gemini-api-integration

name	gemini-api-integration
description	Use when integrating Google Gemini API into projects. Covers model selection, multimodal inputs, streaming, function calling, and production best practices.
type	skill
created	2026-02-27T00:00:00.000Z
domain	ai-ml
category	llm-agents
risk	safe
source	community
tags	["skill","ai-ml","llm-agents","gemini","api","integration"]

Gemini API Integration

Overview

This skill guides AI agents through integrating Google Gemini API into applications — from basic text generation to advanced multimodal, function calling, and streaming use cases. It covers the full Gemini SDK lifecycle with production-grade patterns.

When to Use This Skill

• Use when setting up Gemini API for the first time in a Node.js, Python, or browser project
• Use when implementing multimodal inputs (text + image/audio/video)
• Use when adding streaming responses to improve perceived latency
• Use when implementing function calling / tool use with Gemini
• Use when optimizing model selection (Flash vs Pro vs Ultra) for cost and performance
• Use when debugging Gemini API errors, rate limits, or quota issues

Step-by-Step Guide

1. Installation & Setup

Node.js / TypeScript:

npm install @google/generative-ai

Python:

pip install google-generativeai

Set your API key securely:

export GEMINI_API_KEY="your-api-key-here"

2. Basic Text Generation

Node.js:

import { GoogleGenerativeAI } from "@google/generative-ai";

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" });

const result = await model.generateContent("Explain async/await in JavaScript");
console.log(result.response.text());

Python: