Feature add tigergraph support

[alexander-belikov]

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Related Issues

This PR adds TigerGraph as a new graph storage backend option for LightRAG, expanding the available graph database integrations alongside existing options (Neo4j, Memgraph, PostgreSQL, MongoDB, NetworkX).

Changes Made

1. New TigerGraph Storage Implementation (lightrag/kg/tigergraph_impl.py)

• New file: Complete implementation of TigerGraphStorage class extending BaseGraphStorage

• All abstract methods implemented:

  • Node operations: has_node, get_node, get_nodes_batch, upsert_node, delete_node, remove_nodes
  • Edge operations: has_edge, get_edge, get_edges_batch, upsert_edge, remove_edges
  • Graph traversal: get_node_edges, get_nodes_edges_batch, get_knowledge_graph
  • Query operations: node_degree, node_degrees_batch, edge_degree, edge_degrees_batch
  • Label operations: get_all_labels, get_popular_labels, search_labels
  • Chunk operations: get_nodes_by_chunk_ids, get_edges_by_chunk_ids
  • Bulk operations: get_all_nodes, get_all_edges
  • Lifecycle: initialize, finalize, index_done_callback, drop

• Key features:

  • Uses pyTigerGraph Python driver with async wrappers (asyncio.to_thread)
  • URI-based connection pattern (similar to Neo4j): TIGERGRAPH_URI
  • Workspace isolation using workspace label as vertex type name
  • Automatic schema creation on initialization
  • Undirected edge support (DIRECTED edge type for compatibility)
  • Chinese text support in label search
  • Retry logic with tenacity for write operations
  • Error handling and logging consistent with other backends

2. Storage Registry Updates (lightrag/kg/__init__.py)

• Added TigerGraphStorage to GRAPH_STORAGE implementations list
• Added environment variable requirements: TIGERGRAPH_URI, TIGERGRAPH_USERNAME, TIGERGRAPH_PASSWORD
• Added module mapping: "TigerGraphStorage": ".kg.tigergraph_impl"

3. Configuration Examples

• env.example: Added TigerGraph configuration section with:

  • TIGERGRAPH_URI (default: http://localhost:9000)
  • TIGERGRAPH_USERNAME (default: tigergraph)
  • TIGERGRAPH_PASSWORD (required)
  • TIGERGRAPH_GRAPH_NAME (default: lightrag)
  • TIGERGRAPH_WORKSPACE (optional, for workspace override)

• config.ini.example: Added [tigergraph] section with corresponding configuration options

Implementation Details

• Schema Design: Follows Neo4j pattern with workspace-based vertex types
• Primary Key: Uses entity_id as vertex primary key (STRING type)
• Properties: Supports entity_type, description, keywords, source_id with dynamic attribute support
• Edge Type: Single "DIRECTED" undirected edge type for all relationships
• Async Compatibility: All synchronous pyTigerGraph calls wrapped in asyncio.to_thread() for async compatibility
• Connection Management: Uses get_data_init_lock() and get_graph_db_lock() for thread-safe initialization

Checklist

• Changes tested locally
• Code reviewed
• Documentation updated (if necessary)
• Unit tests added (if applicable)

Additional Notes

Testing Requirements

• Requires a running TigerGraph instance for testing
• Default connection: http://localhost:9000
• Graph must be created or will use default graph name from configuration
• Schema is automatically created on first initialization

Dependencies

• pyTigerGraph:Install via pip install -e ".[offline-storage]" or automatically installed via pipmaster
• No changes to existing dependencies or requirements files

Compatibility

• Follows the same patterns as Neo4j implementation for consistency
• Compatible with existing LightRAG workflows
• Maintains workspace isolation similar to other backends
• Supports all query modes (local, global, hybrid, naive, mix)

Potential Future Enhancements

• Batch query optimization for better performance with large datasets
• TigerVector integration for native vector search capabilities
• Custom GSQL queries for complex graph traversals
• Connection pooling optimization for high-throughput scenarios

Known Limitations

• Some operations (like get_nodes_batch) iterate through nodes sequentially due to TigerGraph API limitations
• Schema creation uses GSQL commands which require appropriate permissions
• Large graph queries may need optimization for production use

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[danielaskdd]

Querying via traversal is inefficient and not recommended.

[alexander-belikov]

done

[danielaskdd]

Querying via traversal is inefficient and not recommended.

[alexander-belikov]

done

[danielaskdd]

get_nodes_by_chunk_ids is deprecated

[alexander-belikov]

done

[danielaskdd]

get_edges_by_chunk_ids is deprecated

[alexander-belikov]

done