> For the complete documentation index, see [llms.txt](https://aether-framework.gitbook.io/aetherframework/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://aether-framework.gitbook.io/aetherframework/knowledge-graph-integration.md).

# Knowledge Graph Integration

Aether Framework supports the integration of **knowledge graphs** to enable agents to store, query, and reason about structured information. This feature enhances the decision-making capabilities of agents by providing a persistent and queryable knowledge base.

***

#### **Key Features**

1. **Concept Storage**\
   Agents can store concepts, attributes, and relationships in a graph structure.
2. **Reasoning and Querying**\
   Agents can query the knowledge graph to retrieve relevant information or relationships.
3. **Visualization**\
   The knowledge graph can be visualized for better understanding and debugging.

***

#### **Example Workflow**

1. **Add Knowledge to the Graph**

   ```python
   from src.utils.knowledge_graph import KnowledgeGraph

   # Initialize the Knowledge Graph
   knowledge_graph = KnowledgeGraph()

   # Add a concept
   knowledge_graph.add_concept("AI Agent", {"role": "worker", "status": "active"})

   # Add a relationship between concepts
   knowledge_graph.add_relationship("AI Agent", "Swarm", "belongs_to")
   ```
2. **Query the Knowledge Graph**

   ```python
   # Query a concept
   result = knowledge_graph.query_concept("AI Agent")
   print(f"Attributes of AI Agent: {result}")

   # Query relationships
   relationships = knowledge_graph.query_relationships("AI Agent")
   print(f"Relationships of AI Agent: {relationships}")
   ```
3. **Visualize the Knowledge Graph**

   ```python
   # Visualize the graph
   knowledge_graph.visualize_graph(output_path="knowledge_graph.png")
   print("Knowledge graph saved as knowledge_graph.png")
   ```

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#### **Benefits of Knowledge Graphs in Aether**

1. **Enhanced Reasoning**\
   Agents can use structured knowledge to make more informed decisions.
2. **Collaboration**\
   Agents can share knowledge across the swarm, improving collective performance.
3. **Persistent Memory**\
   Knowledge graphs serve as a long-term memory for agents.

***

#### **Best Practices**

1. **Use Attributes Effectively**\
   Add meaningful attributes to concepts for better querying and reasoning.
2. **Structure Relationships Clearly**\
   Define relationships that reflect real-world connections (e.g., "belongs\_to", "depends\_on").
3. **Regular Updates**\
   Periodically update the graph to reflect the latest knowledge and task history.

***