deep-agents-core

To build AI agents for multi-step task planning, use the Deep Agents framework to configure custom tools and integrate Task Planning middleware. This guides you through agent creation, file context management, and sub-agent delegation.

Middleware integration in AI agent development involves adding modular layers like Task Planning, Context Management, and Human-in-the-loop to your agent. The Deep Agents framework provides these middleware components to handle complex processing workflows.

Yes, you can use LangChain with the Deep Agents framework for agent creation. The framework supports LangChain middleware integration, allowing you to configure custom tools and manage multi-step task workflows effectively.

To delegate tasks to sub-agents in an AI agent framework, configure your Deep Agents setup to support sub-agent delegation. This allows your primary agent to manage file context and distribute multi-step workloads to specialized sub-agents.

The SKILL.md format is a structured configuration standard for developing AI agents within the Deep Agents framework. It defines best practices for skill development, ensuring your agent's custom tools and middleware are correctly documented and implemented.

Yes, the Deep Agents framework supports human-in-the-loop middleware. You can integrate this middleware during agent creation to enable interactive task planning, context management, and manual intervention within your multi-step agent workflows.