From 40142b4789197e7f2a96263e551cd70e6aa70670 Mon Sep 17 00:00:00 2001
From: Vasilije <8619304+Vasilije1990@users.noreply.github.com>
Date: Tue, 15 Apr 2025 16:22:21 +0200
Subject: [PATCH] Delete cognee/modules/graph/README.md

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-# Layered Knowledge Graph
-
-This module provides a simplified implementation of a layered knowledge graph, which allows organizing nodes and edges into hierarchical layers.
-
-## Features
-
-- **Hierarchical Layer Structure**: Organize your graph into layers with parent-child relationships
-- **Cumulative Views**: Access nodes and edges from a layer and all its parent layers
-- **Adapter-based Design**: Connect to different database backends using adapter pattern
-- **NetworkX Integration**: Built-in support for NetworkX graph database
-- **Type Safety**: Pydantic models ensure type safety and data validation
-- **Async API**: All methods are async for better performance
-
-## Components
-
-- **GraphNode**: A node in the graph with a name, type, properties, and metadata
-- **GraphEdge**: An edge connecting two nodes with an edge type, properties, and metadata
-- **GraphLayer**: A layer in the graph that can contain nodes and edges, and can have parent layers
-- **LayeredKnowledgeGraph**: The main graph class that manages layers, nodes, and edges
-
-## Usage Example
-
-```python
-import asyncio
-from uuid import UUID
-from cognee.modules.graph.simplified_layered_graph import LayeredKnowledgeGraph
-from cognee.modules.graph.enhanced_layered_graph_adapter import LayeredGraphDBAdapter
-from cognee.infrastructure.databases.graph.networkx.adapter import NetworkXAdapter
-
-async def main():
-    # Initialize adapter
-    adapter = NetworkXAdapter(filename="graph.pkl")
-    await adapter.create_empty_graph("graph.pkl")
-    
-    # Create graph
-    graph = LayeredKnowledgeGraph.create_empty("My Knowledge Graph")
-    graph.set_adapter(LayeredGraphDBAdapter(adapter))
-    
-    # Add layers with parent-child relationships
-    base_layer = await graph.add_layer(
-        name="Base Layer", 
-        description="Foundation concepts",
-        layer_type="base"
-    )
-    
-    derived_layer = await graph.add_layer(
-        name="Derived Layer",
-        description="Concepts built upon the base layer",
-        layer_type="derived",
-        parent_layers=[base_layer.id]  # Parent-child relationship
-    )
-    
-    # Add nodes to layers
-    node1 = await graph.add_node(
-        name="Concept A",
-        node_type="concept",
-        properties={"importance": "high"},
-        layer_id=base_layer.id
-    )
-    
-    node2 = await graph.add_node(
-        name="Concept B",
-        node_type="concept",
-        properties={"importance": "medium"},
-        layer_id=derived_layer.id
-    )
-    
-    # Connect nodes with an edge
-    edge = await graph.add_edge(
-        source_id=node1.id,
-        target_id=node2.id,
-        edge_type="RELATES_TO",
-        properties={"strength": "high"},
-        layer_id=derived_layer.id
-    )
-    
-    # Get cumulative view (including parent layers)
-    nodes, edges = await graph.get_cumulative_layer_graph(derived_layer.id)
-    
-    print(f"Nodes in cumulative view: {[n.name for n in nodes]}")
-    print(f"Edges in cumulative view: {[e.edge_type for e in edges]}")
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-## Design Improvements
-
-The simplified layered graph implementation offers several improvements over the previous approach:
-
-1. **Clear Separation of Concerns**: In-memory operations vs. database operations
-2. **More Intuitive API**: Methods have clear, consistent signatures
-3. **Better Error Handling**: Comprehensive validation and error reporting
-4. **Enhanced Debugging**: Detailed logging throughout
-5. **Improved Caching**: Local caches reduce database load
-6. **Method Naming Consistency**: All methods follow consistent naming conventions
-7. **Reduced Complexity**: Simpler implementation with equivalent functionality
-
-## Best Practices
-
-- Always use the adapter pattern for database operations
-- Use the provided factory methods for creating nodes and edges
-- Leverage parent-child relationships for organizing related concepts
-- Utilize cumulative views to access inherited nodes and edges
-- Consider layer types for additional semantic meaning
-- Use properties and metadata for storing additional information 
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