使用 Gemini API 构建多轮对话（聊天）

 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-2.5-flash") // Optionally specify existing chat history let history = [  ModelContent(role: "user", parts: "Hello, I have 2 dogs in my house."),  ModelContent(role: "model", parts: "Great to meet you. What would you like to know?"), ] // Initialize the chat with optional chat history let chat = model.startChat(history: history) // To generate text output, call sendMessage and pass in the message let response = try await chat.sendMessage("How many paws are in my house?") 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") // Initialize the chat val chat = model.startChat(  history = listOf(  content(role = "user") { text("Hello, I have 2 dogs in my house.") },  content(role = "model") { text("Great to meet you. What would you like to know?") }  ) ) val response = chat.sendMessage("How many paws are in my house?") 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); // (optional) Create previous chat history for context Content.Builder userContentBuilder = new Content.Builder(); userContentBuilder.setRole("user"); userContentBuilder.addText("Hello, I have 2 dogs in my house."); Content userContent = userContentBuilder.build(); Content.Builder modelContentBuilder = new Content.Builder(); modelContentBuilder.setRole("model"); modelContentBuilder.addText("Great to meet you. What would you like to know?"); Content modelContent = userContentBuilder.build(); List<Content> history = Arrays.asList(userContent, modelContent); // Initialize the chat ChatFutures chat = model.startChat(history); // Create a new user message Content.Builder messageBuilder = new Content.Builder(); messageBuilder.setRole("user"); messageBuilder.addText("How many paws are in my house?"); Content message = messageBuilder.build(); // Send the message ListenableFuture<GenerateContentResponse> response = chat.sendMessage(message); 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" }); async function run() {  const chat = model.startChat({  history: [  {  role: "user",  parts: [{ text: "Hello, I have 2 dogs in my house." }],  },  {  role: "model",  parts: [{ text: "Great to meet you. What would you like to know?" }],  },  ],  generationConfig: {  maxOutputTokens: 100,  },  });  const msg = "How many paws are in my house?";  const result = await chat.sendMessage(msg);  const text = result.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'); final chat = model.startChat(); // Provide a prompt that contains text final prompt = [Content.text('Write a story about a magic backpack.')]; final response = await chat.sendMessage(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"); // Optionally specify existing chat history var history = new [] {  ModelContent.Text("Hello, I have 2 dogs in my house."),  new ModelContent("model", new ModelContent.TextPart("Great to meet you. What would you like to know?")), }; // Initialize the chat with optional chat history var chat = model.StartChat(history); // To generate text output, call SendMessageAsync and pass in the message var response = await chat.SendMessageAsync("How many paws are in my house?"); UnityEngine.Debug.Log(response.Text ?? "No text in response."); 

 import FirebaseAILogic // Initialize the Gemini Developer API backend service // Create a `GenerativeModel` instance with a Gemini model that supports image output let generativeModel = FirebaseAI.firebaseAI(backend: .googleAI()).generativeModel(  modelName: "gemini-2.5-flash-image",  // Configure the model to respond with text and images (required)  generationConfig: GenerationConfig(responseModalities: [.text, .image]) ) // Initialize the chat let chat = model.startChat() guard let image = UIImage(named: "scones") else { fatalError("Image file not found.") } // Provide an initial text prompt instructing the model to edit the image let prompt = "Edit this image to make it look like a cartoon" // To generate an initial response, send a user message with the image and text prompt let response = try await chat.sendMessage(image, prompt) // Inspect the generated image guard let inlineDataPart = response.inlineDataParts.first else {  fatalError("No image data in response.") } guard let uiImage = UIImage(data: inlineDataPart.data) else {  fatalError("Failed to convert data to UIImage.") } // Follow up requests do not need to specify the image again let followUpResponse = try await chat.sendMessage("But make it old-school line drawing style") // Inspect the edited image after the follow up request guard let followUpInlineDataPart = followUpResponse.inlineDataParts.first else {  fatalError("No image data in response.") } guard let followUpUIImage = UIImage(data: followUpInlineDataPart.data) else {  fatalError("Failed to convert data to UIImage.") } 

 // Initialize the Gemini Developer API backend service // Create a `GenerativeModel` instance with a Gemini model that supports image output val model = Firebase.ai(backend = GenerativeBackend.googleAI()).generativeModel(  modelName = "gemini-2.5-flash-image",  // Configure the model to respond with text and images (required)  generationConfig = generationConfig { responseModalities = listOf(ResponseModality.TEXT, ResponseModality.IMAGE) } ) // Provide an image for the model to edit val bitmap = BitmapFactory.decodeResource(context.resources, R.drawable.scones) // Create the initial prompt instructing the model to edit the image val prompt = content {  image(bitmap)  text("Edit this image to make it look like a cartoon") } // Initialize the chat val chat = model.startChat() // To generate an initial response, send a user message with the image and text prompt var response = chat.sendMessage(prompt) // Inspect the returned image var generatedImageAsBitmap = response  .candidates.first().content.parts.filterIsInstance<ImagePart>().firstOrNull()?.image // Follow up requests do not need to specify the image again response = chat.sendMessage("But make it old-school line drawing style") generatedImageAsBitmap = response  .candidates.first().content.parts.filterIsInstance<ImagePart>().firstOrNull()?.image 

 // Initialize the Gemini Developer API backend service // Create a `GenerativeModel` instance with a Gemini model that supports image output GenerativeModel ai = FirebaseAI.getInstance(GenerativeBackend.googleAI()).generativeModel(  "gemini-2.5-flash-image",  // Configure the model to respond with text and images (required)  new GenerationConfig.Builder()  .setResponseModalities(Arrays.asList(ResponseModality.TEXT, ResponseModality.IMAGE))  .build() ); GenerativeModelFutures model = GenerativeModelFutures.from(ai); // Provide an image for the model to edit Bitmap bitmap = BitmapFactory.decodeResource(resources, R.drawable.scones); // Initialize the chat ChatFutures chat = model.startChat(); // Create the initial prompt instructing the model to edit the image Content prompt = new Content.Builder()  .setRole("user")  .addImage(bitmap)  .addText("Edit this image to make it look like a cartoon")  .build(); // To generate an initial response, send a user message with the image and text prompt ListenableFuture<GenerateContentResponse> response = chat.sendMessage(prompt); // Extract the image from the initial response ListenableFuture<@Nullable Bitmap> initialRequest = Futures.transform(response, result -> {  for (Part part : result.getCandidates().get(0).getContent().getParts()) {  if (part instanceof ImagePart) {  ImagePart imagePart = (ImagePart) part;  return imagePart.getImage();  }  }  return null; }, executor); // Follow up requests do not need to specify the image again ListenableFuture<GenerateContentResponse> modelResponseFuture = Futures.transformAsync(  initialRequest,  generatedImage -> {  Content followUpPrompt = new Content.Builder()  .addText("But make it old-school line drawing style")  .build();  return chat.sendMessage(followUpPrompt);  },  executor); // Add a final callback to check the reworked image Futures.addCallback(modelResponseFuture, new FutureCallback<GenerateContentResponse>() {  @Override  public void onSuccess(GenerateContentResponse result) {  for (Part part : result.getCandidates().get(0).getContent().getParts()) {  if (part instanceof ImagePart) {  ImagePart imagePart = (ImagePart) part;  Bitmap generatedImageAsBitmap = imagePart.getImage();  break;  }  }  }  @Override  public void onFailure(Throwable t) {  t.printStackTrace();  } }, executor); 

 import { initializeApp } from "firebase/app"; import { getAI, getGenerativeModel, GoogleAIBackend, ResponseModality } 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-image",  // Configure the model to respond with text and images (required)  generationConfig: {  responseModalities: [ResponseModality.TEXT, ResponseModality.IMAGE],  }, }); // Prepare an image for the model to edit async function fileToGenerativePart(file) {  const base64EncodedDataPromise = new Promise((resolve) => {  const reader = new FileReader();  reader.onloadend = () => resolve(reader.result.split(',')[1]);  reader.readAsDataURL(file);  });  return {  inlineData: { data: await base64EncodedDataPromise, mimeType: file.type },  }; } const fileInputEl = document.querySelector("input[type=file]"); const imagePart = await fileToGenerativePart(fileInputEl.files[0]); // Provide an initial text prompt instructing the model to edit the image const prompt = "Edit this image to make it look like a cartoon"; // Initialize the chat const chat = model.startChat(); // To generate an initial response, send a user message with the image and text prompt const result = await chat.sendMessage([prompt, imagePart]); // Request and inspect the generated image try {  const inlineDataParts = result.response.inlineDataParts();  if (inlineDataParts?.[0]) {  // Inspect the generated image  const image = inlineDataParts[0].inlineData;  console.log(image.mimeType, image.data);  } } catch (err) {  console.error('Prompt or candidate was blocked:', err); } // Follow up requests do not need to specify the image again const followUpResult = await chat.sendMessage("But make it old-school line drawing style"); // Request and inspect the returned image try {  const followUpInlineDataParts = followUpResult.response.inlineDataParts();  if (followUpInlineDataParts?.[0]) {  // Inspect the generated image  const followUpImage = followUpInlineDataParts[0].inlineData;  console.log(followUpImage.mimeType, followUpImage.data);  } } catch (err) {  console.error('Prompt or candidate was blocked:', err); } 

 import 'package:firebase_ai/firebase_ai.dart'; import 'package:firebase_core/firebase_core.dart'; import 'firebase_options.dart'; await Firebase.initializeApp(  options: DefaultFirebaseOptions.currentPlatform, ); // Initialize the Gemini Developer API backend service // Create a `GenerativeModel` instance with a Gemini model that supports image output final model = FirebaseAI.googleAI().generativeModel(  model: 'gemini-2.5-flash-image',  // Configure the model to respond with text and images (required)  generationConfig: GenerationConfig(responseModalities: [ResponseModalities.text, ResponseModalities.image]), ); // Prepare an image for the model to edit final image = await File('scones.jpg').readAsBytes(); final imagePart = InlineDataPart('image/jpeg', image); // Provide an initial text prompt instructing the model to edit the image final prompt = TextPart("Edit this image to make it look like a cartoon"); // Initialize the chat final chat = model.startChat(); // To generate an initial response, send a user message with the image and text prompt final response = await chat.sendMessage([  Content.multi([prompt,imagePart]) ]); // Inspect the returned image if (response.inlineDataParts.isNotEmpty) {  final imageBytes = response.inlineDataParts[0].bytes;  // Process the image } else {  // Handle the case where no images were generated  print('Error: No images were generated.'); } // Follow up requests do not need to specify the image again final followUpResponse = await chat.sendMessage([  Content.text("But make it old-school line drawing style") ]); // Inspect the returned image if (followUpResponse.inlineDataParts.isNotEmpty) {  final followUpImageBytes = response.inlineDataParts[0].bytes;  // Process the image } else {  // Handle the case where no images were generated  print('Error: No images were generated.'); } 

 using Firebase; using Firebase.AI; // Initialize the Gemini Developer API backend service // Create a `GenerativeModel` instance with a Gemini model that supports image output var model = FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI()).GetGenerativeModel(  modelName: "gemini-2.5-flash-image",  // Configure the model to respond with text and images (required)  generationConfig: new GenerationConfig(  responseModalities: new[] { ResponseModality.Text, ResponseModality.Image }) ); // Prepare an image for the model to edit var imageFile = System.IO.File.ReadAllBytes(System.IO.Path.Combine(  UnityEngine.Application.streamingAssetsPath, "scones.jpg")); var image = ModelContent.InlineData("image/jpeg", imageFile); // Provide an initial text prompt instructing the model to edit the image var prompt = ModelContent.Text("Edit this image to make it look like a cartoon."); // Initialize the chat var chat = model.StartChat(); // To generate an initial response, send a user message with the image and text prompt var response = await chat.SendMessageAsync(new [] { prompt, image }); // Inspect the returned image var imageParts = response.Candidates.First().Content.Parts  .OfType<ModelContent.InlineDataPart>()  .Where(part => part.MimeType == "image/png"); // Load the image into a Unity Texture2D object UnityEngine.Texture2D texture2D = new(2, 2); if (texture2D.LoadImage(imageParts.First().Data.ToArray())) {  // Do something with the image } // Follow up requests do not need to specify the image again var followUpResponse = await chat.SendMessageAsync("But make it old-school line drawing style"); // Inspect the returned image var followUpImageParts = followUpResponse.Candidates.First().Content.Parts  .OfType<ModelContent.InlineDataPart>()  .Where(part => part.MimeType == "image/png"); // Load the image into a Unity Texture2D object UnityEngine.Texture2D followUpTexture2D = new(2, 2); if (followUpTexture2D.LoadImage(followUpImageParts.First().Data.ToArray())) {  // Do something with the image }