Vercel AI SDK | Opik Documentation

Setup

The AI SDK supports tracing via OpenTelemetry. With the OpikExporter you can collect these traces in Opik. While telemetry is experimental (docs), you can enable it by setting experimental_telemetry on each request that you want to trace.

1 const result = await generateText({
2   model: openai("gpt-4o"),
3   prompt: "Tell a joke",
4   experimental_telemetry: { isEnabled: true },
5 });

To collect the traces in Opik, you need to add the OpikExporter to your application, first you have to set your environment variables

filename=".env"

$ OPIK_API_KEY="<opik-api-key>"
> OPIK_URL_OVERRIDE=https://www.comet.com/opik/api # in case you are using the Cloud version
> OPIK_PROJECT_NAME="<custom-project-name>"
> OPIK_WORKSPACE="<your-workspace>"
> OPENAI_API_KEY="<openai-api-key>" # in case you are using an OpenAI model

1 import { OpikExporter } from "opik/vercel";
2 
3 new OpikExporter();

Now you need to register this exporter via the OpenTelemetry SDK.

Next.js

Next.js has support for OpenTelemetry instrumentation on the framework level. Learn more about it in the Next.js OpenTelemetry guide.

Install dependencies:

$ npm install opik @vercel/otel @opentelemetry/api-logs @opentelemetry/instrumentation @opentelemetry/sdk-logs

Add OpikExporter to your instrumentation file:

filename="instrumentation.ts"

1 import { registerOTel } from "@vercel/otel";
2 import { OpikExporter } from "opik/vercel";
3 
4 export function register() {
5   registerOTel({
6     serviceName: "opik-vercel-ai-nextjs-example",
7     traceExporter: new OpikExporter(),
8   });
9 }

Node.js

Install dependencies:

$ npm install opik ai @ai-sdk/openai @opentelemetry/sdk-node @opentelemetry/auto-instrumentations-node

1 import { openai } from "@ai-sdk/openai";
2 import { generateText } from "ai";
3 import { NodeSDK } from "@opentelemetry/sdk-node";
4 import { getNodeAutoInstrumentations } from "@opentelemetry/auto-instrumentations-node";
5 import { OpikExporter } from "opik/vercel";
6 
7 const sdk = new NodeSDK({
8   traceExporter: new OpikExporter(),
9   instrumentations: [getNodeAutoInstrumentations()],
10 });
11 
12 sdk.start();
13 
14 async function main() {
15   const result = await generateText({
16     model: openai("gpt-4o"),
17     maxTokens: 50,
18     prompt: "What is love?",
19     experimental_telemetry: OpikExporter.getSettings({
20       name: "opik-nodejs-example",
21     }),
22   });
23 
24   console.log(result.text);
25 
26   await sdk.shutdown(); // Flushes the trace to Opik
27 }
28 
29 main().catch(console.error);

Done! All traces that contain AI SDK spans are automatically captured in Opik.

Configuration

Custom Tags and Metadata

You can add custom tags and metadata to all traces generated by the OpikExporter:

1 const exporter = new OpikExporter({
2   // Optional: add custom tags to all traces
3   tags: ["production", "gpt-4o"],
4   // Optional: add custom metadata to all traces
5   metadata: {
6     environment: "production",
7     version: "1.0.0",
8     team: "ai-team",
9   },
10 });

Tags are useful for filtering and grouping traces, while metadata adds additional context that can be valuable for debugging and analysis.

Pass Custom Trace name

1 const result = await generateText({
2   model: openai("gpt-4o"),
3   prompt: "Tell a joke",
4   experimental_telemetry: OpikExporter.getSettings({
5     name: "custom-trace-name",
6   }),
7 });

Debugging

Use the logger level to see the more verbose logs of the exporter.

filename=".env"

$ OPIK_LOG_LEVEL=DEBUG