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320 lines
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<li><a href="/csharp-examples.html">C# Examples</a></li>
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<li><a href="/dart-examples.html" class="active">Dart Examples</a></li>
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<a href="https://uncloseai.com"><h1 class="unturf" style="font-family: 'ChunkFiveRegular';">uncloseai.</h1></a>
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<p>Dart Examples - Free LLM & TTS AI Service</p>
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</header>
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<h2 id="dart-intro">Dart Examples</h2>
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<p>This page demonstrates how to use the <strong>uncloseai.</strong> API endpoints with Dart/Flutter using the dart_openai community library. All examples use the same OpenAI-compatible API interface, making it easy to switch between different models and endpoints.</p>
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<p><strong>Available Endpoints:</strong></p>
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<ul>
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<li><strong>Hermes:</strong> <code>https://hermes.ai.unturf.com/v1</code> - General purpose conversational AI</li>
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<li><strong>Qwen 3 Coder:</strong> <code>https://qwen.ai.unturf.com/v1</code> - Specialized coding model</li>
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<li><strong>TTS:</strong> <code>https://speech.ai.unturf.com/v1</code> - Text-to-speech generation</li>
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</ul>
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<h3 id="dart-client">Dart Client Installation</h3>
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<p>Add dart_openai to your <code>pubspec.yaml</code>:</p>
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<pre><code class="yaml">dependencies:
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dart_openai: ^5.1.0</code></pre>
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<h2 id="dart-non-streaming">Non-Streaming Examples</h2>
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<p>Non-streaming mode waits for the complete response before returning. This is simpler to use but provides no intermediate feedback during generation.</p>
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<h3 id="dart-hermes-non-stream">Using Hermes (General Purpose)</h3>
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<pre><code class="dart">import 'package:dart_openai/dart_openai.dart';
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void main() async {
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OpenAI.apiKey = "choose-any-value";
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OpenAI.baseUrl = "https://hermes.ai.unturf.com/v1";
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final chatCompletion = await OpenAI.instance.chat.create(
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model: "adamo1139/Hermes-3-Llama-3.1-8B-FP8-Dynamic",
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messages: [
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OpenAIChatCompletionChoiceMessageModel(
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role: OpenAIChatMessageRole.user,
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content: [
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OpenAIChatCompletionChoiceMessageContentItemModel.text(
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"Give a Python Fizzbuzz solution in one line of code?"
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),
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],
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),
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],
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temperature: 0.5,
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maxTokens: 150,
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);
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print(chatCompletion.choices.first.message.content?.first.text);
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}
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</code></pre>
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<h3 id="dart-qwen-non-stream">Using Qwen 3 Coder (Specialized for Coding)</h3>
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<pre><code class="dart">import 'package:dart_openai/dart_openai.dart';
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void main() async {
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OpenAI.apiKey = "choose-any-value";
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OpenAI.baseUrl = "https://qwen.ai.unturf.com/v1";
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final chatCompletion = await OpenAI.instance.chat.create(
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model: "hf.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF:Q4_K_M",
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messages: [
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OpenAIChatCompletionChoiceMessageModel(
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role: OpenAIChatMessageRole.user,
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content: [
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OpenAIChatCompletionChoiceMessageContentItemModel.text(
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"Give a Python Fizzbuzz solution in one line of code?"
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),
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],
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),
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],
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temperature: 0.5,
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maxTokens: 150,
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);
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print(chatCompletion.choices.first.message.content?.first.text);
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}
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</code></pre>
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<h2 id="dart-streaming">Streaming Examples</h2>
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<p>Streaming mode returns chunks of the response as they are generated, providing real-time feedback. This is ideal for interactive applications and long responses.</p>
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<h3 id="dart-hermes-stream">Using Hermes (General Purpose)</h3>
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<pre><code class="dart">import 'package:dart_openai/dart_openai.dart';
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import 'dart:io';
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void main() async {
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OpenAI.apiKey = "choose-any-value";
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OpenAI.baseUrl = "https://hermes.ai.unturf.com/v1";
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final chatStream = OpenAI.instance.chat.createStream(
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model: "adamo1139/Hermes-3-Llama-3.1-8B-FP8-Dynamic",
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messages: [
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OpenAIChatCompletionChoiceMessageModel(
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role: OpenAIChatMessageRole.user,
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content: [
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OpenAIChatCompletionChoiceMessageContentItemModel.text(
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"Give a Python Fizzbuzz solution in one line of code?"
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),
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],
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),
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],
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temperature: 0.5,
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maxTokens: 150,
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);
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await for (final chunk in chatStream) {
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final content = chunk.choices.first.delta.content;
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if (content != null && content.isNotEmpty) {
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stdout.write(content.first.text);
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}
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}
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}
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</code></pre>
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<h3 id="dart-qwen-stream">Using Qwen 3 Coder (Specialized for Coding)</h3>
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<pre><code class="dart">import 'package:dart_openai/dart_openai.dart';
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import 'dart:io';
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void main() async {
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OpenAI.apiKey = "choose-any-value";
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OpenAI.baseUrl = "https://qwen.ai.unturf.com/v1";
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final chatStream = OpenAI.instance.chat.createStream(
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model: "hf.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF:Q4_K_M",
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messages: [
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OpenAIChatCompletionChoiceMessageModel(
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role: OpenAIChatMessageRole.user,
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content: [
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OpenAIChatCompletionChoiceMessageContentItemModel.text(
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"Give a Python Fizzbuzz solution in one line of code?"
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),
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],
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),
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],
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temperature: 0.5,
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maxTokens: 150,
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);
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await for (final chunk in chatStream) {
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final content = chunk.choices.first.delta.content;
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if (content != null && content.isNotEmpty) {
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stdout.write(content.first.text);
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}
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}
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}
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</code></pre>
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<h2 id="dart-tts">Text-to-Speech Example</h2>
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<p>Generate audio speech from text using the TTS endpoint. The audio is saved as an MP3 file.</p>
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<pre><code class="dart">import 'package:dart_openai/dart_openai.dart';
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import 'dart:io';
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void main() async {
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OpenAI.apiKey = "YOLO";
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OpenAI.baseUrl = "https://speech.ai.unturf.com/v1";
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final speech = await OpenAI.instance.audio.createSpeech(
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model: "tts-1",
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input: "I think so therefore, Today is a wonderful day to build something people love!",
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voice: "alloy",
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speed: 0.9,
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);
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final file = File("speech.mp3");
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await file.writeAsBytes(speech);
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print("Audio saved to: ${file.path}");
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}
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</code></pre>
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<ul>
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<li><a href="#dart-intro" class="active">Overview</a></li>
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<li><a href="#dart-client">Installation</a></li>
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<li><a href="#dart-non-streaming">Non-Streaming</a>
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<ul>
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<li><a href="#dart-hermes-non-stream">Hermes</a></li>
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<li><a href="#dart-qwen-non-stream">Qwen Coder</a></li>
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<ul>
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<li><a href="#dart-hermes-stream">Hermes</a></li>
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<li><a href="#dart-qwen-stream">Qwen Coder</a></li>
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</ul>
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</li>
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<li><a href="#dart-tts">Text-to-Speech</a></li>
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</ul>
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