nocobase-ai-employee

name	nocobase-ai-employee
description	Guide AI to create and manage NocoBase AI employees — chatbot assistants with page integration
triggers	["AI员工","AI助手","ai employee","ai assistant","chatbot","创建AI","头像","浮动按钮"]
tools	["nb_create_ai_employee","nb_list_ai_employees","nb_get_ai_employee","nb_update_ai_employee","nb_delete_ai_employee","nb_ai_shortcut","nb_ai_button"]

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

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)

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

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:

{
  "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:

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:

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:

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