Vercel AI SDK observability installation

npm install @posthog/ai@^8.7.0 @ai-sdk/openai @ai-sdk/otel ai @opentelemetry/sdk-node @opentelemetry/resources zod

import { OpenTelemetry } from '@ai-sdk/otel'
import { NodeSDK } from '@opentelemetry/sdk-node'
import { resourceFromAttributes } from '@opentelemetry/resources'
import { PostHogSpanProcessor } from '@posthog/ai/otel'
import { registerTelemetry } from 'ai'

export const posthogSpanProcessor = new PostHogSpanProcessor({
  projectToken: '<ph_project_token>',
  host: 'https://us.i.posthog.com',
})

const sdk = new NodeSDK({
  resource: resourceFromAttributes({
    'service.name': 'my-app',
  }),
  spanProcessors: [posthogSpanProcessor],
})

sdk.start()

registerTelemetry(
  new OpenTelemetry({
    enrichSpan: ({ runtimeContext }) => ({
      environment:
        typeof runtimeContext?.properties === 'object' &&
        runtimeContext.properties !== null &&
        'environment' in runtimeContext.properties &&
        typeof runtimeContext.properties.environment === 'string'
          ? runtimeContext.properties.environment
          : undefined,
      'posthog.distinct_id':
        typeof runtimeContext?.distinctId === 'string'
          ? runtimeContext.distinctId
          : undefined,
      '$ai_session_id':
        typeof runtimeContext?.sessionId === 'string'
          ? runtimeContext.sessionId
          : undefined,
      '$ai_trace_name':
        typeof runtimeContext?.traceName === 'string'
          ? runtimeContext.traceName
          : undefined,
      '$groups':
        typeof runtimeContext?.groups === 'object' &&
        runtimeContext.groups !== null &&
        !Array.isArray(runtimeContext.groups)
          ? JSON.stringify(runtimeContext.groups)
          : undefined,
    }),
  })
)

import { generateText, tool, stepCountIs } from 'ai'
import { openai } from '@ai-sdk/openai'
import { z } from 'zod'
import { posthogSpanProcessor } from './instrumentation'

async function runWeatherAgent(): Promise<string> {
  const result = await generateText({
    model: openai('gpt-5-mini'),
    prompt: "What's the weather in Paris?",
    tools: {
      get_weather: tool({
        description: 'Get the weather for a city',
        inputSchema: z.object({ city: z.string() }),
        execute: async ({ city }) => `It's always sunny in ${city}!`,
      }),
    },
    stopWhen: stepCountIs(5), // let the model see the tool result and respond
    runtimeContext: {
      distinctId: 'user_123',
      sessionId: 'conversation-abc',
      traceName: 'weather-agent',
      groups: {
        company: 'company_123',
      },
      properties: {
        environment: 'production',
      },
    },
    telemetry: {
      functionId: 'my-ai-function',
      includeRuntimeContext: {
        distinctId: true,
        sessionId: true,
        traceName: true,
        groups: true,
        properties: true,
      },
    },
  })

  return result.text
}

try {
  console.log(await runWeatherAgent())
} finally {
  // Spans are still queued in the batch processor when this script exits,
  // so without this flush they never reach PostHog.
  await posthogSpanProcessor.forceFlush()
}