AgentJo

AgentJo is an open-source, task-based agentic framework designed for efficient and focused execution. Unlike conversational-text-heavy frameworks, AgentJo leverages StrictJSON, a robust JSON parser with type checking, enabling agents to perform Chain of Thought reasoning natively through JSON keys and descriptions. This approach minimizes verbosity, making agents highly efficient. AgentJo's unique Global Context feature allows agents to access and learn from environmental states and shared variables across tasks, promoting adaptability and continuous learning. Its task-oriented design facilitates the automatic generation of subtasks and incorporates a memory buffer for past interactions, ensuring seamless task completion.

AgentJo is aimed at developers and AI practitioners seeking an effective, non-verbose solution for building and integrating agents into their workflows. The framework offers both automatic and manual function control, giving users full command over task execution. Through free consultations, users can explore the possibilities of integrating AgentJo into their production pipelines. By prioritizing focused task execution, learning through shared variables, and adaptable agent behavior, AgentJo provides a practical and powerful platform for task-based AI development.