Cost-guarded chat

npm install @agentskit/runtime @agentskit/adapters

import { createRuntime } from '@agentskit/runtime'
import { openai } from '@agentskit/adapters'
import type { Observer } from '@agentskit/core'

// Pricing as of late 2025 — keep in sync with provider docs
const PRICE_PER_1K = { input: 0.0025, output: 0.01 }   // gpt-4o
const BUDGET_USD = 0.10

function createCostGuard(budgetUsd: number, abort: () => void): Observer {
  let inputTokens = 0
  let outputTokens = 0

  return {
    name: 'cost-guard',
    on(event) {
      if (event.type === 'llm:end') {
        // AgentEvent carries usage totals at the end of each LLM call
        if (event.usage) {
          inputTokens += event.usage.promptTokens
          outputTokens += event.usage.completionTokens
        }

        const costUsd =
          (inputTokens / 1000) * PRICE_PER_1K.input +
          (outputTokens / 1000) * PRICE_PER_1K.output

        if (costUsd > budgetUsd) {
          console.warn(`Cost budget exceeded: $${costUsd.toFixed(4)} > $${budgetUsd}`)
          abort()
        }
      }

      if (event.type === 'agent:step') {
        const total =
          (inputTokens / 1000) * PRICE_PER_1K.input +
          (outputTokens / 1000) * PRICE_PER_1K.output
        console.log(`Step ${event.step} running cost: $${total.toFixed(4)} (${inputTokens}+${outputTokens} tokens)`)
      }
    },
  }
}

const controller = new AbortController()

const runtime = createRuntime({
  adapter: openai({ apiKey: KEY, model: 'gpt-4o' }),
  observers: [createCostGuard(BUDGET_USD, () => controller.abort())],
})

try {
  const result = await runtime.run('Write a 5000-word essay on quantum computing', {
    signal: controller.signal,
  })
  console.log(result.content)
} catch (err) {
  if ((err as Error).name === 'AbortError') {
    console.log('Aborted due to cost budget.')
  } else {
    throw err
  }
}