ThreeAgents is built in Python, leveraging OpenAI's chat completions API to instantiate multiple AI agents with distinct roles (system, assistant, user). It provides abstractions for agent prompting, role-based message handling, and context memory management. Developers can define custom prompt templates, configure agent personalities, and chain interactions to simulate realistic dialogues or task-oriented workflows. The framework handles message passing, context window management, and logging, enabling experiments in collaborative decision-making or hierarchical task decomposition. With support for environment variables and modular agents, ThreeAgents allows seamless swapping between OpenAI and local LLM backends, facilitating rapid prototyping of multi-agent AI systems. It ships with example scripts and Docker support for quick setup.

AI-Agents provides a modular architecture for defining and running Python-based AI agents. Developers can configure agent behaviors, integrate external APIs or tools, and manage agent memory across sessions. It leverages popular LLMs, supports multi-agent collaboration, and enables plugin-based extensions for complex workflows like data analysis, automated support, and personalized assistants.

Anyscale provides a unified compute platform that integrates seamlessly with the Ray framework, offering a fully managed solution for developing, scaling, and deploying AI applications. By abstracting away the complexities of infrastructure management, Anyscale enables developers to focus on building innovative AI solutions. The platform supports extensive integration with popular AI/ML libraries and frameworks, making it suitable for varying workloads, from batching to real-time inference. Anyscale is designed to cater to both beginners and experts in AI development, providing robust tools for efficient and scalable AI application development.