genkit_anthropic 0.3.1

genkit_anthropic: ^0.3.1 copied to clipboard

Anthropic plugin for Genkit Dart.

Usage #

Initialization #

import 'dart:io';
import 'package:genkit/genkit.dart';
import 'package:genkit_anthropic/genkit_anthropic.dart';

void main() async {
  // Initialize Genkit with the Anthropic plugin
  // Make sure ANTHROPIC_API_KEY is allowed in your environment
  final ai = Genkit(
    plugins: [anthropic(apiKey: Platform.environment['ANTHROPIC_API_KEY']!)],
  );
}

Basic Generation #

final response = await ai.generate(
  model: anthropic.model('claude-sonnet-4-5'),
  prompt: 'Tell me a joke about a developer.',
);
print(response.text);

Streaming #

final stream = ai.generateStream(
  model: anthropic.model('claude-sonnet-4-5'),
  prompt: 'Count to 5',
);

await for (final chunk in stream) {
  print(chunk.text);
}

final response = await stream.onResult;
print('Full response: ${response.text}');

Tool Calling #

import 'package:schemantic/schemantic.dart';

part 'main.g.dart';

@Schema()
abstract class $CalculatorInput {
  int get a;
  int get b;
}

// ... inside main ...

ai.defineTool(
  name: 'calculator',
  description: 'Multiplies two numbers',
  inputSchema: CalculatorInput.$schema,
  outputSchema: .integer(),
  fn: (input, context) async => .response(input.a * input.b),
);

final response = await ai.generate(
  model: anthropic.model('claude-sonnet-4-5'),
  prompt: 'What is 123 * 456?',
  toolNames: ['calculator'],
);

print(response.text);

Thinking #

final response = await ai.generate(
  model: anthropic.model('claude-sonnet-5'),
  prompt: 'Solve this 24 game: 2, 3, 10, 10',
  config: AnthropicOptions(
    // Uses the model's compatible default thinking mode.
    thinking: ThinkingConfig(),
    outputConfig: AnthropicOutputConfig(effort: 'high'),
  ),
);

// The thinking content is available in the message parts
print(response.message?.content);

An omitted thinking type resolves to the model's own default: Claude 4.6 and newer default to adaptive, while Claude 4.5 models default to enabled, which uses a manual token budget. You can also select a mode explicitly with ThinkingConfig(type: 'enabled', budgetTokens: 2048). For model names outside the curated catalog, set thinking.type explicitly so the plugin does not guess an incompatible mode.

Structured Output #

@Schema()
abstract class $Person {
  String get name;
  int get age;
}

// ... inside main ...

final response = await ai.generate(
  model: anthropic.model('claude-sonnet-4-5'),
  prompt: 'Generate a person named John Doe, age 30',
  outputSchema: Person.$schema,
);

final person = response.output; // Typed Person object
print('Name: ${person.name}, Age: ${person.age}');