dd4715643c
- Completed Task 2: Context-aware and timeline search - ContextAwareSearch class with topic classification and result prioritization - TimelineSearch class with date-range filtering and temporal proximity - Enhanced MemoryManager with unified search interface - Supports semantic, keyword, context-aware, timeline, and hybrid search - Added search result dataclasses with relevance scoring - Integrated all search strategies into MemoryManager.search() method All search modes operational: - Semantic search with sentence-transformers embeddings - Context-aware search with topic-based prioritization - Timeline search with date filtering and recency weighting - Hybrid search combining multiple strategies Search results include conversation context and relevance scoring as required.
12 lines
290 B
Python
12 lines
290 B
Python
"""
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Storage module for memory operations.
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Provides SQLite database management and vector storage capabilities
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for conversation persistence and semantic search.
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"""
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from .sqlite_manager import SQLiteManager
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from .vector_store import VectorStore
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__all__ = ["SQLiteManager", "VectorStore"]
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