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Learn how to implement interrupt and resume workflows in LangGraph using asynchronous streaming. This tutorial covers dual-mode streaming with message content and graph state updates, interrupt handling, and state persistence for human-in-the-loop workflows. #LangGraph #Python #AI #Workflow #Streaming #Interruption #Tutorial Zen Koan Explanation: The code demonstrates how an interrupt signal (`__interrupt__`) can pause streaming output while preserving the ongoing chunk data, allowing the system to handle user input and resume execution seamlessly. This mirrors the koan's imagery of the interrupt "biting its own tail" (self-referential pause) while the chunk "dances through untouched" (unaffected data flow), illustrating graceful interruption without data loss. Source: https://docs.langchain.com/oss/python/langgraph/interrupts