denisovav The MediaPipe engine
Rules
- Depend on
flutter_gemmaandflutter_gemma_mediapipe, and import both. The engine package does not re-export core. - Declare
fileType: ModelFileType.taskfor.taskfiles andModelFileType.binaryfor.binfiles. - An app that includes this package needs iOS 16.0.
- There is no desktop support.
maxTokensis the real context limit — small values are not raised as they are on.litertlm.maxOutputTokensis ignored; stop generation withsession.stopGeneration().- On Android and iOS,
createChatinherits the model's audio support but not its image support — passsupportImage: trueto the chat as well, or the image is dropped.
Setup
flutter pub add flutter_gemma flutter_gemma_mediapipe
import 'package:flutter_gemma/flutter_gemma.dart';
import 'package:flutter_gemma_mediapipe/flutter_gemma_mediapipe.dart';
await FlutterGemma.initialize(inferenceEngines: [MediaPipeEngine()]);
await FlutterGemma.installModel(
modelType: ModelType.gemmaIt,
fileType: ModelFileType.task,
).fromNetwork(url).install();
final InferenceModel model = await FlutterGemma.getActiveModel(maxTokens: 1024);
Sessions, chats, streaming and the common traps work as in the flutter-gemma-inference skill — except that openSession / openChat (its concurrent-conversation pattern) work on Android and iOS only; on web they throw UnsupportedError.
iOS
ios/Podfile, declared once:
platform :ios, '16.0'
use_frameworks! :linkage => :static
With Swift Package Manager, also set iOS Deployment Target to 16.0 on the Runner target in Xcode. This package ships no Swift package manifest, so the app gets an ios/Podfile either way.
Core and the other engines build from iOS 15.0. If the app does not use .task models, leave this package out and stay on 15.
Large models also need Extended Virtual Addressing and Increased Memory Limit, added in Xcode under Signing & Capabilities, or the app is killed for memory.
Images and audio
final model = await FlutterGemma.getActiveModel(maxTokens: 4096, supportImage: true);
final chat = await model.createChat(supportImage: true);
await chat.addQueryChunk(
Message(text: 'Describe this image.', isUser: true, imageBytes: bytes),
);
On Android and iOS, a chat without supportImage: true drops the image and the model answers the text alone. On web the chat follows the model: an image sent to a model loaded without supportImage: true throws ArgumentError.
Audio input works on Android and iOS with a model that takes audio, such as Gemma 3n.
Bounding output
final session = await model.createSession();
await session.addQueryChunk(Message(text: prompt, isUser: true));
final reply = StringBuffer();
var produced = 0;
await for (final token in session.getResponseAsync()) {
reply.write(token);
if (++produced >= 200) {
await session.stopGeneration();
break;
}
}
await session.close();
Web
Add to web/index.html <head>, before Flutter boots:
<script type="module">
import { FilesetResolver, LlmInference } from 'https://cdn.jsdelivr.net/npm/@mediapipe/tasks-genai@0.10.27';
window.FilesetResolver = FilesetResolver;
window.LlmInference = LlmInference;
</script>
<script src="cache_api.js"></script>
<script src="opfs_helper.js"></script>
Pin the version — an unpinned import takes whatever was published last. Copy cache_api.js and opfs_helper.js from the flutter_gemma package's web/ directory into the app's web/; find it with grep -A1 '"name": "flutter_gemma"' .dart_tool/package_config.json.
Web is GPU-only. Models over about 2 GB need OPFS streaming storage:
await FlutterGemma.initialize(
webStorageMode: WebStorageMode.streaming,
inferenceEngines: [MediaPipeEngine()],
);
Android
Text inference runs on arm64-v8a, x86_64 and armeabi-v7a. The release build needs <uses-permission android:name="android.permission.INTERNET"/> in android/app/src/main/AndroidManifest.xml to download a model — Flutter's template declares it only for debug and profile builds.