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Ace Knowledge Graph

Open in ChatGPT →

Overview

Tools Available3
DeveloperSider AI
CategoryEducation

Turn Docs & Topics to Graphs

Available Tools

Ace Knowledge Graph provides 3 tools that can be used to interact with its services.

App Fetch

fetch
Full Description

Internal APP fetch tool for accessing internal APIs

Parameters

Required
idstring

Unique identifier for the authentication token, Generally starts with sk-

Optional
headersobject

Additional request headers

methodstring

HTTP method (defaults to configured method for endpoint)

Options:GETPOSTPUTDELETE
payload

Request payload (for POST/PUT requests)

queryParamsobject

Query parameters for the request

Knowledge Graph

knowledge-graph
Full Description

Generate a non-hierarchical, network-based knowledge graph visualization.

You (ChatGPT) should create a FLAT, interconnected knowledge graph where nodes represent entities, concepts, or objects, and edges represent semantic relationships between them.

IMPORTANT

  • Network Topology (NO Hierarchy):

This is NOT a tree structure. Create a densely connected network where:

✓ All nodes are peers with equal hierarchical weight ✓ Any node can connect to any other node through multiple relationship types ✓ Support many-to-many connections and cyclic relationships ✓ Avoid parent-child hierarchies or tree-like structures ✓ Create clusters based on relationship patterns, not hierarchy

Node Design:

  • Each node should include:

• id: Unique identifier (kebab-case, e.g., "react", "typescript") • label: Display name • type: concept/issue/solution/metric/technology/skill/project • description: 1-2 sentences explaining the entity • metadata: Optional properties (e.g., {popularity: "high", difficulty: "medium"})

Edge Design

  • Semantic Relationships:
    • Use SPECIFIC semantic relationships, not generic "connected to"
  • Examples of good relationship labels:

• "depends on", "implements", "extends", "uses" • "influences", "causes", "leads to", "results in" • "belongs to", "part of", "contains" • "similar to", "related to", "contrasts with" • "requires", "enables", "supports"

Connection Patterns: 1. Hub Nodes: Some nodes naturally have many connections (e.g., "React" in a frontend tech graph) 2. Cross-domain Links: Connect different entity types (e.g., technology → concept → skill) 3. Bidirectional Relations: Same nodes can have multiple edges with different meanings 4. Transitive Relations: Show both direct and indirect relationships 5. Cyclic Relations: Allow circular dependencies where they exist

Example

  • React Ecosystem (Network Structure):

Nodes (all peers):

  • react, typescript, nextjs, hooks, state-management, redux, testing, jest, tailwind

Edges (many-to-many connections):

  • react → typescript ("commonly used with")
  • react → nextjs ("framework built on")
  • react → hooks ("provides")
  • hooks → state-management ("enables")
  • state-management → redux ("can use")
  • react → testing ("requires")
  • testing → jest ("uses")
  • react → tailwind ("styled with")
  • typescript → testing ("improves")
  • nextjs → typescript ("built-in support")

Note: No center node, no layers, dense interconnections forming natural clusters.

Parameters

Required
dataobject
Optional
languagestring

Language code (ISO 639-1, e.g., 'en', 'zh-CN', 'ja'). Default: en

Default: en

Knowledge Graph List

knowledge-graph-list
Full Description

When to use:

  • User asks: "Show me my saved knowledge graph list"
  • User asks: "Display my knowledge graph"
  • User asks: "Load the knowledge graph I saved"
  • User asks: "Show my knowledge graph history"

you can call the tool

Parameters

Optional
languagestring

Language code (ISO 639-1, e.g., 'en', 'zh-CN', 'ja'). Default: en

Default: en