LLM auto-capture

The wrappers patch the supplied client instance’s create method, preserve its return value, and emit one nozle.track() event when provider usage metadata is available. They capture model, input tokens, output tokens, latency, and an optional feature tag. Prompt and completion content are not inspected or sent.

OpenAI

npm install openai

import OpenAI from 'openai'
import { Nozle, wrapOpenAI } from '@nozle-js/node'

const nozle = new Nozle({
  apiKey: process.env.NOZLE_SECRET_KEY!,
  baseUrl: 'https://api.nozle.app',
  eventsUrl: 'https://core.nozle.app',
})

const openai = wrapOpenAI(new OpenAI(), nozle, {
  customerId: 'workspace_123',
  metricCode: 'llm_tokens',
  feature: 'assistant_reply',
})

const response = await openai.chat.completions.create({
  model: 'example-chat-model',
  messages: [{ role: 'user', content: 'Hello' }],
})

OpenAI streaming

The wrapper reads usage from stream chunks. Request usage in the stream so a final usage-bearing chunk is available:

const stream = await openai.chat.completions.create({
  model: 'example-chat-model',
  messages: [{ role: 'user', content: 'Explain vector search' }],
  stream: true,
  stream_options: { include_usage: true },
})

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? '')
}

Tracking is attempted after the stream finishes.

Anthropic

npm install @anthropic-ai/sdk

import Anthropic from '@anthropic-ai/sdk'
import { Nozle, wrapAnthropic } from '@nozle-js/node'

const anthropic = wrapAnthropic(new Anthropic(), nozle, {
  customerId: 'workspace_123',
  metricCode: 'llm_tokens',
  feature: 'assistant_reply',
})

const message = await anthropic.messages.create({
  model: 'example-anthropic-model',
  max_tokens: 1_024,
  messages: [{ role: 'user', content: 'Hello' }],
})

For Anthropic streams, the wrapper reads input usage from message_start and output usage from message_delta events.

`WrapOptions`

Field	Type	Required	Description
`customerId`	`string`	yes	Customer passed to `nozle.track()`.
`metricCode`	`string`	no	Event code; defaults to `llm_tokens`.
`feature`	`string`	no	Included as a `feature` event property.

Event properties

{
  "model": "example-chat-model",
  "input_tokens": 320,
  "output_tokens": 84,
  "latency_ms": 742,
  "feature": "assistant_reply"
}

Cost calculation remains server-side. Configure the Feature and model cost rules to interpret these raw values.

Delivery behavior

The wrapper starts tracking without awaiting it so billing telemetry does not delay the provider response. It also relies on nozle.track() subscription resolution when no explicit subscription can be supplied through WrapOptions. For workflows requiring durable delivery, explicit transaction IDs, or strict error handling, track manually through your queue instead of relying on the wrapper.

const response = await providerCall()

await nozle.track(
  'workspace_123',
  'llm_tokens',
  {
    model: response.model,
    input_tokens: response.inputTokens,
    output_tokens: response.outputTokens,
  },
  {
    subscriptionId: 'workspace_123_subscription',
    transactionId: `llm:${response.id}:usage`,
  },
)

Setup

Billing

Customers

Entitlements

Margin Intelligence

LLM Usage

LLM auto-capture

OpenAI

OpenAI streaming

Anthropic

`WrapOptions`

Event properties

Delivery behavior

​OpenAI

​OpenAI streaming

​Anthropic

​WrapOptions

​Event properties

​Delivery behavior

OpenAI

OpenAI streaming

Anthropic

`WrapOptions`

Event properties

Delivery behavior