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:
- Floating Avatar (
AIEmployeeShortcutListModel+AIEmployeeShortcutModel): Circular avatar buttons in page top-right corner - 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 queriestemperature: 0.9— more creative, better for writing/suggestionstimeout: 120000— longer timeout for complex multi-step queriesresponseFormat: "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
- Role-focused: Each AI employee covers one business domain
- Progressive: Start with basic query tools, add workflow tools later
- Chinese-first: Use
{{$nLang}}in system prompts for language awareness - Data scope: Explicitly list accessible tables in the system prompt
- Preset tasks: Add 1-2 quick-start tasks to shortcuts and buttons
- System prompt structure: Role → Data scope (table names) → Behavior rules → Output format
- Skill selection: Start with
dataSource-dataSourceQuery+dataModeling-getCollectionMetadatafor data-oriented employees