Vercel AI SDK Tracing (JS)

OpenInference Vercel

This package provides a set of utilities to ingest Vercel AI SDK(>= 3.3) spans into platforms like Arize AX and Phoenix.

Note: This package requires you to be using the Vercel AI SDK version 3.3 or higher.

Installation

npm i --save @arizeai/openinference-vercel

You will also need to install OpenTelemetry packages into your project.

npm i --save @arizeai/openinference-semantic-conventions @opentelemetry/api @opentelemetry/exporter-trace-otlp-proto @opentelemetry/resources @opentelemetry/sdk-trace-node @opentelemetry/semantic-conventions

Usage

@arizeai/openinference-vercel provides a set of utilities to help you ingest Vercel AI SDK spans into OpenTelemetry compatible platforms and works in conjunction with Vercel’s AI SDK OpenTelemetry support. @arizeai/openinference-vercel works with typical node projects, as well as Next.js projects. This page will describe usage within a node project, for detailed usage instructions in Next.js follow Vercel’s guide on instrumenting Next.js. To process your Vercel AI SDK Spans, setup a typical OpenTelemetry instrumentation boilerplate file, add a OpenInferenceSimpleSpanProcessor or OpenInferenceBatchSpanProcessor to your OpenTelemetry configuration.

Note: The OpenInferenceSpanProcessor alone does not handle the exporting of spans so you will need to pass it an exporter as a parameter.

Here are two example instrumentation configurations:

Manual instrumentation config for a Node v23+ application.
Next.js register function utilizing @vercel/otel .

Manual Instrumentation
@vercel/otel

// instrumentation.ts
// Node environment instrumentation
// Boilerplate imports
import { diag, DiagConsoleLogger, DiagLogLevel } from "@opentelemetry/api";
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-proto";
import { resourceFromAttributes } from "@opentelemetry/resources";
import { NodeTracerProvider } from "@opentelemetry/sdk-trace-node";
import { ATTR_SERVICE_NAME } from "@opentelemetry/semantic-conventions";
// OpenInference Vercel imports
import { SEMRESATTRS_PROJECT_NAME } from "@arizeai/openinference-semantic-conventions";
import { OpenInferenceSimpleSpanProcessor } from "@arizeai/openinference-vercel";

diag.setLogger(new DiagConsoleLogger(), DiagLogLevel.ERROR);

// e.g. http://localhost:6006
// e.g. https://app.phoenix.arize.com/s/<your-space>
const COLLECTOR_ENDPOINT = process.env.PHOENIX_COLLECTOR_ENDPOINT;
// The project name that may appear in your collector's interface
const SERVICE_NAME = "phoenix-vercel-ai-sdk-app";

export const provider = new NodeTracerProvider({
  resource: resourceFromAttributes({
    [ATTR_SERVICE_NAME]: SERVICE_NAME,
    [SEMRESATTRS_PROJECT_NAME]: SERVICE_NAME,
  }),
  spanProcessors: [
    // In production-like environments it is recommended to use
    // OpenInferenceBatchSpanProcessor instead
    new OpenInferenceSimpleSpanProcessor({
      exporter: new OTLPTraceExporter({
        url: `${COLLECTOR_ENDPOINT}/v1/traces`,
        // (optional) if connecting to a collector with Authentication enabled
        headers: { Authorization: `Bearer ${process.env.PHOENIX_API_KEY}` },
      }),
    }),
  ],
});

provider.register();

console.log("Provider registered");

// Run this file before the rest of program execution
// e.g node --import ./instrumentation.ts index.ts
// or at the top of your application's entrypoint
// e.g. import "instrumentation.ts";

// instrumentation.ts
// Vercel / Next.js environment instrumentation
import { registerOTel, OTLPHttpProtoTraceExporter } from "@vercel/otel";
import {
  isOpenInferenceSpan,
  OpenInferenceSimpleSpanProcessor,
} from "@arizeai/openinference-vercel";
import { SEMRESATTRS_PROJECT_NAME } from "@arizeai/openinference-semantic-conventions";
import { diag, DiagConsoleLogger, DiagLogLevel } from "@opentelemetry/api";

diag.setLogger(new DiagConsoleLogger(), DiagLogLevel.ERROR);

// e.g. http://localhost:6006
// e.g. https://app.phoenix.arize.com/s/<your-space>
const COLLECTOR_ENDPOINT = process.env.PHOENIX_COLLECTOR_ENDPOINT;
// The project name that may appear in your collector's interface
const SERVICE_NAME = "phoenix-vercel-ai-sdk-app";

/**
 * Register function used by Next.js to instantiate instrumentation
 * correctly in all environments that Next.js can be deployed to
 */
export function register() {
  registerOTel({
    serviceName: SERVICE_NAME,
    attributes: {
      [SEMRESATTRS_PROJECT_NAME]: SERVICE_NAME,
    },
    spanProcessors: [
      new OpenInferenceSimpleSpanProcessor({
        exporter: new OTLPHttpProtoTraceExporter({
          url: `${COLLECTOR_ENDPOINT}/v1/traces`,
        }),
        spanFilter: isOpenInferenceSpan,
      }),
    ],
  });
  console.log("Provider registered");
}

See Vercel’s instrumentation guide for more details on configuring your instrumentation file and @vercel/otel within a Next.js project

When instrumenting a Next.js application, traced spans will not be “root spans” when the OpenInference span filter is configured. This is because Next.js parents spans underneath http requests, which do not meet the requirements to be an OpenInference span.

Now enable telemetry in your AI SDK calls by setting the experimental_telemetry parameter to true.

import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const result = await generateText({
  model: openai("gpt-4o"),
  prompt: "Write a short story about a cat.",
  experimental_telemetry: { isEnabled: true },
});

Ensure your installed version of @opentelemetry/api matches the version installed by ai otherwise the ai sdk will not emit traces to the TracerProvider that you configure. If you install ai before other the packages, then dependency resolution in your package manager should install the correct version.

For details on Vercel AI SDK telemetry see the Vercel AI SDK Telemetry documentation.

Spans may not be exported if still queued in the processor when your process exits. Use OpenInferenceSimpleSpanProcessor for immediate export, or call provider.shutdown() to explicitly flush spans before exit when using OpenInferenceBatchSpanProcessor.For simpler setup, consider using @arizeai/phoenix-otel which handles this automatically.

Examples

To see an example go to the Next.js OpenAI Telemetry Example in the OpenInference repo. For more information on Vercel OpenTelemetry support see the Vercel AI SDK Telemetry documentation.

Developer Tools

MCP

LLM Providers

TypeScript

Python

Java

Platform

Sandboxes

Evaluation Integrations

Vercel AI SDK Tracing (JS)

OpenInference Vercel

Installation

Usage

Examples

​OpenInference Vercel

​Installation

​Usage

​Examples

OpenInference Vercel

Installation

Usage

Examples