---
name: firebase-ai-logic-basico
description: Guía oficial para integrar Firebase AI Logic (API de Gemini) en aplicaciones web y móviles, cubriendo configuración, inferencia multimodal, salida estructurada y seguridad con App Check.
license: Apache-2.0
metadata:
  id: 0327109c
  slug: firebase-ai-logic-basico
  titulo: "Firebase AI Logic: Integración Básica con Gemini"
  servicio: Web
  categoria_recurso: Web-Desarrollo
  tipo: referencia
  nivel: intermedio
  idioma: es
  idioma_original: en
  acceso: gratis
  precio_eur: 0
  plataformas: [Firebase, Google Cloud, Web, Android, iOS, Flutter]
  dependencias: [Firebase SDK, Gemini Developer API, Node.js 16+, firebase-tools]
  licencia: { spdx: Apache-2.0, redistribuible: true, uso_comercial: true }
  fuente:
    repo: firebase/skills
    url: https://github.com/firebase/skills/tree/main/skills/firebase-ai-logic-basics
    commit: aeb478e
    autor: firebase
    nombre_original: firebase-ai-logic-basics
    duplicados_en: []
  seguridad: { veredicto: seguro, riesgo: bajo, escaneado: "2026-06-14", motor: "grep-estatico+auditor-llm" }
  ficha:
    que_hace: "Documenta cómo añadir IA generativa (Gemini) a apps web y móviles usando Firebase AI Logic sin gestionar un backend propio."
    como_lo_hace: "Proporciona instrucciones de instalación, ejemplos de código para text, multimodal, streaming y JSON estructurado, y buenas prácticas de seguridad con App Check y Remote Config."
  content_hash: "0327109c3cfdd85683db305755d2cc56d4422799b8ec4282f1e7b273e52cdd7b"
  version: 1.0.0
---

# Firebase AI Logic Basics

## Overview

Firebase AI Logic is a product of Firebase that allows developers to add gen AI to their mobile and web apps using client-side SDKs. You can call Gemini models directly from your app without managing a dedicated backend. Firebase AI Logic, which was previously known as "Vertex AI for Firebase", represents the evolution of Google's AI integration platform for mobile and web developers.

It supports the two Gemini API providers:
- **Gemini Developer API**: It has a free tier ideal for prototyping, and pay-as-you-go for production 
- **Vertex AI Gemini API**: Ideal for scale with enterprise-grade production readiness, requires Blaze plan

Use the Gemini Developer API as a default, and only Vertex AI Gemini API if the application requires it.

## Setup & Initialization

### Prerequisites

- Before starting, ensure you have **Node.js 16+** and npm installed. Install them if they aren’t already available. 
- Identify the platform the user is interested in building on prior to starting: Android, iOS, Flutter or Web.
- If their platform is unsupported, Direct the user to Firebase Docs to learn how to set up AI Logic for their application (share this link with the user https://firebase.google.com/docs/ai-logic/get-started)

### Installation

The library is part of the standard Firebase Web SDK.

`npm install -g firebase@latest`

If you're in a firebase directory (with a firebase.json) the currently selected project will be marked with "current" using this command:  

`npx -y firebase-tools@latest projects:list`

Ensure there's at least one app associated with the current project 

`npx -y firebase-tools@latest apps:list`

Initialize AI logic SDK with the init command

`npx -y firebase-tools@latest init ailogic`

This will automatically enable the Gemini Developer API in the Firebase console.

More info in [Firebase AI Logic Getting Started](https://firebase.google.com/docs/ai-logic/get-started.md.txt)

## Core Capabilities

> [!WARNING]
> **CRITICAL: Use current model names:**
> Always check the [Firebase AI Logic Models documentation](https://firebase.google.com/docs/ai-logic/models.md.txt) for the currently supported model names. Do NOT use `gemini-2.0-pro` or `gemini-2.0-flash` or other older models that are shutdown.

### Text-Only Generation

### Multimodal (Text + Images/Audio/Video/PDF input)

Firebase AI Logic allows Gemini models to analyze image files directly from your app. This enables features like creating captions, answering questions about images, detecting objects, and categorizing images. Beyond images, Gemini can analyze other media types like audio, video, and PDFs by passing them as inline data with their MIME type. For files larger than 20 megabytes (which can cause HTTP 413 errors as inline data), store them in Cloud Storage for Firebase and pass their URLs to the Gemini Developer API.

### Chat Session (Multi-turn)

Maintain history automatically using `startChat`.

### Streaming Responses

To improve the user experience by showing partial results as they arrive (like a typing effect), use `generateContentStream` instead of `generateContent` for faster display of results.

### Generate Images with Nano Banana

> [!WARNING]
> **Use current Image model names:**
> Always check the [Firebase AI Logic Models documentation](https://firebase.google.com/docs/ai-logic/models.md.txt) for the currently supported image generation (Nano Banana) model names.

- Requires an upgraded Blaze pay-as-you-go billing plan.

### Search Grounding with the built in googleSearch tool

## Supported Platforms and Frameworks

Supported Platforms and Frameworks include Kotlin and Java for Android, Swift for iOS, JavaScript for web apps, Dart for Flutter, and C Sharp for Unity.

## Advanced Features

### Structured Output (JSON)

Enforce a specific JSON schema for the response.

### On-Device AI (Hybrid)

Hybrid on-device inference for web apps, where the Firebase Javascript SDK automatically checks for Gemini Nano's availability (after installation) and switches between on-device or cloud-hosted prompt execution. This requires specific steps to enable model usage in the Chrome browser, more info in the [hybrid-on-device-inference documentation](https://firebase.google.com/docs/ai-logic/hybrid-on-device-inference.md.txt).

## Security & Production

### App Check

> [!WARNING]
> **Critical Safety Requirement:** In order to use AI Logic safely, you MUST set up App Check on your app. This prevents unauthorized clients from using your API quota and accessing your backend resources.

See [App Check with reCAPTCHA Enterprise](https://firebase.google.com/docs/app-check/web/recaptcha-enterprise-provider.md.txt) for setup instructions.

### Remote Config

Consider that you do not need to hardcode model names (e.g., a specific model version string). Use Firebase Remote Config to update model versions dynamically without deploying new client code.  See [Changing model names remotely](https://firebase.google.com/docs/ai-logic/change-model-name-remotely.md.txt) 

> [!WARNING]
> **CRITICAL: Backend Provisioning Required**
> For all platforms (Flutter, Android, iOS, Web), you MUST run `npx firebase-tools init ailogic` to provision the service. `flutterfire configure` ONLY handles client configuration and does NOT enable the AI service, leading to `PERMISSION_DENIED` errors.

## Initialization Code References

| Language, Framework, Platform | Gemini API provider | Context URL |
| :---- | :---- | :---- |
| Web Modular API | Gemini Developer API (Developer API) | firebase://docs/ai-logic/get-started  |
| iOS (Swift) | Gemini Developer API | [ios_setup.md](references/ios_setup.md) |
| Flutter (Dart) | Gemini Developer API | [flutter_setup.md](references/flutter_setup.md) |

> [!WARNING]
> **CRITICAL: Use current model names:**
> Always check the [Firebase AI Logic Models documentation](https://firebase.google.com/docs/ai-logic/models.md.txt) for the currently supported model names. Do NOT use `gemini-2.0-pro` or `gemini-2.0-flash` or other older models that are shutdown.

## References

[Web SDK code examples and usage patterns](references/usage_patterns_web.md)
[iOS SDK code examples and usage patterns](references/ios_setup.md)
[Flutter SDK code examples and usage patterns](references/flutter_setup.md)


[Android (Kotlin) SDK usage patterns](references/usage_patterns_android.md)