Crewai provides a Python-based library to design and execute multi-AI agent systems. Users can define individual agents with specialized roles, configure messaging channels for inter-agent communication, and implement dynamic planners to allocate tasks based on real-time context. Its modular architecture enables plugging in different LLMs or custom models for each agent. Built-in logging and monitoring tools track conversations and decisions, allowing seamless debugging and iterative refinement of agent behaviors.

MultiMind is an AI platform that enables developers to build multi-agent workflows by defining specialized agents for tasks like data analysis, support chatbots, and content generation. It provides a visual workflow builder alongside Python and JavaScript SDKs, automates inter-agent communication, and maintains persistent memory. You can integrate external APIs and deploy projects on MultiMind cloud or your own infrastructure, ensuring scalable, modular AI applications without extensive boilerplate code.

Multi-Agent-Conversation-AutoGen is engineered to automate the creation of interactive dialogue sequences among multiple AI agents for testing, research, and educational applications. Users supply a configuration file to define agent profiles, personas, and conversation flows. The framework orchestrates turn-based interactions, leveraging OpenAI GPT APIs to generate each message dynamically. Key features include customizable prompt templates, flexible API integration, conversation length control, and exportable logs in JSON or text formats. With this tool, developers can simulate complex group discussions, stress-test conversational agents in diverse scenarios, and rapidly produce large sets of dialogue data without manual scripting. The modular architecture allows extension to other LLM providers and integration into existing development pipelines.