Conversation flow agents allow you to create multiple nodes to handle different scenarios in conversations. This approach provides more fine-grained control over the conversation flow compared to Single/Multi Prompt agents, enabling you to handle more complex scenarios with predictable outcomes.
Every node defines a small set of logic, and the transition condition is used to determine which node to transition to. Once the condition is met when checked, the agent will transition to the next node. There are also finetune examples on nodes that can help you further improve the performance. It might take longer to set up, as you want to cover all the scenarios, but after that it’s much easier to maintain and the performance is more stable and predictable.
Head to the Dashboard, create a new conversation flow agent and select a pre-built template to get started. You can view all options available to the agent within the Dashboard, with details of the options and any latency implications listed there. You can also view the estimated latency and cost of the agent. Modify the template to your needs, all changes are auto-saved.
Since the choice of model can be overridden within individual nodes, the pricing for each call is calculated based on:
Time spent in each node (seconds)
Model price per second for that specific node
Total aggregated across all nodes visited during the call
This allows you to optimize costs by using different models for different parts of the conversation (e.g., cheaper models for simple routing, premium models for complex interactions).