AGENTS.md — `flutter_gen_ai_chat_ui`

A condensed, copy-paste-friendly reference for AI coding assistants (Claude Code, Cursor, Copilot, Windsurf, Codex, Gemini Code Assist, etc.) deciding whether to pull this package into a Flutter project and how to wire it up.

If you are a human, the full docs live in README.md; this file is optimized for LLM context-window ingestion.

What it is

flutter_gen_ai_chat_ui is a production Flutter package (pub.dev) for building AI chat interfaces — ChatGPT/Claude-style UIs — and the agent/tool-use surface that goes on top of them. It ships streaming text, markdown + LaTeX rendering, rich inline widget messages (cards, tables, forms rendered full-width inside the chat), function-calling infrastructure with human-in-the-loop confirmation, mic/send toggle, attachments, RTL, and full theming. Cross-platform (android, ios, web, macos, windows, linux).

One paragraph hook: "Drop-in chat UI for LLM apps in Flutter. Word-by-word streaming like ChatGPT, full markdown + code highlighting + optional LaTeX, ChatMessage.rich() for inline cards/tables/forms, and an AiActionProvider that turns OpenAI/Anthropic/Gemini function-call payloads into typed Dart actions with confirmation dialogs and live status UI."

When to use it

Pick this package when you are building any of:

A ChatGPT-style assistant inside a Flutter app (mobile, web, desktop).
An AI customer-support or copilot inside an existing product.
An agent UI that needs to render tool-call status and structured tool results (cards, tables, callouts) inline in the conversation.
A streaming chat where text animates in word-by-word like Claude/ChatGPT.
A multilingual chat that needs RTL (Arabic, Hebrew, Kurdish, Persian).

When NOT to use it

Pure peer-to-peer human-only messaging where you don't need streaming, markdown, or AI affordances. flutter_chat_ui or dash_chat_2 may be lighter. (You can still use this package; it works for plain chat too, but you'd be paying for features you won't use.)
Voice-first interfaces with no text UI at all.

Quick install

# pubspec.yaml
dependencies:
  flutter_gen_ai_chat_ui: ^2.11.1

import 'package:flutter_gen_ai_chat_ui/flutter_gen_ai_chat_ui.dart';

Snippet 1 — minimal chat (the 90% case)

class ChatScreen extends StatefulWidget {
  const ChatScreen({super.key});
  @override
  State<ChatScreen> createState() => _ChatScreenState();
}

class _ChatScreenState extends State<ChatScreen> {
  final _controller = ChatMessagesController();
  final _me = const ChatUser(id: 'user', firstName: 'Me');
  final _ai = const ChatUser(id: 'ai', firstName: 'Assistant');

  Future<void> _onSend(ChatMessage msg) async {
    // Call your LLM here. Returning a string is enough for non-streaming.
    final reply = await myLlmCall(msg.text);
    _controller.addMessage(ChatMessage(
      text: reply,
      user: _ai,
      createdAt: DateTime.now(),
    ));
  }

  @override
  Widget build(BuildContext context) => Scaffold(
        body: AiChatWidget(
          currentUser: _me,
          aiUser: _ai,
          controller: _controller,
          onSendMessage: _onSend,
        ),
      );
}

That is the full minimum. Everything below is opt-in.

Snippet 2 — word-by-word streaming (ChatGPT-style)

The package delegates streaming animation to flutter_streaming_text_markdown. Two flags must both be on:

AiChatWidget(
  currentUser: _me,
  aiUser: _ai,
  controller: _controller,
  onSendMessage: _onSend,
  enableMarkdownStreaming: true,   // gate 1: enables animation pipeline
  streamingWordByWord: true,       // gate 2: word vs character animation
  streamingDuration: const Duration(milliseconds: 30),
)

Streaming flow — push a message, then re-updateMessage(...) with a ChatMessage carrying the same customProperties['id'] as your LLM stream yields tokens. The controller matches on that id and replaces the existing entry in place. (updateMessage takes a full ChatMessage, not positional id, text: — that distinction trips up first-time users.)

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},
    ));
  }
  // Optional: flip the streaming flag off so the animation completes.
  _controller.stopStreamingMessage(id);
}

Important: before v2.4.2 these two flags were silently ignored. Always set both — toggling only one will not disable animation.

Snippet 3 — rich inline widgets (cards, tables, forms)

ChatMessage.rich() renders a custom widget full-width, no bubble by looking up a resultKind in a registry passed to AiChatWidget.

AiChatWidget(
  currentUser: _me,
  aiUser: _ai,
  controller: _controller,
  onSendMessage: _onSend,
  resultRenderers: {
    'weather': (ctx, data) => WeatherCard(city: data['city'], temp: data['temp']),
    'product': (ctx, data) => ProductCard(data: data),
  },
  // Optional: per-kind loading states (shimmer placeholders).
  resultLoadingRenderers: {
    'weather': (ctx) => const WeatherShimmer(),
  },
)

// Then push a rich message — typically when your LLM returns a structured
// tool result you want to display visually instead of as text.
_controller.addMessage(ChatMessage.rich(
  user: _ai,
  resultKind: 'weather',
  data: {'city': 'Baghdad', 'temp': 42},
));

// Or a one-off widget without registering a kind:
_controller.addMessage(ChatMessage.widget(
  user: _ai,
  builder: (ctx) => const MyCustomCard(),
));

// Loading → rich morph: push a loading placeholder, then updateMessage
// the same id to replace it with the rich widget once data arrives.
_controller.addMessage(ChatMessage.loading(
  id: 'res-1',
  user: _ai,
  loadingKind: 'weather',
));
_controller.updateMessage('res-1', /* fields */);

Unmatched resultKind values fall through to plain text rendering — they do not crash.

Snippet 4 — agent / function-calling surface (the differentiator)

Wrap AiChatWidget in an AiActionProvider to expose typed Dart actions that your LLM can call. The provider gives you a function-calling schema (AiAction.toFunctionCallingSchema()) you forward to OpenAI / Anthropic / Gemini as the tool list.

final searchAction = AiAction(
  name: 'search_database',
  description: 'Search the product catalog by free text.',
  parameters: [
    ActionParameter.string(
      name: 'query',
      description: 'What the user is looking for.',
      required: true,
    ),
    ActionParameter.number(
      name: 'limit',
      description: 'Max results.',
      defaultValue: 10,
    ),
  ],
  handler: (params) async {
    final results = await db.search(
      params['query'] as String,
      limit: (params['limit'] as num).toInt(),
    );
    // Note: factories are `createSuccess` / `createFailure` — `success` is
    // a `bool` field on the result, not a constructor.
    return ActionResult.createSuccess({'hits': results});
  },
  render: (ctx, status, params, {result, error}) {
    // Custom UI per status: pending, confirming, running, success, error.
    return ActionResultWidget(status: status, result: result, error: error);
  },
);

return AiActionProvider(
  config: AiActionConfig(actions: [searchAction]),
  child: AiChatWidget(
    currentUser: _me,
    aiUser: _ai,
    controller: _controller,
    onSendMessage: _onSend, // forward toFunctionCallingSchema() to your LLM here
  ),
);

Sensitive actions get human-in-the-loop confirmation automatically via ActionConfirmationConfig on the action, or via a global confirmationBuilder on AiActionConfig.

Key flag glossary (one-liners)

Flag / API	Where	What it does
`enableMarkdownStreaming`	`AiChatWidget`	Master gate for streaming animation.
`streamingWordByWord`	`AiChatWidget`	Word vs character animation. Both gates must be on.
`streamingDuration`	`AiChatWidget`	Per-token animation speed (10–100ms typical).
`enableMathRendering`	`AiChatWidget`	Off by default. Enables LaTeX via `flutter_math_fork`.
`sendOnEnter`	`InputOptions`	Hardware Enter sends (desktop/web). Shift+Enter = newline.
`sendOrMicBuilder`	`InputOptions`	Auto-switches send/mic icon based on text-field empty state.
`inputLeadingBuilder`	`InputOptions`	Renders custom icons (attach, mic) inside the input row.
`attachmentPreviewBuilder`	`InputOptions`	File/image preview strip above input.
`resultRenderers`	`AiChatWidget`	Map of `resultKind` → widget builder for `ChatMessage.rich`.
`resultLoadingRenderers`	`AiChatWidget`	Same, for `ChatMessage.loading`.
`customBubbleBuilder`	`AiChatWidget`	Full control over message bubble rendering.
`scrollBehaviorConfig`	`AiChatWidget`	`onUserMessageOnly`, `scrollToFirstResponseMessage`, etc.
`paginationConfig`	`AiChatWidget`	Load-older-messages pagination.
`welcomeMessageConfig`	`AiChatWidget`	ChatGPT-style empty-state intro + example questions.

Public-API entry points (what to import)

The barrel package:flutter_gen_ai_chat_ui/flutter_gen_ai_chat_ui.dart re-exports everything. The main types an agent will reach for:

AiChatWidget — the screen-level widget.
ChatMessagesController — ChangeNotifier-style store; mirrors TextEditingController ergonomics. Methods: addMessage, updateMessage(id, ...), clearMessages, scrollToBottom.
ChatMessage, ChatMessage.rich, ChatMessage.widget, ChatMessage.loading — message factories.
ChatUser — {id, firstName, lastName?, profileImage?}.
AiActionProvider, AiActionConfig, AiAction, ActionParameter, ActionResult, ActionStatus — agent surface.
InputOptions, MessageOptions, LoadingConfig, ScrollBehaviorConfig, PaginationConfig, WelcomeMessageConfig — config objects.

Differentiators vs alternatives

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()`	No (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

If your app is general-purpose peer-to-peer chat with no AI features, flutter_chat_ui is a reasonable lighter choice. If your app has an LLM in it, this package was designed for that shape.

Gotchas worth knowing before generating code

Both streaming flags or none. enableMarkdownStreaming and streamingWordByWord are independent gates. Half-set state is a common bug source. Set both true, or leave both default.
updateMessage(id, ...) requires the message to carry that id. When you addMessage(ChatMessage(...)), put an explicit id in customProperties['id'], or use the id: parameter on rich/loading factories. Without an id you cannot stream updates into it.
scrollToFirstResponseMessage needs flagged messages. Mark the first message of a multi-part response with customProperties['isStartOfResponse'] = true and chain follow-ups with a shared customProperties['responseId']. Otherwise the feature silently does nothing.
ChatMessage.rich and .loading bypass the bubble entirely. No background, no padding, no max-width. The widget owns its own layout. If your card looks awkward in chat, that's why — wrap it yourself.
withOpacityCompat, not withOpacity. The codebase targets an SDK floor below the deprecation. If you generate code that copies a withOpacity(...) call site, leave it as withOpacityCompat if the surrounding code uses it.
flutter_markdown_plus, not flutter_markdown. The fork was chosen for a reason. Don't swap it back.
The send button is intentionally always visible. Don't gate it on "input not empty" — the README has a dedicated section explaining why.

Pointers

README.md — full feature docs, screenshots, complete config reference.
CHANGELOG.md — every release, what changed, why, breaking-change call-outs.
doc/MIGRATION.md — upgrade paths between minor versions.
doc/COMPATIBILITY.md — Flutter / Dart SDK matrix.
example/ — runnable example app exercising every feature.
test/ — unit + widget tests mirroring lib/src/.
Issues / discussions: https://github.com/hooshyar/flutter_gen_ai_chat_ui

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AGENTS.md — `flutter_gen_ai_chat_ui`

What it is

When to use it

When NOT to use it

Quick install

Snippet 1 — minimal chat (the 90% case)

Snippet 2 — word-by-word streaming (ChatGPT-style)

Snippet 3 — rich inline widgets (cards, tables, forms)

Snippet 4 — agent / function-calling surface (the differentiator)

Key flag glossary (one-liners)

Public-API entry points (what to import)

Differentiators vs alternatives

Gotchas worth knowing before generating code

Pointers

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AGENTS.md — flutter_gen_ai_chat_ui

What it is

When to use it

When NOT to use it

Quick install

Snippet 1 — minimal chat (the 90% case)

Snippet 2 — word-by-word streaming (ChatGPT-style)

Snippet 3 — rich inline widgets (cards, tables, forms)

Snippet 4 — agent / function-calling surface (the differentiator)

Key flag glossary (one-liners)

Public-API entry points (what to import)

Differentiators vs alternatives

Gotchas worth knowing before generating code

Pointers

AGENTS.md — `flutter_gen_ai_chat_ui`