<br />

You can ask a Gemini model to generate text from a text-only prompt or
a multimodal prompt. When you use Firebase AI Logic, you can make this
request directly from your app.

Multimodal prompts can include multiple types of input
(like text along with images, PDFs, plain-text files, audio, and video).

This guide shows how to generate text from a text-only prompt and from a basic
multimodal prompt that includes a file.

[arrow_downward Jump to code for text-only input](https://firebase.google.com/docs/ai-logic/generate-text#text-in-text-out)
[arrow_downward Jump to code for multimodal input](https://firebase.google.com/docs/ai-logic/generate-text#base64)
[arrow_downward Jump to code for streamed responses](https://firebase.google.com/docs/ai-logic/generate-text#streaming)

<br />

|---|
| **See other guides for additional options for working with text** [Generate structured output](https://firebase.google.com/docs/ai-logic/generate-structured-output) [Multi-turn chat](https://firebase.google.com/docs/ai-logic/chat) [Bidirectional streaming](https://firebase.google.com/docs/ai-logic/live-api) [Generate text on-device](https://firebase.google.com/docs/ai-logic/hybrid-and-on-device-inference) [Generate images from text](https://firebase.google.com/docs/ai-logic/generate-images-imagen) |

## Before you begin


|---|
| *Click your Gemini API provider to view provider-specific content and code on this page.* Gemini Developer API Vertex AI Gemini API |

<br />

If you haven't already, complete the
[getting started guide](https://firebase.google.com/docs/ai-logic/get-started), which describes how to
set up your Firebase project, connect your app to Firebase, add the SDK,
initialize the backend service for your chosen Gemini API provider, and
create a `GenerativeModel` instance.


| All our docs assume that you're using the [](https://firebase.google.com/support/releases)latest versions of the Firebase AI Logic SDKs.

<br />

For testing and iterating on your prompts, we recommend using [Google AI Studio](https://aistudio.google.com).

## Generate text from text-only input


|---|
| *Before trying this sample, complete the [Before you begin](https://firebase.google.com/docs/ai-logic/generate-text#before-you-begin) section of this guide to set up your project and app. **In that section, you'll also click a button for your chosen Gemini API provider so that you see provider-specific content on this page**.* |

<br />

You can ask a Gemini model to generate text by prompting with text-only
input.  

### Swift

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/swift/firebaseailogic/api/reference/Classes/GenerativeModel#generatecontent_:_1)
to generate text from text-only input.  


    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")


    // 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.")

### Kotlin

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/kotlin/com/google/firebase/ai/GenerativeModel#generateContent(kotlin.String))
to generate text from text-only input.
^*For Kotlin, the methods in this SDK are suspend functions and need to be called
from a [Coroutine scope](https://developer.android.com/kotlin/coroutines).*^  


    // 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 = model.generateContent(prompt)
    print(response.text)

### Java

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/android/com/google/firebase/ai/GenerativeModel#generateContent(kotlin.String))
to generate text from text-only input.
^*For Java, the methods in this SDK return a
[`ListenableFuture`](https://developer.android.com/guide/background/asynchronous/listenablefuture).*^  


    // 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);

### Web

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/js/ai.generativemodel#generativemodelgeneratecontent)
to generate text from text-only input.  


    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();

### Dart

You can call
[`generateContent()`](https://pub.dev/documentation/firebase_ai/latest/firebase_ai/GenerativeModel/generateContent.html)
to generate text from text-only input.  


    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);

### Unity

You can call
[`GenerateContentAsync()`](https://firebase.google.com/docs/reference/unity/class/firebase/a-i/generative-model#generatecontentasync)
to generate text from text-only input.  


    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.");


Learn how to choose a [model](https://firebase.google.com/docs/ai-logic/models)

appropriate for your use case and app.

## Generate text from text-and-file (multimodal) input


|---|
| *Before trying this sample, complete the [Before you begin](https://firebase.google.com/docs/ai-logic/generate-text#before-you-begin) section of this guide to set up your project and app. **In that section, you'll also click a button for your chosen Gemini API provider so that you see provider-specific content on this page**.* |

<br />

You can ask a Gemini model to
generate text by prompting with text and a file---providing each
input file's `mimeType` and the file itself. Find
[requirements and recommendations for input files](https://firebase.google.com/docs/ai-logic/generate-text#requirements-recommendations-for-input)
later on this page.

The following example shows the basics of how to generate text from a file input
by analyzing a single video file provided as inline data (base64-encoded file).
Note that this example shows providing the file inline, but the SDKs also support [providing a YouTube URL](https://firebase.google.com/docs/ai-logic/input-file-requirements).

<br />

Need a sample video file?

<br />

> You can use this publicly available file with a MIME type of `video/mp4`
> ([view or download file](https://storage.googleapis.com/cloud-samples-data/video/animals.mp4)).
> `https://storage.googleapis.com/cloud-samples-data/video/animals.mp4`

<br />

<br />


| **Important** : **The total request size limit is
| 20 MB.** To send large files, review the [options for providing files in multimodal requests](https://firebase.google.com/docs/ai-logic/input-file-requirements).

<br />

### Swift

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/swift/firebaseailogic/api/reference/Classes/GenerativeModel#generatecontent_:)
to generate text from multimodal input of text and video files.  


    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")


    // Provide the video as \`Data\` with the appropriate MIME type.
    let video = InlineDataPart(data: try Data(contentsOf: videoURL), mimeType: "video/mp4")
    // Provide a text prompt to include with the video
    let prompt = "What is in the video?"
    // To generate text output, call generateContent with the text and video
    let response = try await model.generateContent(video, prompt)
    print(response.text ?? "No text in response.")

### Kotlin

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/kotlin/com/google/firebase/ai/GenerativeModel#generateContent(kotlin.Array))
to generate text from multimodal input of text and video files.
^*For Kotlin, the methods in this SDK are suspend functions and need to be called
from a [Coroutine scope](https://developer.android.com/kotlin/coroutines).*^  


    // 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")


    val contentResolver = applicationContext.contentResolver
    contentResolver.openInputStream(videoUri).use { stream -\>
    stream?.let {
    val bytes = stream.readBytes()
    // Provide a prompt that includes the video specified above and text
    val prompt = content {
    inlineData(bytes, "video/mp4")
    text("What is in the video?")
    }
    // To generate text output, call generateContent with the prompt
    val response = model.generateContent(prompt)
    Log.d(TAG, response.text ?: "")
    }
    }

### Java

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/android/com/google/firebase/ai/GenerativeModel#generateContent(kotlin.Array))
to generate text from multimodal input of text and video files.
^*For Java, the methods in this SDK return a
[`ListenableFuture`](https://developer.android.com/guide/background/asynchronous/listenablefuture).*^  


    // 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);


    ContentResolver resolver = getApplicationContext().getContentResolver();
    try (InputStream stream = resolver.openInputStream(videoUri)) {
    File videoFile = new File(new URI(videoUri.toString()));
    int videoSize = (int) videoFile.length();
    byte\[\] videoBytes = new byte\[videoSize\];
    if (stream != null) {
    stream.read(videoBytes, 0, videoBytes.length);
    stream.close();
    // Provide a prompt that includes the video specified above and text
    Content prompt = new Content.Builder()
    .addInlineData(videoBytes, "video/mp4")
    .addText("What is in the video?")
    .build();
    // To generate text output, call generateContent with the prompt
    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);
    }
    } catch (IOException e) {
    e.printStackTrace();
    } catch (URISyntaxException e) {
    e.printStackTrace();
    }

### Web

You can call
[`generateContent()`](https://firebase.google.com/docs/reference/js/ai.generativemodel#generativemodelgeneratecontent)
to generate text from multimodal input of text and video files.  


    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" });


    // Converts a File object to a Part object.
    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 },
    };
    }
    async function run() {
    // Provide a text prompt to include with the video
    const prompt = "What do you see?";
    const fileInputEl = document.querySelector("input\[type=file\]");
    const videoPart = await fileToGenerativePart(fileInputEl.files\[0\]);
    // To generate text output, call generateContent with the text and video
    const result = await model.generateContent(\[prompt, videoPart\]);
    const response = result.response;
    const text = response.text();
    console.log(text);
    }
    run();

### Dart

You can call
[`generateContent()`](https://pub.dev/documentation/firebase_ai/latest/firebase_ai/GenerativeModel/generateContent.html)
to generate text from multimodal input of text and video files.  


    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 text prompt to include with the video
    final prompt = TextPart("What's in the video?");
    // Prepare video for input
    final video = await File('video0.mp4').readAsBytes();
    // Provide the video as \`Data\` with the appropriate mimetype
    final videoPart = InlineDataPart('video/mp4', video);
    // To generate text output, call generateContent with the text and images
    final response = await model.generateContent(\[
    Content.multi(\[prompt, ...videoPart\])
    \]);
    print(response.text);

### Unity

You can call
[`GenerateContentAsync()`](https://firebase.google.com/docs/reference/unity/class/firebase/a-i/generative-model#generatecontentasync)
to generate text from multimodal input of text and video files.  


    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 the video as \`data\` with the appropriate MIME type.
    var video = ModelContent.InlineData("video/mp4",
    System.IO.File.ReadAllBytes(System.IO.Path.Combine(
    UnityEngine.Application.streamingAssetsPath, "yourVideo.mp4")));
    // Provide a text prompt to include with the video
    var prompt = ModelContent.Text("What is in the video?");
    // To generate text output, call GenerateContentAsync with the text and video
    var response = await model.GenerateContentAsync(new \[\] { video, prompt });
    UnityEngine.Debug.Log(response.Text ?? "No text in response.");


Learn how to choose a [model](https://firebase.google.com/docs/ai-logic/models)

appropriate for your use case and app.

## Stream the response


|---|
| *Before trying this sample, complete the [Before you begin](https://firebase.google.com/docs/ai-logic/generate-text#before-you-begin) section of this guide to set up your project and app. **In that section, you'll also click a button for your chosen Gemini API provider so that you see provider-specific content on this page**.* |

<br />

You can achieve faster interactions by not waiting for the entire result from
the model generation, and instead use streaming to handle partial results.
To stream the response, call `generateContentStream`.

<br />

#### View example: Stream generated text from text-only input

<br />

### Swift

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/swift/firebaseailogic/api/reference/Classes/GenerativeModel#generatecontentstream_:_1)
to stream generated text from text-only input.  


    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")


    // Provide a prompt that contains text
    let prompt = "Write a story about a magic backpack."
    // To stream generated text output, call generateContentStream with the text input
    let contentStream = try model.generateContentStream(prompt)
    for try await chunk in contentStream {
    if let text = chunk.text {
    print(text)
    }
    }

### Kotlin

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/kotlin/com/google/firebase/ai/GenerativeModel#generateContentStream(kotlin.String))
to stream generated text from text-only input.
^*For Kotlin, the methods in this SDK are suspend functions and need to be called
from a [Coroutine scope](https://developer.android.com/kotlin/coroutines).*^  


    // 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 includes only text
    val prompt = "Write a story about a magic backpack."
    // To stream generated text output, call generateContentStream and pass in the prompt
    var response = ""
    model.generateContentStream(prompt).collect { chunk -\>
    print(chunk.text)
    response += chunk.text
    }

### Java

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/android/com/google/firebase/ai/GenerativeModel#generateContentStream(kotlin.String))
to stream generated text from text-only input.
^*For Java, the streaming methods in this SDK return a
`Publisher` type from the [Reactive Streams library](https://www.reactive-streams.org/).*^  


    // 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 stream generated text output, call generateContentStream with the text input
    Publisher\<GenerateContentResponse\> streamingResponse =
    model.generateContentStream(prompt);
    // Subscribe to partial results from the response
    final String\[\] fullResponse = {""};
    streamingResponse.subscribe(new Subscriber\<GenerateContentResponse\>() {
    @Override
    public void onNext(GenerateContentResponse generateContentResponse) {
    String chunk = generateContentResponse.getText();
    fullResponse\[0\] += chunk;
    }
    @Override
    public void onComplete() {
    System.out.println(fullResponse\[0\]);
    }
    @Override
    public void onError(Throwable t) {
    t.printStackTrace();
    }
    @Override
    public void onSubscribe(Subscription s) { }
    });

### Web

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/js/ai.generativemodel#generativemodelgeneratecontent)
to stream generated text from text-only input.  


    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 stream generated text output, call generateContentStream with the text input
    const result = await model.generateContentStream(prompt);
    for await (const chunk of result.stream) {
    const chunkText = chunk.text();
    console.log(chunkText);
    }
    console.log('aggregated response: ', await result.response);
    }
    run();

### Dart

You can call
[`generateContentStream()`](https://pub.dev/documentation/firebase_ai/latest/firebase_ai/GenerativeModel/generateContentStream.html)
to stream generated text from text-only input.  


    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 stream generated text output, call generateContentStream with the text input
    final response = model.generateContentStream(prompt);
    await for (final chunk in response) {
    print(chunk.text);
    }

### Unity

You can call
[`GenerateContentStreamAsync()`](https://firebase.google.com/docs/reference/unity/class/firebase/a-i/generative-model#generatecontentstreamasync)
to stream generated text from text-only input.  


    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 stream generated text output, call GenerateContentStreamAsync with the text input
    var responseStream = model.GenerateContentStreamAsync(prompt);
    await foreach (var response in responseStream) {
    if (!string.IsNullOrWhiteSpace(response.Text)) {
    UnityEngine.Debug.Log(response.Text);
    }
    }


Learn how to choose a [model](https://firebase.google.com/docs/ai-logic/models)

appropriate for your use case and app.

<br />

<br />

<br />

#### View example: Stream generated text from multimodal input

<br />

### Swift

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/swift/firebaseailogic/api/reference/Classes/GenerativeModel#generatecontentstream_:)
to stream generated text from multimodal input of text and a single video.  


    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")


    // Provide the video as \`Data\` with the appropriate MIME type
    let video = InlineDataPart(data: try Data(contentsOf: videoURL), mimeType: "video/mp4")
    // Provide a text prompt to include with the video
    let prompt = "What is in the video?"
    // To stream generated text output, call generateContentStream with the text and video
    let contentStream = try model.generateContentStream(video, prompt)
    for try await chunk in contentStream {
    if let text = chunk.text {
    print(text)
    }
    }

### Kotlin

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/kotlin/com/google/firebase/ai/GenerativeModel#generateContentStream(kotlin.Array))
to stream generated text from multimodal input of text and a single video.
^*For Kotlin, the methods in this SDK are suspend functions and need to be called
from a [Coroutine scope](https://developer.android.com/kotlin/coroutines).*^  


    // 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")


    val contentResolver = applicationContext.contentResolver
    contentResolver.openInputStream(videoUri).use { stream -\>
    stream?.let {
    val bytes = stream.readBytes()
    // Provide a prompt that includes the video specified above and text
    val prompt = content {
    inlineData(bytes, "video/mp4")
    text("What is in the video?")
    }
    // To stream generated text output, call generateContentStream with the prompt
    var fullResponse = ""
    model.generateContentStream(prompt).collect { chunk -\>
    Log.d(TAG, chunk.text ?: "")
    fullResponse += chunk.text
    }
    }
    }

### Java

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/android/com/google/firebase/ai/GenerativeModel#generateContentStream(kotlin.Array))
to stream generated text from multimodal input of text and a single video.
^*For Java, the streaming methods in this SDK return a
`Publisher` type from the [Reactive Streams library](https://www.reactive-streams.org/).*^  


    // 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);


    ContentResolver resolver = getApplicationContext().getContentResolver();
    try (InputStream stream = resolver.openInputStream(videoUri)) {
    File videoFile = new File(new URI(videoUri.toString()));
    int videoSize = (int) videoFile.length();
    byte\[\] videoBytes = new byte\[videoSize\];
    if (stream != null) {
    stream.read(videoBytes, 0, videoBytes.length);
    stream.close();
    // Provide a prompt that includes the video specified above and text
    Content prompt = new Content.Builder()
    .addInlineData(videoBytes, "video/mp4")
    .addText("What is in the video?")
    .build();
    // To stream generated text output, call generateContentStream with the prompt
    Publisher\<GenerateContentResponse\> streamingResponse =
    model.generateContentStream(prompt);
    final String\[\] fullResponse = {""};
    streamingResponse.subscribe(new Subscriber\<GenerateContentResponse\>() {
    @Override
    public void onNext(GenerateContentResponse generateContentResponse) {
    String chunk = generateContentResponse.getText();
    fullResponse\[0\] += chunk;
    }
    @Override
    public void onComplete() {
    System.out.println(fullResponse\[0\]);
    }
    @Override
    public void onError(Throwable t) {
    t.printStackTrace();
    }
    @Override
    public void onSubscribe(Subscription s) {
    }
    });
    }
    } catch (IOException e) {
    e.printStackTrace();
    } catch (URISyntaxException e) {
    e.printStackTrace();
    }

### Web

You can call
[`generateContentStream()`](https://firebase.google.com/docs/reference/js/ai.generativemodel#generativemodelgeneratecontentstream)
to stream generated text from multimodal input of text and a single video.  


    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" });


    // Converts a File object to a Part object.
    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 },
    };
    }
    async function run() {
    // Provide a text prompt to include with the video
    const prompt = "What do you see?";
    const fileInputEl = document.querySelector("input\[type=file\]");
    const videoPart = await fileToGenerativePart(fileInputEl.files\[0\]);
    // To stream generated text output, call generateContentStream with the text and video
    const result = await model.generateContentStream(\[prompt, videoPart\]);
    for await (const chunk of result.stream) {
    const chunkText = chunk.text();
    console.log(chunkText);
    }
    }
    run();

### Dart

You can call
[`generateContentStream()`](https://pub.dev/documentation/firebase_ai/latest/firebase_ai/GenerativeModel/generateContentStream.html)
to stream generated text from multimodal input of text and a single video.  


    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 text prompt to include with the video
    final prompt = TextPart("What's in the video?");
    // Prepare video for input
    final video = await File('video0.mp4').readAsBytes();
    // Provide the video as \`Data\` with the appropriate mimetype
    final videoPart = InlineDataPart('video/mp4', video);
    // To stream generated text output, call generateContentStream with the text and image
    final response = await model.generateContentStream(\[
    Content.multi(\[prompt,videoPart\])
    \]);
    await for (final chunk in response) {
    print(chunk.text);
    }

### Unity

You can call
[`GenerateContentStreamAsync()`](https://firebase.google.com/docs/reference/unity/class/firebase/a-i/generative-model#generatecontentstreamasync)
to stream generated text from multimodal input of text and a single video.  


    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 the video as \`data\` with the appropriate MIME type.
    var video = ModelContent.InlineData("video/mp4",
    System.IO.File.ReadAllBytes(System.IO.Path.Combine(
    UnityEngine.Application.streamingAssetsPath, "yourVideo.mp4")));
    // Provide a text prompt to include with the video
    var prompt = ModelContent.Text("What is in the video?");
    // To stream generated text output, call GenerateContentStreamAsync with the text and video
    var responseStream = model.GenerateContentStreamAsync(new \[\] { video, prompt });
    await foreach (var response in responseStream) {
    if (!string.IsNullOrWhiteSpace(response.Text)) {
    UnityEngine.Debug.Log(response.Text);
    }
    }


Learn how to choose a [model](https://firebase.google.com/docs/ai-logic/models)

appropriate for your use case and app.

<br />

<br />

<br />

*** ** * ** ***

## Requirements and recommendations for input image files


| **Important** : **The total request size limit is
| 20 MB.** To send large files, review the [options for providing files in multimodal requests](https://firebase.google.com/docs/ai-logic/input-file-requirements).

<br />

Note that a file provided as inline data is encoded to base64 in transit, which
increases the size of the request. You get an HTTP 413 error if a request is
too large.

See
[Supported input files and requirements for the Vertex AI Gemini API](https://firebase.google.com/docs/ai-logic/input-file-requirements)
to learn detailed information about the following:

- Different options for providing a file in a request (either inline or using the file's URL or URI)
- Supported file types
- Supported MIME types and how to specify them
- Requirements and best practices for files and multimodal requests

<br />

*** ** * ** ***

## What else can you do?

- Learn how to [count tokens](https://firebase.google.com/docs/ai-logic/count-tokens) before sending long prompts to the model.
- [Set up Cloud Storage for Firebase](https://firebase.google.com/docs/ai-logic/solutions/cloud-storage) so that you can include large files in your multimodal requests and have a more managed solution for providing files in prompts. Files can include images, PDFs, video, and audio.
- Start thinking about preparing for production (see the [production checklist](https://firebase.google.com/docs/ai-logic/production-checklist)), including:
  - [Setting up Firebase App Check](https://firebase.google.com/docs/ai-logic/app-check) to protect the Gemini API from abuse by unauthorized clients.
  - [Integrating Firebase Remote Config](https://firebase.google.com/docs/ai-logic/solutions/remote-config) to update values in your app (like model name) without releasing a new app version.


#### Try out other capabilities

<br />

- Build [multi-turn conversations (chat)](https://firebase.google.com/docs/ai-logic/chat).
- Generate text from [text-only prompts](https://firebase.google.com/docs/ai-logic/generate-text).
- Generate [structured output (like JSON)](https://firebase.google.com/docs/ai-logic/generate-structured-output) from both text and multimodal prompts.
- Generate images from text prompts ([Gemini](https://firebase.google.com/docs/ai-logic/generate-images-gemini) or [Imagen](https://firebase.google.com/docs/ai-logic/generate-images-imagen)).
- [Stream input and output](https://firebase.google.com/docs/ai-logic/live-api) (including audio) using the Gemini Live API.
- Use tools (like [function calling](https://firebase.google.com/docs/ai-logic/function-calling) and [grounding with Google Search](https://firebase.google.com/docs/ai-logic/grounding-google-search)) to connect a Gemini model to other parts of your app and external systems and information.


#### Learn how to control content generation

- [Understand prompt design](https://firebase.google.com/docs/ai-logic/prompt-design), including best practices, strategies, and example prompts.
- [Configure model parameters](https://firebase.google.com/docs/ai-logic/model-parameters) like temperature and maximum output tokens (for Gemini) or aspect ratio and person generation (for Imagen).
- [Use safety settings](https://firebase.google.com/docs/ai-logic/safety-settings) to adjust the likelihood of getting responses that may be considered harmful.

You can also experiment with prompts and model configurations and even get a generated code snippet using [Google AI Studio](https://aistudio.google.com).

<br />


#### Learn more about the supported models

Learn about the [models available for various use cases](https://firebase.google.com/docs/ai-logic/models) and their [quotas](https://firebase.google.com/docs/ai-logic/quotas) and [pricing](https://firebase.google.com/docs/ai-logic/pricing).

<br />

<br />

[Give feedback
about your experience with Firebase AI Logic](https://firebase.google.com/docs/ai-logic/feedback)

<br />