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.agents/skills/firebase-ai-logic-basics/SKILL.md

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+---
+name: firebase-ai-logic-basics
+description: Official skill for integrating Firebase AI Logic (Gemini API) into web applications. Covers setup, multimodal inference, structured output, and security.
+version: 1.0.1
+---
+
+# 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
+
+### 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
+
+> [!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., `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) 
+
+
+> [!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) |
+
+**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)
+[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)
+
+
+

.agents/skills/firebase-ai-logic-basics/references/flutter_setup.md

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+# Flutter Setup for Firebase AI Logic
+
+This guide covers how to integrate Firebase AI Logic (Gemini API) into your Flutter applications.
+
+> [!IMPORTANT]
+> **Foundational Workflows & CLI-First Approach:**
+> 1. **Review Foundation:** Before implementing platform-specific code, ALWAYS review the foundational `firebase-basics` skill to ensure familiarity with core workflows.
+> 2. **Backend Provisioning via CLI:** Use the Firebase CLI for backend setup. Running `npx firebase-tools init ailogic` is MANDATORY to provision the service. `flutterfire configure` does NOT enable the AI service and will result in `PERMISSION_DENIED` if skipped.
+> 3. **Client Configuration:** Use `flutterfire configure` strictly for generating `firebase_options.dart`. Avoid manual Console configuration.
+
+> [!NOTE]
+> `firebase_vertexai` has been replaced by `firebase_ai`. Always use `firebase_ai` for new projects.
+
+## Installation
+
+Add the necessary Firebase dependencies to your `pubspec.yaml`:
+
+```yaml
+dependencies:
+  flutter:
+    sdk: flutter
+  firebase_core: ^4.0.0
+  firebase_auth: ^6.0.0
+  firebase_ai: ^3.0.0
+```
+
+Run `flutter pub get` to install the packages.
+
+## Initialization
+
+Initialize Firebase and sign in (anonymously or via authenticated user) before using AI Logic.
+
+```dart
+import 'package:firebase_core/firebase_core.dart';
+import 'package:firebase_auth/firebase_auth.dart';
+import 'package:firebase_ai/firebase_ai.dart';
+
+void main() async {
+  WidgetsFlutterBinding.ensureInitialized();
+  await Firebase.initializeApp();
+  await FirebaseAuth.instance.signInAnonymously();
+  runApp(const MyApp());
+}
+```
+
+## Usage
+
+Use `FirebaseAI.googleAI` for the **Gemini Developer API**.
+
+> [!IMPORTANT]
+> **Model Selection:** Always use **`gemini-flash-latest`**. DO NOT USE `gemini-1.5-flash`.
+
+> [!IMPORTANT]
+> **Choose the Right API Provider:** Always use `FirebaseAI.googleAI` (Gemini Developer API) as the default for prototyping and standard use. Avoid using the Vertex AI Gemini API unless your application specifically requires enterprise-grade scalability and is configured for the Blaze plan.
+
+### Text Generation
+
+```dart
+import 'package:firebase_ai/firebase_ai.dart';
+import 'package:firebase_auth/firebase_auth.dart';
+
+Future<String> generateText(String prompt) async {
+  final googleAI = FirebaseAI.googleAI(auth: FirebaseAuth.instance);
+
+  // Use the latest Gemini Flash model
+  final model = googleAI.generativeModel(model: 'gemini-flash-latest');
+
+  final response = await model.generateContent([Content.text(prompt)]);
+  return response.text ?? 'No response';
+}
+```
+
+### Chat Session
+
+```dart
+final chat = model.startChat(history: [
+  Content.text('Hello, I am a user.'),
+  Content.model([TextPart('Hello! How can I help you today?')]),
+]);
+
+final response = await chat.sendMessage(Content.text('What is CBT?'));
+```

.agents/skills/firebase-ai-logic-basics/references/ios_setup.md

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+# Firebase AI Logic iOS Setup Guide
+
+## 1. Import and Initialize
+Ensure you have installed the `FirebaseAILogic` SDK via Swift Package Manager.
+
+```swift
+import FirebaseAILogic
+
+// Initialize the Firebase AI service and the generative model.
+let ai = FirebaseAI.firebaseAI()
+
+// Specify a model that's appropriate for your use case.
+let model = ai.generativeModel(modelName: "gemini-flash-latest")
+```
+
+## 2. SwiftUI Integration (Best Practices)
+Use the `@Observable` pattern to manage AI state and provide a smooth UX with loading indicators and error handling.
+
+> **⛔️ CRITICAL WARNING:** Do NOT initialize the model inline as a class property if there's any chance the view model is instantiated before `FirebaseApp.configure()` executes in the app root. 
+> To be safe, initialize the model lazily or pass it in from a point in the hierarchy where Firebase is guaranteed to be configured.
+
+```swift
+import SwiftUI
+import FirebaseAILogic
+
+@MainActor
+@Observable
+final class AIViewModel {
+    // Initialize lazily to ensure FirebaseApp is configured first
+    private lazy var model = FirebaseAI.firebaseAI().generativeModel(modelName: "gemini-flash-latest")
+
+    var responseText: String = ""
+    var isFetching: Bool = false
+    var errorMessage: String?
+
+    func generate(prompt: String) async {
+        isFetching = true
+        errorMessage = nil
+        defer { isFetching = false }
+
+        do {
+            let response = try await model.generateContent(prompt)
+            self.responseText = response.text ?? "No response"
+        } catch {
+            self.errorMessage = error.localizedDescription
+        }
+    }
+}
+
+struct AIView: View {
+    @State private var viewModel = AIViewModel()
+    @State private var prompt = "Write a story about a magic backpack."
+
+    var body: some View {
+        VStack {
+            TextField("Enter prompt", text: $prompt)
+
+            Button("Generate") {
+                Task { await viewModel.generate(prompt: prompt) }
+            }
+            .disabled(viewModel.isFetching)
+
+            if viewModel.isFetching {
+                ProgressView()
+            } else if let error = viewModel.errorMessage {
+                Text(error).foregroundStyle(.red)
+            } else {
+                ScrollView {
+                    Text(viewModel.responseText)
+                }
+            }
+        }
+        .padding()
+    }
+}
+```
+
+## 3. Safety Settings
+You can configure safety thresholds to prevent the model from generating harmful content.
+
+```swift
+let safetySettings = [
+  SafetySetting(category: .harassment, threshold: .blockLowAndAbove),
+  SafetySetting(category: .hateSpeech, threshold: .blockMediumAndAbove)
+]
+
+let model = FirebaseAI.firebaseAI().generativeModel(
+  modelName: "gemini-flash-latest",
+  safetySettings: safetySettings
+)
+```
+
+# Advanced Features
+
+### Chat Session (Multi-turn)
+Chat sessions persist state across multiple interactions, which is essential for ongoing conversations or when using tools like function calling.
+
+```swift
+let chat = model.startChat()
+
+Task {
+    do {
+        let response1 = try await chat.sendMessage("Hello! I have two dogs in my house.")
+        print(response1.text ?? "")
+
+        let response2 = try await chat.sendMessage("How many paws are in my house?")
+        print(response2.text ?? "")
+    } catch {
+        print("Error in chat: \(error)")
+    }
+}
+```
+
+### Function Calling (Tools)
+Define functions that the model can request to execute to interact with external systems. *Note: Advanced workflows like function calling generally require a multi-turn Chat Session to handle the back-and-forth execution.*
+
+```swift
+let getStockPriceTool = Tool(functionDeclarations: [
+  FunctionDeclaration(
+    name: "getStockPrice",
+    description: "Get the current stock price for a given symbol.",
+    parameters: [
+      "symbol": Schema(
+        type: .string,
+        description: "The stock symbol, e.g. AAPL"
+      )
+    ]
+  )
+])
+
+let model = FirebaseAI.firebaseAI().generativeModel(
+  modelName: "gemini-flash-latest",
+  tools: [getStockPriceTool]
+)
+
+// In your task (using a chat session):
+let chat = model.startChat()
+let response = try await chat.sendMessage("What is the stock price of Apple?")
+if let functionCall = response.functionCalls.first {
+    // Handle the function call (e.g. call a local API and send the result back)
+    print("Model requested function: \(functionCall.name) with args: \(functionCall.args)")
+}
+```