58f9380ec4
- alphaear-deepear-lite: DeepEar Lite API integration - alphaear-logic-visualizer: Draw.io XML finance diagrams - alphaear-news: Real-time finance news (10+ sources) - alphaear-predictor: Kronos time-series forecasting - alphaear-reporter: Professional financial reports - alphaear-search: Web search + local RAG - alphaear-sentiment: FinBERT/LLM sentiment analysis - alphaear-signal-tracker: Signal evolution tracking - alphaear-stock: A-Share/HK/US stock data Updates: - All scripts updated to use universal .env path - Added JINA_API_KEY, LLM_*, DEEPSEEK_API_KEY to .env.example - Updated load_dotenv() to use ~/.config/opencode/.env
257 lines
9.9 KiB
Python
257 lines
9.9 KiB
Python
import requests
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from requests.exceptions import RequestException, Timeout
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import json
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import time
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from datetime import datetime
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from typing import List, Dict, Optional
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from loguru import logger
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from .database_manager import DatabaseManager
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from .content_extractor import ContentExtractor
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class NewsNowTools:
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"""热点新闻获取工具 - 接入 NewsNow API 与 Jina 内容提取"""
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BASE_URL = "https://newsnow.busiyi.world"
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SOURCES = {
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# 金融类
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"cls": "财联社",
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"wallstreetcn": "华尔街见闻",
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"xueqiu": "雪球热榜",
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# 综合/社交
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"weibo": "微博热搜",
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"zhihu": "知乎热榜",
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"baidu": "百度热搜",
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"toutiao": "今日头条",
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"douyin": "抖音热榜",
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"thepaper": "澎湃新闻",
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# 科技类
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"36kr": "36氪",
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"ithome": "IT之家",
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"v2ex": "V2EX",
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"juejin": "掘金",
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"hackernews": "Hacker News",
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}
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def __init__(self, db: DatabaseManager):
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self.db = db
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self.user_agent = (
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"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
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"AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36"
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)
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self.extractor = ContentExtractor()
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# Simple in-memory cache: source_id -> {"time": timestamp, "data": []}
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self._cache = {}
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def fetch_hot_news(self, source_id: str, count: int = 15, fetch_content: bool = False) -> List[Dict]:
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"""
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从指定新闻源获取热点新闻列表（支持5分钟缓存）。
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"""
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# 1. Check cache validity (5 minutes)
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cache_key = f"{source_id}_{count}"
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cached = self._cache.get(cache_key)
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now = time.time()
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if cached and (now - cached["time"] < 300):
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logger.info(f"⚡ Using cached news for {source_id} (Age: {int(now - cached['time'])}s)")
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return cached["data"]
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try:
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url = f"{self.BASE_URL}/api/s?id={source_id}"
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response = requests.get(url, headers={"User-Agent": self.user_agent}, timeout=30)
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if response.status_code == 200:
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data = response.json()
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items = data.get("items", [])[:count]
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processed_items = []
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for i, item in enumerate(items, 1):
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item_url = item.get("url", "")
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content = ""
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if fetch_content and item_url:
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content = self.extractor.extract_with_jina(item_url) or ""
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processed_items.append({
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"id": item.get("id") or f"{source_id}_{int(time.time())}_{i}",
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"source": source_id,
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"rank": i,
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"title": item.get("title", ""),
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"url": item_url,
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"content": content,
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"publish_time": item.get("publish_time"),
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"meta_data": item.get("extra", {})
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})
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# Update Cache
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self._cache[cache_key] = {"time": now, "data": processed_items}
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logger.info(f"✅ Fetched and cached news for {source_id}")
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self.db.save_daily_news(processed_items)
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return processed_items
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else:
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logger.error(f"NewsNow API Error: {response.status_code}")
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# Fallback to stale cache if available
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if cached:
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logger.warning(f"⚠️ API failed, using stale cache for {source_id}")
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return cached["data"]
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return []
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except Timeout:
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logger.error(f"Timeout fetching hot news from {source_id}")
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if cached:
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logger.warning(f"⚠️ Timeout, using stale cache for {source_id}")
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return cached["data"]
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return []
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except RequestException as e:
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logger.error(f"Network error fetching hot news from {source_id}: {e}")
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if cached:
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logger.warning(f"⚠️ Network check failed, using stale cache for {source_id}")
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return cached["data"]
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return []
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except json.JSONDecodeError:
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logger.error(f"Failed to parse JSON response from NewsNow for {source_id}")
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return []
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except Exception as e:
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logger.error(f"Unexpected error fetching hot news from {source_id}: {e}")
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return []
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def fetch_news_content(self, url: str) -> Optional[str]:
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"""
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使用 Jina Reader 抓取指定 URL 的网页正文内容。
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Args:
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url: 需要抓取内容的完整网页 URL，必须以 http:// 或 https:// 开头。
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Returns:
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提取的网页正文内容 (Markdown 格式)，如果失败则返回 None。
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"""
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return self.extractor.extract_with_jina(url)
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def get_unified_trends(self, sources: Optional[List[str]] = None) -> str:
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"""
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获取多平台综合热点报告，自动聚合多个新闻源的热门内容。
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Args:
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sources: 要扫描的新闻源列表。可选值按类别:
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**金融类**: "cls", "wallstreetcn", "xueqiu"
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**综合类**: "weibo", "zhihu", "baidu", "toutiao", "douyin", "thepaper"
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**科技类**: "36kr", "ithome", "v2ex", "juejin", "hackernews"
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Returns:
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格式化的 Markdown 热点汇总报告，包含各平台 Top 10 热点标题和链接。
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"""
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sources = sources or ["weibo", "zhihu", "wallstreetcn"]
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all_news = []
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for src in sources:
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all_news.extend(self.fetch_hot_news(src))
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time.sleep(0.2)
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if not all_news:
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return "❌ 未能获取到热点数据"
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report = f"# 实时全网热点汇总 ({datetime.now().strftime('%Y-%m-%d %H:%M')})\n\n"
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for src in sources:
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src_name = self.SOURCES.get(src, src)
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report += f"### 🔥 {src_name}\n"
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src_news = [n for n in all_news if n['source'] == src]
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for n in src_news[:10]:
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report += f"- {n['title']} ([链接]({n['url']}))\n"
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report += "\n"
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return report
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class PolymarketTools:
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"""Polymarket 预测市场数据工具 - 获取热门预测市场反映公众情绪和预期"""
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BASE_URL = "https://gamma-api.polymarket.com"
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def __init__(self, db: DatabaseManager):
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self.db = db
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self.user_agent = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36"
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def get_active_markets(self, limit: int = 20) -> List[Dict]:
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"""
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获取活跃的预测市场，用于分析公众情绪和预期。
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预测市场数据可以反映:
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- 公众对重大事件的预期概率
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- 市场情绪和风险偏好
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- 热门话题的关注度
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Args:
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limit: 获取的市场数量，默认 20 个。
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Returns:
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包含预测市场信息的列表，每个市场包含:
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- question: 预测问题
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- outcomes: 可能的结果
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- outcomePrices: 各结果的概率价格
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- volume: 交易量
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"""
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try:
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response = requests.get(
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f"{self.BASE_URL}/markets",
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params={"active": "true", "closed": "false", "limit": limit},
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headers={"User-Agent": self.user_agent, "Accept": "application/json"},
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timeout=30
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)
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if response.status_code == 200:
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markets = response.json()
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result = []
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for m in markets:
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result.append({
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"id": m.get("id"),
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"question": m.get("question"),
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"slug": m.get("slug"),
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"outcomes": m.get("outcomes"),
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"outcomePrices": m.get("outcomePrices"),
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"volume": m.get("volume"),
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"liquidity": m.get("liquidity"),
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})
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logger.info(f"✅ 获取 {len(result)} 个预测市场")
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return result
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else:
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logger.warning(f"⚠️ Polymarket API 返回 {response.status_code}")
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return []
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except Timeout:
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logger.error("Timeout fetching Polymarket markets")
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return []
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except RequestException as e:
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logger.error(f"Network error fetching Polymarket markets: {e}")
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return []
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except json.JSONDecodeError:
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logger.error("Failed to parse JSON response from Polymarket")
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return []
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except Exception as e:
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logger.error(f"Unexpected error fetching Polymarket markets: {e}")
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return []
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def get_market_summary(self, limit: int = 10) -> str:
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"""
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获取预测市场摘要报告，用于了解当前热门话题和公众预期。
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Args:
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limit: 获取的市场数量
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Returns:
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格式化的预测市场报告
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"""
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markets = self.get_active_markets(limit)
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if not markets:
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return "❌ 无法获取 Polymarket 数据"
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report = f"# 🔮 Polymarket 热门预测 ({datetime.now().strftime('%Y-%m-%d %H:%M')})\n\n"
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for i, m in enumerate(markets, 1):
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question = m.get("question", "Unknown")
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prices = m.get("outcomePrices", [])
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volume = m.get("volume", 0)
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report += f"**{i}. {question}**\n"
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if prices:
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report += f" 概率: {prices}\n"
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if volume:
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report += f" 交易量: ${float(volume):,.0f}\n"
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report += "\n"
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return report
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