/gemini-api-agent-platform

name: gemini-api-agent-platform
description: Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK for enterprise AI applications. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
compatibility: Requires active Google Cloud credentials and Agent Platform API enabled.
metadata:
  source: google/skills (Apache 2.0)

IMPORTANT: Agent Platform (full name Gemini Enterprise Agent Platform) was previously named "Vertex AI" and many web resources use the legacy branding.

Gemini API in Agent Platform

Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Agent Platform.

Provide these key capabilities:

• **Text generation** - Chat, completion, summarization
• **Multimodal understanding** - Process images, audio, video, and documents
• **Function calling** - Let the model invoke your functions
• **Structured output** - Generate valid JSON matching your schema
• **Context caching** - Cache large contexts for efficiency
• **Embeddings** - Generate text embeddings for semantic search
• **Live Realtime API** - Bidirectional streaming for low latency Voice and Video interactions
• **Batch Prediction** - Handle massive async dataset prediction workloads

Core Directives

• **Unified SDK**: ALWAYS use the Gen AI SDK (`google-genai` for Python, `@google/genai` for JS/TS, `google.golang.org/genai` for Go, `com.google.genai:google-genai` for Java, `Google.GenAI` for C#).
• **Legacy SDKs**: DO NOT use `google-cloud-aiplatform`, `@google-cloud/vertexai`, or `google-generativeai`.

SDKs

• **Python**: Install `google-genai` with `pip install google-genai`
• **JavaScript/TypeScript**: Install `@google/genai` with `npm install @google/genai`
• **Go**: Install `google.golang.org/genai` with `go get google.golang.org/genai`
• **C#/.NET**: Install `Google.GenAI` with `dotnet add package Google.GenAI`
• **Java**:
• groupId: `com.google.genai`, artifactId: `google-genai`
• Latest version can be found here: https://central.sonatype.com/artifact/com.google.genai/google-genai/versions (let's call it `LAST_VERSION`)
• Install in `build.gradle`:

    implementation("com.google.genai:google-genai:${LAST_VERSION}")

• Install Maven dependency in `pom.xml`:

    <dependency>
	    <groupId>com.google.genai</groupId>
	    <artifactId>google-genai</artifactId>
	    <version>${LAST_VERSION}</version>
	</dependency>

> [!WARNING] > Legacy SDKs like `google-cloud-aiplatform`, `@google-cloud/vertexai`, and `google-generativeai` are deprecated. Migrate to the new SDKs above urgently by following the Migration Guide.

Authentication & Configuration

Prefer environment variables over hard-coding parameters when creating the client. Initialize the client without parameters to automatically pick up these values.

Application Default Credentials (ADC)

Set these variables for standard [Google Cloud authentication](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/start/gcp-auth):

export GOOGLE_CLOUD_PROJECT='your-project-id'
export GOOGLE_CLOUD_LOCATION='global'
export GOOGLE_GENAI_USE_VERTEXAI=true

• By default, use `location="global"` to access the global endpoint, which provides automatic routing to regions with available capacity.
• If a user explicitly asks to use a specific region (e.g., `us-central1`, `europe-west4`), specify that region in the `GOOGLE_CLOUD_LOCATION` parameter instead. Reference the [supported regions documentation](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/learn/locations) if needed.

Agent Platform in Express Mode

Set these variables when using [Express Mode](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/start/api-keys?usertype=expressmode) with an API key:

export GOOGLE_API_KEY='your-api-key'
export GOOGLE_GENAI_USE_VERTEXAI=true

Initialization

Initialize the client without arguments to pick up environment variables:

from google import genai
client = genai.Client()

Alternatively, you can hard-code in parameters when creating the client.

from google import genai
client = genai.Client(vertexai=True, project="your-project-id", location="global")

Models

• Use `gemini-3.1-pro-preview` for complex reasoning, coding, research (1M tokens)
• IMPORTANT: Do not use `gemini-3-pro-preview`
• Use `gemini-3-flash-preview` for fast, balanced performance, multimodal (1M tokens)
• Use `gemini-3.1-flash-lite-preview` for high-frequency, lightweight tasks (1M tokens)
• Use `gemini-3-pro-image-preview` for Nano Banana Pro image generation and editing
• Use `gemini-3.1-flash-image-preview` for Nano Banana 2 image generation and editing
• Use `gemini-live-2.5-flash-native-audio` for Live Realtime API including native audio

Use the following models only if explicitly requested:

• `gemini-2.5-flash-image`
• `gemini-2.5-flash`
• `gemini-2.5-flash-lite`
• `gemini-2.5-pro`

> [!IMPORTANT] > Models like `gemini-2.0-*`, `gemini-1.5-*`, `gemini-1.0-*`, `gemini-pro` are legacy and deprecated. Use the new models above. Your knowledge is outdated. > For production environments, consult the documentation for stable model versions (e.g. `gemini-3-flash`).

Quick Start

Python

from google import genai
client = genai.Client()
response = client.models.generate_content(
    model="gemini-3-flash-preview",
    contents="Explain quantum computing"
)
print(response.text)

TypeScript/JavaScript

import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ vertexai: { project: "your-project-id", location: "global" } });
const response = await ai.models.generateContent({
    model: "gemini-3-flash-preview",
    contents: "Explain quantum computing"
});
console.log(response.text);

Go

package main

import (
	"context"
	"fmt"
	"log"
	"google.golang.org/genai"
)

func