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Showing content from https://docs.github.com/en/rest/models/inference below:

REST API endpoints for models inference

model string Required

ID of the specific model to use for the request. The model ID should be in the format of {publisher}/{model_name} where "openai/gpt-4.1" is an example of a model ID. You can find supported models in the catalog/models endpoint.

messages array of objects Required

The collection of context messages associated with this chat completion request. Typical usage begins with a chat message for the System role that provides instructions for the behavior of the assistant, followed by alternating messages between the User and Assistant roles.

role string Required

The chat role associated with this message

Can be one of: assistant, developer, system, user

content string Required

The content of the message

frequency_penalty number

A value that influences the probability of generated tokens appearing based on their cumulative frequency in generated text. Positive values will make tokens less likely to appear as their frequency increases and decrease the likelihood of the model repeating the same statements verbatim. Supported range is [-2, 2].

max_tokens integer

The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. For example, if your prompt is 100 tokens and you set max_tokens to 50, the API will return a completion with a maximum of 50 tokens.

modalities array of strings

The modalities that the model is allowed to use for the chat completions response. The default modality is text. Indicating an unsupported modality combination results in a 422 error. Supported values are: text, audio

presence_penalty number

A value that influences the probability of generated tokens appearing based on their existing presence in generated text. Positive values will make tokens less likely to appear when they already exist and increase the model's likelihood to output new tokens. Supported range is [-2, 2].

response_format object

The desired format for the response.

Object object

type string

Can be one of: text, json_object

Schema for structured JSON response object Required

type string Required

The type of the response.

Value: json_schema

json_schema object Required

The JSON schema for the response.

seed integer

If specified, the system will make a best effort to sample deterministically such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed.

stream boolean

A value indicating whether chat completions should be streamed for this request.

Default: false

stream_options object

Whether to include usage information in the response. Requires stream to be set to true.

include_usage boolean

Whether to include usage information in the response.

Default: false

stop array of strings

A collection of textual sequences that will end completion generation.

temperature number

The sampling temperature to use that controls the apparent creativity of generated completions. Higher values will make output more random while lower values will make results more focused and deterministic. It is not recommended to modify temperature and top_p for the same completion request as the interaction of these two settings is difficult to predict. Supported range is [0, 1]. Decimal values are supported.

tool_choice string

If specified, the model will configure which of the provided tools it can use for the chat completions response.

Can be one of: auto, required, none

tools array of objects

A list of tools the model may request to call. Currently, only functions are supported as a tool. The model may respond with a function call request and provide the input arguments in JSON format for that function.

top_p number

An alternative to sampling with temperature called nucleus sampling. This value causes the model to consider the results of tokens with the provided probability mass. As an example, a value of 0.15 will cause only the tokens comprising the top 15% of probability mass to be considered. It is not recommended to modify temperature and top_p for the same request as the interaction of these two settings is difficult to predict. Supported range is [0, 1]. Decimal values are supported.

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