🤖 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.

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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.

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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

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✨ 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

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📦 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.

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🚀 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);

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🤖 Providers

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

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🛠️ 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

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🔌 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'],
  ),
);

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🗺️ 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

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🤝 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

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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

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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.

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📄 License

MIT