npm install @hypelab/hype-dash

cd python
pip install -r requirements.txt

import { LarkDashboardClient, ChartBlockBuilder, AggregationType } from '@hypelab/hype-dash';

const client = new LarkDashboardClient({
  apiKey: process.env.LARK_API_KEY!,
  region: 'sg', // 'sg' | 'cn' | 'us'
  logging: true,
});

// Create a dashboard
const dashboardId = await client.createDashboard({
  name: 'Sales Dashboard',
  appToken: 'YOUR_APP_TOKEN',
});

// Add a bar chart
const chartBlock = ChartBlockBuilder.bar()
  .dataSource('YOUR_APP_TOKEN', 'YOUR_TABLE_ID')
  .xAxis({ fieldName: 'Category' })
  .yAxis([{ fieldName: 'Revenue', aggregation: AggregationType.SUM }])
  .title('Revenue by Category')
  .colors(['#3b82f6', '#10b981', '#f59e0b'])
  .build();

await client.addBlock('YOUR_APP_TOKEN', dashboardId, chartBlock);

import { ChartBlockBuilder, ChartType, AggregationType } from '@hypelab/hype-dash';

// Bar Chart
const barChart = ChartBlockBuilder.bar()
  .dataSource(appToken, tableId)
  .xAxis({ fieldName: 'Month' })
  .yAxis([
    { fieldName: 'Sales', aggregation: AggregationType.SUM, label: 'Total Sales' },
    { fieldName: 'Orders', aggregation: AggregationType.COUNT, label: 'Order Count' }
  ])
  .title('Monthly Sales Performance')
  .showLegend(true)
  .build();

// Line Chart
const lineChart = ChartBlockBuilder.line()
  .dataSource(appToken, tableId)
  .xAxis({ fieldName: 'Date' })
  .yAxis([{ fieldName: 'Revenue', aggregation: AggregationType.SUM }])
  .build();

// Pie Chart
const pieChart = ChartBlockBuilder.pie()
  .dataSource(appToken, tableId)
  .series({ fieldName: 'Category' })
  .yAxis([{ fieldName: 'Amount', aggregation: AggregationType.SUM }])
  .build();

import { MetricsBlockBuilder, AggregationType } from '@hypelab/hype-dash';

const metrics = new MetricsBlockBuilder()
  .dataSource(appToken, tableId)
  .fieldName('Revenue')
  .aggregation(AggregationType.SUM)
  .title('Total Revenue')
  .prefix('$')
  .decimals(2)
  .trendComparison(30, 'days')
  .build();

import { ViewBlockBuilder, ViewType } from '@hypelab/hype-dash';

const tableView = ViewBlockBuilder.table()
  .dataSource(appToken, tableId, viewId)
  .title('Customer List')
  .showToolbar(true)
  .height(400)
  .build();

const kanbanView = ViewBlockBuilder.kanban()
  .dataSource(appToken, tableId, viewId)
  .build();

import { TextBlockBuilder } from '@hypelab/hype-dash';

const heading = new TextBlockBuilder()
  .heading('Dashboard Overview')
  .alignment('center')
  .build();

const paragraph = new TextBlockBuilder()
  .paragraph('Welcome to the sales dashboard.')
  .build();

{
  "mcpServers": {
    "hype-dash": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@hypelab/hype-dash"],
      "env": {
        "LARK_API_KEY": "your-api-key-here",
        "LARK_REGION": "sg"
      }
    }
  }
}

Create a sales dashboard with:
- Bar chart showing revenue by month
- KPI card for total revenue
- Table view of recent orders

from lark_client import LarkBaseClient, LarkConfig
from data_manager import DataManager

# Initialize client
config = LarkConfig(
    app_id=os.getenv('LARK_APP_ID'),
    app_secret=os.getenv('LARK_APP_SECRET')
)
client = LarkBaseClient(config)
data_manager = DataManager(client)

# Sync TikTok campaign data
tiktok_data = fetch_tiktok_campaigns()  # Your data source
result = data_manager.batch_upsert_records(
    app_token='YOUR_APP_TOKEN',
    table_id='YOUR_TABLE_ID',
    records=tiktok_data,
    key_field='campaign_id'
)

print(f"Synced {result['total']} campaigns")
# Your dashboards now show updated data automatically!

# 1. Python: Sync data
data_manager.batch_upsert_records(...)

// 2. TypeScript: Create dashboard
const chart = ChartBlockBuilder.bar()
  .dataSource(appToken, tableId)
  .build();

const client = new LarkDashboardClient({
  apiKey: string;          // Required: Lark API key
  region?: 'sg' | 'cn' | 'us';  // Default: 'sg'
  apiUrl?: string;         // Optional: Custom API URL
  logging?: boolean;       // Default: false
  timeout?: number;        // Default: 30000ms
  maxRetries?: number;     // Default: 3
  retryDelay?: number;     // Default: 1000ms
});

LARK_API_KEY=your-api-key
LARK_REGION=sg
LARK_LOGGING=true

const blocks = [
  ChartBlockBuilder.bar().dataSource(appToken, tableId).build(),
  MetricsBlockBuilder.sum('Revenue').dataSource(appToken, tableId).build(),
  ViewBlockBuilder.table().dataSource(appToken, tableId, viewId).build(),
];

const results = await client.batchCreateBlocks(appToken, blocks);

import { FilterOperator, FilterConjunction } from '@hypelab/hype-dash';

const chart = ChartBlockBuilder.bar()
  .dataSource(appToken, tableId)
  .filters(FilterConjunction.AND, [
    { fieldName: 'Status', operator: FilterOperator.IS, value: 'Active' },
    { fieldName: 'Revenue', operator: FilterOperator.GT, value: 1000 }
  ])
  .build();

import { ValidationError } from '@hypelab/hype-dash';

try {
  await client.addBlock(appToken, dashboardId, block);
} catch (error) {
  if (error instanceof ValidationError) {
    console.error('Validation failed:', error.message);
  } else {
    console.error('API error:', error);
  }
}

import type {
  DashboardBlock,
  ChartConfig,
  MetricsConfig,
  ViewConfig,
  ChartType,
  ViewType,
  AggregationType,
} from '@hypelab/hype-dash';