LangGraph is a framework for building stateful, multi-step agentic workflows by modeling application logic as a directed graph. It provides a runtime environment where complex tasks are orchestrated through interconnected nodes and edges, allowing developers to manage state transitions, persistent memory, and control flow across long-running automated processes.
The platform distinguishes itself through its native support for human-in-the-loop automation, enabling developers to define breakpoints that pause execution for manual review, modification, or approval. It also features checkpoint-based persistence, which serializes the entire graph state to external storage to facilitate fault tolerance, process recovery, and the ability to inspect or replay historical execution states for debugging.
Beyond its core orchestration capabilities, the project functions as a comprehensive agent deployment platform. It includes administrative tools for scaling and monitoring agent instances, enforcing metadata-driven access control, and managing resource consumption through rate and usage limits. The system also provides real-time visibility into internal processes by streaming execution updates from individual nodes as they progress.
