Human-in-the-loop with OpenGPTs and LangGraph

OpenGPTs has introduced two "human in the loop" features, Interrupt and Authorize, both powered by the newly launched LangGraph library, which aids developers in creating multi-actor, multi-step, stateful LLM applications. LangGraph enables applications to function with multiple actors, such as an LLM paired with a search engine, requiring a coordination layer to manage interactions and execution across discrete steps, all while maintaining a central state that is updated collaboratively. The Interrupt feature allows users to manually pause the application's process, saving the state and resuming or redirecting as desired, while the Authorize feature gives users the power to confirm actions before tools are engaged, enabling human supervision in complex LLM application deployments. These enhancements aim to transform LLM applications from experimental tools into practical, real-world solutions by allowing for observation, intervention, and modification during operation.

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