LiteSwarm is a comprehensive AI agent orchestration framework designed to facilitate collaboration among multiple specialized agents. Users define individual agents with distinct roles—such as data fetching, analysis, summarization, or external API calls—and link them within a visual workflow. LiteSwarm handles inter-agent communication, persistent memory storage, error recovery, and logging. It supports API integration, custom code extensions, and real-time monitoring, so teams can prototype, test, and deploy complex multi-agent solutions without extensive engineering overhead.

AgentSmith is a modular agent orchestration framework built in Python that enables developers to define, configure, and run multiple AI agents collaboratively. Each agent can be assigned specialized roles—such as researcher, planner, coder, or reviewer—and communicate via an internal message bus. AgentSmith supports memory management through vector stores like FAISS or Pinecone, task decomposition into subtasks, and automated supervision to ensure goal completion. Agents and pipelines are configured via human-readable YAML files, and the framework integrates seamlessly with OpenAI APIs and custom LLMs. It includes built-in logging, monitoring, and error handling, making it ideal for automating software development workflows, data analysis, and decision support systems.