🤖 AI SDK Dart

A Dart/Flutter port of Vercel AI SDK v6 — provider-agnostic APIs for text generation, streaming, structured output, tool use, embeddings, image generation, speech, and more.

What is this?

AI SDK Dart brings the full power of Vercel AI SDK v6 to Dart and Flutter. Write your AI logic once, swap providers without changing a line of business code, and ship on every platform — mobile, web, and server. Every API mirrors its JavaScript counterpart so the official Vercel docs apply directly to your Dart code.

Screenshots

Flutter Chat App (`examples/flutter_chat`)

Multi-turn Chat	Streaming Response

Completion	Object Stream

Advanced App (`examples/advanced_app`)

Provider Chat	Tools Chat

Image Generation	Multimodal

✨ Features

🗣️ Text Generation & Streaming

generateText — single-turn or multi-step text generation with full result envelope
streamText — real-time token streaming with typed event taxonomy
smoothStream transform — configurable chunk-size smoothing for UX
Multi-step agentic loops with maxSteps, prepareStep, and stopConditions
Callbacks: onFinish, onStepFinish, onChunk, onError, experimentalOnStart

🧩 Structured Output

Output.object(schema) — parse model output into a typed Dart object
Output.array(schema) — parse model output into a typed Dart list
Output.choice(options) — constrain output to a fixed set of string values
Output.json() — raw JSON without schema validation
Automatic code-fence stripping (```json ... ```)

🔧 Type-Safe Tools & Multi-Step Agents

tool<Input, Output>() — fully typed tool definitions with JSON schema
dynamicTool() — tools with unknown input type for dynamic use cases
Tool choice: auto, required, none, or specific tool
Tool approval workflow with needsApproval
Multi-step agentic loops with automatic tool result injection
onInputStart, onInputDelta, onInputAvailable lifecycle hooks

🖼️ Multimodal

generateImage — image generation (DALL-E 3 via OpenAI)
generateSpeech — text-to-speech audio synthesis
transcribe — speech-to-text transcription
Image inputs in prompts (multimodal vision)

🧮 Embeddings & Cosine Similarity

embed() — single value embedding with usage tracking
embedMany() — batch embedding for multiple values
cosineSimilarity() — built-in similarity computation

🧱 Middleware System

wrapLanguageModel(model, middlewares) — composable middleware pipeline
extractReasoningMiddleware — strips <think> tags into ReasoningPart
extractJsonMiddleware — strips ```json ``` fences
simulateStreamingMiddleware — converts non-streaming models to streaming
defaultSettingsMiddleware — applies default temperature/top-p/etc.
addToolInputExamplesMiddleware — enriches tool descriptions with examples

🌐 Provider Registry

createProviderRegistry — map provider aliases to model factories
Resolve models by 'provider:modelId' string at runtime
Mix providers in a single registry for multi-provider apps

📱 Flutter UI Controllers

ChatController — multi-turn streaming chat with message history
CompletionController — single-turn text completion with status
ObjectStreamController — streaming typed JSON object updates

🔌 MCP Client (Model Context Protocol)

MCPClient — connect to MCP servers, discover tools, invoke them
SseClientTransport — HTTP SSE transport
StdioMCPTransport — stdio process transport
Discovered tools are directly compatible with generateText/streamText

🧪 Conformance Suite

178+ tests covering every public API
Spec-driven JSON fixtures as the source of truth
Provider wire-format conformance tests for OpenAI, Anthropic, and Google

📦 Packages

Package	pub.dev	What it gives you
`ai_sdk_dart`	`dart pub add ai`	`generateText`, `streamText`, tools, middleware, embeddings, registry
`ai_sdk_openai`	`dart pub add ai_sdk_openai`	`openai('gpt-4.1-mini')`, embeddings, image gen, speech, transcription
`ai_sdk_anthropic`	`dart pub add ai_sdk_anthropic`	`anthropic('claude-sonnet-4-5')`, extended thinking
`ai_sdk_google`	`dart pub add ai_sdk_google`	`google('gemini-2.0-flash')`, embeddings
`ai_sdk_flutter_ui`	`dart pub add ai_sdk_flutter_ui`	`ChatController`, `CompletionController`, `ObjectStreamController`
`ai_sdk_mcp`	`dart pub add ai_sdk_mcp`	`MCPClient`, `SseClientTransport`, `StdioMCPTransport`
`ai_sdk_provider`	(transitive)	Provider interfaces for building custom providers

ai_sdk_provider is a transitive dependency — you do not need to add it directly.

🚀 Quick Start

Dart CLI

dart pub add ai_sdk_dart ai_sdk_openai
export OPENAI_API_KEY=sk-...

import 'package:ai_sdk_dart/ai_sdk_dart.dart';
import 'package:ai_sdk_openai/ai_sdk_openai.dart';

void main() async {
  // Text generation
  final result = await generateText(
    model: openai('gpt-4.1-mini'),
    prompt: 'Say hello from AI SDK Dart!',
  );
  print(result.text);
}

Streaming

final result = await streamText(
  model: openai('gpt-4.1-mini'),
  prompt: 'Count from 1 to 5.',
);
await for (final chunk in result.textStream) {
  stdout.write(chunk);
}

Structured Output

final result = await generateText<Map<String, dynamic>>(
  model: openai('gpt-4.1-mini'),
  prompt: 'Return the capital and currency of Japan as JSON.',
  output: Output.object(
    schema: Schema<Map<String, dynamic>>(
      jsonSchema: const {
        'type': 'object',
        'properties': {
          'capital': {'type': 'string'},
          'currency': {'type': 'string'},
        },
      },
      fromJson: (json) => json,
    ),
  ),
);
print(result.output); // {capital: Tokyo, currency: JPY}

Type-Safe Tools

final result = await generateText(
  model: openai('gpt-4.1-mini'),
  prompt: 'What is the weather in Paris?',
  maxSteps: 5,
  tools: {
    'getWeather': tool<Map<String, dynamic>, String>(
      description: 'Get current weather for a city.',
      inputSchema: Schema(
        jsonSchema: const {
          'type': 'object',
          'properties': {'city': {'type': 'string'}},
        },
        fromJson: (json) => json,
      ),
      execute: (input, _) async => 'Sunny, 18°C',
    ),
  },
);
print(result.text);

Flutter Chat UI

dart pub add ai_sdk_dart ai_sdk_openai ai_sdk_flutter

import 'package:ai_sdk_flutter_ui/ai_sdk_flutter_ui.dart';

final chat = ChatController(model: openai('gpt-4.1-mini'));

// In your widget:
await chat.append('Tell me a joke');
print(chat.messages.last.content);

🤖 Providers

Capability	OpenAI	Anthropic	Google
Text generation	✅	✅	✅
Streaming	✅	✅	✅
Structured output	✅	✅	✅
Tool use	✅	✅	✅
Embeddings	✅	—	✅
Image generation	✅	—	—
Speech synthesis	✅	—	—
Transcription	✅	—	—
Extended thinking	—	✅	—
Multimodal (image input)	✅	✅	✅

🛠️ Flutter UI Controllers

The ai_sdk_flutter_ui package provides three reactive controllers that integrate with any Flutter state management approach.

ChatController — Multi-turn streaming chat

final chat = ChatController(model: openai('gpt-4.1-mini'));

// In your widget:
ListenableBuilder(
  listenable: chat,
  builder: (context, _) {
    return Column(
      children: [
        for (final msg in chat.messages)
          Text('${msg.role}: ${msg.content}'),
        if (chat.isLoading) const CircularProgressIndicator(),
      ],
    );
  },
);

// Send a message:
await chat.append('What is the capital of France?');

CompletionController — Single-turn completion

final completion = CompletionController(model: openai('gpt-4.1-mini'));
await completion.complete('Write a haiku about Dart.');
print(completion.text);

ObjectStreamController — Streaming typed JSON

final controller = ObjectStreamController<Map<String, dynamic>>(
  model: openai('gpt-4.1-mini'),
  schema: Schema<Map<String, dynamic>>(
    jsonSchema: const {'type': 'object'},
    fromJson: (json) => json,
  ),
);
await controller.submit('Describe Japan as a JSON object.');
print(controller.object); // Partial updates arrive in real-time

🔌 MCP Support

Connect to any Model Context Protocol server and use its tools directly in your AI calls:

import 'package:ai_sdk_mcp/ai_sdk_mcp.dart';

final client = MCPClient(
  transport: SseClientTransport(
    url: Uri.parse('http://localhost:3000/mcp'),
  ),
);

await client.initialize();
final tools = await client.tools(); // Returns a ToolSet

final result = await generateText(
  model: openai('gpt-4.1-mini'),
  prompt: 'What files are in the project?',
  tools: tools,
  maxSteps: 5,
);

For stdio-based MCP servers (local processes):

final client = MCPClient(
  transport: StdioMCPTransport(
    command: 'npx',
    args: ['-y', '@modelcontextprotocol/server-filesystem', '/path/to/dir'],
  ),
);

🗺️ Roadmap

✅ Implemented

✅ generateText — full result envelope (text, steps, usage, reasoning, sources, files)
✅ streamText — complete event taxonomy (22 typed event types)
✅ generateObject / structured output (object, array, choice, json)
✅ embed / embedMany + cosineSimilarity
✅ generateImage (OpenAI DALL-E 3)
✅ generateSpeech (OpenAI TTS)
✅ transcribe (OpenAI Whisper)
✅ rerank
✅ Middleware system with 5 built-in middlewares
✅ Provider registry (createProviderRegistry)
✅ Multi-step agentic loops with tool approval
✅ Flutter UI controllers (Chat, Completion, ObjectStream)
✅ MCP client (SSE + stdio transports)
✅ OpenAI, Anthropic, Google providers
✅ 178+ conformance tests

🔜 Planned

🔜 Video generation support
🔜 Streaming MCP tool outputs + automatic reconnection
🔜 Cohere / Vertex AI / Mistral / Ollama providers
🔜 Additional Flutter widgets (file picker, reasoning display, citation cards)
🔜 Dart Edge / Cloudflare Workers support
🔜 WebSocket transport for MCP

🤝 Contributing

Contributions are welcome! Please open an issue first to discuss changes before submitting a PR.

🐛 Bug reports — use the Bug Report template
💡 Feature requests — use the Feature Request template
💬 Questions & discussions — use GitHub Discussions

Running tests

dart pub global activate melos
melos bootstrap
melos test       # run all package tests
melos analyze    # dart analyze across all packages

Or with the Makefile:

make get      # install all workspace dependencies
make test     # run all package tests
make analyze  # run dart analyze
make format   # format all Dart source files

Runnable examples

Set API keys before running:

export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...
export GOOGLE_API_KEY=AIza...

Example	Command	What it shows
Dart CLI	`make run-basic`	`generateText`, streaming, structured output, tools, embeddings, middleware
Flutter chat	`make run`	ChatController, CompletionController, ObjectStreamController
Flutter chat (web)	`make run-web`	Same as above on Chrome
Advanced app	`make run-advanced`	All providers, image gen, TTS, STT, multimodal
Advanced app (web)	`make run-advanced-web`	Same as above on Chrome

Development

Managed with Melos as a monorepo workspace:

dart pub global activate melos
melos bootstrap
melos analyze
melos test

See docs/v6-parity-matrix.md for a feature-by-feature parity matrix against Vercel AI SDK v6.

📄 License

MIT

🤖 AI SDK Dart

What is this?

Screenshots

Flutter Chat App (`examples/flutter_chat`)

Advanced App (`examples/advanced_app`)

✨ Features

🗣️ Text Generation & Streaming

🧩 Structured Output

🔧 Type-Safe Tools & Multi-Step Agents

🖼️ Multimodal

🧮 Embeddings & Cosine Similarity

🧱 Middleware System

🌐 Provider Registry

📱 Flutter UI Controllers

🔌 MCP Client (Model Context Protocol)

🧪 Conformance Suite

📦 Packages

🚀 Quick Start

Dart CLI

Streaming

Structured Output

Type-Safe Tools

Flutter Chat UI

🤖 Providers

🛠️ Flutter UI Controllers

ChatController — Multi-turn streaming chat

CompletionController — Single-turn completion

ObjectStreamController — Streaming typed JSON

🔌 MCP Support

🗺️ Roadmap

✅ Implemented

🔜 Planned

🤝 Contributing

Running tests

Runnable examples

Development

📄 License

Libraries

ai_sdk_dart package

🤖 AI SDK Dart

What is this?

Screenshots

Flutter Chat App (examples/flutter_chat)

Advanced App (examples/advanced_app)

✨ Features

🗣️ Text Generation & Streaming

🧩 Structured Output

🔧 Type-Safe Tools & Multi-Step Agents

🖼️ Multimodal

🧮 Embeddings & Cosine Similarity

🧱 Middleware System

🌐 Provider Registry

📱 Flutter UI Controllers

🔌 MCP Client (Model Context Protocol)

🧪 Conformance Suite

📦 Packages

🚀 Quick Start

Dart CLI

Streaming

Structured Output

Type-Safe Tools

Flutter Chat UI

🤖 Providers

🛠️ Flutter UI Controllers

ChatController — Multi-turn streaming chat

CompletionController — Single-turn completion

ObjectStreamController — Streaming typed JSON

🔌 MCP Support

🗺️ Roadmap

✅ Implemented

🔜 Planned

🤝 Contributing

Running tests

Runnable examples

Development

📄 License

Libraries

ai_sdk_dart package

Flutter Chat App (`examples/flutter_chat`)

Advanced App (`examples/advanced_app`)