Flutter genui
Skill Poorgramer-Zack/dart-expert-skills/skills/flutter-genui
Generative UI (GenUI) for Flutter using AI models like Google Gemini, Anthropic Claude, or OpenAI via the genui package. Use this skill when building dynamic AI-driven interfaces, conversational UI flows, server-rendered screen layouts, LLM-powered dashboards, chat-based UI generation, or implementing prompt-to-UI systems. Supports AI-generated widgets, reactive data binding, ContentGenerator integration, and A2uiMessageProcessor for real-time UI updates from AI responses. Ideal for apps where UI structure is determined by AI/LLM output rather than hardcoded layouts.From its SKILL.md
npx -y skills add Poorgramer-Zack/dart-expert-skills --skill flutter-genuiAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
5.3 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Flutter Generative UI (GenUI) Best Practices
Goal
Implement a dynamic user interface generated by AI using the genui package. This is the recommended approach when an application needs to build reactive screens or components directly from AI responses without hardcoding the layout.
Instructions
The genui package orchestrates a conversational loop between the user, the AI (via ContentGenerator), and the Flutter UI (via A2uiMessageProcessor and DataModel).
1. Project Setup
Add the necessary packages to your pubspec.yaml:
flutter pub add genui
# For Gemini integration via Firebase:
flutter pub add genui_firebase_ai
If targeting macOS/iOS, enable outbound network requests in entitlements:
<key>com.apple.security.network.client</key>
<true/>
2. Core Integration Structure
To connect your Flutter application to the AI agent, you need to instantiate three main components:
A2uiMessageProcessor: Handles the UI side, translating AI messages into UI actions. Supply it with aCatalogof widgets the AI is allowed to use.ContentGenerator: Handles communication with the AI. Supply it with system instructions and tools.GenUiConversation: The facade coordinating the processor and generator.
Example Setup in a StatefulWidget:
import 'package:flutter/material.dart';
import 'package:genui/genui.dart';
import 'package:genui_firebase_ai/genui_firebase_ai.dart';
class GenUIPage extends StatefulWidget {
const GenUIPage({super.key});
@override
State<GenUIPage> createState() => _GenUIPageState();
}
class _GenUIPageState extends State<GenUIPage> {
late final A2uiMessageProcessor _a2uiMessageProcessor;
late final GenUiConversation _genUiConversation;
@override
void initState() {
super.initState();
// 1. Initialize Message Processor with predefined catalog widgets
_a2uiMessageProcessor = A2uiMessageProcessor(
catalogs: [CoreCatalogItems.asCatalog()],
);
// 2. Initialize Content Generator (e.g., Firebase AI / Gemini)
final contentGenerator = FirebaseAiContentGenerator(
catalog: CoreCatalogItems.asCatalog(),
systemInstruction: '''
You are an AI assistant. You must generate UI by responding with JSON
matching the provided widget schemas. Always output valid UI structures.
''',
tools: _a2uiMessageProcessor.getTools(),
);
// 3. Orchestrate the Conversation
_genUiConversation = GenUiConversation(
a2uiMessageProcessor: _a2uiMessageProcessor,
contentGenerator: contentGenerator,
// Implement your handlers for rendering generated surfaces
onSurfaceAdded: (surfaceId) { /* Handle surface creation */ },
onSurfaceDeleted: (surfaceId) { /* Handle surface deletion */ },
onTextResponse: (text) { /* Optional: show text explicitly */ },
onError: (error) { /* Handle generation errors */ },
);
}
@override
void dispose() {
_genUiConversation.dispose();
super.dispose();
}
@override
Widget build(BuildContext context) {
// UI Implementation interacting with _genUiConversation.sendRequest()
return const Scaffold();
}
}
3. Data Model & Data Binding
A core philosophy of genui is utilizing a central DataModel. Widgets don't manage their own dynamic state; instead, they bind to paths within the DataModel.
When creating custom widgets to add to your Catalog, ensure they react to the data context:
// The AI will generate JSON like:
// { "Text": { "text": { "literalString": "Hello" } } }
// OR
// { "Text": { "text": { "path": "/user/welcome_message" } } }
- literalString: Static data directly from the AI.
- path: A reference to a location in the
DataModel. Updates to this path automatically rebuild any widgets bound to it. Input widgets (likeTextField) should directly update thisDataModel.
4. Customizing the Catalog
To extend GenUI beyond the CoreCatalogItems, define your own CatalogItems and provide them to both the A2uiMessageProcessor and the ContentGenerator. This tells the AI what Custom Widgets are available and what parameters they accept.
Constraints
- Architecture Scope: Do not use
genuifor static screens or standard layouts. It should be reserved exclusively for features needing generative or highly dynamic, AI-driven UI presentation. - State Management: Within GenUI components, prefer the unified
DataModelreactivity over localsetStatefor data shared with the AI. - Error Handling: Always ensure
onErrorinGenUiConversationis handled appropriately, as AI responses can sometimes fail parsing or violate catalog schemas.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.