"""Indexing services for skills (vector + graph hybrid RAG).
This package provides a hybrid search architecture combining:
- Vector similarity search (ChromaDB)
- Knowledge graph relationships (NetworkX)
Public API:
- IndexingEngine: Main orchestration class
- VectorStore: ChromaDB vector operations
- GraphStore: NetworkX graph operations
- HybridSearcher: Result combination logic
- ScoredSkill: Search result dataclass
- IndexStats: Index statistics dataclass
Example Usage:
>>> from mcp_skills.services.indexing import IndexingEngine
>>> engine = IndexingEngine(skill_manager=manager)
>>> stats = engine.reindex_all(force=True)
>>> results = engine.search("python testing", top_k=5)
"""
from mcp_skills.services.indexing.engine import IndexingEngine, IndexStats
from mcp_skills.services.indexing.graph_store import GraphStore
from mcp_skills.services.indexing.hybrid_search import HybridSearcher, ScoredSkill
from mcp_skills.services.indexing.vector_store import VectorStore
__all__ = [
"IndexingEngine",
"VectorStore",
"GraphStore",
"HybridSearcher",
"ScoredSkill",
"IndexStats",
]
