feat(04-02): implement context-aware and timeline search capabilities

- 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.

src/memory/storage/__init__.py

@@ -6,6 +6,6 @@ for conversation persistence and semantic search.
 """
 
 from .sqlite_manager import SQLiteManager
-# from .vector_store import VectorStore  # Will be added in Task 2
+from .vector_store import VectorStore
 
 __all__ = ["SQLiteManager", "VectorStore"]