Stay organized with collectionsSave and categorize content based on your preferences.
You can ask aGeminimodel to analyze video files that you provide
either inline (base64-encoded) or via URL. When you useFirebase AI Logic,
you can make this request directly from your app.
With this capability, you can do things like:
Caption and answer questions about videos
Analyze specific segments of a video using timestamps
Transcribe video content by processing both the audio track and visual frames
Describe, segment, and extract information from videos, including both the
audio track and visual frames
Click yourGemini APIprovider to view provider-specific content
and code on this page.
If you haven't already, complete thegetting started guide, which describes how to
set up your Firebase project, connect your app to Firebase, add the SDK,
initialize the backend service for your chosenGemini APIprovider, and
create aGenerativeModelinstance.
For testing and iterating on your prompts and even
getting a generated code snippet, we recommend usingGoogle AI Studio.
Need a sample video file?
You can use this publicly available file with a MIME type ofvideo/mp4(view or download file).https://storage.googleapis.com/cloud-samples-data/video/animals.mp4
Generate text from video files (base64-encoded)
Before trying this sample, complete theBefore you beginsection of this guide
to set up your project and app. In that section, you'll also click a button for your chosenGemini APIprovider so that you see provider-specific content
on this page.
You can ask aGeminimodel to
generate text by prompting with text and video—providing each
input file'smimeTypeand the file itself. Findrequirements and recommendations for input fileslater on this page.
Note that this example shows providing the file inline, but the SDKs also
supportproviding a YouTube URL.
Swift
You can callgenerateContent()to generate text from multimodal input of text and video files.
importFirebaseAI// Initialize the Gemini Developer API backend serviceletai=FirebaseAI.firebaseAI(backend:.googleAI())// Create a `GenerativeModel` instance with a model that supports your use caseletmodel=ai.generativeModel(modelName:"gemini-2.5-flash")// Provide the video as `Data` with the appropriate MIME type.letvideo=InlineDataPart(data:tryData(contentsOf:videoURL),mimeType:"video/mp4")// Provide a text prompt to include with the videoletprompt="What is in the video?"// To generate text output, call generateContent with the text and videoletresponse=tryawaitmodel.generateContent(video,prompt)print(response.text??"No text in response.")
Kotlin
You can callgenerateContent()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 aCoroutine scope.
// Initialize the Gemini Developer API backend service// Create a `GenerativeModel` instance with a model that supports your use casevalmodel=Firebase.ai(backend=GenerativeBackend.googleAI()).generativeModel("gemini-2.5-flash")valcontentResolver=applicationContext.contentResolvercontentResolver.openInputStream(videoUri).use{stream->stream?.let{valbytes=stream.readBytes()// Provide a prompt that includes the video specified above and textvalprompt=content{inlineData(bytes,"video/mp4")text("What is in the video?")}// To generate text output, call generateContent with the promptvalresponse=generativeModel.generateContent(prompt)Log.d(TAG,response.text?:"")}}
Java
You can callgenerateContent()to generate text from multimodal input of text and video files.
// Initialize the Gemini Developer API backend service// Create a `GenerativeModel` instance with a model that supports your use caseGenerativeModelai=FirebaseAI.getInstance(GenerativeBackend.googleAI()).generativeModel("gemini-2.5-flash");// Use the GenerativeModelFutures Java compatibility layer which offers// support for ListenableFuture and Publisher APIsGenerativeModelFuturesmodel=GenerativeModelFutures.from(ai);ContentResolverresolver=getApplicationContext().getContentResolver();try(InputStreamstream=resolver.openInputStream(videoUri)){FilevideoFile=newFile(newURI(videoUri.toString()));intvideoSize=(int)videoFile.length();byte[]videoBytes=newbyte[videoSize];if(stream!=null){stream.read(videoBytes,0,videoBytes.length);stream.close();// Provide a prompt that includes the video specified above and textContentprompt=newContent.Builder().addInlineData(videoBytes,"video/mp4").addText("What is in the video?").build();// To generate text output, call generateContent with the promptListenableFuture<GenerateContentResponse>response=model.generateContent(prompt);Futures.addCallback(response,newFutureCallback<GenerateContentResponse>(){@OverridepublicvoidonSuccess(GenerateContentResponseresult){StringresultText=result.getText();System.out.println(resultText);}@OverridepublicvoidonFailure(Throwablet){t.printStackTrace();}},executor);}}catch(IOExceptione){e.printStackTrace();}catch(URISyntaxExceptione){e.printStackTrace();}
Web
You can callgenerateContent()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-objectconstfirebaseConfig={// ...};// Initialize FirebaseAppconstfirebaseApp=initializeApp(firebaseConfig);// Initialize the Gemini Developer API backend serviceconstai=getAI(firebaseApp,{backend:newGoogleAIBackend()});// Create a `GenerativeModel` instance with a model that supports your use caseconstmodel=getGenerativeModel(ai,{model:"gemini-2.5-flash"});// Converts a File object to a Part object.asyncfunctionfileToGenerativePart(file){constbase64EncodedDataPromise=newPromise((resolve)=>{constreader=newFileReader();reader.onloadend=()=>resolve(reader.result.split(',')[1]);reader.readAsDataURL(file);});return{inlineData:{data:awaitbase64EncodedDataPromise,mimeType:file.type},};}asyncfunctionrun(){// Provide a text prompt to include with the videoconstprompt="What do you see?";constfileInputEl=document.querySelector("input[type=file]");constvideoPart=awaitfileToGenerativePart(fileInputEl.files[0]);// To generate text output, call generateContent with the text and videoconstresult=awaitmodel.generateContent([prompt,videoPart]);constresponse=result.response;consttext=response.text();console.log(text);}run();
Dart
You can callgenerateContent()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 FirebaseAppawaitFirebase.initializeApp(options:DefaultFirebaseOptions.currentPlatform,);// Initialize the Gemini Developer API backend service// Create a `GenerativeModel` instance with a model that supports your use casefinalmodel=FirebaseAI.googleAI().generativeModel(model:'gemini-2.5-flash');// Provide a text prompt to include with the videofinalprompt=TextPart("What's in the video?");// Prepare video for inputfinalvideo=awaitFile('video0.mp4').readAsBytes();// Provide the video as `Data` with the appropriate mimetypefinalvideoPart=InlineDataPart('video/mp4',video);// To generate text output, call generateContent with the text and imagesfinalresponse=awaitmodel.generateContent([Content.multi([prompt,...videoPart])]);print(response.text);
Unity
You can callGenerateContentAsync()to generate text from multimodal input of text and video files.
usingFirebase;usingFirebase.AI;// Initialize the Gemini Developer API backend servicevarai=FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());// Create a `GenerativeModel` instance with a model that supports your use casevarmodel=ai.GetGenerativeModel(modelName:"gemini-2.5-flash");// Provide the video as `data` with the appropriate MIME type.varvideo=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 videovarprompt=ModelContent.Text("What is in the video?");// To generate text output, call GenerateContentAsync with the text and videovarresponse=awaitmodel.GenerateContentAsync(new[]{video,prompt});UnityEngine.Debug.Log(response.Text??"No text in response.");
Learn how to choose amodelappropriate for your use case and app.
Stream the response
Before trying this sample, complete theBefore you beginsection of this guide
to set up your project and app. In that section, you'll also click a button for your chosenGemini APIprovider so that you see provider-specific content
on this page.
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, callgenerateContentStream.
View example: Stream generated text from video files
Swift
You can callgenerateContentStream()to stream generated text from multimodal input of text and a single video.
importFirebaseAI// Initialize the Gemini Developer API backend serviceletai=FirebaseAI.firebaseAI(backend:.googleAI())// Create a `GenerativeModel` instance with a model that supports your use caseletmodel=ai.generativeModel(modelName:"gemini-2.5-flash")// Provide the video as `Data` with the appropriate MIME typeletvideo=InlineDataPart(data:tryData(contentsOf:videoURL),mimeType:"video/mp4")// Provide a text prompt to include with the videoletprompt="What is in the video?"// To stream generated text output, call generateContentStream with the text and videoletcontentStream=trymodel.generateContentStream(video,prompt)fortryawaitchunkincontentStream{iflettext=chunk.text{print(text)}}
Kotlin
You can callgenerateContentStream()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 aCoroutine scope.
// Initialize the Gemini Developer API backend service// Create a `GenerativeModel` instance with a model that supports your use casevalmodel=Firebase.ai(backend=GenerativeBackend.googleAI()).generativeModel("gemini-2.5-flash")valcontentResolver=applicationContext.contentResolvercontentResolver.openInputStream(videoUri).use{stream->stream?.let{valbytes=stream.readBytes()// Provide a prompt that includes the video specified above and textvalprompt=content{inlineData(bytes,"video/mp4")text("What is in the video?")}// To stream generated text output, call generateContentStream with the promptvarfullResponse=""generativeModel.generateContentStream(prompt).collect{chunk->Log.d(TAG,chunk.text?:"")fullResponse+=chunk.text}}}
Java
You can callgenerateContentStream()to stream generated text from multimodal input of text and a single video.
For Java, the streaming methods in this SDK return aPublishertype from theReactive Streams library.
// Initialize the Gemini Developer API backend service// Create a `GenerativeModel` instance with a model that supports your use caseGenerativeModelai=FirebaseAI.getInstance(GenerativeBackend.googleAI()).generativeModel("gemini-2.5-flash");// Use the GenerativeModelFutures Java compatibility layer which offers// support for ListenableFuture and Publisher APIsGenerativeModelFuturesmodel=GenerativeModelFutures.from(ai);ContentResolverresolver=getApplicationContext().getContentResolver();try(InputStreamstream=resolver.openInputStream(videoUri)){FilevideoFile=newFile(newURI(videoUri.toString()));intvideoSize=(int)videoFile.length();byte[]videoBytes=newbyte[videoSize];if(stream!=null){stream.read(videoBytes,0,videoBytes.length);stream.close();// Provide a prompt that includes the video specified above and textContentprompt=newContent.Builder().addInlineData(videoBytes,"video/mp4").addText("What is in the video?").build();// To stream generated text output, call generateContentStream with the promptPublisher<GenerateContentResponse>streamingResponse=model.generateContentStream(prompt);finalString[]fullResponse={""};streamingResponse.subscribe(newSubscriber<GenerateContentResponse>(){@OverridepublicvoidonNext(GenerateContentResponsegenerateContentResponse){Stringchunk=generateContentResponse.getText();fullResponse[0]+=chunk;}@OverridepublicvoidonComplete(){System.out.println(fullResponse[0]);}@OverridepublicvoidonError(Throwablet){t.printStackTrace();}@OverridepublicvoidonSubscribe(Subscriptions){}});}}catch(IOExceptione){e.printStackTrace();}catch(URISyntaxExceptione){e.printStackTrace();}
Web
You can callgenerateContentStream()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-objectconstfirebaseConfig={// ...};// Initialize FirebaseAppconstfirebaseApp=initializeApp(firebaseConfig);// Initialize the Gemini Developer API backend serviceconstai=getAI(firebaseApp,{backend:newGoogleAIBackend()});// Create a `GenerativeModel` instance with a model that supports your use caseconstmodel=getGenerativeModel(ai,{model:"gemini-2.5-flash"});// Converts a File object to a Part object.asyncfunctionfileToGenerativePart(file){constbase64EncodedDataPromise=newPromise((resolve)=>{constreader=newFileReader();reader.onloadend=()=>resolve(reader.result.split(',')[1]);reader.readAsDataURL(file);});return{inlineData:{data:awaitbase64EncodedDataPromise,mimeType:file.type},};}asyncfunctionrun(){// Provide a text prompt to include with the videoconstprompt="What do you see?";constfileInputEl=document.querySelector("input[type=file]");constvideoPart=awaitfileToGenerativePart(fileInputEl.files[0]);// To stream generated text output, call generateContentStream with the text and videoconstresult=awaitmodel.generateContentStream([prompt,videoPart]);forawait(constchunkofresult.stream){constchunkText=chunk.text();console.log(chunkText);}}run();
Dart
You can callgenerateContentStream()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 FirebaseAppawaitFirebase.initializeApp(options:DefaultFirebaseOptions.currentPlatform,);// Initialize the Gemini Developer API backend service// Create a `GenerativeModel` instance with a model that supports your use casefinalmodel=FirebaseAI.googleAI().generativeModel(model:'gemini-2.5-flash');// Provide a text prompt to include with the videofinalprompt=TextPart("What's in the video?");// Prepare video for inputfinalvideo=awaitFile('video0.mp4').readAsBytes();// Provide the video as `Data` with the appropriate mimetypefinalvideoPart=InlineDataPart('video/mp4',video);// To stream generated text output, call generateContentStream with the text and imagefinalresponse=awaitmodel.generateContentStream([Content.multi([prompt,videoPart])]);awaitfor(finalchunkinresponse){print(chunk.text);}
Unity
You can callGenerateContentStreamAsync()to stream generated text from multimodal input of text and a single video.
usingFirebase;usingFirebase.AI;// Initialize the Gemini Developer API backend servicevarai=FirebaseAI.GetInstance(FirebaseAI.Backend.GoogleAI());// Create a `GenerativeModel` instance with a model that supports your use casevarmodel=ai.GetGenerativeModel(modelName:"gemini-2.5-flash");// Provide the video as `data` with the appropriate MIME type.varvideo=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 videovarprompt=ModelContent.Text("What is in the video?");// To stream generated text output, call GenerateContentStreamAsync with the text and videovarresponseStream=model.GenerateContentStreamAsync(new[]{video,prompt});awaitforeach(varresponseinresponseStream){if(!string.IsNullOrWhiteSpace(response.Text)){UnityEngine.Debug.Log(response.Text);}}
Learn how to choose amodelappropriate for your use case and app.
Requirements and recommendations for input video files
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" page to learn detailed information
about the following:
Geminimultimodal models support the following video MIME types:
FLV -video/x-flv
MOV -video/quicktime
MPEG -video/mpeg
MPEGPS -video/mpegps
MPG -video/mpg
MP4 -video/mp4
WEBM -video/webm
WMV -video/wmv
3GPP -video/3gpp
Limits per request
Maximum files per request: 10 video files
What else can you do?
Learn how tocount tokensbefore sending long prompts to the model.
Set upCloud Storage for Firebaseso 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 theproduction checklist),
including:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[],[],null,[]]
