This repository provides a hands-on course for implementing advanced AI agents from scratch using LangGraph. It targets developers and researchers seeking to build sophisticated agents capable of complex, long-horizon tasks by mastering patterns like task planning, context offloading via virtual file systems, and sub-agent delegation. The benefit is a deep understanding and practical implementation of robust agent architectures.

How It Works

The project leverages LangGraph to construct agents, beginning with a ReAct (Reason-Act) loop foundation. It systematically introduces key architectural patterns: structured task planning using TODO lists for workflow management, virtual file systems for context offloading and state persistence, and sub-agent delegation for context isolation and parallel processing. This modular approach allows for building complex, multi-step reasoning and action capabilities.

Quick Start & Requirements

• Primary Install: Clone the repository and use uv sync for installation and virtual environment management.
• Prerequisites: Python 3.11 or later is mandatory. Requires API keys for Anthropic (ANTHROPIC_API_KEY) and Tavily (TAVILY_API_KEY), with optional LangSmith keys.
• Setup: Requires obtaining API keys and creating a .env file. Running Jupyter notebooks is facilitated via uv run jupyter notebook.
• Resources: Setup involves cloning, syncing dependencies, and configuring API keys.

Highlighted Details

• Implements the ReAct (Reason-Act) loop as a core agent mechanism.
• Features structured task planning with TODO lists, status tracking, and workflow management.
• Utilizes virtual file systems for context offloading, enabling agent "memory" and reduced token usage.
• Demonstrates sub-agent delegation for context isolation and parallel research streams.
• Integrates all techniques into a complete research agent, with LangGraph Studio integration.

Maintenance & Community

No information on maintenance, community channels, or contributors is provided in the README.

Licensing & Compatibility

The repository's license is not specified in the provided README.

Limitations & Caveats

The project mandates Python 3.11+, requires external API keys for core functionality, and is presented as a tutorial series, suggesting it may be in an educational or developmental stage rather than a stable library release.