@llama_index
Build durable workflows that persist across multiple runs π By default, LlamaIndex workflows are ephemeral - but production applications need persistence. Our new guide shows you three strategies: π Store data in workflow instances for simple persistence across multiple runs πΎ Use the Context object's state store for async-safe, serializable workflow state that survives process restarts π¨ Implement external checkpointing to resume exactly where you left off β‘ Bonus: inject dependencies directly into workflow steps to reduce boilerplate code Perfect for long-running document processing, multi-step AI agents, or any workflow that can't afford to start over from scratch. Learn how to write durable workflows: https://t.co/JnH9alMCoy