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Browse files- reasoning/market_analysis.py +108 -0
reasoning/market_analysis.py
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@@ -9,6 +9,8 @@ from datetime import datetime
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import numpy as np
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from collections import defaultdict
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@dataclass
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class MarketSegment:
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"""Market segment analysis."""
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@@ -340,3 +342,109 @@ class MarketAnalyzer:
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for t in self.trends
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]
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}
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import numpy as np
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from collections import defaultdict
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from .base import ReasoningStrategy
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@dataclass
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class MarketSegment:
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"""Market segment analysis."""
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for t in self.trends
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]
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}
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class MarketAnalysisStrategy(ReasoningStrategy):
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"""
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Advanced market analysis strategy that combines multiple analytical tools
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to provide comprehensive market insights.
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"""
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def __init__(self, config: Optional[Dict[str, Any]] = None):
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"""Initialize market analysis strategy."""
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super().__init__()
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self.config = config or {}
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self.analyzer = MarketAnalyzer()
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async def reason(self, query: str, context: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Perform market analysis based on query and context.
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Args:
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query: The market analysis query
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context: Additional context and parameters
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Returns:
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Dict containing market analysis results and confidence scores
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"""
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try:
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# Extract market segment from query/context
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segment = self._extract_segment(query, context)
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# Perform market analysis
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analysis = await self._analyze_market(segment, context)
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# Get insights
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insights = self.analyzer.get_market_insights()
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# Calculate confidence based on data quality and completeness
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confidence = self._calculate_confidence(analysis, insights)
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return {
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'answer': self._format_insights(insights),
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'confidence': confidence,
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'analysis': analysis,
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'insights': insights,
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'segment': segment
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}
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except Exception as e:
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logging.error(f"Market analysis failed: {str(e)}")
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return {
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'error': f"Market analysis failed: {str(e)}",
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'confidence': 0.0
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}
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def _extract_segment(self, query: str, context: Dict[str, Any]) -> str:
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"""Extract market segment from query and context."""
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# Use context if available
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if 'segment' in context:
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return context['segment']
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# Default to general market
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return 'general'
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async def _analyze_market(self, segment: str, context: Dict[str, Any]) -> Dict[str, Any]:
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"""Perform comprehensive market analysis."""
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return await self.analyzer.analyze_market(segment, context)
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def _calculate_confidence(self, analysis: Dict[str, Any], insights: Dict[str, Any]) -> float:
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"""Calculate confidence score based on analysis quality."""
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# Base confidence
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confidence = 0.5
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# Adjust based on data completeness
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if analysis.get('segment_analysis'):
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confidence += 0.1
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if analysis.get('competitor_analysis'):
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confidence += 0.1
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if analysis.get('trend_analysis'):
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confidence += 0.1
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# Adjust based on insight quality
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if insights.get('opportunities'):
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confidence += 0.1
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if insights.get('risks'):
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confidence += 0.1
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return min(confidence, 1.0)
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def _format_insights(self, insights: Dict[str, Any]) -> str:
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"""Format market insights into readable text."""
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sections = []
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if 'market_overview' in insights:
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sections.append(f"Market Overview: {insights['market_overview']}")
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if 'opportunities' in insights:
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opps = insights['opportunities']
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sections.append("Key Opportunities:\n- " + "\n- ".join(opps))
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if 'risks' in insights:
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risks = insights['risks']
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sections.append("Key Risks:\n- " + "\n- ".join(risks))
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if 'recommendations' in insights:
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recs = insights['recommendations']
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sections.append("Recommendations:\n- " + "\n- ".join(recs))
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return "\n\n".join(sections)
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