POST
/
threads
/
{thread_id}
/
runs

Authorizations

x-portkey-api-key
string
headerrequired
x-portkey-virtual-key
string
headerrequired

Path Parameters

thread_id
string
required

The ID of the thread to run.

Body

application/json
assistant_id
string
required

The ID of the assistant to use to execute this run.

model

The ID of the Model to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.

instructions
string | null

Overrides the instructions of the assistant. This is useful for modifying the behavior on a per-run basis.

additional_instructions
string | null

Appends additional instructions at the end of the instructions for the run. This is useful for modifying the behavior on a per-run basis without overriding other instructions.

additional_messages
object[] | null

Adds additional messages to the thread before creating the run.

tools
object[] | null

Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.

metadata
object | null

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.

temperature
number | null
default: 1

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.

Required range: 0 < x < 2
top_p
number | null
default: 1

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.

Required range: 0 < x < 1
stream
boolean | null

If true, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a data: [DONE] message.

max_prompt_tokens
integer | null

The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status incomplete. See incomplete_details for more info.

Required range: x > 256
max_completion_tokens
integer | null

The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete. See incomplete_details for more info.

Required range: x > 256
truncation_strategy
object

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

tool_choice

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.

Available options:
none,
auto,
required
parallel_tool_calls
boolean
default: true

Whether to enable parallel function calling during tool use.

response_format

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_object" } enables JSON mode, which guarantees 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.

Available options:
none,
auto

Response

200 - application/json

Represents an execution run on a thread.

id
string
required

The identifier, which can be referenced in API endpoints.

object
enum<string>
required

The object type, which is always thread.run.

Available options:
thread.run
created_at
integer
required

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

thread_id
string
required

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

assistant_id
string
required

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

status
enum<string>
required

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

Available options:
queued,
in_progress,
requires_action,
cancelling,
cancelled,
failed,
completed,
incomplete,
expired
required_action
object | null
required

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

last_error
object | null
required

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

expires_at
integer | null
required

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

started_at
integer | null
required

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

cancelled_at
integer | null
required

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

failed_at
integer | null
required

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

completed_at
integer | null
required

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

incomplete_details
object | null
required

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

model
string
required

The model that the assistant used for this run.

instructions
string
required

The instructions that the assistant used for this run.

tools
object[]
required

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

metadata
object | null
required

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.

usage
object | null
required

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.).

max_prompt_tokens
integer | null
required

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

Required range: x > 256
max_completion_tokens
integer | null
required

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

Required range: x > 256
truncation_strategy
object
required

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

tool_choice
required

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.

Available options:
none,
auto,
required
parallel_tool_calls
boolean
default: truerequired

Whether to enable parallel function calling during tool use.

response_format
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_object" } enables JSON mode, which guarantees 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.

Available options:
none,
auto
temperature
number | null

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

top_p
number | null

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

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