Felipe Cardoso
0d2005ddcb
Add comprehensive scoring system with three strategies: - RelevanceScorer: Semantic similarity with keyword fallback - RecencyScorer: Exponential decay with type-specific half-lives - PriorityScorer: Priority-based scoring with type bonuses Implement CompositeScorer combining all strategies with configurable weights (default: 50% relevance, 30% recency, 20% priority). Add ContextRanker for budget-aware context selection with: - Greedy selection algorithm respecting token budgets - CRITICAL priority contexts always included - Diversity reranking to prevent source dominance - Comprehensive selection statistics 68 tests covering all scoring and ranking functionality. Part of #61 - Context Management Engine 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
13 lines
187 B
Python
13 lines
187 B
Python
"""
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Context Prioritization Module.
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Provides context ranking and selection.
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"""
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from .ranker import ContextRanker, RankingResult
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__all__ = [
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"ContextRanker",
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"RankingResult",
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]
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