vertex-ai-api-dev

Implement Gemini API integrations on Vertex AI using Gen AI SDKs.

302|22|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/JetBrains/skills --skill vertex-ai-api-dev-jetbrains
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vertex-ai-api-dev
Source: https://github.com/JetBrains/skills/tree/main/vertex-ai-api-dev
Command: npx skills add https://github.com/JetBrains/skills --skill vertex-ai-api-dev-jetbrains

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Streamlines access to Gemini APIs on Vertex AI for enterprise teams, simplifying SDK usage, authentication, and model management.

Core Features & Use Cases

  • Unified SDKs across Python, JavaScript/TypeScript, Go, Java, and C# to call Gemini models on Vertex AI.
  • Rich model capabilities including text generation, multimodal inputs, embeddings, live streaming, and batch prediction.
  • Use cases include enterprise chat assistants, automated content generation, and data processing pipelines integrated with Vertex AI.

Quick Start

Install the Gen AI SDKs and run a quick Vertex AI Gemini sample to generate content.

Frequently Asked Questions about vertex-ai-api-dev

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use the Gemini API on Vertex AI for enterprise text generation?

The Gemini API on Vertex AI supports multimodal inputs, text generation, embeddings, live streaming, and batch prediction. It enables enterprise workloads like automated content generation and data processing pipelines using official Gen AI SDKs across multiple programming languages.

Can I call Gemini models on Vertex AI using TypeScript and Go?

Yes, you can call Gemini models on Vertex AI using TypeScript, Go, Python, Java, and C#. The official Gen AI SDKs provide unified access across these languages to implement enterprise capabilities like multimodal inputs and batch prediction.

How do I authenticate Vertex AI Gemini API requests in an enterprise environment?

Authenticate Vertex AI Gemini API requests by using Application Default Credentials (ADC) or Vertex AI Express Mode. These methods ensure secure access when integrating official Gen AI SDKs into enterprise workloads and data processing pipelines.

Does the Gen AI SDK support live streaming and batch prediction on Vertex AI?

Yes, the Gen AI SDK supports live streaming and batch prediction on Vertex AI. These rich model capabilities allow enterprise applications to handle real-time content generation and large-scale data processing efficiently.

What are the safety and context-management capabilities of Vertex AI Gemini APIs?

Vertex AI Gemini APIs include safety, caching, tooling, and context-management capabilities. These features ensure secure and contextually aware enterprise integrations when generating content or processing multimodal inputs via the official SDKs.