I need help understanding how flex mode works. Can you please give me an example of a rigid mode conversation flow and how it is transformed into in flex mode?
What goes into the transition of rigid mode to flex mode? Explaning with an example would be great!
In rigid mode, a conversation is structured as a sequence of separate nodes, each responsible for a specific step. The system sends only the prompt of the current node to the LLM, and moves to the next node when a defined condition is met (e.g., when the user provides a name or date).
And in flex mode, all conversation nodes are combined into a single prompt as tasks, allowing the AI agent to handle the entire flow dynamically instead of moving step-by-step through fixed nodes.
Hi @shaw! Thanks for the explanation!
Can you help me understand how the transition conditions in rigid mode transformed into in flex mode?
Can you explain with an example please?
When you switch to flex mode, imagine that all your nodes are inside a big prompt and your agent will freely move between the nodes/states that have been declared. This means that it will not strictly follow the order that you set.