diff --git a/lightrag/api/README.md b/lightrag/api/README.md index 4ba9b2cf..590c4ef5 100644 --- a/lightrag/api/README.md +++ b/lightrag/api/README.md @@ -181,9 +181,9 @@ The command-line `workspace` argument and the `WORKSPACE` environment variable i - **For local file-based databases, data isolation is achieved through workspace subdirectories:** `JsonKVStorage`, `JsonDocStatusStorage`, `NetworkXStorage`, `NanoVectorDBStorage`, `FaissVectorDBStorage`. - **For databases that store data in collections, it's done by adding a workspace prefix to the collection name:** `RedisKVStorage`, `RedisDocStatusStorage`, `MilvusVectorDBStorage`, `QdrantVectorDBStorage`, `MongoKVStorage`, `MongoDocStatusStorage`, `MongoVectorDBStorage`, `MongoGraphStorage`, `PGGraphStorage`. - **For relational databases, data isolation is achieved by adding a `workspace` field to the tables for logical data separation:** `PGKVStorage`, `PGVectorStorage`, `PGDocStatusStorage`. -- **For the Neo4j graph database, logical data isolation is achieved through labels:** `Neo4JStorage` +- **For graph databases, logical data isolation is achieved through labels:** `Neo4JStorage`, `MemgraphStorage` -To maintain compatibility with legacy data, the default workspace for PostgreSQL is `default` and for Neo4j is `base` when no workspace is configured. For all external storages, the system provides dedicated workspace environment variables to override the common `WORKSPACE` environment variable configuration. These storage-specific workspace environment variables are: `REDIS_WORKSPACE`, `MILVUS_WORKSPACE`, `QDRANT_WORKSPACE`, `MONGODB_WORKSPACE`, `POSTGRES_WORKSPACE`, `NEO4J_WORKSPACE`. +To maintain compatibility with legacy data, the default workspace for PostgreSQL is `default` and for Neo4j is `base` when no workspace is configured. For all external storages, the system provides dedicated workspace environment variables to override the common `WORKSPACE` environment variable configuration. These storage-specific workspace environment variables are: `REDIS_WORKSPACE`, `MILVUS_WORKSPACE`, `QDRANT_WORKSPACE`, `MONGODB_WORKSPACE`, `POSTGRES_WORKSPACE`, `NEO4J_WORKSPACE`, `MEMGRAPH_WORKSPACE`. ### Multiple workers for Gunicorn + Uvicorn @@ -396,6 +396,7 @@ MongoKVStorage MongoDB NetworkXStorage NetworkX (default) Neo4JStorage Neo4J PGGraphStorage PostgreSQL with AGE plugin +MemgraphStorage. Memgraph ``` > Testing has shown that Neo4J delivers superior performance in production environments compared to PostgreSQL with AGE plugin. diff --git a/lightrag/kg/memgraph_impl.py b/lightrag/kg/memgraph_impl.py index 8c6d6574..3d2c131e 100644 --- a/lightrag/kg/memgraph_impl.py +++ b/lightrag/kg/memgraph_impl.py @@ -435,7 +435,7 @@ class MemgraphStorage(BaseGraphStorage): async def upsert_node(self, node_id: str, node_data: dict[str, str]) -> None: """ - Upsert a node in the Neo4j database. + Upsert a node in the Memgraph database. Args: node_id: The unique identifier for the node (used as label) @@ -448,7 +448,9 @@ class MemgraphStorage(BaseGraphStorage): properties = node_data entity_type = properties["entity_type"] if "entity_id" not in properties: - raise ValueError("Neo4j: node properties must contain an 'entity_id' field") + raise ValueError( + "Memgraph: node properties must contain an 'entity_id' field" + ) try: async with self._driver.session(database=self._DATABASE) as session: @@ -732,7 +734,7 @@ class MemgraphStorage(BaseGraphStorage): self, node_label: str, max_depth: int = 3, - max_nodes: int = MAX_GRAPH_NODES, + max_nodes: int = None, ) -> KnowledgeGraph: """ Retrieve a connected subgraph of nodes where the label includes the specified `node_label`. @@ -740,120 +742,118 @@ class MemgraphStorage(BaseGraphStorage): Args: node_label: Label of the starting node, * means all nodes max_depth: Maximum depth of the subgraph, Defaults to 3 - max_nodes: Maxiumu nodes to return by BFS, Defaults to 1000 + max_nodes: Maximum nodes to return by BFS, Defaults to 1000 Returns: KnowledgeGraph object containing nodes and edges, with an is_truncated flag indicating whether the graph was truncated due to max_nodes limit - - Raises: - Exception: If there is an error executing the query """ - if self._driver is None: - raise RuntimeError( - "Memgraph driver is not initialized. Call 'await initialize()' first." - ) + # Get max_nodes from global_config if not provided + if max_nodes is None: + max_nodes = self.global_config.get("max_graph_nodes", 1000) + else: + # Limit max_nodes to not exceed global_config max_graph_nodes + max_nodes = min(max_nodes, self.global_config.get("max_graph_nodes", 1000)) + workspace_label = self._get_workspace_label() result = KnowledgeGraph() seen_nodes = set() seen_edges = set() - workspace_label = self._get_workspace_label() + async with self._driver.session( database=self._DATABASE, default_access_mode="READ" ) as session: try: if node_label == "*": - # First check if database has any nodes - count_query = "MATCH (n) RETURN count(n) as total" + # First check total node count to determine if graph is truncated + count_query = ( + f"MATCH (n:`{workspace_label}`) RETURN count(n) as total" + ) count_result = None - total_count = 0 try: count_result = await session.run(count_query) count_record = await count_result.single() - if count_record: - total_count = count_record["total"] - if total_count == 0: - logger.debug("No nodes found in database") - return result - if total_count > max_nodes: - result.is_truncated = True - logger.info( - f"Graph truncated: {total_count} nodes found, limited to {max_nodes}" - ) + + if count_record and count_record["total"] > max_nodes: + result.is_truncated = True + logger.info( + f"Graph truncated: {count_record['total']} nodes found, limited to {max_nodes}" + ) finally: if count_result: await count_result.consume() - # Run the main query to get nodes with highest degree + # Run main query to get nodes with highest degree main_query = f""" MATCH (n:`{workspace_label}`) OPTIONAL MATCH (n)-[r]-() WITH n, COALESCE(count(r), 0) AS degree ORDER BY degree DESC LIMIT $max_nodes - WITH collect(n) AS kept_nodes - MATCH (a)-[r]-(b) + WITH collect({{node: n}}) AS filtered_nodes + UNWIND filtered_nodes AS node_info + WITH collect(node_info.node) AS kept_nodes, filtered_nodes + OPTIONAL MATCH (a)-[r]-(b) WHERE a IN kept_nodes AND b IN kept_nodes - RETURN [node IN kept_nodes | {{node: node}}] AS node_info, + RETURN filtered_nodes AS node_info, collect(DISTINCT r) AS relationships """ result_set = None try: result_set = await session.run( - main_query, {"max_nodes": max_nodes} + main_query, + {"max_nodes": max_nodes}, ) record = await result_set.single() - if not record: - logger.debug("No record returned from main query") - return result finally: if result_set: await result_set.consume() else: - bfs_query = f""" + # Run subgraph query for specific node_label + subgraph_query = f""" MATCH (start:`{workspace_label}`) WHERE start.entity_id = $entity_id - WITH start - CALL {{ - WITH start - MATCH path = (start)-[*0..{max_depth}]-(node) - WITH nodes(path) AS path_nodes, relationships(path) AS path_rels - UNWIND path_nodes AS n - WITH collect(DISTINCT n) AS all_nodes, collect(DISTINCT path_rels) AS all_rel_lists - WITH all_nodes, reduce(r = [], x IN all_rel_lists | r + x) AS all_rels - RETURN all_nodes, all_rels - }} - WITH all_nodes AS nodes, all_rels AS relationships, size(all_nodes) AS total_nodes + + MATCH path = (start)-[*BFS 0..{max_depth}]-(end:`{workspace_label}`) + WHERE ALL(n IN nodes(path) WHERE '{workspace_label}' IN labels(n)) + WITH collect(DISTINCT end) + start AS all_nodes_unlimited WITH CASE - WHEN total_nodes <= {max_nodes} THEN nodes - ELSE nodes[0..{max_nodes}] + WHEN size(all_nodes_unlimited) <= $max_nodes THEN all_nodes_unlimited + ELSE all_nodes_unlimited[0..$max_nodes] END AS limited_nodes, - relationships, - total_nodes, - total_nodes > {max_nodes} AS is_truncated + size(all_nodes_unlimited) > $max_nodes AS is_truncated + + UNWIND limited_nodes AS n + MATCH (n)-[r]-(m) + WHERE m IN limited_nodes + WITH collect(DISTINCT n) AS limited_nodes, collect(DISTINCT r) AS relationships, is_truncated + RETURN [node IN limited_nodes | {{node: node}}] AS node_info, relationships, - total_nodes, is_truncated """ + result_set = None try: result_set = await session.run( - bfs_query, + subgraph_query, { "entity_id": node_label, + "max_nodes": max_nodes, }, ) record = await result_set.single() + + # If no record found, return empty KnowledgeGraph if not record: logger.debug(f"No nodes found for entity_id: {node_label}") return result - # Check if the query indicates truncation - if "is_truncated" in record and record["is_truncated"]: + # Check if the result was truncated + if record.get("is_truncated"): result.is_truncated = True logger.info( f"Graph truncated: breadth-first search limited to {max_nodes} nodes" @@ -863,13 +863,11 @@ class MemgraphStorage(BaseGraphStorage): if result_set: await result_set.consume() - # Process the record if it exists - if record and record["node_info"]: + if record: for node_info in record["node_info"]: node = node_info["node"] node_id = node.id if node_id not in seen_nodes: - seen_nodes.add(node_id) result.nodes.append( KnowledgeGraphNode( id=f"{node_id}", @@ -877,11 +875,11 @@ class MemgraphStorage(BaseGraphStorage): properties=dict(node), ) ) + seen_nodes.add(node_id) for rel in record["relationships"]: edge_id = rel.id if edge_id not in seen_edges: - seen_edges.add(edge_id) start = rel.start_node end = rel.end_node result.edges.append( @@ -893,14 +891,13 @@ class MemgraphStorage(BaseGraphStorage): properties=dict(rel), ) ) + seen_edges.add(edge_id) - logger.info( - f"Subgraph query successful | Node count: {len(result.nodes)} | Edge count: {len(result.edges)}" - ) + logger.info( + f"Subgraph query successful | Node count: {len(result.nodes)} | Edge count: {len(result.edges)}" + ) except Exception as e: - logger.error(f"Error getting knowledge graph: {str(e)}") - # Return empty but properly initialized KnowledgeGraph on error - return KnowledgeGraph() + logger.warning(f"Memgraph error during subgraph query: {str(e)}") return result