285 lines
9.2 KiB
Python
285 lines
9.2 KiB
Python
"""
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舆情监控 - Sentiment Monitoring Module
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功能：
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- 直接用全量数据做关键词过滤
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- 监控特定关键词的舆情
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"""
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from typing import List, Dict, Optional, Any
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from dataclasses import dataclass, field
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from enum import Enum
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from datetime import datetime
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import asyncio
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class SentimentType(Enum):
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"""舆情类型"""
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ALL = "all" # 全部
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POSITIVE = "positive" # 正面
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NEGATIVE = "negative" # 负面
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NEUTRAL = "neutral" # 中性
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@dataclass
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class SentimentConfig:
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"""舆情监控配置"""
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keywords: List[str] = field(default_factory=list) # 监控关键词
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sentiment_type: SentimentType = SentimentType.ALL # 舆情类型
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items_per_platform: int = 10 # 每个平台获取的条目数
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total_items: int = 50 # 总条目数限制
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include_platforms: List[str] = None # 包含的平台
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exclude_platforms: List[str] = None # 排除的平台
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class SentimentMonitor:
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"""舆情监控类"""
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def __init__(self, api_client=None, formatter=None):
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"""
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初始化舆情监控
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Args:
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api_client: API客户端实例（可选）
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formatter: 格式化器实例（可选）
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"""
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self.api_client = api_client
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self.formatter = formatter
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self.all_platforms = self._get_default_platforms()
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def _get_default_platforms(self) -> List[str]:
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"""获取默认的全部平台列表"""
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return [
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"weibo", "zhihu", "douban-group", "douban-movie",
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"ithome", "36kr", "sspai", "csdn", "juejin",
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"genshin", "miyoushe", "bilibili", "hupu",
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"sina-news", "netease-news", "qq-news",
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"sina-money", "eastmoney", "xueqiu",
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"autohome", "懂车帝", "mafengwo", "ctrip",
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"dianping", "xiaohongshu", "weibo"
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]
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async def fetch_all_hot_data(self, limit_per_platform: int = 10) -> List[Dict[str, Any]]:
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"""
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一次性获取全部平台的热榜数据
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Args:
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limit_per_platform: 每个平台获取的条目数
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Returns:
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全部平台的热榜数据列表
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"""
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all_items = []
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if self.api_client:
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for platform in self.all_platforms:
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try:
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items = await self.api_client.get_hot榜单(platform, limit=limit_per_platform)
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if items:
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for item in items:
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item["source_platform"] = platform
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all_items.extend(items)
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except Exception as e:
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print(f"Error fetching {platform}: {e}")
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continue
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return all_items
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async def monitor_keywords(self, keywords: List[str], config: Optional[SentimentConfig] = None) -> Dict[str, Any]:
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"""
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监控关键词舆情（新版：先全部获取，再关键词过滤）
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Args:
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keywords: 关键词列表
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config: 配置对象（可选）
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Returns:
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舆情监控数据
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"""
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if config is None:
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config = SentimentConfig(keywords=keywords)
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# 步骤1：全部获取
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all_items = await self.fetch_all_hot_data(limit_per_platform=config.items_per_platform)
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# 步骤2：关键词过滤
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filtered_items = self._filter_by_keywords(all_items, config.keywords)
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# 平台过滤
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if config.include_platforms:
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filtered_items = [item for item in filtered_items if item.get("source_platform") in config.include_platforms]
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if config.exclude_platforms:
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filtered_items = [item for item in filtered_items if item.get("source_platform") not in config.exclude_platforms]
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# 限制总数
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filtered_items = filtered_items[:config.total_items]
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return {
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"keywords": config.keywords,
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"total_items": len(filtered_items),
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"items": filtered_items
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}
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def _filter_by_keywords(self, items: List[Dict], keywords: List[str]) -> List[Dict]:
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"""
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按关键词过滤
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Args:
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items: 条目列表
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keywords: 关键词列表
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Returns:
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过滤后的条目列表
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"""
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if not keywords:
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return items
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filtered = []
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for item in items:
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title = item.get("title", "").lower()
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desc = item.get("description", "").lower()
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# 检查是否匹配任何关键词
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matches = False
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for kw in keywords:
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if kw.lower() in title or kw.lower() in desc:
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matches = True
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break
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if matches:
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filtered.append(item)
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# 按热度排序
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filtered.sort(key=lambda x: x.get("hot", 0) or x.get("score", 0), reverse=True)
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return filtered
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def format_monitoring_response(self, monitor_data: Dict[str, Any]) -> str:
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"""
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格式化监控响应
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Args:
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monitor_data: 监控数据
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Returns:
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格式化的响应文本
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"""
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items = monitor_data.get("items", [])
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keywords = monitor_data.get("keywords", [])
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if not items:
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return f"❌ 暂无关于「{', '.join(keywords)}」的舆情数据"
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response = f"🔍 **舆情监控 - {', '.join(keywords)}**\n"
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response += f"共 {monitor_data['total_items']} 条相关内容\n"
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response += "-" * 40 + "\n\n"
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for i, item in enumerate(items, 1):
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title = item.get("title", "无标题")
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hot = item.get("hot", item.get("score", ""))
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platform = item.get("source_platform", "")
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response += f"{i}. {title}\n"
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if hot:
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response += f" 🔥 热度: {hot}"
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if platform:
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response += f" | 📱 {platform}"
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response += "\n\n"
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return response
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def parse_keywords_from_input(self, user_input: str) -> List[str]:
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"""
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从用户输入解析关键词
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Args:
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user_input: 用户输入
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Returns:
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关键词列表
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"""
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user_input = user_input.strip()
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# 常用监控关键词
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common_keywords = [
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"AI", "人工智能", "ChatGPT", "大模型",
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"特斯拉", "比亚迪", "新能源汽车",
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"华为", "iPhone", "小米",
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"直播", "电商", "网红",
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"房价", "股票", "基金",
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"高考", "考研", "留学"
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]
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matched_keywords = []
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for kw in common_keywords:
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if kw.lower() in user_input.lower():
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matched_keywords.append(kw)
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# 如果没有匹配到常用关键词，尝试提取用户输入的词
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if not matched_keywords:
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# 按逗号、空格等分隔
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import re
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words = re.split(r'[,，\s]+', user_input)
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matched_keywords = [w for w in words if w.strip()]
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return matched_keywords
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async def process_user_request(self, user_input: str) -> Dict[str, Any]:
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"""
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处理用户请求
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Args:
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user_input: 用户输入
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Returns:
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处理结果
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"""
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# 解析关键词
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keywords = self.parse_keywords_from_input(user_input)
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if not keywords:
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# 返回引导信息
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return {
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"action": "ask_keywords",
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"message": "🔍 **舆情监控**\n\n"
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"请输入您想监控的关键词，例如：\n"
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"• AI、人工智能、ChatGPT\n"
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"• 特斯拉、比亚迪、新能源汽车\n"
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"• 华为、iPhone、小米\n"
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"• 直播、电商、网红\n"
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"• 房价、股票、基金\n\n"
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"💡 您可以直接输入任意关键词进行监控"
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}
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# 获取监控数据
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monitor_data = await self.monitor_keywords(keywords)
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# 格式化响应
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response_text = self.format_monitoring_response(monitor_data)
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return {
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"action": "show_monitoring",
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"data": monitor_data,
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"message": response_text
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}
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# 便捷函数
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async def create_sentiment_monitor(api_client=None, formatter=None) -> SentimentMonitor:
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"""创建舆情监控实例"""
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return SentimentMonitor(api_client=api_client, formatter=formatter)
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if __name__ == "__main__":
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# 测试代码
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async def test():
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monitor = await create_sentiment_monitor()
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print("测试舆情监控...")
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result = await monitor.process_user_request("监控AI和特斯拉")
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print(result["message"])
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asyncio.run(test())
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