AI Workflows

id: daily-sales-forecast
namespace: trendteller.insights

tasks:
  - id: fetch-data
    type: io.kestra.plugin.scripts.node.Script
    script: |
      const data = await fetchSalesData()
      return { data }

  - id: generate-forecast
    type: io.kestra.plugin.scripts.node.Script
    script: |
      const forecast = await openai.forecast(data)
      return { forecast }

  - id: save-results
    type: io.kestra.plugin.gcp.bigquery.Query
    sql: INSERT INTO forecasts ...

kestra-scripts/
├── insights/
│   ├── sales-forecast.js      # Sales predictions
│   ├── trend-analysis.js      # Trend detection
│   └── anomaly-detection.js   # Outlier identification
├── crawlers/
│   ├── price-monitor.js       # Competitive pricing
│   ├── availability-check.js  # Stock monitoring
│   └── review-scraper.js      # Customer reviews
├── reports/
│   ├── daily-summary.js       # Daily reports
│   ├── weekly-analysis.js     # Weekly deep dive
│   └── executive-dashboard.js # Executive KPIs
└── shared/
    ├── bigquery-client.js     # BigQuery utilities
    ├── ai-helpers.js          # AI model wrappers
    └── email-sender.js        # Report distribution

import { GoogleGenerativeAI } from '@google/generative-ai'

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY)
const model = genAI.getGenerativeModel({ model: "gemini-pro" })

// Generate multi-modal insights
const result = await model.generateContent([
  "Analyze this sales trend chart and provide insights",
  { inlineData: { data: chartImageBase64, mimeType: "image/png" } }
])

import { BigQuery } from '@google-cloud/bigquery'

const bigquery = new BigQuery({
  projectId: 'togo-425319',
  keyFilename: process.env.GOOGLE_APPLICATION_CREDENTIALS
})

// Query sales data
const query = `
  SELECT date, brand_id, total_revenue
  FROM \`togo-425319.gold.daily_sales\`
  WHERE date >= DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)
  ORDER BY date
`

const [rows] = await bigquery.query(query)

import { Client } from 'pg'

const client = new Client({
  host: process.env.PG_HOST,
  database: 'trendteller',
  user: process.env.PG_USER,
  password: process.env.PG_PASSWORD
})

await client.connect()
const result = await client.query('SELECT * FROM users WHERE active = true')

import puppeteer from 'puppeteer'

const browser = await puppeteer.launch({ headless: true })
const page = await browser.newPage()

// Navigate to competitor site
await page.goto('https://competitor.com/product/12345')

// Extract price
const price = await page.$eval('.product-price', el => el.textContent)

// Take screenshot for verification
await page.screenshot({ path: `screenshots/${productId}.png` })

await browser.close()

// Use stealth plugin to avoid detection
import puppeteer from 'puppeteer-extra'
import StealthPlugin from 'puppeteer-extra-plugin-stealth'

puppeteer.use(StealthPlugin())

// Random delays to mimic human behavior
await page.waitForTimeout(Math.random() * 2000 + 1000)

// Rotate user agents
const userAgents = [/* ... */]
await page.setUserAgent(userAgents[Math.floor(Math.random() * userAgents.length)])