gemini-api-agent-platform
This Claude Code skill provides guidance for integrating Google's Gemini API through Agent Platform using the Gen AI SDK across multiple programming languages (Python, JavaScript/TypeScript, Go, Java, and C#). Use it when building enterprise AI applications requiring text generation, multimodal understanding, function calling, structured outputs, context caching, embeddings, real-time voice/video interactions, or batch prediction workloads.
git clone --depth 1 https://github.com/davila7/claude-code-templates /tmp/gemini-api-agent-platform && cp -r /tmp/gemini-api-agent-platform/cli-tool/components/skills/ai-research/gemini-api-agent-platform ~/.claude/skills/gemini-api-agent-platformSKILL.md
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:${LAST_VERSION}")
```
- Install Maven dependency in `pom.xml`:
```xml
<dependency>
<groupId>com.google.genai</groupId>
<artifactId>google-genai</artifactId>
<version>${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):
```bash
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:
```bash
export GOOGLE_API_KEY='your-api-key'
export GOOGLE_GENAI_USE_VERTEXAI=true
```
### Initialization
Initialize the client without arguments to pick up environment variables:
```python
from google import genai
client = genai.Client()
```
Alternatively, you can hard-code in parameters when creating the client.
```python
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
```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
```typescript
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
```go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, &genai.ClientConfig{
Backend: genai.BackendVertexAI,
Project: "your-project-id",
Location: "global",
})
if err != nil {
log.Fatal(err)
}
resp, err := client.Models.GenerateContent(ctx, "gemini-3-flash-preview", genai.Text("Explain quantum computing"), nil)
if err != nil {
log.Fatal(err)
}
fmt.Println(resp.Text)
}
```
### Java
```java
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