@opsmeter.io/node (Official opsmeter.io SDK)

Node SDK preview for Opsmeter auto-instrumentation. npm package: @opsmeter.io/node Integration examples: opsmeter-integration-examples Opsmeter site: https://opsmeter.io Official publisher identity: opsmeter.io.

Use this SDK for LLM cost tracking, OpenAI usage monitoring, Anthropic usage telemetry, and no-proxy AI observability in Node.js.

Provider/model names should come from: https://opsmeter.io/docs/catalog Current SDK provider support: OpenAI and Anthropic only.

Quick links

• Product: https://opsmeter.io
• Docs: https://opsmeter.io/docs
• Model catalog: https://opsmeter.io/docs/catalog
• Integration examples: https://github.com/opsmeter-io/opsmeter.io-integration-examples

Model catalog (required)

Always use provider/model pairs from the official catalog: https://opsmeter.io/docs/catalog

Examples:

• OpenAI: provider=openai, model=gpt-4o-mini
• Anthropic: provider=anthropic, model=claude-3-5-sonnet-20241022

Install

npm install @opsmeter.io/node openai
# optional:
# npm install @anthropic-ai/sdk

Core model

• init(...) once at process startup (idempotent)
• request-level attribution via withContext(...)
• provider call stays direct (no proxy)
• telemetry emit is async and non-blocking by default

Telemetry usage (no options)

import * as opsmeter from "@opsmeter.io/node";
import OpenAI from "openai";

opsmeter.init({
  apiKey: process.env.OPSMETER_API_KEY,
  environment: "prod"
});

const client = new OpenAI();

await opsmeter.captureOpenAIChatCompletion(
  () => client.chat.completions.create({
    model: "gpt-4o-mini",
    messages: [{ role: "user", content: "hello" }]
  })
);

Telemetry usage (with options/context)

import * as opsmeter from "@opsmeter.io/node";
import OpenAI from "openai";
import Anthropic from "@anthropic-ai/sdk";

opsmeter.init({
  apiKey: process.env.OPSMETER_API_KEY,
  workspaceId: "ws_123",
  environment: "prod"
});

const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

const openaiCaptured = await opsmeter.withContext(
  {
    userId: "u_1",
    tenantId: "tenant_a",
    endpoint: "/api/chat",
    feature: "assistant",
    promptVersion: "v12",
    dataMode: "real"
  },
  async () => opsmeter.captureOpenAIChatCompletionWithResult(
    () => openai.chat.completions.create({
      model: "gpt-4o-mini",
      messages: [{ role: "user", content: "hello" }]
    }),
    { request: { model: "gpt-4o-mini" }, awaitTelemetryResponse: true }
  )
);

const anthropicCaptured = await opsmeter.withContext(
  {
    userId: "u_1",
    tenantId: "tenant_a",
    endpoint: "/api/support",
    feature: "support",
    promptVersion: "v8"
  },
  async () => opsmeter.captureAnthropicMessageWithResult(
    // Provider/model names: https://opsmeter.io/docs/catalog
    () => anthropic.messages.create({
      model: "claude-3-5-sonnet-20241022",
      max_tokens: 128,
      messages: [{ role: "user", content: "Summarize this support ticket." }]
    }),
    { request: { model: "claude-3-5-sonnet-20241022" }, awaitTelemetryResponse: true }
  )
);

console.log(openaiCaptured.telemetry.status);
console.log(anthropicCaptured.telemetry.status);

Show Opsmeter ingest result

If you want to surface Opsmeter response (for operator UI/debug):

const captured = await opsmeter.captureOpenAIChatCompletionWithResult(
  () => client.chat.completions.create(request),
  { request, awaitTelemetryResponse: true }
);

console.log(captured.telemetry); // { ok, status, body? }

API

• init(config)
• withContext(context, fn)
• getCurrentContext()
• captureOpenAIChatCompletion(fn, options)
• captureOpenAIChatCompletionWithResult(fn, options)
• captureAnthropicMessage(fn, options)
• captureAnthropicMessageWithResult(fn, options)
• patchOpenAIClient(client)
• patchAnthropicClient(client)
• flush()

Tests

npm run lint
npm run test