deep-agents-core

You can build a multi-agent system with planning and task delegation using the Deep Agents framework, which provides a "Hub and Spoke" architecture for creating core agents and specialized subagents. It guides you through agent creation, context management, and middleware configuration.

Configuring AI agent middleware and tools is handled through the Deep Agents framework's comprehensive configuration options. You can select middleware capabilities, define custom tools, and apply persistence settings to manage context and task delegation effectively.

Yes, you can create Deep Agents in both Python and TypeScript. The framework provides the `create_deep_agent` function to build and configure your AI assistant with custom tools, planning capabilities, and subagent delegation in either language.

You need a Hub and Spoke architecture for AI agent development when your assistant requires planning, file management, and delegation to specialized subagents. This model allows a central agent to route tasks to subagents while maintaining overall context.

Yes, LangChain works alongside the Deep Agents framework for building agents. The framework integrates middleware capabilities and configuration options that complement LangChain workflows for multi-agent system development, context management, and task delegation.