Recall

Recall memories using semantic search with optional multi-hop graph expansion.

Performs semantic search using ChromaDB vector similarity, applies filters, and optionally expands results via graph edges using configurable multi-hop traversal.

Args: query: Search query text (will be embedded with mxbai query prefix) n_results: Maximum number of primary results (default: 5) namespace: Filter by namespace (optional, e.g., 'global' or 'project:myapp') memory_type: Filter by memory type (optional, e.g., 'preference', 'decision') min_importance: Minimum importance score filter (0.0 to 1.0, optional) include_related: If True, include related memories via graph edges (default: False) max_depth: Maximum number of hops for graph expansion (default: 1) max_expanded: Maximum number of expanded memories to return (default: 20) decay_factor: Factor by which relevance decays per hop (default: 0.7) include_edge_types: Optional list of edge types to include (None means all). Valid types: relates_to, supersedes, caused_by, contradicts exclude_edge_types: Optional list of edge types to exclude (None means none). Valid types: relates_to, supersedes, caused_by, contradicts

Returns: Dictionary with: - success: Boolean indicating operation success - memories: List of primary memory dicts with id, content, type, etc. - total: Total count of primary memories returned - score: Average similarity score of primary memories (or None) - expanded: List of expanded memory dicts (when include_related=True) with: - id: Memory ID - content: Memory content - type: Memory type - relevance_score: Combined relevance score (0.0 to 1.0) - hop_distance: Number of edges traversed to reach this memory - path: List of edge types in traversal order - explanation: Human-readable relevance explanation