เริ่มต้นใช้งาน Gemini API โดยใช้ Firebase AI Logic SDK

dependencies {   // ... other androidx dependencies    // Import the BoM for the Firebase platform   implementation(platform("com.google.firebase:firebase-bom:34.1.0"))    // 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") }

dependencies {   // ... other androidx dependencies    // Import the BoM for the Firebase platform   implementation(platform("com.google.firebase:firebase-bom:34.1.0"))    // 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")    // Required for one-shot operations (to use `ListenableFuture` from Guava Android)   implementation("com.google.guava:guava:31.0.1-android")    // Required for streaming operations (to use `Publisher` from Reactive Streams)   implementation("org.reactivestreams:reactive-streams:1.0.4") }

 import FirebaseAI  // 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-2.5-flash")  

 // 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-2.5-flash")  

 // 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-2.5-flash");  // Use the GenerativeModelFutures Java compatibility layer which offers // support for ListenableFuture and Publisher APIs GenerativeModelFutures model = GenerativeModelFutures.from(ai);  

 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-2.5-flash" });  

 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-2.5-flash');  

 using Firebase; using Firebase.AI;  // Initialize the Gemini Developer API backend service var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());  // Create a `GenerativeModel` instance with a model that supports your use case var model = ai.GetGenerativeModel(modelName: "gemini-2.5-flash");  

 import FirebaseAI  // 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-2.5-flash")  // Provide a prompt that contains text let prompt = "Write a story about a magic backpack."  // To generate text output, call generateContent with the text input let response = try await model.generateContent(prompt) print(response.text ?? "No text in response.") 

 // 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-2.5-flash")  // Provide a prompt that contains text val prompt = "Write a story about a magic backpack."  // To generate text output, call generateContent with the text input val response = generativeModel.generateContent(prompt) print(response.text) 

 // 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-2.5-flash");  // Use the GenerativeModelFutures Java compatibility layer which offers // support for ListenableFuture and Publisher APIs GenerativeModelFutures model = GenerativeModelFutures.from(ai);  // Provide a prompt that contains text Content prompt = new Content.Builder()     .addText("Write a story about a magic backpack.")     .build();  // To generate text output, call generateContent with the text input ListenableFuture<GenerateContentResponse> response = model.generateContent(prompt); Futures.addCallback(response, new FutureCallback<GenerateContentResponse>() {     @Override     public void onSuccess(GenerateContentResponse result) {         String resultText = result.getText();         System.out.println(resultText);     }      @Override     public void onFailure(Throwable t) {         t.printStackTrace();     } }, executor); 

 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-2.5-flash" });  // Wrap in an async function so you can use await async function run() {   // Provide a prompt that contains text   const prompt = "Write a story about a magic backpack."    // To generate text output, call generateContent with the text input   const result = await model.generateContent(prompt);    const response = result.response;   const text = response.text();   console.log(text); }  run(); 

 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-2.5-flash');  // Provide a prompt that contains text final prompt = [Content.text('Write a story about a magic backpack.')];  // To generate text output, call generateContent with the text input final response = await model.generateContent(prompt); print(response.text); 

 using Firebase; using Firebase.AI;  // Initialize the Gemini Developer API backend service var ai = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());  // Create a `GenerativeModel` instance with a model that supports your use case var model = ai.GetGenerativeModel(modelName: "gemini-2.5-flash");  // Provide a prompt that contains text var prompt = "Write a story about a magic backpack.";  // To generate text output, call GenerateContentAsync with the text input var response = await model.GenerateContentAsync(prompt); UnityEngine.Debug.Log(response.Text ?? "No text in response.");