/agent-platform-migrate-from-ai-studio

name: agent-platform-migrate-from-ai-studio
metadata:
  category: AiAndMachineLearning
description: >-
  Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).

Migrating from Gemini API in AI Studio to Agent Platform

Use this skill when you need to transition an application from the developer-centric Google AI Studio ecosystem (`generativelanguage.googleapis.com`) to the enterprise-grade Google Cloud Agent Platform (`aiplatform.googleapis.com`).

--------------------------------------------------------------------------------

When to Invoke This Skill

• You want to migrate an application from Google AI Studio to Agent Platform

(formerly Vertex AI).

• You have **Google Cloud credits** (e.g., the $300 Welcome Free Trial) that

you want to apply toward Gemini API inferencing costs.

• You need to unify your inferencing pipelines, IAM permissions, telemetry,

and billing with existing Google Cloud infrastructure (Compute Engine, Cloud SQL, BigQuery).

• You are deploying open-source orchestration engines (like OpenClaw or ADK

agents) on Google Cloud VMs, and want the entire system to run under a unified Google Cloud billing structure.

--------------------------------------------------------------------------------

Gemini API Comparison

Feature / Control | Google AI Studio (Gemini Developer API) | Agent Platform (Enterprise Gemini API) :--------------------- | :-------------------------------------------------------------------- | :------------------------------------- **API Endpoint** | `generativelanguage.googleapis.com` | `aiplatform.googleapis.com` **Target Audience** | Developers, startups, students, researchers building production apps. | Enterprise production, MLOps engineers **GCP Credit Support** | No (GCP credits/Free Trial **cannot** be applied) | Yes (Fully covered by Welcome or custom credits) **Data Privacy** | Data may be reviewed to improve Google products | Prompts/responses are **never** used for training **Security & IAM** | API key, OAuth | Google Cloud IAM (Service Accounts, OAuth 2.0, VPC-SC) **Compliance & SLAs** | None (Best-effort availability) | 24/7 Enterprise Support, SLAs, HIPAA, SOC2 **Throughput Options** | Shared / Rate-limited | Pay-as-you-go OR Provisioned Throughput **MLOps Ecosystem** | Basic prompt management | Model Registry, Model Monitoring, Pipeline Evaluation **Inferencing Scope** | Global endpoints only | Both Global and strict Regional endpoints

See [Google Cloud Documentation](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/migrate/migrate-google-ai.md.txt) to learn more about the differences between the two offerings.

--------------------------------------------------------------------------------

Migration Guide

Billing and Credits

Google Cloud Free Trial credits **[do not apply to AI Studio](https://docs.cloud.google.com/free/docs/free-cloud-features.md.txt)**. To use your credits for Gemini models, you must route calls through the Agent Platform.

1. Create a Google Cloud billing account. You must provide a valid payment method during setup to verify identity. 2. If you are a new customer, ensure your $300 Welcome credit is active in the Billing Console. 3. **Avoid Billing Surprises:** To prevent automatic fallback to your standard form of payment when credits are exhausted, you should establish a budget alert:

• Go to **Billing** -> **Budgets & Alerts** -> **Create Budget**.
• Set the threshold to map to your credit limit or maximum comfortable

spend.

Enable the Agent Platform API

You must explicitly enable the Agent Platform API on your target Google Cloud Project. Run the following command via your local shell:

gcloud services enable aiplatform.googleapis.com --project="{project_id}"

Authentication & Authorization (IAM)

User Auth

For local debugging or script execution, authenticate using [Application Default Credentials](https://docs.cloud.google.com/docs/authentication/application-default-credentials.md.txt) (ADC).

**Option 1 - Automated Script**:

bash <(curl -sSL https://storage.googleapis.com/cloud-samples-data/adc/setup_adc.sh)

**Option 2 - Manual Setup**:

gcloud auth login
gcloud auth application-default login

Grant your user identity the required IAM role to perform inferencing calls:

gcloud projects add-iam-policy-binding "{project_id}" \
    --member="user:YOUR_EMAIL@domain.com" \
    --role="roles/aiplatform.user"

Service Auth

When running your application on Google Cloud infrastructure such as a Compute Engine VM, authenticate using the machine's attached Service Account. For example, the [Compute Engine Default Service Account](https://docs.cloud.google.com/compute/docs/access/service-accounts#default_service_account.md.txt).

1. Grant the virtual machine's underlying Service Account the user role:

gcloud projects add-iam-policy-binding "{project_id}" \
    --member="serviceAccount:PROJECT_NUMBER-compute@developer.gserviceaccount.com" \
    --role="roles/aiplatform.user"

2. **[Compute Engine Access Scopes](https://docs.cloud.google.com/compute/docs/access/service-accounts.md.txt):** Legacy access scopes can override IAM bindings. When provisioning or modifying your Compute Engine instance, you must v