Weave Observability

Weave is a toolkit built by Weights & Biases for tracking, experimenting with, evaluating, deploying, and improving LLM-based applications.

After integrating with the AI SDK, you can use Weave to view and interact with trace information for your AI SDK application including prompts, responses, flow, cost and more.

Setup

To set up Weave as an OpenTelemetry backend, you'll need to route the traces to Weave's OpenTelemetry endpoint, set your API key, and specify a team and project. In order to log your traces to Weave, you must you must have a Weights & Biases account.

Authentication

First, go to wandb.ai/authorize, copy your API key and generate a base64-encoded authorization string by running:

echo -n "api:<YOUR_API_KEY>" | base64

Note the output. You'll use it in your environment configuration.

Project Configuration

Your W&B project ID identifies where your telemetry data will be logged. It follows the format <YOUR_TEAM_NAME>/<YOUR_PROJECT_NAME>.

Navigate to the Weights & Biases dashboard.
In the Teams section, select or create a team.
Select an existing project or create a new one.
Note <YOUR_TEAM_NAME>/<YOUR_PROJECT_NAME> for the next step.

Next.js

In your Next.js app’s .env file, set the OTEL environment variables. Replace <BASE64_AUTH_STRING> and <YOUR_TEAM_NAME>/<YOUR_PROJECT_NAME> with your values from the previous steps:

OTEL_EXPORTER_OTLP_ENDPOINT="https://trace.wandb.ai/otel/v1/traces"
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic <BASE64_AUTH_STRING>,project_id=<YOUR_TEAM_NAME>/<YOUR_PROJECT_NAME>"

You can then use the experimental_telemetry option to enable telemetry on supported AI SDK function calls:

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

const result = await generateText({
  model: openai('gpt-4o-mini'),
  prompt: 'What is 2 + 2?',
  experimental_telemetry: {
    isEnabled: true,
    metadata: {
      query: 'math',
      difficulty: 'easy',
    },
  },
});