Create an assistant with a model and instructions.
Request body
The name of the assistant. The maximum length is 256 characters.
The description of the assistant. The maximum length is 512 characters.
The system instructions that the assistant uses. The maximum length is 256,000 characters.
Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
Example request
{
"temperature": 1,
"top_p": 1
}Response
OK
The identifier, which can be referenced in API endpoints.
The object type, which is always assistant.
The Unix timestamp (in seconds) for when the assistant was created.
The name of the assistant. The maximum length is 256 characters.
The description of the assistant. The maximum length is 512 characters.
ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
The system instructions that the assistant uses. The maximum length is 256,000 characters.
Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
Example response
{
"temperature": 1,
"top_p": 1
}