DeepInfraModel

This is the starting state for the conversation for the assistant role.

This determines whether we detect user's emotion while they speak and send it as an additional info to model. Default false because the model is usually good at understanding the user's emotion from text.

This is the starting state for the conversation for the function role.

This is the max number of tokens that the assistant will be allowed to generate in each turn of the conversation. Default is 250.

This is the name of the model.

This sets how many turns at the start of the conversation to use a smaller, faster model from the same provider before switching to the primary model. Example, gpt-3.5-turbo if provider is openai. Default is 0.

This is the starting state for the conversation for the system role.

This is the temperature that will be used for calls.

These are the tools that the assistant can use during the call. To use transient tools, use tools.

This is the starting state for the conversation for the tool role.

This is the starting state for the conversation for the user role.

This is the function definition of the tool. For endCall, transferCall, and dtmf tools, this is auto-filled based on tool-specific fields like tool.destinations. But, even in those cases, you can provide a custom function definition for advanced use cases. An example of an advanced use case is if you want to customize the message that's spoken for endCall tool. You can specify a function where it returns an argument "reason". Then, in messages array, you can have many "request-complete" messages. One of these messages will be triggered if the messages[].conditions matches the "reason" argument.

These are the options for the knowledge base.

These are the tools that the assistant can use during the call. To use existing tools, use toolIds. Both tools and toolIds can be used together.