llm_dart 0.8.0

A modular Dart library for AI provider interactions with unified interface for OpenAI, Anthropic, Google, DeepSeek, Ollama, xAI, Groq, ElevenLabs and more.

example/README.md

LLM Dart Examples

Practical examples for the LLM Dart library, organized by learning path and use case.

Quick Start

I need to...	Go to
Get started quickly	quick_start.dart
Build a chatbot	chatbot.dart
Compare providers	provider_comparison.dart
Use streaming	streaming_chat.dart
Call functions	tool_calling.dart
Handle audio	audio_processing.dart
Generate images	image_generation.dart
Process large datasets	batch_processor.dart
Build multimodal apps	multimodal_app.dart
Connect external tools	mcp_concept_demo.dart

Directory Structure

Getting Started

First-time users

• quick_start.dart - Basic usage
• provider_comparison.dart - Compare providers
• basic_configuration.dart - Configuration
• environment_setup.dart - Environment setup

Core Features

Essential functionality

• capability_factory_methods.dart - Type-safe provider initialization
• chat_basics.dart - Basic chat
• streaming_chat.dart - Real-time streaming
• tool_calling.dart - Function calling
• enhanced_tool_calling.dart - Advanced tool usage
• structured_output.dart - JSON output
• assistants.dart - AI assistants
• embeddings.dart - Text embeddings
• audio_processing.dart - Speech/TTS
• image_generation.dart - Image generation
• file_management.dart - File operations
• web_search.dart - Web search integration
• content_moderation.dart - Content filtering
• model_listing.dart - Available models
• capability_detection.dart - Feature detection
• error_handling.dart - Error handling

Advanced Features

Specialized capabilities

• reasoning_models.dart - AI thinking processes
• multi_modal.dart - Images/audio processing
• batch_processing.dart - Concurrent processing
• realtime_audio.dart - Real-time audio
• semantic_search.dart - Vector search
• custom_providers.dart - Custom providers
• performance_optimization.dart - Optimization

Provider Examples

Provider-specific features

Provider	Features	Directory
OpenAI	GPT, DALL-E, assistants	openai/
Anthropic	Claude, thinking	anthropic/
DeepSeek	Reasoning, cost-effective	deepseek/
Groq	Fast inference	groq/
Ollama	Local models	ollama/
ElevenLabs	Voice synthesis	elevenlabs/
xAI	Live search, Grok	xai/
Others	OpenAI-compatible	others/

Use Cases

Complete applications

• chatbot.dart - Interactive chatbot with personality
• cli_tool.dart - Command-line AI assistant
• web_service.dart - HTTP API with authentication
• flutter_integration.dart - Flutter app patterns
• batch_processor.dart - Large-scale data processing
• multimodal_app.dart - Text, image, and audio processing

MCP Integration

External tool connections

• mcp_concept_demo.dart - Core concepts
• simple_mcp_demo.dart - Basic integration
• basic_mcp_client.dart - MCP client
• custom_mcp_server_stdio.dart - Custom server
• mcp_tool_bridge.dart - Tool bridging
• mcp_with_llm.dart - LLM integration
• test_all_examples.dart - Test runner

Setup

Set API keys for the providers you want to use:

export OPENAI_API_KEY="your-key"
export ANTHROPIC_API_KEY="your-key"
export GROQ_API_KEY="your-key"
export DEEPSEEK_API_KEY="your-key"

Run examples:

dart run 01_getting_started/quick_start.dart
dart run 02_core_features/chat_basics.dart
dart run 05_use_cases/chatbot.dart
dart run 05_use_cases/batch_processor.dart --help
dart run 05_use_cases/multimodal_app.dart --demo

Learning Path

Beginner: Start with quick_start.dart → provider_comparison.dart → chat_basics.dart

Intermediate: Focus on tool_calling.dart → structured_output.dart → chatbot.dart

Advanced: Study batch_processor.dart → multimodal_app.dart → custom_providers.dart

Production: Explore performance_optimization.dart → provider-specific features → MCP integration

Production Example

Yumcha - A production Flutter app built with LLM Dart, showcasing real-world integration patterns and best practices.

Resources

• Main Documentation
• API Reference
• GitHub Issues