Required. The structured textual input given
to the model as a prompt.
Given a
prompt, the model will return what it predicts
is the next message in the discussion.
temperature
float
Optional. Controls the randomness of the output.
Values can range over [0.0,1.0], inclusive. A value
closer to 1.0 will produce responses that are more
varied, while a value closer to 0.0 will typically
result in less surprising responses from the model.
candidate_count
int
Optional. The number of generated response messages to
return.
This value must be between [1, 8], inclusive. If unset,
this will default to 1.
top_p
float
Optional. The maximum cumulative probability of tokens to
consider when sampling.
The model uses combined Top-k and nucleus sampling.
Nucleus sampling considers the smallest set of tokens whose
probability sum is at least top_p.
top_k
int
Optional. The maximum number of tokens to consider when
sampling.
The model uses combined Top-k and nucleus sampling.
Top-k sampling considers the set of top_k most probable
tokens.
View source on GitHub