> [!NOTE] > **This guide helps you migrate from the Preview (or beta) > versions of the "Vertex AI in Firebase" SDKs to the > Firebase AI Logic client SDKs** . > These client SDKs are available in Swift for Apple platforms, Kotlin and Java for Android, JavaScript for Web, Dart for Flutter, and Unity. > > If you're using a GA version of a "Vertex AI in Firebase" SDK, > then go to the guide for > [migrating from the GA > version of the SDK](https://firebase.google.com/docs/ai-logic/migrate-to-latest-sdk).
Firebase AI Logic and its client SDKs were formerly called "Vertex AI in Firebase". To better reflect our expanded services and features (for example, we now support the Gemini Developer API!), **we renamed and repackaged our services into Firebase AI Logic**. To securely access Google's generative AI models directly from your mobile or web apps, **you can now choose a "Gemini API" provider --- either the long-available Agent Platform Gemini API (formerly Vertex AI) or now the Gemini Developer API** . This means that you now have the option to use the Gemini Developer API, which provides a **no-cost tier** with reasonable rate limits and quotas. #### Overview of steps to migrate to the Firebase AI Logic SDKs - **Step 1**: Choose the best "Gemini API" provider for your app and use cases. - **Step 2**: Enable the required APIs. - **Step 3**: Update the library used in your app. - **Step 4**: Update the initialization in your app. - **Step 5**: Update your code depending on the features that you use. ## **Step 1**: Choose the best "Gemini API" provider for your app With this migration, you have a choice in "Gemini API" provider: - The old "Vertex AI in Firebase" SDKs could only use the Agent Platform Gemini API (formerly Vertex AI). - The new Firebase AI Logic SDKs let you choose which "Gemini API" provider you want to call directly from your mobile or web app -- either the Gemini Developer API or the Agent Platform Gemini API (formerly Vertex AI). Review the [differences between using the two Gemini API providers](https://firebase.google.com/docs/ai-logic/faq-and-troubleshooting.md.txt#differences-between-gemini-api-providers), especially in terms of supported features, pricing, and rate limits. For just one example, the Gemini Developer API doesn't support providing files using Cloud Storage URLs, but it might be a good choice if you want to take advantage of its no-cost tier and reasonable quota. > [!NOTE] > **Important** : If you want to use the "free tier" for the Gemini Developer API, you need to [downgrade](https://console.firebase.google.com/project/_/overview?purchaseBillingPlan=free) the Firebase project that you currently use with the client SDKs to the no-cost Spark pricing plan (that is, unlink the Cloud Billing account). Before downgrading, make sure that you're not depending on any other services or quotas that require the Blaze pricing plan. > > If your Firebase project stays on the Blaze pricing plan, > then you'll be on one of the > ["paid tiers" for the Gemini Developer API](https://ai.google.dev/gemini-api/docs/pricing). ## **Step 2**: Enable the required APIs Ensure that all required APIs are enabled in your Firebase project to use your chosen "Gemini API" provider. Note that you can have both of API providers enabled in your project at the same time. 1. Sign into the [Firebase console](https://console.firebase.google.com/), and then select your Firebase project. 2. In the Firebase console, go to **AI Services** \> [**AI Logic**](https://console.firebase.google.com/project/_/ailogic/?useAutoProject=true). 3. Click **Get started** to launch a guided workflow that helps you set up the [required APIs](https://firebase.google.com/docs/ai-logic/faq-and-troubleshooting.md.txt#required-apis) and resources for your project. 4. Select the "Gemini API" provider that you'd like to use with the Firebase AI Logic SDKs. You can always set up and use the other API provider later, if you'd like. - **Gemini Developer API** --- [billing optional](https://firebase.google.com/docs/ai-logic/pricing.md.txt?api=dev#api-provider-pricing-plans) (available on the no-cost Spark pricing plan) The console's workflow will enable the required APIs and create a Gemini API key in your project. *Do **not** add this Gemini API key into your app's codebase.* [Learn more.](https://firebase.google.com/docs/ai-logic/faq-and-troubleshooting.md.txt#add-gemini-api-key-to-codebase) - **Agent Platform Gemini API (formerly Vertex AI)** --- [billing required](https://firebase.google.com/docs/ai-logic/pricing.md.txt?api=vertex#api-provider-pricing-plans) (requires the pay-as-you-go Blaze pricing plan) The console's workflow will enable the required APIs in your project. 5. Continue in this migration guide to update the library and initialization in your app. ## **Step 3**: Update the library used in your app Update your app's codebase to use the Firebase AI Logic library. ### Swift 1. In Xcode, with your app project open, update your Firebase package to v12.5.0 or later using one of the following options: - **Option 1** : Update all packages: Navigate to **File \> Packages \> Update to Latest Package Versions**. - **Option 2** : Update Firebase individually: Navigate to the Firebase package in the section called **Package Dependencies** . Right-click on the Firebase package, and then select **Update Package**. 2. Make sure that the Firebase package now shows v12.5.0 or later. If it doesn't, verify that your specified [Package Requirements](https://developer.apple.com/documentation/xcode/adding-package-dependencies-to-your-app#Decide-on-package-requirements) allow updating to v12.5.0 or later. 3. Select your app's target in the Project Editor, and then navigate to the **Frameworks, Libraries, and Embedded Content** section. 4. Add the new library: Select the **+** button, and then add **FirebaseAILogic** from the Firebase package. 5. After you've finished migrating your app (see the remaining sections in this guide), make sure to remove the old library: Select **FirebaseVertexAI-Preview** , and then press the **---** button. ### Kotlin 1. In your **module (app-level) Gradle file** (usually `//build.gradle.kts` or `//build.gradle`), replace old dependencies (as applicable) with the following. Note that it might be easier to migrate your app's codebase (see the remaining sections in this guide) before deleting the old dependency. ```kotlin // BEFORE dependencies { implementation("com.google.firebase:firebase-vertexai:16.0.0-betaXX") } // AFTER dependencies { // Import the BoM for the Firebase platform implementation(platform("com.google.firebase:firebase-bom:35.1.0")) // Add the dependency for the Firebase AI Logic library // When using the BoM, you don't specify versions in Firebase library dependencies implementation("com.google.firebase:firebase-ai") } ``` 2. Sync your Android project with Gradle files. Note that if you choose to not use the Firebase Android BoM, then just add the dependency for the `firebase-ai` library and accept the latest version that's suggested by Android Studio. ### Java 1. In your **module (app-level) Gradle file** (usually `//build.gradle.kts` or `//build.gradle`), replace old dependencies (as applicable) with the following. Note that it might be easier to migrate your app's codebase (see the remaining sections in this guide) before deleting the old dependency. ```java // BEFORE dependencies { implementation("com.google.firebase:firebase-vertexai:16.0.0-betaXX") } // AFTER dependencies { // Import the BoM for the Firebase platform implementation(platform("com.google.firebase:firebase-bom:35.1.0")) // Add the dependency for the Firebase AI Logic library // When using the BoM, you don't specify versions in Firebase library dependencies implementation("com.google.firebase:firebase-ai") } ``` 2. Sync your Android project with Gradle files. Note that if you choose to not use the Firebase Android BoM, then just add the dependency for the `firebase-ai` library and accept the latest version that's suggested by Android Studio. ### Web 1. Get the latest version of the Firebase JS SDK for Web using npm: ``` npm i firebase@latest ``` OR ``` yarn add firebase@latest ``` 2. Wherever you've imported the library, update your import statements to use `firebase/ai` instead. Note that it might be easier to migrate your app's codebase (see the remaining sections in this guide) before deleting the old imports. ```javascript // BEFORE import { initializeApp } from "firebase/app"; import { getVertexAI, getGenerativeModel } from "firebase/vertexai-preview"; // AFTER import { initializeApp } from "firebase/app"; import { getAI, getGenerativeModel } from "firebase/ai"; ``` ### Dart 1. Update to the use the `firebase_ai` package in your `pubspec.yaml` file by running the following command from your Flutter project directory: ``` flutter pub add firebase_ai ``` 2. Rebuild your Flutter project: ``` flutter run ``` 3. After you've finished migrating your app (see the remaining sections in this guide), make sure to delete the old package: ``` flutter pub remove firebase_vertexai ```
### Unity Support for Unity wasn't available from "Vertex AI in Firebase". Learn how to [get started with the Firebase AI Logic SDK for Unity](https://firebase.google.com/docs/ai-logic/get-started.md.txt). ## **Step 4**: Update the initialization in your app |---| | *Click your Gemini API provider to view provider-specific content and code on this page.* |
Update how you initialize the service for your chosen API provider and create a `GenerativeModel` instance. ### Swift ```swift import FirebaseAILogic // Initialize the Gemini Developer API backend service let ai = FirebaseAI.firebaseAI(backend: .googleAI()) // Create a `GenerativeModel` instance with a model that supports your use case let model = ai.generativeModel(modelName: "gemini-3.8-flash") ``` ### Kotlin ```kotlin // Initialize the Gemini Developer API backend service. // Create a `GenerativeModel` instance with a model that supports your use case. val model = Firebase.ai(backend = GenerativeBackend.googleAI()) .generativeModel("gemini-3.8-flash") ``` ### Java ```java // Initialize the Gemini Developer API backend service. // Create a `GenerativeModel` instance with a model that supports your use case. GenerativeModel ai = FirebaseAI.getInstance(GenerativeBackend.googleAI()) .generativeModel("gemini-3.8-flash"); // Use the GenerativeModelFutures Java compatibility layer which offers // support for ListenableFuture and Publisher APIs GenerativeModelFutures model = GenerativeModelFutures.from(ai); ``` ### Web ```javascript import { initializeApp } from "firebase/app"; import { getAI, getGenerativeModel, GoogleAIBackend } from "firebase/ai"; // TODO(developer): Replace the following with your app's Firebase configuration // See: https://firebase.google.com/docs/web/learn-more#config-object const firebaseConfig = { // ... }; // Initialize FirebaseApp const firebaseApp = initializeApp(firebaseConfig); // Initialize the Gemini Developer API backend service. const ai = getAI(firebaseApp, { backend: new GoogleAIBackend() }); // Create a \`GenerativeModel\` instance with a model that supports your use case. const model = getGenerativeModel(ai, { model: "gemini-3.8-flash" }); ``` ### Dart ```dart import 'package:firebase_ai/firebase_ai.dart'; import 'package:firebase_core/firebase_core.dart'; import 'firebase_options.dart'; // Initialize FirebaseApp await Firebase.initializeApp( options: DefaultFirebaseOptions.currentPlatform, ); // Initialize the Gemini Developer API backend service // Create a \`GenerativeModel\` instance with a model that supports your use case final model = FirebaseAI.googleAI().generativeModel(model: 'gemini-3.8-flash'); ``` ### Unity Support for Unity wasn't available from "Vertex AI in Firebase". Learn how to [get started with the Firebase AI Logic SDK for Unity](https://firebase.google.com/docs/ai-logic/get-started.md.txt). Note that **depending on the capability you're using, you might not always create a `GenerativeModel` instance** . To [stream input and output using the Gemini Live API](https://firebase.google.com/docs/ai-logic/live-api.md.txt), create a `LiveModel` instance. ## **Step 5**: Update your code depending on features that you use This step describes changes that may be required depending on which features you use. - If you use Cloud Storage URLs ***and*** you swapped to use the Gemini Developer API in this migration, then you must update your multimodal requests to [include files as inline data](https://firebase.google.com/docs/ai-logic/generate-text.md.txt?api=dev#base64) (or use YouTube URLs for videos). - Several changes were introduced for the GA versions of the "Vertex AI in Firebase" SDKs. These same changes are required to use the Firebase AI Logic SDKs. Review the following lists for any changes that you might need to make in your code to accommodate taking up the Firebase AI Logic SDK. ### Required for all languages and platforms - **Function calling** If you implemented this feature before GA, then you'll need to make updates to how you define your schema. We recommend reviewing the updated [function calling guide](https://firebase.google.com/docs/ai-logic/function-calling.md.txt) to learn how to write your function declarations. - **Generating structured output (like JSON) using `responseSchema`** If you implemented this feature before GA, then you'll need to make updates to how you define your schema. We recommend reviewing the new [structured output guide](https://firebase.google.com/docs/ai-logic/generate-structured-output.md.txt) to learn how to write JSON schemas. - **Timeout** - Changed the default timeout for requests to be 180 seconds. ### Required based on platform or language ### Swift - **Enumerations** - Replaced most `enum` types with `struct`s with static variables. This change allows more flexibility for evolving the API in a backward-compatible way. When using `switch` statements, you must now include a `default:` case to cover unknown or unhandled values, including new values that are added to the SDK in the future. - Renamed the `BlockThreshold` enumeration to `HarmBlockThreshold`; this type is now a `struct`. - Removed `unknown` and `unspecified` cases from the following enumerations (now `struct`s): `HarmCategory`, `HarmBlockThreshold`, `HarmProbability`, `BlockReason`, and `FinishReason`. - Replaced the enumeration `ModelContent.Part` with a protocol named `Part` to allow new types to be added in a backward-compatible way. This change is described in greater detail in the **Content parts** section. - **Content parts** - Removed the `ThrowingPartsRepresentable` protocol, and simplified the initializers for `ModelContent` to avoid occasional compiler errors. Images that don't encode properly will still throw errors when being used in `generateContent`. - Replaced the `ModelContent.Part` cases with the following `struct` types conforming to the `Part` protocol: - `.text` to `TextPart` - `.data` to `InlineDataPart` - `.fileData` to `FileDataPart` - `.functionCall` to `FunctionCallPart` - `.functionResponse` to `FunctionResponsePart` - **Harm category** - Changed the `HarmCategory` to no longer be nested in the `SafetySetting` type. If you're referring to it as `SafetySetting.HarmCategory`, that can be replaced with `HarmCategory`. - **Safety feedback** - Removed the `SafetyFeedback` type, since it wasn't used in any of the responses. - **Citation metadata** - Renamed the `citationSources` property to `citations` in `CitationMetadata`. - **Total billable characters** - Changed the `totalBillableCharacters` property in `CountTokensResponse` to be optional to reflect situations where no characters are sent. - **Candidate response** - Renamed `CandidateResponse` to `Candidate` to match other platforms. - **Generation configuration** - Changed the public properties of `GenerationConfig` to `internal`. They all remain configurable in the initializer. ### Kotlin - **Enumerations** - Replaced `enum` classes and `sealed` classes with regular classes. This change allows more flexibility for evolving the API in a backward compatible way. - Renamed the `BlockThreshold` enumeration to `HarmBlockThreshold`. - Removed values from the following enumerations: `HarmBlockThreshold`, `HarmProbability`, `HarmSeverity`, `BlockReason`, and `FinishReason`. - **Blob methods** - Renamed all methods that included `Blob` as part of their name to use `InlineData` instead. - **Safety settings** - Changed the field `method` to be nullable. - **Duration class** - Removed all usages of Kotlin's `Duration` class, and replaced it with `long`. This change provides better interoperability with Java. - **Citation metadata** - Wrapped all the fields previously declared in `CitationMetadata` into a new class called `Citation`. Citations can be found in the list called `citations` in `CitationMetadata`. This change allows better alignment of types across platforms. - **Count tokens** - Changed the field `totalBillableCharacters` to be nullable. - **Total billable characters** - Changed the `totalBillableCharacters` property in `CountTokensResponse` to be optional to reflect situations where no characters are sent. - **Instantiating a model** - Moved the `requestOptions` parameter to the end of the parameter list to align with other platforms. - **Live API** - Removed `UNSPECIFIED` value for enum class `ResponseModality`. Instead use `null`. - Renamed `LiveGenerationConfig.setResponseModalities` to `LiveGenerationConfig.setResponseModality`. - Removed the `LiveContentResponse.Status` class, and instead have nested the status fields as properties of `LiveContentResponse`. - Removed the `LiveContentResponse` class, and instead have provided subclasses of `LiveServerMessage` that match the responses from the model. - Changed `LiveModelFutures.connect` to return `ListenableFuture` instead of `ListenableFuture`. ### Java - **Enumerations** - Replaced `enum` classes and `sealed` classes with regular classes. This change allows more flexibility for evolving the API in a backward compatible way. - Renamed the `BlockThreshold` enumeration to `HarmBlockThreshold`. - Removed values from the following enumerations: `HarmBlockThreshold`, `HarmProbability`, `HarmSeverity`, `BlockReason`, and `FinishReason`. - **Blob methods** - Renamed all methods that included `Blob` as part of their name to use `InlineData` instead. - **Safety settings** - Changed the field `method` to be nullable. - **Duration class** - Removed all usages of Kotlin's `Duration` class, and replaced it with `long`. This change provides better interoperability with Java. - **Citation metadata** - Wrapped all the fields previously declared in `CitationMetadata` into a new class called `Citation`. Citations can be found in the list called `citations` in `CitationMetadata`. This change allows better alignment of types across platforms. - **Count tokens** - Changed the field `totalBillableCharacters` to be nullable. - **Total billable characters** - Changed the `totalBillableCharacters` property in `CountTokensResponse` to be optional to reflect situations where no characters are sent. - **Instantiating a model** - Moved the `requestOptions` parameter to the end of the parameter list to align with other platforms. - **Live API** - Removed `UNSPECIFIED` value for enum class `ResponseModality`. Instead use `null`. - Renamed `LiveGenerationConfig.setResponseModalities` to `LiveGenerationConfig.setResponseModality`. - Removed the `LiveContentResponse.Status` class, and instead have nested the status fields as properties of `LiveContentResponse`. - Removed the `LiveContentResponse` class, and instead have provided subclasses of `LiveServerMessage` that match the responses from the model. - Changed `LiveModelFutures.connect` to return `ListenableFuture` instead of `ListenableFuture`. - Changed various Java builder methods to now correctly return the instance of their class, instead of `void`. ### Web - **Enumerations** - Removed values from the following enumerations: `HarmCategory`, `BlockThreshold`, `HarmProbability`, `HarmSeverity`, `BlockReason`, and `FinishReason`. - **Block reason** - Changed `blockReason` in `PromptFeedback` to be optional. Changes required *only if you're starting to use the Gemini Developer API* (instead of the Agent Platform Gemini API (formerly Vertex AI)): - **Safety settings** - Removed usages of the unsupported `SafetySetting.method`. - **Inline data** - Removed usages of the unsupported `InlineDataPart.videoMetadata`. ### Dart - **Enumerations** - Removed values from the following enumerations: `HarmCategory`, `HarmProbability`, `BlockReason`, and `FinishReason`. - **Data part** - Renamed `DataPart` to `InlineDataPart`, and the `static` `data` function to `inlineData` to align with other platforms. - **Request options** - Removed `RequestOptions` since `timeout` wasn't functional. It will be re-added in the near future, but it will be moved to the `GenerativeModel` type to match other platforms. - **Stop sequences** - Changed the `stopSequences` parameter in `GenerationConfig` to be optional and to default to `null` instead of an empty array. - **Citations** - Renamed the `citationSources` property to `citations` in `CitationMetadata`. The `CitationSource` type was renamed to `Citation` to match other platforms. - **Unnecessary public types, methods, and properties** - Removed the following types, methods, and properties which were unintentionally exposed: `defaultTimeout`, `CountTokensResponseFields`, `parseCountTokensResponse`, `parseEmbedContentResponse`, `parseGenerateContentResponse`, `parseContent`, `BatchEmbedContentsResponse`, `ContentEmbedding`, `EmbedContentRequest`, and `EmbedContentResponse`. - **Count tokens** - Removed extra fields from the `countTokens` function that are no longer necessary. Only `contents` is needed. - **Instantiating a model** - Moved the `systemInstruction` parameter to the end of the parameter list to align with other platforms. - **Embedding functionality** - Removed unsupported embedding functionality (`embedContent` and `batchEmbedContents`) from the model. ### Unity Support for Unity wasn't available from "Vertex AI in Firebase". Learn how to [get started with the Firebase AI Logic SDK for Unity](https://firebase.google.com/docs/ai-logic/get-started.md.txt). ## Possible errors related to migrating As you're migrating to use the GA version of Firebase AI Logic, you might encounter errors if you haven't completed all of the required changes as described in this migration guide. ### 403 Error: `Requests to this API firebasevertexai.googleapis.com ... are blocked.` If you receive a 403 error that says `Requests to this API firebasevertexai.googleapis.com ... are blocked.`, it usually means that the Firebase API key in your Firebase configuration file or object doesn't have a required API in its allowlist for the product that you're trying to use. Make sure that the Firebase API key used by your app has all the [required APIs included in the key's "API restrictions" allowlist](https://firebase.google.com/docs/projects/api-keys.md.txt#faq-required-apis-for-restricted-firebase-api-key). **For Firebase AI Logic, your Firebase API key needs to have at minimum the Firebase AI Logic API in its allowlist.** This API should have been automatically added to your API key's allowlist when you [enabled the required APIs in the Firebase console](https://firebase.google.com/docs/ai-logic/migrate-to-ga#enable-required-apis). You can view all your API keys in the [*APIs \& Services* \> *Credentials*](https://console.cloud.google.com/apis/credentials?project=_) panel in the Google Cloud console. > [!NOTE] > **Note:** Firebase-related APIs use API keys only to *identify* the Firebase project or app, *not for authorization* to call the API (like some other APIs allow). Authorization for Firebase-related APIs is handled separately from the API key, either through Google Cloud IAM permissions, Firebase Security Rules, or Firebase App Check. Learn more about [Firebase API keys](https://firebase.google.com/docs/projects/api-keys.md.txt).
[Give feedback about your experience with Firebase AI Logic](https://firebase.google.com/docs/ai-logic/feedback)