Dart framework for stateful AI agents — tool use, skills, sub-agent delegation, planning, streaming, and multi-provider LLM support (OpenAI, Gemini, Bedrock).

Dart Agent Core

A mobile-first, local-first Dart library for building stateful, tool-using AI agents

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dart_agent_core is a mobile-first, local-first Dart library that implements an agentic loop with tool use, state persistence, and multi-turn memory. It connects to LLM APIs (OpenAI, Gemini, AWS Bedrock) and handles the orchestration layer — tool calling, streaming, context management, and sub-agent delegation — entirely in Dart, which makes it suitable for use in Flutter apps without a Python or Node.js backend.

Features

• Multi-provider support: Unified LLMClient interface for OpenAI (Chat Completions & Responses API), Google Gemini, and Anthropic Claude via AWS Bedrock.
• Tool use: Wrap any Dart function as a tool with a JSON Schema definition. The agent dispatches calls, feeds results back, and loops until done. Tools can return AgentToolResult to carry multimodal content, metadata, or a stop signal.
• Multimodal input: UserMessage accepts text, images, audio, video, and documents as content parts. Model responses can include text, images, video, and audio.
• Stateful sessions: AgentState tracks conversation history, token usage, active skills, plan, and custom metadata. FileStateStorage persists state to disk as JSON.
• Streaming: runStream() yields StreamingEvents for model chunks, tool call requests/results, and retries — suitable for real-time UI updates in Flutter.
• Pure Dart Skills: Define modular capabilities (Skill) with their own system prompts and tools. Ski