aicreat

Guide AI to create and manage NocoBase AI employees — chatbot assistants with page integration

NocoBase AI Employee Management

You are guiding the user to create and manage AI employees (chatbot assistants) in NocoBase.

Key Concepts

AI Employee

An AI employee is a chatbot assistant configured with:

• username (PK): Unique identifier, e.g. am-asset-keeper
• nickname: Display name shown to users
• about: System prompt defining role, data scope, and behavior
• skills: Tool bindings (query, count, form fill, workflow call)
• modelSettings: LLM configuration (service, model, temperature)

Page Integration

AI employees appear on pages in two ways:

1. Floating Avatar (AIEmployeeShortcutListModel + AIEmployeeShortcutModel): Circular avatar buttons in page top-right corner
2. Action Bar Button (AIEmployeeButtonModel): AI button in table/form action bars

Workflow

Phase 1: Create AI Employees

text

nb_create_ai_employee("my-helper", "助手", "通用助手",
    "nocobase-015-male", "One-line description",
    "Full system prompt with role, data scope, behavior rules...",
    "Welcome message...",
    '[{"name":"dataSource-dataSourceQuery","autoCall":true}]')

Phase 2: Add Page Shortcuts (Floating Avatars)

text

nb_ai_shortcut("tab_uid", '[
    {"username": "my-helper", "tasks": [
        {"title": "Quick Query", "message": {"user": "帮我查询数据"}, "autoSend": false}
    ]}
]')

Phase 3: Add Block Buttons

text

nb_ai_button("table_uid", "my-helper", '[
    {"title": "Analyze Data", "message": {"user": "分析当前数据"}, "autoSend": false}
]')

Available Skills (Tool Bindings)

Tool Name	Description	autoCall
dataModeling-getCollectionNames	Discover table names	true
dataModeling-getCollectionMetadata	Get field definitions	true
dataSource-dataSourceQuery	Query database	true
dataSource-dataSourceCounting	Count records	true
frontend-formFiller	Auto-fill forms	true
workflowCaller-<key>	Custom workflow tool	false

Avatar IDs

Common avatar IDs: nocobase-001-male through nocobase-060-male, nocobase-001-female through nocobase-060-female.

Model Settings

Default LLM configuration:

json

{
  "llmService": "gemini",
  "model": "models/gemini-2.5-flash",
  "temperature": 0.7,
  "topP": 1,
  "timeout": 60000,
  "maxRetries": 1,
  "responseFormat": "text"
}

Common adjustments:

• temperature: 0.3 — more deterministic, better for data queries
• temperature: 0.9 — more creative, better for writing/suggestions
• timeout: 120000 — longer timeout for complex multi-step queries
• responseFormat: "markdown" — for formatted output

Page Integration — Complete Example

Floating Avatar (Shortcut)

Place AI employee avatars on a page for quick access:

text

nb_ai_shortcut("tab_uid", '[
    {"username": "my-helper", "tasks": [
        {"title": "Quick Query", "message": {"user": "帮我查一下最新数据"}, "autoSend": false},
        {"title": "Generate Report", "message": {"user": "生成本月汇总报表"}, "autoSend": false}
    ]}
]')

Multiple employees on the same page:

text

nb_ai_shortcut("tab_uid", '[
    {"username": "data-analyst", "tasks": [...]},
    {"username": "form-helper", "tasks": [...]}
]')

Block Button

Add AI action button to a table's action bar:

text

nb_ai_button("table_uid", "my-helper", '[
    {"title": "Analyze Selected", "message": {"user": "分析当前选中的记录"}, "autoSend": false}
]')

Best Practices

1. Role-focused: Each AI employee covers one business domain
2. Progressive: Start with basic query tools, add workflow tools later
3. Chinese-first: Use {{$nLang}} in system prompts for language awareness
4. Data scope: Explicitly list accessible tables in the system prompt
5. Preset tasks: Add 1-2 quick-start tasks to shortcuts and buttons
6. System prompt structure: Role → Data scope (table names) → Behavior rules → Output format
7. Skill selection: Start with dataSource-dataSourceQuery + dataModeling-getCollectionMetadata for data-oriented employees