LangGraph videos

LangGraph is a Python library for building stateful, multi-agent applications with Large Language Models (LLMs). It's built on top of LangChain and uses graph-based workflows to orchestrate complex AI agent interactions.

Key features include:

• Graph-based architecture: Define agent workflows as graphs with nodes (functions/agents) and edges (control flow)
• Built-in state management: Maintains conversation state and memory across multiple agent interactions
• Cyclic graph support: Unlike traditional DAG-based systems, LangGraph allows loops and cycles, enabling more complex agent behaviors
• Human-in-the-loop capabilities: Supports checkpoints and interrupts for human review and intervention
• Multi-agent coordination: Facilitates building systems where multiple AI agents work together on tasks

LangGraph is particularly useful for creating sophisticated AI applications like conversational agents, task automation systems, and complex reasoning chains that require multiple steps and decision points. It provides the structure needed to move beyond simple prompt-response patterns to more advanced agentic AI systems.