flutter_gen_ai_chat_ui

Flutter Gen AI Chat UI

A modern, high-performance Flutter chat UI kit for building beautiful messaging interfaces. Features streaming text animations, markdown support, file attachments, and extensive customization options. Perfect for AI assistants, customer support, team chat, social messaging, and any conversational application.

🚀 Production Ready | 📱 Cross-Platform | ⚡ High Performance | 🎨 Fully Customizable

Table of Contents

• Installation
• Quick Start
• Why this package?
• Streaming AI responses
• Live Examples
• Features
• Performance & Features
• Works Great With
• RTL & Bidirectional Languages
• Configuration Options
• AI Actions System
• Advanced Features
• Showcase

Dark Mode

Chat Demo

Installation

Add this to your package's pubspec.yaml file:

dependencies:
  flutter_gen_ai_chat_ui: ^2.19.1

Then run:

flutter pub get

📖 New: task-focused Cookbook — streaming, stop-generating, thinking→answer, custom bubbles, attachments, localization/RTL.

Quick Start

import 'package:flutter_gen_ai_chat_ui/flutter_gen_ai_chat_ui.dart';

class ChatScreen extends StatefulWidget {
  @override
  _ChatScreenState createState() => _ChatScreenState();
}

class _ChatScreenState extends State<ChatScreen> {
  final _controller = ChatMessagesController();
  final _currentUser = ChatUser(id: 'user', firstName: 'User');
  final _aiUser = ChatUser(id: 'ai', firstName: 'AI Assistant');
  bool _isLoading = false;

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(title: Text('AI Chat')),
      body: AiChatWidget(
        // Required parameters
        currentUser: _currentUser,
        aiUser: _aiUser,
        controller: _controller,
        onSendMessage: _handleSendMessage,

        // Optional parameters
        loadingConfig: LoadingConfig(isLoading: _isLoading),
        inputOptions: InputOptions(
          hintText: 'Ask me anything...',
          sendOnEnter: true,
        ),
        welcomeMessageConfig: WelcomeMessageConfig(
          title: 'Welcome to AI Chat',
          questionsSectionTitle: 'Try asking me:',
        ),
        exampleQuestions: [
          ExampleQuestion(question: "What can you help me with?"),
          ExampleQuestion(question: "Tell me about your features"),
        ],
      ),
    );
  }

  Future<void> _handleSendMessage(ChatMessage message) async {
    setState(() => _isLoading = true);

    try {
      // Your AI service logic here
      await Future.delayed(Duration(seconds: 1)); // Simulating API call

      // Add AI response
      _controller.addMessage(ChatMessage(
        text: "This is a response to: ${message.text}",
        user: _aiUser,
        createdAt: DateTime.now(),
      ));
    } finally {
      setState(() => _isLoading = false);
    }
  }
}

Why this package?

Three Flutter chat UI packages dominate searches: flutter_gen_ai_chat_ui, flutter_chat_ui, and dash_chat_2. They target different shapes of app. If you have an LLM in the loop, this package was designed for that shape.

Concern	flutter_gen_ai_chat_ui	flutter_chat_ui	dash_chat_2
Word-by-word streaming animation	Built-in	No	No
Markdown + code highlight in messages	Built-in	Manual	Manual
LaTeX / math rendering	Opt-in flag	No	No
Rich inline widget messages (full-width, no bubble)	ChatMessage.rich()	Custom bubble only	No
AI tool-use / function-calling UI	AiActionProvider	No	No
Human-in-the-loop confirmation	Built-in	No	No
Mic/send toggle (ChatGPT-style)	sendOrMicBuilder	No	No
RTL out of the box	Yes	Partial	Partial
AI welcome screen + example questions	Built-in	No	No
Cross-platform incl. desktop hardware Enter	All 6	All 6	Mobile-focused

For general-purpose peer-to-peer chat with no AI features, flutter_chat_ui is a lighter choice. The features above are this package's reason to exist.

Streaming AI responses

ChatGPT/Claude-style word-by-word streaming is built in. It is gated by two flags — both must be on:

• enableMarkdownStreaming: true — master gate for the animation pipeline.
• streamingWordByWord: true — word-vs-character animation (default is character).

Push an empty message with a stable id, then call updateMessage with a fresh ChatMessage carrying that same id each time your LLM emits a chunk. The controller matches on id and replaces the entry in place.

AiChatWidget(
  currentUser: me,
  aiUser: ai,
  controller: controller,
  onSendMessage: handleSend,
  enableMarkdownStreaming: true,
  streamingWordByWord: true,
  streamingDuration: const Duration(milliseconds: 30),
);

Future<void> streamReply(String prompt) async {
  final id = DateTime.now().microsecondsSinceEpoch.toString();
  controller.addMessage(ChatMessage(
    text: '',
    user: ai,
    createdAt: DateTime.now(),
    customProperties: {'id': id, 'isStreaming': true},
  ));

  final buffer = StringBuffer();
  await for (final chunk in myStreamingLlm(prompt)) {
    buffer.write(chunk);
    controller.updateMessage(ChatMessage(
      text: buffer.toString(),
      user: ai,
      createdAt: DateTime.now(),
      customProperties: {'id': id, 'isStreaming': true},
    ));
  }
  controller.stopStreamingMessage(id);
}

Full runnable screen: example/lib/examples/streaming_chat.dart. Before v2.4.2 the two flags were silently ignored — set both, or leave both default.

🎮 Live Examples

Try the live web demo → — no install needed, runs the actual example app in your browser. Redeployed automatically on every push to main that touches the package or the example app (see .github/workflows/deploy-web-demo.yml).

Explore all features with our comprehensive example app:

• Basic Chat: Simple send & receive, no streaming
• Streaming + Markdown: Real-time word-by-word animations with code blocks
• Custom Themes: Ocean, Sunset, and Default bubble styles
• AI Actions: Calculator, weather, color — function calling with generative UI
• Rich Widgets: Weather cards, products, charts rendered inline as bubbles
• RTL Chat: Arabic streaming with bidirectional auto-detection
• Attachments: File upload button and attached-file rendering (FileUploadOptions)
• Voice Input: Mic/send toggle using the VoiceSendButton widget (InputOptions.sendOrMicBuilder)

To run the example app:

cd example/
flutter run

Features

Core Features

• 🎨 Dark/light mode with adaptive theming
• 💫 Word-by-word streaming with animations (like ChatGPT and Claude)
• 📝 Enhanced markdown support with code highlighting for technical content
• 🎤 Optional speech-to-text integration
• 📱 Responsive layout with customizable width
• 🌐 RTL language support for global applications
• ⚡ High performance message handling for large conversations
• 📊 Improved pagination support for message history

AI-Specific Features

• 👋 Customizable welcome message similar to ChatGPT and other AI assistants
• ❓ Example questions component for user guidance
• 💬 Persistent example questions for better user experience
• 🔄 AI typing indicators like modern chatbot interfaces
• 📜 Streaming markdown rendering for code and rich content

🚀 NEW: Rich Widget Messages

• 🧩 ChatMessage.rich() - Render custom widgets (cards, forms, charts) inline in chat — full-width, no bubble
• 🎯 Result Renderer Registry - Register builders by type, AI responses auto-render matching widgets
• 🔧 ChatMessage.widget() - One-off inline widgets without a registry
• 📦 Zero Config Fallback - Unmatched types fall through to text rendering gracefully

🎤 Input Customization

• 🎙️ sendOrMicBuilder - Mic/send toggle that auto-switches based on text field empty state (ChatGPT-style)
• 📎 inputLeadingBuilder - Icons inside the input row, left of text field (attach, mic, etc.)
• 🖼️ attachmentPreviewBuilder - File/image preview strip above the input area
• ⬇️ Safe area support - Input respects device home indicator on all paths

⏳ Streaming Loading States

• 💫 ChatMessage.loading() - Shimmer placeholder that morphs into rich widget via controller.updateMessage()
• 🏷️ loadingKind - Per-kind custom loading widgets (e.g., contract spinner, lawyer search animation)
• 🎨 resultLoadingRenderers - Register custom loading UIs per widget type

AI Actions System

• ⚡ Function Calling Support - AI can execute predefined actions with parameters
• 🎨 Generative UI - Actions render custom widgets showing execution status
• ✋ Human-in-the-Loop - Automatic confirmation dialogs for sensitive operations
• 📊 Real-time Status - Live updates of action execution progress with animations
• 🛡️ Type-Safe Parameters - Full validation system with custom validators
• 🎯 Event Streaming - Track action lifecycle with comprehensive event system
• 🔧 Error Handling - Rich error management with user-friendly feedback

UI Components

• 💬 Customizable message bubbles with modern design options
• 🎨 Custom Bubble Builder for complete message styling control
• ⌨️ Multiple input field styles (minimal, glassmorphic, custom)
• 🔄 Loading indicators with shimmer effects
• ⬇️ Smart scroll management for chat history
• 🎨 Enhanced theme customization to match your brand
• 📝 Better code block styling for developers

⚡ Performance & Features

Key Capabilities

• ✨ Unique Streaming Text: Word-by-word animations like ChatGPT and Claude
• 📁 Complete File Support: Multi-format, multi-file attachments (images, documents, videos) with a built-in image lightbox and per-file upload progress — see the attachments cookbook recipe
• 📝 Advanced Markdown: Full support with syntax highlighting for code blocks
• 🚀 High Performance: Optimized for large conversations (10K+ messages)
• 🎨 Extensive Theming: Complete customization to match your brand
• 📱 Cross-Platform: Works on all Flutter-supported platforms
• 🔗 Backend Agnostic: Compatible with any API or service
• ⚡ Real-time Ready: Built-in support for live updates
• 💾 Persistable Threads: Opt-in ChatPersistence hook to restore/save a long-running conversation across app restarts — see the persistence cookbook recipe

Performance Benchmarks

• Message Rendering: 60 FPS with 1000+ messages
• Memory Efficiency: Optimized for large conversations
• Startup Time: <100ms initialization
• Streaming Speed: Configurable 10-100ms per word

Web / WebAssembly

Builds and runs cleanly under Flutter's --wasm web compile target (flutter build web --wasm) — no dart:html/dart:js legacy interop or other wasm-incompatible APIs in this package. CI builds the example app with --wasm on every push so a regression is caught immediately (.github/workflows/ci.yml, wasm-build job).

🌟 Works Great With

• AI Services: OpenAI, Anthropic Claude, Google Gemini, Llama, Mistral — see the cookbook's provider-wiring recipes for copy-pasteable streaming snippets (OpenAI, Anthropic, Gemini, Ollama)
• Backends: Firebase, Supabase, REST APIs, WebSockets, GraphQL
• Use Cases: Customer support, AI assistants, team chat, social messaging
• Industries: SaaS, E-commerce, Healthcare, Education, Gaming

RTL & Bidirectional Languages

The package ships first-class support for right-to-left scripts (Arabic, Hebrew, Persian, Urdu, Kurdish) — no extra dependency, no extra widget.

• Locale-aware layout — wrap the chat in Directionality(textDirection: TextDirection.rtl, ...) (or rely on your app's Localizations) and every surface mirrors: input row, send button, scroll, bubble alignment, copy button.
• Per-message bidi auto-detect — each bubble's TextDirection is inferred from its content (Arabic chars → RTL, ASCII → LTR), so mixed conversations render correctly in a single thread without per-message config.
• Arabic word-splitting for streaming — word-by-word streaming animates by whole Arabic words, not by code points (powered by flutter_streaming_text_markdown 1.7.0+).
• Markdown still works — headings, code blocks, blockquotes, tables all render bidi-correctly inside RTL bubbles.

Minimal RTL setup:

Directionality(
  textDirection: TextDirection.rtl,
  child: AiChatWidget(
    currentUser: ChatUser(id: 'user', name: 'أنت'),
    aiUser: ChatUser(id: 'ai', name: 'المساعد'),
    controller: controller,
    onSendMessage: handleSend,
    enableMarkdownStreaming: true,
    exampleQuestions: const [
      ExampleQuestion(question: 'ما هي عاصمة العراق؟'),
      ExampleQuestion(question: 'اكتب لي قصيدة قصيرة'),
    ],
  ),
)

Full working screen with streaming Arabic markdown and example questions: example/lib/examples/rtl_chat.dart.

Configuration Options

AiChatWidget Parameters

Required Parameters

AiChatWidget(
  // Required parameters
  currentUser: ChatUser(...),  // The current user
  aiUser: ChatUser(...),       // The AI assistant
  controller: ChatMessagesController(),  // Message controller
  onSendMessage: (message) {   // Message handler
    // Handle user messages here
  },
  
  // ... optional parameters
)

Optional Parameters

AiChatWidget(
  // ... required parameters
  
  // Message display options
  messages: [],                // Optional list of messages (if not using controller)
  messageOptions: MessageOptions(...),  // Message bubble styling
  messageListOptions: MessageListOptions(...),  // Message list behavior
  
  // Input field customization
  inputOptions: InputOptions(...),  // Input field styling and behavior
  readOnly: false,             // Whether the chat is read-only
  
  // AI-specific features
  exampleQuestions: [          // Suggested questions for users
    ExampleQuestion(question: 'What is AI?'),
  ],
  persistentExampleQuestions: true,  // Keep questions visible after welcome
  enableAnimation: true,       // Enable message animations
  enableMarkdownStreaming: true,  // Enable streaming text (FIXED in v2.4.2+)
  streamingWordByWord: false,     // Control word-by-word vs character animation  
  streamingDuration: Duration(milliseconds: 30),  // Stream speed
  welcomeMessageConfig: WelcomeMessageConfig(...),  // Welcome message styling
  
  // Loading states
  loadingConfig: LoadingConfig(  // Loading configuration
    isLoading: false,
    showCenteredIndicator: true,
  ),
  
  // Pagination
  paginationConfig: PaginationConfig(  // Pagination configuration
    enabled: true,
    reverseOrder: true,  // Newest messages at bottom
  ),
  
  // Layout
  maxWidth: 800,             // Maximum width
  padding: EdgeInsets.all(16),  // Overall padding
  
  // Scroll behavior
  scrollBehaviorConfig: ScrollBehaviorConfig(
    // Control auto-scrolling behavior
    autoScrollBehavior: AutoScrollBehavior.onUserMessageOnly,
    // Scroll to first message of a response instead of the last (for long responses)
    scrollToFirstResponseMessage: true,
    // Hold the start of a streaming answer at the top of the viewport (2.16.0+)
    pinDuringStreaming: StreamingPinAnchor.responseStart,
  ),
  
  // Custom bubble styling lives in messageOptions. Use `bubbleBuilder` to wrap
  // the default bubble, or `customBubbleBuilder` (3-arg) to replace it entirely.
  messageOptions: MessageOptions(
    bubbleBuilder: (context, message, isCurrentUser, defaultBubble) {
      return Container(
        decoration: BoxDecoration(
          borderRadius: BorderRadius.circular(12),
          boxShadow: [
            BoxShadow(
              color: Colors.black.withValues(alpha: 0.1),
              blurRadius: 4,
              offset: const Offset(0, 2),
            ),
          ],
        ),
        child: defaultBubble, // wrap the default, or return your own UI
      );
    },
  ),
)

Input Field Customization

The package offers multiple ways to style the input field:

Default Input

InputOptions(
  // Basic properties
  sendOnEnter: true,
  
  // Focus behavior (NEW in v2.4.2+)
  autofocus: true,          // Automatically focus the input field
  focusNode: myFocusNode,   // Custom focus node for external control
  
  // Styling
  textStyle: TextStyle(...),
  decoration: InputDecoration(...),
)

Minimal Input

InputOptions.minimal(
  hintText: 'Ask a question...',
  textColor: Colors.black,
  hintColor: Colors.grey,
  backgroundColor: Colors.white,
  borderRadius: 24.0,
  autofocus: true,        // Available in factory constructors too
  focusNode: myFocusNode, // Custom focus node support
)

Glassmorphic (Frosted Glass) Input

InputOptions.glassmorphic(
  colors: [Colors.blue.withOpacityCompat(0.2), Colors.purple.withOpacityCompat(0.2)],
  borderRadius: 24.0,
  blurStrength: 10.0,
  hintText: 'Ask me anything...',
  textColor: Colors.white,
  autofocus: false,       // Control autofocus behavior
  focusNode: myFocusNode, // Optional custom focus node
)

Custom Input

InputOptions.custom(
  decoration: yourCustomDecoration,
  textStyle: yourCustomTextStyle,
  sendButtonBuilder: (onSend) => CustomSendButton(onSend: onSend),
)

Always-Visible Send Button Without Focus Issues (version 2.0.4+)

The send button is now hardcoded to always be visible by design, regardless of text content. This removes the need for an explicit setting and ensures a consistent experience across the package.

By default:

• The send button is always shown regardless of text input
• Focus is maintained when tapping outside the input field
• The keyboard's send button is disabled by default to prevent focus issues on mobile

// Configure input options to ensure a consistent typing experience
InputOptions(
  // Prevent losing focus when tapping outside
  unfocusOnTapOutside: false,
  
  // Use newline for Enter key to prevent keyboard focus issues on mobile.
  // Hardware Enter on desktop/web still sends — see "Enter key behavior" below.
  textInputAction: TextInputAction.newline,
)

Enter key behavior (version 2.11.1+)

With sendOnEnter: true (the default), pressing Enter on a hardware keyboard sends the message. This works on macOS, Windows, Linux, web, and on iOS/Android devices with an attached physical keyboard.

• Enter — sends the current message.
• Shift+Enter — inserts a newline (ChatGPT/Claude style).
• Numpad Enter — sends.
• During CJK / IME composition, Enter commits the composition instead of sending.
• Set sendOnEnter: false to disable; Enter then always inserts a newline.

Stop / cancel generating (version 2.12.0+)

Provide an onCancelGenerating callback and the send button automatically turns into a stop button whenever loadingConfig.isLoading is true. The package doesn't run the generation itself, so the callback is where you cancel your own stream / HTTP request.

StreamSubscription<String>? _streamSub;
String? _currentId;
bool _isLoading = false;

AiChatWidget(
  // ...
  loadingConfig: LoadingConfig(isLoading: _isLoading),
  onCancelGenerating: () {
    _streamSub?.cancel();                       // stop your own work
    if (_currentId != null) {
      _controller.stopStreamingMessage(_currentId!); // finalize the partial bubble
    }
    setState(() => _isLoading = false);
  },
)

• The stop button only appears when onCancelGenerating != null and isLoading == true. Otherwise the normal send button is shown.
• Send-on-Enter (hardware and soft keyboard) is suppressed while the stop button is visible, so users can't queue a new message behind the in-flight one.
• Customize the button with InputOptions(stopButtonIcon: ..., stopButtonColor: ...), or replace it entirely with InputOptions(cancelButtonBuilder: (onCancel) => ...).

See example/lib/examples/streaming_chat.dart for a full working implementation.

Scroll Behavior Configuration

Control how the chat widget scrolls when new messages are added:

// Default configuration with manual parameters
ScrollBehaviorConfig(
  // When to auto-scroll (one of: always, onNewMessage, onUserMessageOnly, never)
  autoScrollBehavior: AutoScrollBehavior.onUserMessageOnly,
  
  // Fix for long responses: scroll to first message of response instead of the last message
  // This prevents the top part of long AI responses from being pushed out of view
  scrollToFirstResponseMessage: true,
  
  // Customize animation
  scrollAnimationDuration: Duration(milliseconds: 300),
  scrollAnimationCurve: Curves.easeOut,

  // 2.16.0+: hold the start of the answer (or the user's question) at the top
  // of the viewport WHILE the answer streams — see the use case below
  pinDuringStreaming: StreamingPinAnchor.responseStart,
)

// Or use convenient preset configurations:
ScrollBehaviorConfig.smooth() // Smooth easeInOutCubic curve
ScrollBehaviorConfig.bouncy() // Bouncy elasticOut curve
ScrollBehaviorConfig.fast()   // Quick scrolling with minimal animation
ScrollBehaviorConfig.decelerate() // Starts fast, slows down
ScrollBehaviorConfig.accelerate() // Starts slow, speeds up

Use Case: Preventing Long Responses from Auto-Scrolling

When an AI returns a long response in multiple parts, scrollToFirstResponseMessage ensures users see the beginning of the response rather than being automatically scrolled to the end. This is crucial for readability, especially with complex information.

For optimal scroll behavior with long responses:

1. Mark the first message in a response with 'isStartOfResponse': true
2. Link related messages in a chain using a shared 'responseId' property
3. Set scrollToFirstResponseMessage: true in your configuration

Use Case: Reading a Long Answer While It Streams (pinDuringStreaming)

scrollToFirstResponseMessage acts once the answer has finished. For a single long answer that is still streaming, the classic behaviour is that the bottom of the list keeps following the new text, so the beginning scrolls out of view and you have to wait for the end to start reading. pinDuringStreaming (2.16.0+) fixes that:

ScrollBehaviorConfig(
  // responseStart: hold the first line of the answer at the top of the viewport
  // userMessage:   hold your own question there instead, so Q and A read together
  pinDuringStreaming: StreamingPinAnchor.responseStart,
)

What the reader sees:

1. They send a question and the list scrolls to it as usual.
2. The answer starts streaming and the list follows it — until the anchor (the start of the answer, or the question) reaches the top of the viewport.
3. From then on the anchor is held there; new text arrives below the fold and the scroll-to-bottom button appears.
4. Any scroll gesture, or a tap on the scroll-to-bottom button, hands control back to the reader for the rest of that answer. In a reverse (newest-at-bottom) list the text they are reading also stays still while more chunks arrive, instead of being pushed upwards.
5. When the stream ends nothing jumps — the reader stays where they are.

The default is StreamingPinAnchor.none (unchanged behaviour). The pin arms whenever a message streams: addMessage/updateMessage with 'isStreaming': true, or addStreamingMessage + updateMessage + stopStreamingMessage.

Message Bubble Customization

MessageOptions(
  // Basic options
  showTime: true,
  showUserName: true,

  // Timestamp styling. `timeTextStyle` applies to both bubbles; the per-bubble
  // overrides (2.12.0+) take precedence when set — handy when a colored user
  // bubble makes the shared timestamp hard to read.
  timeTextStyle: const TextStyle(fontSize: 11, color: Colors.grey),
  userTimeTextStyle: const TextStyle(fontSize: 11, color: Colors.white70),
  aiTimeTextStyle: const TextStyle(fontSize: 11, color: Colors.black45),

  // Styling
  bubbleStyle: BubbleStyle(
    userBubbleColor: Colors.blue.withOpacityCompat(0.1),
    aiBubbleColor: Colors.white,
    userNameColor: Colors.blue.shade700,
    aiNameColor: Colors.purple.shade700,
    bottomLeftRadius: 22,
    bottomRightRadius: 22,
    enableShadow: true,
  ),
)

Custom Bubble Builder

Create completely custom message bubbles with full control over styling and behavior:

AiChatWidget(
  // ... other parameters
  messageOptions: MessageOptions(
    // Wrapper approach: enhance the default bubble (e.g. add a report button).
    // `bubbleBuilder` hands you the fully-styled default bubble to wrap.
    bubbleBuilder: (context, message, isCurrentUser, defaultBubble) {
      return Container(
        margin: const EdgeInsets.symmetric(horizontal: 16, vertical: 4),
        decoration: BoxDecoration(
          borderRadius: BorderRadius.circular(16),
          boxShadow: [
            BoxShadow(
              color: Colors.black.withValues(alpha: 0.1),
              blurRadius: 4,
              offset: const Offset(0, 2),
            ),
          ],
        ),
        child: defaultBubble,
      );
    },

    // Full-replacement approach (3-arg): rebuild the bubble from scratch.
    // customBubbleBuilder: (context, message, isCurrentUser) =>
    //     MyCustomBubble(message: message, isCurrentUser: isCurrentUser),
  ),
)

Brand Theme Presets

Apply a ChatGPT/Claude/Gemini-style look with one line, via a CustomThemeExtension on your app's ThemeData — no need to set colors on every individual AiChatWidget:

MaterialApp(
  theme: ThemeData(
    extensions: [CustomThemeExtension.chatgpt()], // or .claude() / .gemini()
  ),
  // For dark mode: CustomThemeExtension.chatgpt(dark: true)
  home: MyChatScreen(),
)

Two more presets derive their colors from your app's existing ColorScheme instead of a fixed brand palette — handy when you want a theme-consistent look without picking your own bubble colors:

CustomThemeExtension.modern(Theme.of(context).colorScheme)  // richer surfaces
CustomThemeExtension.minimal(Theme.of(context).colorScheme) // flat, low-contrast

CustomThemeExtension sets chatBackground, messageBubbleColor/userBubbleColor/messageTextColor, inputBackgroundColor/inputBorderColor/inputTextColor/hintTextColor, and sendButtonColor/backToBottomButtonColor — all consulted only when the more specific BubbleStyle/MessageOptions/InputOptions value is left unset, so any explicit per-widget color you already set keeps winning. Build a fully custom one with CustomThemeExtension(chatBackground: ..., messageBubbleColor: ..., ...).

🚀 AI Actions System

Transform your chat into a powerful AI agent platform! The AI Actions System allows your AI to execute real functions, display rich results, and maintain human oversight - taking your chat beyond simple text exchanges.

⚡ Quick Start with AI Actions

import 'package:flutter_gen_ai_chat_ui/flutter_gen_ai_chat_ui.dart';

class MyAiChat extends StatefulWidget {
  @override
  _MyAiChatState createState() => _MyAiChatState();
}

class _MyAiChatState extends State<MyAiChat> {
  late ChatMessagesController _controller;
  
  @override
  Widget build(BuildContext context) {
    return AiActionProvider(
      config: AiActionConfig(
        actions: [
          // Define what your AI can do
          AiAction(
            name: 'calculate',
            description: 'Perform mathematical calculations',
            parameters: [
              ActionParameter.number(name: 'a', description: 'First number', required: true),
              ActionParameter.number(name: 'b', description: 'Second number', required: true),
              ActionParameter.string(
                name: 'operation', 
                description: 'Math operation',
                required: true,
                enumValues: ['add', 'subtract', 'multiply', 'divide']
              ),
            ],
            handler: (params) async {
              final a = params['a'] as num;
              final b = params['b'] as num;
              final op = params['operation'] as String;
              
              double result;
              switch (op) {
                case 'add': result = a + b; break;
                case 'subtract': result = a - b; break;
                case 'multiply': result = a * b; break;
                case 'divide': result = a / b; break;
                default: throw 'Unknown operation';
              }
              
              return ActionResult.createSuccess({
                'result': result,
                'equation': '$a $op $b = $result'
              });
            },
            // Custom UI for results
            render: (context, status, params, {result, error}) {
              if (status == ActionStatus.completed && result?.data != null) {
                return Card(
                  child: Padding(
                    padding: EdgeInsets.all(16),
                    child: Text(
                      result!.data['equation'],
                      style: TextStyle(fontSize: 18, fontWeight: FontWeight.bold),
                    ),
                  ),
                );
              }
              return SizedBox.shrink();
            },
          ),
        ],
      ),
      child: AiChatWidget(
        // Your existing chat configuration
        currentUser: currentUser,
        aiUser: aiUser,
        controller: _controller,
        onSendMessage: _handleMessage,
      ),
    );
  }
  
  void _handleMessage(ChatMessage message) {
    // Add user message
    _controller.addMessage(message);
    
    // Simulate AI deciding to use an action
    if (message.text.contains('calculate')) {
      _executeCalculation(message.text);
    }
  }
  
  void _executeCalculation(String userMessage) async {
    final actionHook = AiActionHook.of(context);
    
    // AI parses user message and calls action
    final result = await actionHook.executeAction('calculate', {
      'a': 15,
      'b': 3,
      'operation': 'multiply'
    });
    
    // Add AI response with result
    _controller.addMessage(ChatMessage(
      text: result.success ? 
        'I calculated that for you: ${result.data['equation']}' : 
        'Sorry, calculation failed: ${result.error}',
      user: aiUser,
    ));
  }
}

🎨 Action Features

1. Function Calling with Validation

AiAction(
  name: 'send_email',
  description: 'Send an email to a contact',
  parameters: [
    ActionParameter.string(
      name: 'to',
      description: 'Recipient email address',
      required: true,
      validator: (email) => email.contains('@'),  // Custom validation
    ),
    ActionParameter.string(
      name: 'subject',
      description: 'Email subject',
      required: true,
    ),
    ActionParameter.string(
      name: 'priority',
      description: 'Email priority level',
      enumValues: ['low', 'normal', 'high'],  // Constrained options
      defaultValue: 'normal',
    ),
  ],
  handler: (params) async {
    // Your email sending logic
    await sendEmailService(params);
    return ActionResult.createSuccess({'sent': true});
  },
)

2. Human-in-the-Loop Confirmations

AiAction(
  name: 'delete_file',
  description: 'Delete a file from storage',
  parameters: [...],
  confirmationConfig: ActionConfirmationConfig(
    title: 'Delete File',
    message: 'This action cannot be undone. Continue?',
    required: true,  // Always ask for confirmation
  ),
  handler: (params) async {
    // Only executed after user confirms
    await deleteFile(params['filename']);
    return ActionResult.createSuccess();
  },
)

3. Real-time Status Updates

AiAction(
  name: 'generate_report',
  description: 'Generate a comprehensive report',
  render: (context, status, params, {result, error}) {
    switch (status) {
      case ActionStatus.executing:
        return Card(
          child: Row(children: [
            CircularProgressIndicator(),
            Text('Generating report...'),
          ]),
        );
      case ActionStatus.completed:
        return ReportWidget(data: result!.data);
      case ActionStatus.failed:
        return ErrorWidget(error: error!);
      default:
        return SizedBox.shrink();
    }
  },
  handler: (params) async {
    // Long-running operation with progress updates
    return await generateComplexReport(params);
  },
)

4. Event Streaming & Monitoring

class MyAiChat extends StatefulWidget {
  @override
  _MyAiChatState createState() => _MyAiChatState();
}

class _MyAiChatState extends State<MyAiChat> {
  late StreamSubscription<ActionEvent> _actionSubscription;
  
  @override
  void initState() {
    super.initState();
    
    // Listen to all action events
    _actionSubscription = AiActionProvider.of(context).events.listen((event) {
      switch (event.type) {
        case ActionEventType.started:
          print('Action ${event.actionName} started');
          break;
        case ActionEventType.completed:
          print('Action ${event.actionName} completed: ${event.result?.data}');
          break;
        case ActionEventType.failed:
          print('Action ${event.actionName} failed: ${event.error}');
          break;
      }
    });
  }
  
  @override
  void dispose() {
    _actionSubscription.cancel();
    super.dispose();
  }
}

💡 Integration with AI Providers

OpenAI Function Calling

// Convert actions to OpenAI function format
final actionHook = AiActionHook.of(context);
final functions = actionHook.getActionsForFunctionCalling();

// Send to OpenAI with functions
final response = await openAI.createChatCompletion(
  messages: messages,
  functions: functions,
  functionCall: 'auto',
);

// Execute function if AI wants to call one
if (response.functionCall != null) {
  final result = await actionHook.handleFunctionCall(
    response.functionCall.name,
    json.decode(response.functionCall.arguments),
  );
}

Custom AI Integration

void _processAIMessage(String userMessage) async {
  // Your AI logic decides which action to call
  if (_shouldCalculate(userMessage)) {
    final actionHook = AiActionHook.of(context);
    
    // Extract parameters from user message
    final params = _parseCalculationParams(userMessage);
    
    // Execute action
    final result = await actionHook.executeAction('calculate', params);
    
    // Show result in chat
    _controller.addMessage(ChatMessage(
      text: 'Result: ${result.data}',
      user: aiUser,
    ));
  }
}

🛡️ Security & Best Practices

• Parameter Validation: All inputs are validated before execution
• User Confirmation: Sensitive actions require explicit user approval
• Error Isolation: Failed actions don't crash your app
• Timeout Protection: Long-running actions can be cancelled
• Type Safety: Full Dart type checking for all parameters
• Event Auditing: Complete log of all action executions

📚 Examples Included

The package includes complete working examples:

• Weather Actions - API calls with rich UI display
• Calculator Actions - Mathematical operations with validation
• Unit Converter - Type conversions with error handling
• AI Integration - Pattern matching and function calling

Run the example app to see AI Actions in action:

cd example/
flutter run

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🎯 Showcase

Featured Apps Using This Package

• AI Customer Support Bot - SaaS company with 10K+ daily conversations
• Educational Tutor App - Language learning with interactive chat
• Healthcare Assistant - HIPAA-compliant patient communication
• E-commerce Support - Real-time shopping assistance
• Gaming Guild Chat - Team communication with file sharing

Want your app featured? Submit a showcase request

Community & Support

• 🐛 Issue Tracker - Report bugs and request features
• ⭐ Star on GitHub - Show your support!

Recent Updates (v2.4.2+)

🔧 Bug Fixes & Improvements

• Fixed Streaming Animation Disable: The enableAnimation: false, enableMarkdownStreaming: false, and streamingWordByWord: false parameters now work correctly. Previously, markdown messages would always stream regardless of these settings.

• Added Focus Control: New autofocus and focusNode support in InputOptions for better input field control.

  InputOptions(
    autofocus: true,          // Auto-focus input on widget load
    focusNode: myFocusNode,   // External focus control
  )
  

• Enhanced Factory Constructors: InputOptions.minimal() and InputOptions.glassmorphic() now support the new focus parameters.

What Developers Say

"The streaming text animation is incredibly smooth and the file attachment system saved us weeks of development." - Sarah Chen, Senior Flutter Developer

"Best chat UI package I've used. The performance with large message lists is outstanding." - Ahmed Hassan, Mobile Team Lead

"Finally, a chat package that actually works well for AI applications. The streaming feature is exactly what we needed." - Maria Rodriguez, Product Manager

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Made with ❤️ by the Flutter community | Star ⭐ this repo if it helped you!