deep-agents-core

Build deep learning agents by leveraging an agent framework with built-in middleware for task planning, context management, and delegation. This simplifies creating complex workflows and automates setup for capabilities like long-term memory and human-in-the-loop operations.

Yes, LangGraph and LangChain facilitate context management and task delegation in deep agents. The framework integrates middleware to handle long-term memory and automated multi-step tasks within robust agent architectures.

Add human-in-the-loop operations by utilizing built-in middleware within a deep agent framework. This enables configuration flexibility for sophisticated task management, allowing automated workflows to pause for human intervention when necessary.

Yes, LangChain and LangGraph are required dependencies to set up task planning and long-term memory. They provide the foundational framework for constructing agents that manage complex workflows requiring persistent context.

Middleware handles task delegation by distributing complex workflows across configured subagents and skills. This architecture manages automated multi-step tasks, ensuring robust context management and long-term memory throughout the process.

Limitations include the prerequisite knowledge required for LangChain and LangGraph, and the advanced complexity of configuring subagents, skills, and persistence. It is intended for advanced workflows rather than simple, single-step automations.