LangGraph is a new package for creating language model workflows with cycles and supports multi-agent workflows, where multiple independent agents powered by language models collaborate through a graph representation. Each agent in a multi-agent system can have its own prompt, language model, and tools, allowing for specialized task handling, which can improve results by dividing complex problems into manageable units. LangGraph's approach is distinct in its emphasis on graph-based architecture, contrasting with other frameworks like Autogen and CrewAI, which have different mental models for constructing agent interactions. LangGraph's integration into the LangChain ecosystem offers a unique advantage, providing developers with extensive control over agent connections and transitions. Examples of multi-agent workflows using LangGraph include collaborative and hierarchical setups, and applications like GPT-Newspaper leverage these capabilities to create personalized news experiences.