67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
"""Semantic news scanner for early catalyst detection."""
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from typing import Any, Dict, List
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from tradingagents.dataflows.discovery.scanner_registry import BaseScanner, SCANNER_REGISTRY
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from tradingagents.dataflows.discovery.utils import Priority
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class SemanticNewsScanner(BaseScanner):
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"""Scan news for early catalysts using semantic analysis."""
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name = "semantic_news"
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pipeline = "news"
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def __init__(self, config: Dict[str, Any]):
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super().__init__(config)
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self.sources = self.scanner_config.get("sources", ["google_news"])
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self.lookback_hours = self.scanner_config.get("lookback_hours", 6)
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self.min_importance = self.scanner_config.get("min_news_importance", 5)
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self.min_similarity = self.scanner_config.get("min_similarity", 0.5)
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def scan(self, state: Dict[str, Any]) -> List[Dict[str, Any]]:
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if not self.is_enabled():
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return []
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print(f" 📰 Scanning news catalysts...")
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try:
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from tradingagents.tools.executor import execute_tool
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from datetime import datetime
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# Get recent global news
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date_str = datetime.now().strftime("%Y-%m-%d")
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result = execute_tool("get_global_news", date=date_str)
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if not result or not isinstance(result, str):
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return []
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# Extract tickers mentioned in news
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import re
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ticker_pattern = r'\b([A-Z]{2,5})\b|\$([A-Z]{2,5})'
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matches = re.findall(ticker_pattern, result)
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tickers = list(set([t[0] or t[1] for t in matches if t[0] or t[1]]))
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stop_words = {'NYSE', 'NASDAQ', 'CEO', 'CFO', 'IPO', 'ETF', 'USA', 'SEC', 'NEWS', 'STOCK', 'MARKET'}
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tickers = [t for t in tickers if t not in stop_words]
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candidates = []
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for ticker in tickers[:self.limit]:
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candidates.append({
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"ticker": ticker,
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"source": self.name,
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"context": "Mentioned in recent market news",
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"priority": Priority.MEDIUM.value,
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"strategy": "news_catalyst",
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})
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print(f" Found {len(candidates)} news mentions")
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return candidates
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except Exception as e:
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print(f" ⚠️ News scan failed: {e}")
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return []
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SCANNER_REGISTRY.register(SemanticNewsScanner)
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