Feat/cog 553 graph memory projection

cognee/infrastructure/databases/graph/neo4j_driver/adapter.py

@@ -27,9 +27,6 @@ def __init__(
             max_connection_lifetime = 120
         )
 
-    async def close(self) -> None:
-        await self.driver.close()
-
     @asynccontextmanager
     async def get_session(self) -> AsyncSession:
         async with self.driver.session() as session:

cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py

@@ -112,10 +112,18 @@ def create_lance_data_point(data_point: DataPoint, vector: list[float]) -> Lance
                 for (data_point_index, data_point) in enumerate(data_points)
         ]
 
-        await collection.merge_insert("id") \
-            .when_matched_update_all() \
-            .when_not_matched_insert_all() \
-            .execute(lance_data_points)
+        # TODO: This enables us to work with pydantic version but shouldn't
+        #  stay like this, existing rows should be updated
+
+        await collection.delete("id IS NOT NULL")
+
+        original_size = await collection.count_rows()
+        await collection.add(lance_data_points)
+        new_size = await collection.count_rows()
+
+        if new_size <= original_size:
+            raise ValueError(
+                "LanceDB create_datapoints error: data points did not get added.")
 
 
     async def retrieve(self, collection_name: str, data_point_ids: list[str]):

cognee/modules/chunking/TextChunker.py

@@ -17,6 +17,7 @@ def __init__(self, document, get_text: callable, chunk_size: int = 1024):
         self.get_text = get_text
 
     def read(self):
+        self.paragraph_chunks = []
         for content_text in self.get_text():
             for chunk_data in chunk_by_paragraph(
                 content_text,

cognee/modules/graph/cognee_graph/CogneeAbstractGraph.py

@@ -0,0 +1,35 @@
+from abc import ABC, abstractmethod
+from typing import List, Dict, Union
+from CogneeGraphElements import Node, Edge
+from cognee.infrastructure.databases.graph.graph_db_interface import GraphDBInterface
+
+class CogneeAbstractGraph(ABC):
+    """
+    Abstract base class for representing a graph structure.
+
+    """
+
+    @abstractmethod
+    def add_node(self, node: Node) -> None:
+        """Add a node to the graph."""
+        pass
+
+    @abstractmethod
+    def add_edge(self, edge: Edge) -> None:
+        """Add an edge to the graph."""
+        pass
+
+    @abstractmethod
+    def get_node(self, node_id: str) -> Node:
+        """Retrieve a node by its ID."""
+        pass
+
+    @abstractmethod
+    def get_edges(self, node_id: str) -> List[Edge]:
+        """Retrieve edges connected to a specific node."""
+        pass
+
+    @abstractmethod
+    async def project_graph_from_db(self, adapter: GraphDBInterface, directed: bool, dimension: int) -> None:
+        """Project the graph structure from a database using the provided adapter."""
+        pass

cognee/modules/graph/cognee_graph/CogneeGraph.py

@@ -0,0 +1,88 @@
+from typing import List, Dict, Union
+from CogneeGraphElements import Node, Edge
+from CogneeAbstractGraph import CogneeAbstractGraph
+from cognee.infrastructure.databases.graph import get_graph_engine
+from cognee.infrastructure.databases.graph.neo4j_driver.adapter import Neo4jAdapter
+from cognee.infrastructure.databases.graph.networkx.adapter import NetworkXAdapter
+import os
+
+class CogneeGraph(CogneeAbstractGraph):
+    """
+    Concrete implementation of the AbstractGraph class for Cognee.
+
+    This class provides the functionality to manage nodes and edges,
+    and project a graph from a database using adapters.
+    """
+
+    nodes: Dict[str, Node]
+    edges: List[Edge]
+    directed: bool
+
+    def __init__(self, directed: bool = True):
+        self.nodes = {}
+        self.edges = []
+        self.directed = directed
+
+    def add_node(self, node: Node) -> None:
+        if node.id not in self.nodes:
+            self.nodes[node.id] = node
+        else:
+            raise ValueError(f"Node with id {node.id} already exists.")
+
+    def add_edge(self, edge: Edge) -> None:
+        if edge not in self.edges:
+            self.edges.append(edge)
+            edge.node1.add_skeleton_edge(edge)
+            edge.node2.add_skeleton_edge(edge)
+        else:
+            raise ValueError(f"Edge {edge} already exists in the graph.")
+
+    def get_node(self, node_id: str) -> Node:
+        return self.nodes.get(node_id, None)
+
+    def get_edges(self, node_id: str) -> List[Edge]:
+        node = self.get_node(node_id)
+        if node:
+            return node.skeleton_edges
+        else:
+            raise ValueError(f"Node with id {node_id} does not exist.")
+
+    async def project_graph_from_db(self,
+                                    adapter: Union[NetworkXAdapter, Neo4jAdapter],
+                                    node_properties_to_project: List[str],
+                                    edge_properties_to_project: List[str],
+                                    directed = True,
+                                    node_dimension = 1,
+                                    edge_dimension = 1) -> None:
+        try:
+            nodes_data, edges_data = await adapter.get_graph_data()
+
+            if not nodes_data:
+                raise ValueError("No node data retrieved from the database.")
+            if not edges_data:
+                raise ValueError("No edge data retrieved from the database.")
+
+            for node_id, properties in nodes_data:
+                node_attributes = {key: properties.get(key) for key in node_properties_to_project}
+                self.add_node(Node(str(node_id), node_attributes, dimension=node_dimension))
+
+            for source_id, target_id, relationship_type, properties in edges_data:
+                source_node = self.get_node(str(source_id))
+                target_node = self.get_node(str(target_id))
+                if source_node and target_node:
+                    edge_attributes = {key: properties.get(key) for key in edge_properties_to_project}
+                    edge_attributes['relationship_type'] = relationship_type
+
+                    edge = Edge(source_node, target_node, attributes=edge_attributes, directed=directed, dimension=edge_dimension)
+                    self.add_edge(edge)
+
+                    source_node.add_skeleton_edge(edge)
+                    target_node.add_skeleton_edge(edge)
+
+                else:
+                    raise ValueError(f"Edge references nonexistent nodes: {source_id} -> {target_id}")
+
+        except (ValueError, TypeError) as e:
+            print(f"Error projecting graph: {e}")
+        except Exception as ex:
+            print(f"Unexpected error: {ex}")

cognee/modules/graph/cognee_graph/CogneeGraphElements.py

@@ -0,0 +1,110 @@
+import numpy as np
+from typing import List, Dict, Optional, Any
+
+class Node:
+    """
+        Represents a node in a graph.
+        Attributes:
+            id (str): A unique identifier for the node.
+            attributes (Dict[str, Any]): A dictionary of attributes associated with the node.
+            neighbors (List[Node]): Represents the original nodes
+            skeleton_edges (List[Edge]): Represents the original edges
+        """
+    id: str
+    attributes: Dict[str, Any]
+    skeleton_neighbours: List["Node"]
+    skeleton_edges: List["Edge"]
+    status: np.ndarray
+
+    def __init__(self, node_id: str, attributes: Optional[Dict[str, Any]] = None, dimension: int = 1):
+        self.id = node_id
+        self.attributes = attributes if attributes is not None else {}
+        self.skeleton_neighbours = []
+        self.skeleton_edges = []
+        self.status = np.ones(dimension, dtype=int)
+
+    def add_skeleton_neighbor(self, neighbor: "Node") -> None:
+        if neighbor not in self.skeleton_neighbours:
+            self.skeleton_neighbours.append(neighbor)
+
+    def remove_skeleton_neighbor(self, neighbor: "Node") -> None:
+        if neighbor in self.skeleton_neighbours:
+            self.skeleton_neighbours.remove(neighbor)
+
+    def add_skeleton_edge(self, edge: "Edge") -> None:
+        if edge not in self.skeleton_edges:
+            self.skeleton_edges.append(edge)
+            # Add neighbor
+            if edge.node1 == self:
+                self.add_skeleton_neighbor(edge.node2)
+            elif edge.node2 == self:
+                self.add_skeleton_neighbor(edge.node1)
+
+    def remove_skeleton_edge(self, edge: "Edge") -> None:
+        if edge in self.skeleton_edges:
+            self.skeleton_edges.remove(edge)
+            # Remove neighbor if no other edge connects them
+            neighbor = edge.node2 if edge.node1 == self else edge.node1
+            if all(e.node1 != neighbor and e.node2 != neighbor for e in self.skeleton_edges):
+                self.remove_skeleton_neighbor(neighbor)
+
+    def is_node_alive_in_dimension(self, dimension: int) -> bool:
+        if dimension < 0 or dimension >= len(self.status):
+            raise ValueError(f"Dimension {dimension} is out of range. Valid range is 0 to {len(self.status) - 1}.")
+        return self.status[dimension] == 1
+
+    def __repr__(self) -> str:
+        return f"Node({self.id}, attributes={self.attributes})"
+
+    def __hash__(self) -> int:
+        return hash(self.id)
+
+    def __eq__(self, other: "Node") -> bool:
+        return isinstance(other, Node) and self.id == other.id
+
+
+class Edge:
+    """
+        Represents an edge in a graph, connecting two nodes.
+        Attributes:
+            node1 (Node): The starting node of the edge.
+            node2 (Node): The ending node of the edge.
+            attributes (Dict[str, Any]): A dictionary of attributes associated with the edge.
+            directed (bool): A flag indicating whether the edge is directed or undirected.
+    """
+
+    node1: "Node"
+    node2: "Node"
+    attributes: Dict[str, Any]
+    directed: bool
+    status: np.ndarray
+
+    def __init__(self, node1: "Node", node2: "Node", attributes: Optional[Dict[str, Any]] = None, directed: bool = True, dimension: int = 1):
+        if dimension <= 0:
+            raise ValueError("Dimensions must be a positive integer.")
+        self.node1 = node1
+        self.node2 = node2
+        self.attributes = attributes if attributes is not None else {}
+        self.directed = directed
+        self.status = np.ones(dimension, dtype=int)
+
+    def is_edge_alive_in_dimension(self, dimension: int) -> bool:
+        if dimension < 0 or dimension >= len(self.status):
+            raise ValueError(f"Dimension {dimension} is out of range. Valid range is 0 to {len(self.status) - 1}.")
+        return self.status[dimension] == 1
+
+    def __repr__(self) -> str:
+        direction = "->" if self.directed else "--"
+        return f"Edge({self.node1.id} {direction} {self.node2.id}, attributes={self.attributes})"
+
+    def __hash__(self) -> int:
+        if self.directed:
+            return hash((self.node1, self.node2))
+        else:
+            return hash(frozenset({self.node1, self.node2}))
+
+    def __eq__(self, other: "Edge") -> bool:
+        if self.directed:
+            return self.node1 == other.node1 and self.node2 == other.node2
+        else:
+            return {self.node1, self.node2} == {other.node1, other.node2}