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"""
Knowledge Graph Store
Manages nodes, edges, and graph operations
Supports both NetworkX (local) and Neo4j (production)
"""
import networkx as nx
from neo4j import GraphDatabase
from typing import List, Dict, Any, Optional, Tuple, Set
from loguru import logger
from models import GraphNode, GraphEdge, CanonicalTriple, SupportingChunk, NodeType, RelationType
from config import settings
import json
import pickle
from collections import defaultdict
from embedding_service import EmbeddingService
class GraphStore:
"""
Manages the knowledge graph with nodes and edges
Supports multiple backends: NetworkX (default) or Neo4j
"""
def __init__(self, use_neo4j: bool = False, embedding_service: Optional[EmbeddingService] = None):
self.use_neo4j = use_neo4j
self.embedding_service = embedding_service
if use_neo4j:
self._init_neo4j()
else:
self.graph = nx.MultiGraph() # Undirected graph (no arrows)
self.nodes_dict: Dict[str, GraphNode] = {} # node_id -> GraphNode
self.edges_dict: Dict[str, GraphEdge] = {} # edge_id -> GraphEdge
logger.info(f"Initialized GraphStore (backend: {'Neo4j' if use_neo4j else 'NetworkX'}, undirected graph)")
def _init_neo4j(self):
"""Initialize Neo4j connection"""
try:
self.driver = GraphDatabase.driver(
settings.neo4j_uri,
auth=(settings.neo4j_user, settings.neo4j_password)
)
# Test connection
with self.driver.session() as session:
session.run("RETURN 1")
logger.info("Connected to Neo4j successfully")
except Exception as e:
logger.error(f"Failed to connect to Neo4j: {e}")
logger.info("Falling back to NetworkX (undirected)")
self.use_neo4j = False
self.graph = nx.MultiGraph() # Undirected graph
self.nodes_dict = {}
self.edges_dict = {}
def add_node(self, node: GraphNode) -> bool:
"""
Add a node to the graph
Args:
node: GraphNode to add
Returns:
True if added, False if already exists
"""
if self.use_neo4j:
return self._add_node_neo4j(node)
else:
if node.node_id in self.nodes_dict:
return False
self.nodes_dict[node.node_id] = node
# Handle both enum and string for type field
node_type = node.type.value if hasattr(node.type, 'value') else node.type
self.graph.add_node(
node.node_id,
label=node.label,
type=node_type,
importance=node.importance_score
)
return True
def add_edge(self, edge: GraphEdge) -> bool:
"""
Add an edge to the graph
Args:
edge: GraphEdge to add
Returns:
True if added successfully
"""
if self.use_neo4j:
return self._add_edge_neo4j(edge)
else:
self.edges_dict[edge.edge_id] = edge
# Handle both enum and string for relation field
relation_value = edge.relation.value if hasattr(edge.relation, 'value') else edge.relation
self.graph.add_edge(
edge.from_node,
edge.to_node,
key=edge.edge_id,
relation=relation_value,
confidence=edge.confidence
)
return True
def get_node(self, node_id: str) -> Optional[GraphNode]:
"""Get node by ID"""
if self.use_neo4j:
return self._get_node_neo4j(node_id)
else:
return self.nodes_dict.get(node_id)
def update_node(self, node: GraphNode) -> bool:
"""
Update an existing node in the graph
Args:
node: GraphNode with updated data
Returns:
True if updated successfully, False if node doesn't exist
"""
if node.node_id not in self.nodes_dict:
return False
# Update in dictionary
self.nodes_dict[node.node_id] = node
# Update NetworkX graph attributes
if node.node_id in self.graph:
node_type = node.type.value if hasattr(node.type, 'value') else node.type
self.graph.nodes[node.node_id]['label'] = node.label
self.graph.nodes[node.node_id]['type'] = node_type
self.graph.nodes[node.node_id]['importance'] = node.importance_score
return True
def get_node_by_label(self, label: str) -> Optional[GraphNode]:
"""Get node by label (case-insensitive)"""
label_lower = label.lower()
for node in self.nodes_dict.values():
if node.label.lower() == label_lower or label_lower in [a.lower() for a in node.aliases]:
return node
return None
def get_neighbors(self, node_id: str) -> List[Tuple[GraphNode, GraphEdge]]:
"""
Get neighboring nodes and connecting edges (undirected graph)
Args:
node_id: Node to get neighbors for
Returns:
List of (neighbor_node, edge) tuples
"""
if self.use_neo4j:
return self._get_neighbors_neo4j(node_id)
else:
neighbors = []
# For undirected graph, just get all neighbors
for neighbor_id in self.graph.neighbors(node_id):
edges = self.graph.get_edge_data(node_id, neighbor_id)
if edges:
for edge_key, edge_data in edges.items():
edge = self.edges_dict.get(edge_key)
neighbor_node = self.nodes_dict.get(neighbor_id)
if edge and neighbor_node:
neighbors.append((neighbor_node, edge))
return neighbors
def get_all_nodes(self) -> List[GraphNode]:
"""Get all nodes in graph"""
if self.use_neo4j:
return self._get_all_nodes_neo4j()
else:
return list(self.nodes_dict.values())
def get_all_edges(self) -> List[GraphEdge]:
"""Get all edges in graph"""
if self.use_neo4j:
return self._get_all_edges_neo4j()
else:
return list(self.edges_dict.values())
def remove_node(self, node_id: str):
"""Remove node and its edges"""
if self.use_neo4j:
self._remove_node_neo4j(node_id)
else:
if node_id in self.nodes_dict:
del self.nodes_dict[node_id]
self.graph.remove_node(node_id)
def remove_edge(self, edge_id: str):
"""Remove edge"""
if self.use_neo4j:
self._remove_edge_neo4j(edge_id)
else:
if edge_id in self.edges_dict:
edge = self.edges_dict[edge_id]
del self.edges_dict[edge_id]
if self.graph.has_edge(edge.from_node, edge.to_node, key=edge_id):
self.graph.remove_edge(edge.from_node, edge.to_node, key=edge_id)
def compute_centrality(self) -> Dict[str, float]:
"""
Compute node centrality scores (degree centrality for undirected graph)
Returns:
Dict mapping node_id -> centrality score
"""
if self.use_neo4j:
# Use Neo4j's centrality algorithm
return self._compute_centrality_neo4j()
else:
try:
# Use degree centrality for undirected graph (simpler and faster)
centrality = nx.degree_centrality(self.graph)
return centrality
except Exception as e:
logger.error(f"Failed to compute centrality: {e}")
return {}
def save(self, filepath: str):
"""Save graph to file (NetworkX only)"""
if self.use_neo4j:
logger.info("Neo4j graphs are persisted automatically")
return
data = {
"nodes": [node.dict() for node in self.nodes_dict.values()],
"edges": [edge.dict() for edge in self.edges_dict.values()],
}
with open(filepath, 'wb') as f:
pickle.dump(data, f)
logger.info(f"Saved graph with {len(self.nodes_dict)} nodes and {len(self.edges_dict)} edges to {filepath}")
def load(self, filepath: str):
"""Load graph from file (NetworkX only)"""
if self.use_neo4j:
logger.warning("Cannot load into Neo4j from file")
return
with open(filepath, 'rb') as f:
data = pickle.load(f)
# Reconstruct nodes
for node_data in data["nodes"]:
node = GraphNode(**node_data)
self.add_node(node)
# Reconstruct edges
for edge_data in data["edges"]:
edge = GraphEdge(**edge_data)
self.add_edge(edge)
logger.info(f"Loaded graph with {len(self.nodes_dict)} nodes and {len(self.edges_dict)} edges")
def clear(self):
"""Clear all nodes and edges"""
if self.use_neo4j:
self._clear_neo4j()
else:
self.graph.clear()
self.nodes_dict.clear()
self.edges_dict.clear()
# Neo4j implementations (placeholders - implement as needed)
def _add_node_neo4j(self, node: GraphNode) -> bool:
"""Add node to Neo4j"""
with self.driver.session() as session:
# Handle both enum and string for type field
node_type = node.type.value if hasattr(node.type, 'value') else node.type
result = session.run(
"""
MERGE (n:Entity {node_id: $node_id})
ON CREATE SET n.label = $label, n.type = $type,
n.importance = $importance, n.created_at = datetime()
RETURN n
""",
node_id=node.node_id,
label=node.label,
type=node_type,
importance=node.importance_score
)
return result.single() is not None
def _add_edge_neo4j(self, edge: GraphEdge) -> bool:
"""Add edge to Neo4j"""
with self.driver.session() as session:
# Handle both enum and string for relation field
relation_value = edge.relation.value if hasattr(edge.relation, 'value') else edge.relation
session.run(
"""
MATCH (a:Entity {node_id: $from_node})
MATCH (b:Entity {node_id: $to_node})
CREATE (a)-[r:RELATES {edge_id: $edge_id, relation: $relation,
confidence: $confidence}]->(b)
""",
from_node=edge.from_node,
to_node=edge.to_node,
edge_id=edge.edge_id,
relation=relation_value,
confidence=edge.confidence
)
return True
def _get_node_neo4j(self, node_id: str) -> Optional[GraphNode]:
"""Get node from Neo4j"""
# Implementation omitted for brevity
pass
def _get_neighbors_neo4j(self, node_id: str) -> List[Tuple[GraphNode, GraphEdge]]:
"""Get neighbors from Neo4j"""
# Implementation omitted for brevity
pass
def _get_all_nodes_neo4j(self) -> List[GraphNode]:
"""Get all nodes from Neo4j"""
pass
def _get_all_edges_neo4j(self) -> List[GraphEdge]:
"""Get all edges from Neo4j"""
pass
def _remove_node_neo4j(self, node_id: str):
"""Remove node from Neo4j"""
pass
def _remove_edge_neo4j(self, edge_id: str):
"""Remove edge from Neo4j"""
pass
def _compute_centrality_neo4j(self) -> Dict[str, float]:
"""Compute centrality in Neo4j"""
pass
def _clear_neo4j(self):
"""Clear Neo4j database"""
with self.driver.session() as session:
session.run("MATCH (n) DETACH DELETE n")
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