The identifier, which can be referenced in API endpoints.

The ID of the assistant used for execution of this run.

The Unix timestamp (in seconds) for when the run was cancelled.

The Unix timestamp (in seconds) for when the run was completed.

The Unix timestamp (in seconds) for when the run was created.

The Unix timestamp (in seconds) for when the run will expire.

The Unix timestamp (in seconds) for when the run failed.

Details on why the run is incomplete. Will be null if the run is not incomplete.

The instructions that the assistant used for this run.

The last error associated with this run. Will be null if there are no errors.

The maximum number of completion tokens specified to have been used over the course of the run.

The maximum number of prompt tokens specified to have been used over the course of the run.

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 maxium of 512 characters long.

The model that the assistant used for this run.

The object type, which is always thread.run.

Whether to enable parallel function calling during tool use.

Details on the action required to continue the run. Will be null if no action is required.

Specifies the format that the model must output. Compatible with GPT-4o, GPT-4 Turbo, and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.

Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

Setting to { "type": "json_object" } enables JSON mode, which ensures the message the model generates is valid JSON.

Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

The Unix timestamp (in seconds) for when the run was started.

The status of the run, which can be either queued, in_progress, requires_action, cancelling, cancelled, failed, completed, incomplete, or expired.

The ID of the thread that was executed on as a part of this run.

Controls which (if any) tool is called by the model. none means the model will not call any tools and instead generates a message. auto is the default value and means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools before responding to the user. Specifying a particular tool like {"type": "file_search"} or {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.

The list of tools that the assistant used for this run.

Controls for how a thread will be truncated prior to the run. Use this to control the intial context window of the run.

Usage statistics related to the run. This value will be null if the run is not in a terminal state (i.e. in_progress, queued, etc.).

The sampling temperature used for this run. If not set, defaults to 1.

The nucleus sampling value used for this run. If not set, defaults to 1.