┌────────────────┐
            your code ────────► │ wrapped client │ ───► provider (Bedrock / Mistral / …)
                                └───────┬────────┘
                                        │ (extract usage)
                                        ▼
                                ┌────────────────┐
                                │  Lago events   │ ───► api.getlago.com
                                └────────────────┘

What it does

• Wraps your existing LLM client in place — no API surface change for your application code.
• Extracts usage from each response into a normalized shape (CanonicalUsage).
• Buffers events in memory, flushes them in batches to Lago's /events/batch endpoint.
• Survives provider/Lago outages with exponential backoff and a bounded buffer.
• p99 wrap-overhead under 5 ms — your call is never blocked on Lago.

Install

npm install lago-agent-sdk
# plus the provider SDK(s) you use:
npm install @aws-sdk/client-bedrock-runtime
npm install @anthropic-ai/sdk
npm install @mistralai/mistralai
npm install openai
npm install @google/genai

Quickstart — Bedrock

import { BedrockRuntimeClient, ConverseCommand } from "@aws-sdk/client-bedrock-runtime";
import { LagoSDK } from "lago-agent-sdk";

const sdk = new LagoSDK({
  apiKey: process.env.LAGO_API_KEY!,
  defaultSubscriptionId: "sub_acme",
});
const client = sdk.wrap(new BedrockRuntimeClient({ region: "eu-west-1" }));

await client.send(
  new ConverseCommand({
    modelId: "eu.amazon.nova-lite-v1:0",
    messages: [{ role: "user", content: [{ text: "Hello" }] }],
  }),
);
await sdk.flush();

The wrapped client behaves identically to the original — same arguments, same return shape, same exceptions. The SDK adds an in-memory queue that batches events to Lago in the background.

Quickstart — Anthropic

import Anthropic from "@anthropic-ai/sdk";
import { LagoSDK } from "lago-agent-sdk";

const sdk = new LagoSDK({ apiKey: process.env.LAGO_API_KEY!, defaultSubscriptionId: "sub_acme" });
const client = sdk.wrap(new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY! }));

await client.messages.create({
  model: "claude-sonnet-4-6",
  max_tokens: 200,
  messages: [{ role: "user", content: "Hello" }],
});
await sdk.flush();

Quickstart — Mistral

import { Mistral } from "@mistralai/mistralai";
import { LagoSDK } from "lago-agent-sdk";

const sdk = new LagoSDK({ apiKey: process.env.LAGO_API_KEY!, defaultSubscriptionId: "sub_acme" });
const client = sdk.wrap(new Mistral({ apiKey: process.env.MISTRAL_API_KEY! }));

await client.chat.complete({
  model: "mistral-small-latest",
  messages: [{ role: "user", content: "Hello" }],
});
await sdk.flush();

Quickstart — OpenAI

import OpenAI from "openai";
import { LagoSDK } from "lago-agent-sdk";

const sdk = new LagoSDK({ apiKey: process.env.LAGO_API_KEY!, defaultSubscriptionId: "sub_acme" });
const client = sdk.wrap(new OpenAI({ apiKey: process.env.OPENAI_API_KEY! }));

await client.chat.completions.create({
  model: "gpt-4o-mini",
  messages: [{ role: "user", content: "Hello" }],
  max_completion_tokens: 200,
});
await sdk.flush();

Quickstart — Gemini

import { GoogleGenAI } from "@google/genai";
import { LagoSDK } from "lago-agent-sdk";

const sdk = new LagoSDK({ apiKey: process.env.LAGO_API_KEY!, defaultSubscriptionId: "sub_acme" });
const client = sdk.wrap(new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY! }));

await client.models.generateContent({
  model: "gemini-2.5-flash",
  contents: "Hello",
});
await sdk.flush();

Every provider is covered sync + streaming (async where the provider SDK offers it). The full coverage matrix, the token fields each provider populates, and the per-provider quirks that affect billing (cache/reasoning overlap semantics, OpenAI's stream_options auto-inject, Gemini's additive thoughtsTokenCount) live in docs/providers.md.

Gateways

wrap() also detects a client pointed at a gateway and bills what the gateway actually did — each guide covers backfill, attribution and the measured billing caveats for that gateway.

Cloudflare AI Gateway

Point any supported client at your gateway URL; cache hits (cf-aig-cache-status: HIT) are not billed, and Workers AI models get priced automatically from Cloudflare's published rates.

const client = sdk.wrap(
  new Anthropic({
    apiKey: "...",
    baseURL: `https://gateway.ai.cloudflare.com/v1/${accountId}/${gatewayId}/anthropic`,
    defaultHeaders: { "cf-aig-authorization": `Bearer ${gatewayAuth}` },
  }),
);

Full guide, including backfill from the gateway's Logs API: docs/cloudflare.md.

Databricks AI Gateway

BYOK calls bill dollar cost at the vendor's rates; Databricks-hosted models (system.ai.*) bill token counts, and sdk.backfillDatabricks(source, "7 days") fills in what wrap() didn't see.

const client = sdk.wrap(
  new OpenAI({
    apiKey: process.env.DATABRICKS_TOKEN,
    baseURL: `${process.env.DATABRICKS_HOST}/ai-gateway/mlflow/v1`,
    defaultHeaders: {
      "Databricks-Ai-Gateway-Request-Tags": JSON.stringify({ lago_subscription: "sub_acme" }),
    },
  }),
);

Full guide, including BYOK setup, backfill and gotchas: docs/databricks.md.

Snowflake Cortex

The Cortex REST surface wraps like any OpenAI-compatible client; the AI SQL functions (AI_COMPLETE, …) have no client to wrap and are backfilled from Snowflake's usage views. Everything bills as token counts.

const client = sdk.wrap(
  new OpenAI({
    baseURL: `https://${process.env.SNOWFLAKE_ACCOUNT}.snowflakecomputing.com/api/v2/cortex/v1`,
    apiKey: process.env.SNOWFLAKE_PAT,
  }),
);

await sdk.backfillSnowflake(SnowflakeSource.fromEnv(), "7 days", { defaultSubscription: "sub_default" });

Full guide, including cache semantics, dedup, attribution via QUERY_TAG and account setup: docs/snowflake.md.

Ramp Router

A gateway in front of OpenAI, Anthropic, Google Vertex, Fireworks and xAI, with an OpenAI-shaped surface and an Anthropic-shaped one. Point either client at it. The model that answered is the one billed — Router can serve a different model than the one requested.

const client = sdk.wrap(
  new OpenAI({ apiKey: process.env.RAMP_ROUTER_API_KEY!, baseURL: "https://api.router.com/v1" }),
  { subscription: "sub_acme" },
);
await client.responses.create({ model: process.env.RAMP_ROUTER_MODEL!, input: "Summarize this invoice." });

Full guide, including how price mode bills Router's own catalog rate: docs/ramp-router.md.

Multi-tenant — pick a subscription per call

Three ways to set the external_subscription_id, in priority order:

// 1. Per-call override — attach __lago to a Bedrock command, or pass `lago: {...}` on a Mistral call.
const cmd = new ConverseCommand({...});
(cmd as any).__lago = { subscription: "sub_acme", dimensions: { feature: "summarize" } };
await client.send(cmd);

// 2. Context-bound — uses AsyncLocalStorage; safe across `await` boundaries.
sdk.withSubscription("sub_acme", async () => {
  await client.send(...);  // bills sub_acme
});
// The subscription is captured when the CALL is made, so the result can leave the
// scope — a stream returned from a helper and iterated by the caller still bills
// sub_acme.
const stream = await sdk.withSubscription("sub_acme", () => client.chat.completions.create({ ..., stream: true }));
for await (const chunk of stream) { /* still bills sub_acme */ }
// or at the top of a request handler:
sdk.setSubscription("sub_acme");

// 3. Default at init (fallback)
new LagoSDK({ apiKey: "...", defaultSubscriptionId: "sub_default" });

Backed by Node's AsyncLocalStorage for safe propagation across promises.

Pricing mode — send dollar cost instead of tokens

By default the SDK emits token counts (pricingMode: "tokens"). Set pricingMode: "price" to instead emit the dollar cost of each call: Σ(unit_price_per_token × tokens) × markup.

const sdk = new LagoSDK({
  apiKey: "...",
  defaultSubscriptionId: "sub_123",
  config: {
    pricingMode: "price", // "tokens" (default) | "price"
    markup: 1.2, // optional cost multiplier (1.2 = +20%)
  },
});

Price mode emits one llm_cost event per priced field (input, output, cache, ...), each carrying precise_total_amount_cents for Lago's dynamic charge model plus a token_type property so a single billable metric can be grouped by both model and token_type. Prices come from public sources (OpenRouter for native providers, the AWS Bedrock price list for Bedrock) and from a gateway's own catalog where it publishes one (Cloudflare Workers AI, Ramp Router), fetched and cached in the background — your LLM call is never blocked on pricing. If a price isn't available yet, the SDK falls back to token-count events and reports via onError rather than under-billing. Per-call override: lago: { mode: "price", markup: 1.5 } (Bedrock: the command's __lago).

Error policy

The SDK never breaks your LLM call. If anything in instrumentation fails (adapter bug, Lago down, network error), your call returns normally — and the failure is reported through onError and logged, so it never passes in silence. Wire your own observability there:

new LagoSDK({
  apiKey: "...",
  config: {
    onError: (err, where) => Sentry.captureException(err, { tags: { sdk_phase: where } }),
  },
});

where names the stage, so you can tell the failures apart:

| where | What happened | | -------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- | | adapter.<provider> | The provider's response could not be parsed — its usage shape changed. Nothing was billed for that call. | | wrapper.<provider> | Interception itself failed, so the call went uninstrumented. | | emit / pricing / timestamp | The usage was read, but the event could not be built or priced. | | send_batch / overflow / shutdown_drain | Delivery: a batch failed, the buffer is full, or events were still owed at exit. | | queue_loop | The background delivery loop died. Events stop being delivered; the buffer will start reporting overflow on top. |

A drifted provider is the one to alert on: it bills nothing for that provider until it is fixed, and it looks like silence rather than an error anywhere else.

Setting up Lago

The SDK ships with default metric codes (llm_input_tokens, llm_output_tokens, etc.). You need to register matching billable metrics in your Lago tenant before events count toward charges. See Lago docs — Billable Metrics.

Development

git clone https://github.com/getlago/lago-agent-sdk-js
cd lago-agent-sdk-js
npm install
npm test
npm run build

Security

Found a vulnerability? See SECURITY.md.