Council provides a structured environment for designing AI agents by defining roles, chaining tasks, and integrating external tools or APIs. Users can configure memory stores, manage agent state, and implement custom reasoning pipelines. Council’s plugin architecture allows seamless integration with NLP services, data sources, and third-party tools, enabling you to rapidly prototype and deploy multi-agent systems that coordinate to perform complex tasks reliably.

LangGraph Studio is the first Integrated Development Environment (IDE) designed for creating AI agents using the LangChain framework. It enables developers to visually design workflows, manage data connections, and integrate multiple processing components. Users can leverage powerful debugging tools, version control, and real-time collaboration features, making it easier to develop complex AI applications efficiently. This IDE is aimed at simplifying the development process, allowing both novices and experienced developers to build robust AI agents.

ai-agents-trial is an open-source Python project demonstrating how to build autonomous AI agents using LLMs. It provides modular abstractions for agent planning, tool invocation (e.g., web search, calculators), and memory management. Developers can define custom tools, chain actions across multiple steps, and persist context across sessions. The codebase uses OpenAI APIs alongside helper utilities to orchestrate workflows, making it ideal for rapid prototyping of chat-based assistants, research bots, or domain-specific automation agents. Integration points allow extending functionality with new connectors and data sources without altering core logic.