AiChat offers a versatile toolkit for creating intelligent chat agents by providing role-based prompt management, memory handling, and streaming response capabilities. Users can set up multiple conversational roles, such as system, assistant, and user, to shape dialogue context and behavior. The framework supports plugin integrations for external APIs, data retrieval, or custom logic, enabling seamless extension of functionalities. AiChat's modular design allows easy swapping of language models and configuration of feedback loops to refine responses. Built-in memory features provide context persistence across sessions, while streaming API support delivers low-latency interactions. Developers benefit from clear documentation and sample projects to accelerate deployment of chatbots across web, desktop, or server environments.

Mina provides a lightweight yet powerful foundation for constructing AI agents in Python. You can define custom tools (such as web scrapers, calculators, or database connectors), attach memory buffers to maintain conversational context, and orchestrate sequences of calls to language models for multi-step reasoning. Built on top of common LLM APIs, Mina handles asynchronous execution, error handling, and logging out of the box. Its modular design makes it easy to extend with new capabilities, while the CLI interface enables quick prototyping and deployment of agent-driven applications.