Tools

Brightsy AI provides various tool categories that enable intelligent interactions with the platform and external systems.

Command Line Interface (CLI)

The Brightsy CLI provides a powerful way to interact with Brightsy AI directly from your terminal.

For detailed information, see the CLI documentation.

Data Management Tools

Features & Capabilities

• CRUD Operations: Create, read, update, and delete records
• Querying: Filter, sort, and paginate record collections
• Aggregation: Perform calculations on record fields
• Schema Validation: Ensure data integrity based on defined schemas

How to Use

• Creating Records:

  create_record(type_id="record_type_id", data={...})
  

• Querying Records:

  get_records(
    account_id="account_id",
    type_id="record_type_id",
    data_filter=[{"field": "name", "operator": "=", "value": "John"}],
    limit=10,
    page=1
  )
  

• Updating Records:

  update_record(id="record_id", data={...})
  

Best Practices

• Batch Operations: Use pagination for large datasets
• Efficient Queries: Apply specific filters to minimize data transfer
• Validation: Verify data against schema before attempting to create/update
• Error Handling: Handle potential validation errors gracefully

File Tools

Features & Capabilities

• File System Navigation: Browse and search the file structure
• Content Management: Upload, download, and manipulate files
• Organization: Create and manage folder hierarchies
• Access Control: Manage permissions for files and folders

How to Use

• See the File Management section for details on usage.

Best Practices

• Path Handling: Always use correct path formats beginning with "files/"
• Error Checking: Verify file existence before attempting operations
• Content Types: Specify appropriate content types when uploading files
• Clean Up: Remove temporary files when no longer needed

UI Tools

Features & Capabilities

• Forms: Collect structured data from users
• Buttons: Present actionable choices
• Charts: Visualize data in various formats
• Content Display: Present formatted content

How to Use

• User Information Requests:

  user_info_request({
    "props": {
      "prompt": "Please enter your contact information",
      "schema": {
        "type": "object",
        "properties": {
          "name": {"type": "string", "title": "Full Name"},
          "email": {"type": "string", "title": "Email", "format": "email"}
        },
        "required": ["name", "email"]
      }
    }
  })
  

• Button Choices:

  show_buttons({
    "props": {
      "title": "What would you like to do?",
      "buttons": [
        {"text": "Create New Record", "value": "create"},
        {"text": "Search Records", "value": "search"}
      ]
    }
  })
  

• Data Visualization:

  present_chart({
    "props": {
      "type": "bar",
      "title": "Sales by Region",
      "data": [
        {"name": "North", "value": 200},
        {"name": "South", "value": 300},
        {"name": "East", "value": 150},
        {"name": "West", "value": 250}
      ]
    }
  })
  

Best Practices

• Clear Instructions: Provide users with clear prompts and guidance
• Validation: Use appropriate schema validation for form inputs
• Progressive Disclosure: Present complex forms in logical stages
• Responsive Design: Ensure UI components work well on various devices
• Accessibility: Use descriptive labels and provide adequate context

Integration Tools

Features & Capabilities

• API Connections: Interface with external services
• Authentication: Manage OAuth, API keys, and tokens
• Data Exchange: Send and receive data from external systems
• Webhook Processing: Handle incoming webhook data

How to Use

• API Requests:

  fetch_request(
    url="https://api.example.com/data",
    method="GET",
    headers={"Authorization": "Bearer token"}
  )
  

• Authentication Flows:

  handleAppLogin(app_id="app_id")
  

Best Practices

• Error Handling: Gracefully handle API failures and rate limits
• Authentication Management: Store tokens securely
• Data Transformation: Process API responses before storing or displaying
• Rate Limiting: Implement thoughtful retry strategies
• Logging: Monitor API interactions for troubleshooting

Memory Tools

Features & Capabilities

• Contextual Storage: Save important information for later reference
• Memory Types: User, agent, and workspace memories
• Context Retrieval: Find relevant information based on topics
• Memory Management: Create, update, and forget memories

How to Use

• Creating Memories:

  create_user_memory(name="preference", value="dark mode")
  

• Retrieving Memories:

  remember(topic="user preferences")
  

• Forgetting Memories:

  forget(id="memory_id")
  

Best Practices

• Structured Storage: Use consistent naming conventions
• Meaningful Context: Store complete, useful information
• Privacy Considerations: Only store necessary information
• Memory Types: Use appropriate memory types for different contexts
• Regular Cleanup: Remove outdated or unnecessary memories

Web Tools

Features & Capabilities

• HTTP Requests: Make requests to external web resources
• Response Processing: Handle and parse various response formats
• Error Handling: Manage timeouts, failures, and unexpected responses

How to Use

• Web Requests:

  fetch_request(
    url="https://example.com/api/data",
    method="POST",
    body=JSON.stringify({"query": "information"}),
    headers={"Content-Type": "application/json"}
  )
  

Best Practices

• URL Validation: Ensure URLs are properly formatted
• Response Parsing: Handle different content types appropriately
• Error Handling: Implement robust error handling for various response codes
• Timeout Management: Set appropriate timeouts for requests
• Rate Limiting: Respect API rate limits and implement backoff strategies
• Content Processing: Strip HTML when only text content is needed