Building an LLM Chat & Task Bot with Durable Execution

Stephan Ewen's blog post, "Building an LLM Chat & Task Bot with Durable Execution," outlines the process of creating a chatbot using Restate to manage tasks such as setting reminders and checking flight prices. The chatbot leverages a language model (GPT-4o) to process language and generate task actions, utilizing durable execution to ensure reliable and efficient handling of asynchronous workflows. The infrastructure requirements include storage for chat histories, reliable API calls, and persistent queuing of messages, especially for Slack integration, which involves maintaining message state and ensuring linear message history. Virtual Objects in Restate facilitate managing the state per session, ensuring that each chat session operates independently and efficiently. The chat bot's task workflows are designed to be cost-efficient, capable of scaling to zero when idle, and leverage durable promises for asynchronous communication. Additionally, the integration with web interfaces supports idempotency to prevent duplicate messages, showcasing Restate's capability to manage compute, state, and communication effectively.