TinAI

TinAI is a modular open-source framework for constructing autonomous artificial intelligence agents and multi-agent systems. It emphasizes a plugin-based architecture that separates core control, perception, planning, and action execution from task-specific logic. The design aims to pair flexibility with safety, enabling researchers to swap components and test different decision-making strategies.

The project provides a core runtime and a library of interchangeable modules. Perception modules can connect to sensors or data streams; memory modules manage short- and long-term representations; planners generate sequences of actions; tool-using adapters enable external API calls or sandboxed web access. Language interfaces allow agents to interpret and generate natural language. The ecosystem supports integration with popular ML backends and simulation environments.

TinAI supports both single-agent and multi-agent configurations, enabling coordination strategies such as bidding, negotiation, and collaborative planning. It includes tooling for experimentation, logging, and reproducibility, with sandboxing and safety controls to mitigate unintended behavior. Extensions cover reinforcement learning, symbolic reasoning, and retrieval-augmented generation.

Typical use cases include robotics, virtual assistants, game AI, research into agent architectures, and educational demonstrations. The project is maintained under a permissive software license and encourages community contributions, documentation improvements, and interoperability with standard data formats.

Reception has highlighted the clarity of its plugin interfaces and its emphasis on modularity, while some critics note the learning curve and the need for mature benchmarks to compare agents across tasks.