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gemini-api-dev

Develop Gemini API integrations across Python, JavaScript/TypeScript, Java, and Go SDKs.

Updated Jun 7, 2026
Search Tags:#python#javascript#sdk#multimodal#function-calling#gemini-api#google-genai
One-click install
npx skills add https://github.com/vikingokft/vikingo-studio-skills --skill gemini-api-dev-vikingokft
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gemini-api-dev
Source: https://github.com/vikingokft/vikingo-studio-skills/tree/main/google/gemini-api-dev
Command: npx skills add https://github.com/vikingokft/vikingo-studio-skills --skill gemini-api-dev-vikingokft

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Gemini API development is complex due to multiple hosted models, multimodal data handling, and the need for correct SDKs, model selection, and up-to-date capabilities. This skill consolidates guidelines for using Gemini hosted models (Gemini and Gemma 4), multimodal content, function calling, and structured outputs across Python, JavaScript/TypeScript, Java, and Go.

Core Features & Use Cases

  • SDK guidance across Python (google-genai), JavaScript/TypeScript (@google/genai), Java (com.google.genai:google-genai), and Go (google.golang.org/genai).
  • Model selection and API capabilities management for Gemini-family models including Gemini 3.x and Gemma 4 variants.
  • Use cases spanning multimodal content handling, function calling, and structured outputs in production apps.

Quick Start

Instantiate a Gemini API client using the recommended SDKs and run a basic content-generation example.

Frequently Asked Questions about gemini-api-dev

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

FAQPage Schema
How do I implement function calling with the Gemini API using Python or JavaScript SDKs?▼

To implement function calling with the Gemini API, use the recommended Python (google-genai) or JavaScript (@google/genai) SDKs. This skill provides guidelines for mapping external functions to model outputs, enabling structured and actionable responses across supported languages.

Can I handle multimodal content with the Gemini API across different programming languages?▼

Yes, you can handle multimodal content with the Gemini API across Python, JavaScript/TypeScript, Java, and Go. The skill provides SDK-specific guidance for ingesting and processing multimodal data, ensuring correct content handling across your preferred tech stack.

What is the best way to select the correct model for my Gemini API integration?▼

Selecting the correct model for your Gemini API integration involves matching capabilities to your use case. This skill manages model selection and API capabilities for Gemini-family models, including Gemini 3.x and Gemma 4 variants, to ensure you use the right hosted model.

Does the Gemini API support structured outputs in production applications?▼

Yes, the Gemini API supports structured outputs in production applications. By using the official SDKs across Python, JavaScript/TypeScript, Java, and Go, you can enforce specific data schemas and parse structured responses directly within your application logic.

How do I instantiate a Gemini API client for a basic content-generation example?▼

To instantiate a Gemini API client for basic content generation, use the recommended SDK for your language, such as google-genai for Python or @google/genai for JavaScript. The skill provides quick start steps to configure the client and execute your first generation request.

Are there official Gemini API SDKs available for Java and Go environments?▼

Yes, there are official Gemini API SDKs for Java (com.google.genai:google-genai) and Go (google.golang.org/genai). This skill provides integration guidelines and usage patterns for implementing multimodal and function calling features across these environments.

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