firebase-ai-logic

# 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 # Choose AI logic`

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

### 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

- Start with Gemini for most use cases, and choose Imagen for specialized tasks where image quality and specific styles are critical. (Example: gemini-2.5-flash-image)
- 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

Recommended: The developer must enable Firebase App Check to prevent unauthorized clients from using their API quota. see [App-check recaptcha enterprise](https://firebase.google.com/docs/app-check/web/recaptcha-enterprise-provider.md.txt).

### Remote Config

Consider that you do not need to hardcode model names (e.g., `gemini-flash-lite-latest`). 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) 

## 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  |

**Always use the most recent version of Gemini (gemini-flash-latest) unless another model is requested by the docs or the user. DO NOT USE gemini-1.5-flash**

## References

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