flutter_gemma_mediapipe 1.0.9
flutter_gemma_mediapipe: ^1.0.9 copied to clipboard
Moved to flutter_edge_ai_mediapipe. This is the final release under the name flutter_gemma_mediapipe; new versions ship as flutter_edge_ai_mediapipe, part of Flutter Edge AI.
example/README.md
flutter_gemma_mediapipe example #
flutter_gemma_mediapipe is an opt-in inference engine for
flutter_gemma. It runs MediaPipe
.task / .bin models on Android, iOS, and Web. Register the engine once at
startup, then use the unchanged inference API.
import 'package:flutter/widgets.dart';
import 'package:flutter_gemma/flutter_gemma.dart';
import 'package:flutter_gemma_mediapipe/flutter_gemma_mediapipe.dart';
Future<void> main() async {
WidgetsFlutterBinding.ensureInitialized();
// Opt into the MediaPipe engine (handles ModelFileType.task / .bin).
await FlutterGemma.initialize(
inferenceEngines: [MediaPipeEngine()],
);
// Install a .task model (downloads + sets it active).
await FlutterGemma.installModel(
modelType: ModelType.gemmaIt,
fileType: ModelFileType.task,
).fromNetwork('https://example.com/gemma3-1b-it.task').install();
// Create a model + session and generate.
final model = await FlutterGemma.getActiveModel(maxTokens: 1024);
final session = await model.createSession();
await session.addQueryChunk(const Message(text: 'Hello!', isUser: true));
final reply = await session.getResponse();
print(reply);
await session.close();
await model.close();
}
Pass MediaPipeEngine() alongside other engines (e.g. LiteRtLmEngine from
flutter_gemma_litertlm) if your app uses both .task and .litertlm models.
On web the MediaPipe runtime loads from a CDN — see the
package README for the
web/index.html setup. A full runnable app lives in the
flutter_gemma example.