> ## Documentation Index
> Fetch the complete documentation index at: https://latitude-monitoring-docs-docs-sync-2026-08-14.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Google AI Platform

> Connect your Google AI Platform-powered application to Latitude for observability.

## Overview

This guide shows you how to integrate **Latitude Telemetry** into an application that uses **Google Cloud AI Platform**.

<Check>
  You'll keep calling AI Platform exactly as you do today. Telemetry simply
  observes and enriches those calls.
</Check>

***

## Requirements

* A **Latitude account** and **API key**
* A **Latitude project slug**
* A project that uses the **Google Cloud AI Platform SDK**

***

## Steps

<Steps>
  <Step title="Install">
    <Tabs>
      <Tab title="TypeScript">
        <CodeGroup>
          ```bash npm theme={null}
          npm install @latitude-data/telemetry @google-cloud/aiplatform
          ```

          ```bash pnpm theme={null}
          pnpm add @latitude-data/telemetry @google-cloud/aiplatform
          ```

          ```bash yarn theme={null}
          yarn add @latitude-data/telemetry @google-cloud/aiplatform
          ```

          ```bash bun theme={null}
          bun add @latitude-data/telemetry @google-cloud/aiplatform
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Python">
        <CodeGroup>
          ```bash pip theme={null}
          pip install latitude-telemetry
          ```

          ```bash uv theme={null}
          uv add latitude-telemetry
          ```

          ```bash poetry theme={null}
          poetry add latitude-telemetry
          ```
        </CodeGroup>
      </Tab>
    </Tabs>
  </Step>

  <Step title="Initialize and use">
    <Tabs>
      <Tab title="TypeScript">
        ```ts theme={null}
        import { createAIPlatformInstrumentation } from "@latitude-data/telemetry/instrumentations/aiplatform"
        import { Latitude, capture } from "@latitude-data/telemetry"
        import { PredictionServiceClient } from "@google-cloud/aiplatform"
        import * as AIPlatformSDK from "@google-cloud/aiplatform"

        const latitude = new Latitude({
          apiKey: process.env.LATITUDE_API_KEY!,
          project: process.env.LATITUDE_PROJECT_SLUG!,
          instrumentations: [createAIPlatformInstrumentation(AIPlatformSDK)],
        })

        await latitude.ready
        const client = new PredictionServiceClient()

        await capture("generate-prediction", async () => {
          const [response] = await client.predict({
            endpoint: `projects/${process.env.GCP_PROJECT_ID}/locations/us-central1/publishers/google/models/text-bison`,
            instances: [{ content: "Hello" }],
            parameters: { temperature: 0.2, maxOutputTokens: 256 },
          })
          return response.predictions
        })

        await latitude.shutdown()
        ```
      </Tab>

      <Tab title="Python">
        ```python theme={null}
        from google.cloud import aiplatform

        from latitude_telemetry import Latitude, capture

        latitude = Latitude(
            api_key="your-api-key",
            project="your-project-slug",
            instrumentations={"aiplatform": aiplatform},
        )

        aiplatform.init(project="your-gcp-project", location="us-central1")

        def generate_prediction():
            model = aiplatform.TextGenerationModel.from_pretrained("text-bison")
            response = model.predict("Hello", temperature=0.2, max_output_tokens=256)
            return response.text

        capture("generate-prediction", generate_prediction)

        latitude.shutdown()
        ```
      </Tab>
    </Tabs>
  </Step>
</Steps>

***

## Seeing Your Traces

Once connected, traces appear automatically in Latitude:

1. Open your **project** in the Latitude dashboard
2. Each execution shows input/output messages, model, token usage, latency, and errors