL_NEWS"
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FEATURE_DESCRIPTION = "🌍 全球新闻功能 [全球新闻, 国际新闻, 环球新闻, 政经新闻]"
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@property
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def name(self) -> str:
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return "全球新闻"
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@property
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def version(self) -> str:
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return "1.0.0"
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@property
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def description(self) -> str:
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return "提供全球政治经济新闻查询功能"
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@property
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def author(self) -> str:
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return "liu.wei"
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@property
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def command_prefix(self) -> Optional[str]:
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return "" # 不需要前缀，直接匹配命令
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@property
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def commands(self) -> List[str]:
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return self._commands
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@property
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def feature_key(self) -> Optional[str]:
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return self.FEATURE_KEY
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@property
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def feature_description(self) -> Optional[str]:
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return self.FEATURE_DESCRIPTION
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def __init__(self):
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super().__init__()
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self.bot: WechatAPIClient = None
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self._news_tasks = {} # 存储正在进行的新闻抓取任务
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# 注册功能权限
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self.feature = self.register_feature()
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def initialize(self, context: Dict[str, Any]) -> bool:
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"""初始化插件"""
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self.LOG.debug(f"正在初始化 {self.name} 插件...")
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# 保存上下文对象
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self.event_system = context.get("event_system")
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self._commands = self._config.get("GlobalNews", {}).get("command",
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["全球新闻", "国际新闻", "环球新闻", "政经新闻"])
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self.command_format = self._config.get("GlobalNews", {}).get("command-format",
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"全球新闻 - 获取最新的全球政治经济新闻")
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plugin_config = self._config.get("GlobalNews", {})
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self.enable = plugin_config.get("enable", True)
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llm_config = plugin_config.get("llm", {}) or {}
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if not llm_config:
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llm_config = {
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# 场景路由优先，便于后台统一切换新闻分析后端。
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"scene": plugin_config.get("scene", ""),
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"backend": plugin_config.get("backend", ""),
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"provider": "dify",
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"mode": "chat",
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"authorization": plugin_config.get("authorization", ""),
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"url": plugin_config.get("url", ""),
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"response_mode": "blocking",
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}
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self.llm_client = UnifiedLLMClient(llm_config)
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self.LOG.debug(f"[{self.name}] 插件初始化完成，指令：{self._commands}")
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return True
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def start(self) -> bool:
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"""启动插件"""
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self.LOG.debug(f"[{self.name}] 插件已启动")
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self.status = PluginStatus.RUNNING
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return True
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def stop(self) -> bool:
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"""停止插件"""
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self.LOG.info(f"[{self.name}] 插件已停止")
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self.status = PluginStatus.STOPPED
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return True
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def can_process(self, message: Dict[str, Any]) -> bool:
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"""检查是否可以处理该消息"""
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if not self.enable:
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return False
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content = str(message.get("content", "")).strip()
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command = content.split(" ")[0]
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return command in self._commands
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@plugin_stats_decorator(plugin_name="全球新闻")
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@plugin_points_cost(1, "全球新闻消耗积分", FEATURE_KEY)
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async def process_message(self, message: Dict[str, Any]) -> Tuple[bool, Optional[str]]:
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"""处理消息"""
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content = str(message.get("content", "")).strip()
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self.LOG.debug(f"插件执行： {self.name}：{content}")
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sender = message.get("sender")
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roomid = message.get("roomid", "")
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gbm: GroupBotManager = message.get("gbm")
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bot: WechatAPIClient = message.get("bot")
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# 检查权限
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if roomid and gbm.get_group_permission(roomid, self.feature) == PermissionStatus.DISABLED:
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return False, "没有权限"
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# 生成唯一任务ID
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task_id = f"{sender}_{roomid}_{int(time.time())}"
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# 发送等待消息
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await self.bot.send_text_message(
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(roomid if roomid else sender), "🌍正在获取全球新闻，请稍候...", sender)
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# 启动异步任务
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self._start_news_task(task_id, sender, roomid)
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return True, "新闻获取任务已启动"
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def _start_news_task(self, task_id: str, sender: str, roomid: str):
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"""启动异步新闻获取任务"""
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thread = threading.Thread(
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target=self._fetch_news_thread,
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args=(task_id, sender, roomid)
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)
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thread.daemon = True
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thread.start()
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self._news_tasks[task_id] = thread
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self.LOG.info(f"启动新闻获取任务: {task_id}")
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async def _fetch_news_thread(self, task_id: str, sender: str, roomid: str):
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"""在单独的线程中运行异步新闻获取任务"""
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try:
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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news_result = loop.run_until_complete(self._fetch_news_async())
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loop.close()
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# 处理结果
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if news_result:
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# 发送新闻图片
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receiver = roomid if roomid else sender
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await self.bot.send_image_message(receiver, news_result)
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await self.bot.send_text_message("🌍全球新闻获取完成！", receiver, sender)
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else:
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await self.bot.send_text_message(
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(roomid if roomid else sender), "❌获取新闻失败，请稍后再试", sender)
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except Exception as e:
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self.LOG.error(f"新闻获取任务出错: {e}")
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await self.bot.send_text_message((roomid if roomid else sender), f"❌获取新闻出错: {str(e)}",
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sender)
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finally:
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# 清理任务
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if task_id in self._news_tasks:
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del self._news_tasks[task_id]
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async def _fetch_news_async(self) -> str:
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"""异步获取所有新闻源的新闻"""
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try:
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# 创建所有新闻源的任务
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tasks = [
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self._run_in_executor(nbc),
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self._run_in_executor(cnn),
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self._run_in_executor(abc),
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self._run_in_executor(fox),
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self._run_in_executor(bbc)
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]
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# 并行执行所有任务
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results = await asyncio.gather(*tasks)
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# 合并结果
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news_titles = "\n".join(results)
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# 使用AI分析新闻
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markdown_news = await self._run_in_executor(self.analyze_news_titles, news_titles)
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# 转换为图片
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image_path = await self._run_in_executor(
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convert_md_str_to_image, markdown_news, "news_output.png"
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)
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return image_path
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except Exception as e:
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self.LOG.error(f"异步获取新闻失败: {e}")
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return ""
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async def _run_in_executor(self, func, *args):
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"""在线程池中运行同步函数"""
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loop = asyncio.get_event_loop()
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return await loop.run_in_executor(None, func, *args)
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def analyze_news_titles(self, content: str) -> Optional[str]:
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"""同步分析新闻标题，便于在线程池中复用。"""
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response = self.llm_client.run(
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prompt=content,
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user="a-bot-global_news",
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inputs={"query": content},
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tag="global_news",
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)
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if not response:
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self.LOG.error(f"新闻分析请求失败: {self.llm_client.last_error}")
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return None
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return response.get("text") or None
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