Vercel AI LLM analytics installation

Setting up analytics starts with installing the PostHog SDK.

npm install @posthog/ai posthog-node

Install the Vercel AI SDK:

npm install ai @ai-sdk/openai

In the spot where you initialize the Vercel AI SDK, import PostHog and our withTracing wrapper, initialize PostHog with your project API key and host from your project settings, and pass it to the withTracing wrapper.

import { PostHog } from "posthog-node";
import { withTracing } from "@posthog/ai"
import { generateText } from "ai"
import { createOpenAI } from "@ai-sdk/openai"

const phClient = new PostHog(
  '<ph_project_api_key>',
  { host: 'https://us.i.posthog.com' }
);

const openaiClient = createOpenAI({
  apiKey: 'your_openai_api_key',
  compatibility: 'strict'
});

const model = withTracing(openaiClient("gpt-4-turbo"), phClient, {
  posthogDistinctId: "user_123", // optional
  posthogTraceId: "trace_123", // optional
  posthogProperties: { "conversation_id": "abc123", "paid": true }, // optional
  posthogPrivacyMode: false, // optional
  posthogGroups: { "company": "company_id_in_your_db" }, // optional
});

phClient.shutdown()

Now, when you use the Vercel AI SDK, it automatically captures many properties into PostHog including $ai_input, $ai_input_tokens, $ai_latency, $ai_model, $ai_model_parameters, $ai_output_choices, and $ai_output_tokens. This works for both text and image message types.

You can also capture or modify additional properties with the posthogDistinctId, posthogTraceId, posthogProperties, posthogGroups, and posthogPrivacyMode parameters.

const { text } = await generateText({
  model: model,
  prompt: message
});

console.log(text)

Note: If you want to capture LLM events anonymously, don't pass a distinct ID to the request. See our docs on anonymous vs identified events to learn more.

Before proceeding, let's make sure LLM events are being captured and sent to PostHog. Under LLM analytics, you should see rows of data appear in the Traces and Generations tabs.