Eve AI observability installation

Let AI instrument your LLM calls for you

Skip the manual setup — run this in your project and the wizard installs the SDK and wires up AI Observability for you.

Learn more
PostHog Wizard hedgehog

Contents

  1. Install dependencies

    Required

    Install PostHog AI, its OpenTelemetry peer dependencies, and Vercel's OpenTelemetry package.

    npm install @posthog/ai @opentelemetry/api @opentelemetry/exporter-trace-otlp-http @opentelemetry/sdk-trace-base @vercel/otel

    Version note: This example uses projectToken, which is available in @posthog/ai 7.19.6 and later. Earlier 7.x versions use apiKey.

  2. Set environment variables

    Required

    Set your PostHog project token and host in your Eve project's environment.

    POSTHOG_PROJECT_TOKEN=<ph_project_token>
    POSTHOG_HOST=https://us.i.posthog.com

  3. Add Eve instrumentation

    Required

    Create agent/instrumentation.ts. Eve discovers this file and starts the exporter when your agent server starts. The optional events handler uses Eve runtime context to identify spans with the user who started the session, falling back to the caller for the current turn.

    import { trace } from '@opentelemetry/api'
    import { SimpleSpanProcessor } from '@opentelemetry/sdk-trace-base'
    import { PostHogTraceExporter } from '@posthog/ai/otel'
    import { registerOTel } from '@vercel/otel'
    import { defineInstrumentation } from 'eve/instrumentation'
    

    export default defineInstrumentation({
      setup: ({ agentName }) =>
        registerOTel({
          serviceName: agentName,
          spanProcessors: [
            new SimpleSpanProcessor(
              new PostHogTraceExporter({
                projectToken: process.env.POSTHOG_PROJECT_TOKEN!,
                host: process.env.POSTHOG_HOST,
              })
            ),
          ],
        }),
      // Optional: Link Eve and AI SDK spans to a PostHog user.
      events: {
        'step.started'(input) {
          const distinctId =
            input.session.auth.initiator?.principalId ??
            input.session.auth.current?.principalId
    

          if (!distinctId) {
            return undefined
          }
    

          trace.getActiveSpan()?.setAttribute('posthog.distinct_id', distinctId)
          return { runtimeContext: { posthog_distinct_id: distinctId } }
        },
      },
    })

    Note: To capture LLM events anonymously, omit the events handler. See our docs on anonymous vs identified events to learn more.

    You can expect captured $ai_generation events to have the following properties:

    PropertyDescription
    $ai_modelThe specific model, like gpt-5-mini or claude-4-sonnet
    $ai_latencyThe latency of the LLM call in seconds
    $ai_time_to_first_tokenTime to first token in seconds (streaming only)
    $ai_toolsTools and functions available to the LLM
    $ai_inputList of messages sent to the LLM
    $ai_input_tokensThe number of tokens in the input (often found in response.usage)
    $ai_output_choicesList of response choices from the LLM
    $ai_output_tokensThe number of tokens in the output (often found in response.usage)
    $ai_total_cost_usdThe total cost in USD (input + output)
    [...]See full list of properties

  4. Verify traces and generations

    Recommended
    Confirm LLM events are being sent to PostHog

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


    LLM generations in PostHog
    Check for LLM events in PostHog

  5. Next steps

    Recommended

    Now that you're capturing AI conversations, continue with the resources below to learn what else AI Observability enables within the PostHog platform.

    ResourceDescription
    BasicsLearn the basics of how LLM calls become events in PostHog.
    GenerationsRead about the $ai_generation event and its properties.
    TracesExplore the trace hierarchy and how to use it to debug LLM calls.
    SpansReview spans and their role in representing individual operations.
    Anaylze LLM performanceLearn how to create dashboards to analyze LLM performance.

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