Vercel AI SDK Tracing

Automatically trace Vercel AI SDK agent executions, tool calls, and multi-step workflows.

Vercel AI SDK integration captures traces from your Vercel AI SDK applications, including agent execution flow, tool invocations, and multi-step reasoning processes. This integration is designed for TypeScript applications.

AI SDK 7

Quickstart

AI SDK 7 registers telemetry once at startup with @ai-sdk/otel. After that, AI SDK calls emit OpenTelemetry spans through the registered integration.

npm install ai@^7 @ai-sdk/openai@^4 @ai-sdk/otel judgeval zod

yarn add ai@^7 @ai-sdk/openai@^4 @ai-sdk/otel judgeval zod

pnpm add ai@^7 @ai-sdk/openai@^4 @ai-sdk/otel judgeval zod

bun add ai@^7 @ai-sdk/openai@^4 @ai-sdk/otel judgeval zod

import { OpenTelemetry } from "@ai-sdk/otel";
import { registerTelemetry } from "ai";
import { Tracer } from "judgeval";

await Tracer.init({
  projectName: "AI SDK Weather Agent",
});

registerTelemetry(
  new OpenTelemetry({
    tracer: Tracer.getOTELTracer(),
  }),
);

import "./instrumentation"; 
import { openai } from "@ai-sdk/openai";
import { generateText, tool } from "ai";
import * as z from "zod/v4";
import { Tracer } from "judgeval"; 

async function main() {
  const result = await generateText({
    model: openai("gpt-5.2"),
    tools: {
      weather: tool({
        description: "Get the weather in a location",
        inputSchema: z.object({
          location: z.string().describe("The location to get the weather for"),
        }),
        execute: async ({ location }) => ({
          location,
          temperature: 72 + Math.floor(Math.random() * 21) - 10,
        }),
      }),
    },
    prompt: "What is the weather in San Francisco?",
  });

  return result;
}

await main().catch(console.error);
await Tracer.shutdown(); 

Example: Math Agent with Multi-Step Reasoning

Install mathjs for this example:

npm install mathjs

yarn add mathjs

pnpm add mathjs

bun add mathjs

import { OpenTelemetry } from "@ai-sdk/otel";
import { registerTelemetry } from "ai";
import { Tracer } from "judgeval";

await Tracer.init({
  projectName: "AI SDK Math Agent",
});

registerTelemetry(
  new OpenTelemetry({
    tracer: Tracer.getOTELTracer(),
  }),
);

import "./instrumentation";
import { openai } from "@ai-sdk/openai";
import { generateText, stepCountIs, tool } from "ai";
import * as mathjs from "mathjs";
import * as z from "zod/v4";
import { Tracer } from "judgeval";

async function main() {
  return await generateText({
    model: openai("gpt-5.2"),
    tools: {
      calculate: tool({
        description:
          "A tool for evaluating mathematical expressions. Example expressions: " +
          "'1.2 * (2 + 4.5)', '12.7 cm to inch', 'sin(45 deg) ^ 2'.",
        inputSchema: z.object({ expression: z.string() }),
        execute: async ({ expression }) => mathjs.evaluate(expression),
      }),
    },
    stopWhen: stepCountIs(10),
    system:
      "You are solving math problems. " +
      "Reason step by step. " +
      "Use the calculator when necessary. " +
      "The calculator can only do simple additions, subtractions, multiplications, and divisions. " +
      "When you give the final answer, provide an explanation for how you got it.",
    prompt:
      "A taxi driver earns $9461 per 1-hour work. " +
      "If he works 12 hours a day and in 1 hour he uses 14-liters petrol with price $134 for 1-liter. " +
      "How much money does he earn in one day?",
  });
}

await Tracer.observe(main)().catch(console.error);
await Tracer.shutdown();

AI SDK 6 and older

Quickstart

AI SDK 6 and older enables telemetry on each AI SDK call with experimental_telemetry.

npm install ai @ai-sdk/openai judgeval zod

yarn add ai @ai-sdk/openai judgeval zod

pnpm add ai @ai-sdk/openai judgeval zod

bun add ai @ai-sdk/openai judgeval zod

import { Tracer } from "judgeval";

await Tracer.init({
  projectName: "AI SDK Weather Agent",
});

import "./instrumentation"; 
import { openai } from "@ai-sdk/openai";
import { generateText, tool } from "ai";
import { z } from "zod";
import { Tracer } from "judgeval"; 

async function main() {
  const result = await generateText({
    model: openai("gpt-5.2"),
    tools: {
      weather: tool({
        description: "Get the weather in a location",
        inputSchema: z.object({
          location: z.string().describe("The location to get the weather for"),
        }),
        execute: async ({ location }) => ({
          location,
          temperature: 72 + Math.floor(Math.random() * 21) - 10,
        }),
      }),
    },
    experimental_telemetry: { 
      isEnabled: true, 
      tracer: Tracer.getOTELTracer(), 
    }, 
    prompt: "What is the weather in San Francisco?",
  });

  return result;
}

await main().catch(console.error);
await Tracer.shutdown(); 

Next Steps

• Trace conventions - Understand Judgment’s OpenTelemetry boundaries, context, and span semantics.
• Monitor a behavior - Monitor your Vercel AI SDK agents in production with behavioral scoring.
• Instrument your agent - Configure and verify Judgment tracing beyond this integration.