Create a model response

POST/responses

Creates a model response. Provide text or image inputs to generate text or JSON outputs. Have the model call your own custom code or use built-in tools like web search or file search to use your own data as input for the model's response.

Body ParametersJSONExpand Collapse

background: optional boolean

Whether to run the model response in the background. Learn more.

context_management: optional array of object { type, compact_threshold }

Context management configuration for this request.

type: string

The context management entry type. Currently only 'compaction' is supported.

compact_threshold: optional number

Token threshold at which compaction should be triggered for this entry.

minimum1000

conversation: optional string or ResponseConversationParam { id }

The conversation that this response belongs to. Items from this conversation are prepended to input_items for this response request. Input items and output items from this response are automatically added to this conversation after this response completes.

One of the following:

ConversationID = string

The unique ID of the conversation.

ResponseConversationParam = object { id }

The conversation that this response belongs to.

id: string

The unique ID of the conversation.

include: optional array of ResponseIncludable

Specify additional output data to include in the model response. Currently supported values are:

web_search_call.action.sources: Include the sources of the web search tool call.
code_interpreter_call.outputs: Includes the outputs of python code execution in code interpreter tool call items.
computer_call_output.output.image_url: Include image urls from the computer call output.
file_search_call.results: Include the search results of the file search tool call.
message.input_image.image_url: Include image urls from the input message.
message.output_text.logprobs: Include logprobs with assistant messages.
reasoning.encrypted_content: Includes an encrypted version of reasoning tokens in reasoning item outputs. This enables reasoning items to be used in multi-turn conversations when using the Responses API statelessly (like when the store parameter is set to false, or when an organization is enrolled in the zero data retention program).

One of the following:

"file_search_call.results"

"web_search_call.results"

"web_search_call.action.sources"

"message.input_image.image_url"

"computer_call_output.output.image_url"

"code_interpreter_call.outputs"

"reasoning.encrypted_content"

"message.output_text.logprobs"

input: optional string or array of EasyInputMessage { content, role, phase, type } or object { content, role, status, type } or ResponseOutputMessage { id, content, role, 3 more } or 25 more

Text, image, or file inputs to the model, used to generate a response.

Learn more:

One of the following:

TextInput = string

A text input to the model, equivalent to a text input with the user role.

InputItemList = array of EasyInputMessage { content, role, phase, type } or object { content, role, status, type } or ResponseOutputMessage { id, content, role, 3 more } or 25 more

A list of one or many input items to the model, containing different content types.

One of the following:

EasyInputMessage = object { content, role, phase, type }

A message input to the model with a role indicating instruction following hierarchy. Instructions given with the developer or system role take precedence over instructions given with the user role. Messages with the assistant role are presumed to have been generated by the model in previous interactions.

content: string or ResponseInputMessageContentList { , , }

Text, image, or audio input to the model, used to generate a response. Can also contain previous assistant responses.

One of the following:

TextInput = string

A text input to the model.

ResponseInputMessageContentList = array of ResponseInputContent

A list of one or many input items to the model, containing different content types.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

role: "user" or "assistant" or "system" or "developer"

The role of the message input. One of user, assistant, system, or developer.

One of the following:

"user"

"assistant"

"system"

"developer"

phase: optional "commentary" or "final_answer"

Labels an assistant message as intermediate commentary (commentary) or the final answer (final_answer). For models like gpt-5.3-codex and beyond, when sending follow-up requests, preserve and resend phase on all assistant messages — dropping it can degrade performance. Not used for user messages.

One of the following:

"commentary"

"final_answer"

type: optional "message"

The type of the message input. Always message.

Message = object { content, role, status, type }

content: ResponseInputMessageContentList { , , }

A list of one or many input items to the model, containing different content types.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

role: "user" or "system" or "developer"

The role of the message input. One of user, system, or developer.

One of the following:

"user"

"system"

"developer"

status: optional "in_progress" or "completed" or "incomplete"

The status of item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: optional "message"

The type of the message input. Always set to message.

ResponseOutputMessage = object { id, content, role, 3 more }

An output message from the model.

id: string

The unique ID of the output message.

content: array of ResponseOutputText { annotations, logprobs, text, type } or ResponseOutputRefusal { refusal, type }

The content of the output message.

One of the following:

ResponseOutputText = object { annotations, logprobs, text, type }

A text output from the model.

annotations: array of object { file_id, filename, index, type } or object { end_index, start_index, title, 2 more } or object { container_id, end_index, file_id, 3 more } or object { file_id, index, type }

The annotations of the text output.

One of the following:

FileCitation = object { file_id, filename, index, type }

A citation to a file.

file_id: string

The ID of the file.

filename: string

The filename of the file cited.

index: number

The index of the file in the list of files.

type: "file_citation"

The type of the file citation. Always file_citation.

URLCitation = object { end_index, start_index, title, 2 more }

A citation for a web resource used to generate a model response.

end_index: number

The index of the last character of the URL citation in the message.

start_index: number

The index of the first character of the URL citation in the message.

title: string

The title of the web resource.

type: "url_citation"

The type of the URL citation. Always url_citation.

url: string

The URL of the web resource.

ContainerFileCitation = object { container_id, end_index, file_id, 3 more }

A citation for a container file used to generate a model response.

container_id: string

The ID of the container file.

end_index: number

The index of the last character of the container file citation in the message.

file_id: string

The ID of the file.

filename: string

The filename of the container file cited.

start_index: number

The index of the first character of the container file citation in the message.

type: "container_file_citation"

The type of the container file citation. Always container_file_citation.

FilePath = object { file_id, index, type }

A path to a file.

file_id: string

The ID of the file.

index: number

The index of the file in the list of files.

type: "file_path"

The type of the file path. Always file_path.

logprobs: array of object { token, bytes, logprob, top_logprobs }

token: string

bytes: array of number

logprob: number

top_logprobs: array of object { token, bytes, logprob }

token: string

bytes: array of number

logprob: number

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

ResponseOutputRefusal = object { refusal, type }

A refusal from the model.

refusal: string

The refusal explanation from the model.

type: "refusal"

The type of the refusal. Always refusal.

role: "assistant"

The role of the output message. Always assistant.

status: "in_progress" or "completed" or "incomplete"

The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "message"

The type of the output message. Always message.

phase: optional "commentary" or "final_answer"

One of the following:

"commentary"

"final_answer"

FileSearchCall = object { id, queries, status, 2 more }

The results of a file search tool call. See the file search guide for more information.

id: string

The unique ID of the file search tool call.

queries: array of string

The queries used to search for files.

status: "in_progress" or "searching" or "completed" or 2 more

The status of the file search tool call. One of in_progress, searching, incomplete or failed,

One of the following:

"in_progress"

"searching"

"completed"

"incomplete"

"failed"

type: "file_search_call"

The type of the file search tool call. Always file_search_call.

results: optional array of object { attributes, file_id, filename, 2 more }

The results of the file search tool call.

attributes: optional map[string or number or boolean]

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, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

One of the following:

string

number

boolean

file_id: optional string

The unique ID of the file.

filename: optional string

The name of the file.

score: optional number

The relevance score of the file - a value between 0 and 1.

formatfloat

text: optional string

The text that was retrieved from the file.

ComputerCall = object { id, call_id, pending_safety_checks, 4 more }

A tool call to a computer use tool. See the computer use guide for more information.

id: string

The unique ID of the computer call.

call_id: string

An identifier used when responding to the tool call with output.

pending_safety_checks: array of object { id, code, message }

The pending safety checks for the computer call.

id: string

The ID of the pending safety check.

code: optional string

The type of the pending safety check.

message: optional string

Details about the pending safety check.

status: "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "computer_call"

The type of the computer call. Always computer_call.

action: optional ComputerAction

A click action.

One of the following:

Click = object { button, type, x, 2 more }

A click action.

button: "left" or "right" or "wheel" or 2 more

Indicates which mouse button was pressed during the click. One of left, right, wheel, back, or forward.

One of the following:

"left"

"right"

"wheel"

"back"

"forward"

type: "click"

Specifies the event type. For a click action, this property is always click.

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys: optional array of string

The keys being held while clicking.

DoubleClick = object { keys, type, x, y }

A double click action.

keys: array of string

The keys being held while double-clicking.

type: "double_click"

Specifies the event type. For a double click action, this property is always set to double_click.

x: number

The x-coordinate where the double click occurred.

y: number

The y-coordinate where the double click occurred.

Drag = object { path, type, keys }

A drag action.

path: array of object { x, y }

An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg

[
  { x: 100, y: 200 },
  { x: 200, y: 300 }
]

x: number

The x-coordinate.

y: number

The y-coordinate.

type: "drag"

Specifies the event type. For a drag action, this property is always set to drag.

keys: optional array of string

The keys being held while dragging the mouse.

Keypress = object { keys, type }

A collection of keypresses the model would like to perform.

keys: array of string

The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key.

type: "keypress"

Specifies the event type. For a keypress action, this property is always set to keypress.

Move = object { type, x, y, keys }

A mouse move action.

type: "move"

Specifies the event type. For a move action, this property is always set to move.

x: number

The x-coordinate to move to.

y: number

The y-coordinate to move to.

keys: optional array of string

The keys being held while moving the mouse.

Screenshot = object { type }

A screenshot action.

type: "screenshot"

Specifies the event type. For a screenshot action, this property is always set to screenshot.

Scroll = object { scroll_x, scroll_y, type, 3 more }

A scroll action.

scroll_x: number

The horizontal scroll distance.

scroll_y: number

The vertical scroll distance.

type: "scroll"

Specifies the event type. For a scroll action, this property is always set to scroll.

x: number

The x-coordinate where the scroll occurred.

y: number

The y-coordinate where the scroll occurred.

keys: optional array of string

The keys being held while scrolling.

Type = object { text, type }

An action to type in text.

text: string

The text to type.

type: "type"

Specifies the event type. For a type action, this property is always set to type.

Wait = object { type }

A wait action.

type: "wait"

Specifies the event type. For a wait action, this property is always set to wait.

actions: optional ComputerActionList { Click, DoubleClick, Drag, 6 more }

Flattened batched actions for computer_use. Each action includes an type discriminator and action-specific fields.

One of the following:

Click = object { button, type, x, 2 more }

A click action.

button: "left" or "right" or "wheel" or 2 more

Indicates which mouse button was pressed during the click. One of left, right, wheel, back, or forward.

One of the following:

"left"

"right"

"wheel"

"back"

"forward"

type: "click"

Specifies the event type. For a click action, this property is always click.

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys: optional array of string

The keys being held while clicking.

DoubleClick = object { keys, type, x, y }

A double click action.

keys: array of string

The keys being held while double-clicking.

type: "double_click"

Specifies the event type. For a double click action, this property is always set to double_click.

x: number

The x-coordinate where the double click occurred.

y: number

The y-coordinate where the double click occurred.

Drag = object { path, type, keys }

A drag action.

path: array of object { x, y }

An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg

[
  { x: 100, y: 200 },
  { x: 200, y: 300 }
]

x: number

The x-coordinate.

y: number

The y-coordinate.

type: "drag"

Specifies the event type. For a drag action, this property is always set to drag.

keys: optional array of string

The keys being held while dragging the mouse.

Keypress = object { keys, type }

A collection of keypresses the model would like to perform.

keys: array of string

The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key.

type: "keypress"

Specifies the event type. For a keypress action, this property is always set to keypress.

Move = object { type, x, y, keys }

A mouse move action.

type: "move"

Specifies the event type. For a move action, this property is always set to move.

x: number

The x-coordinate to move to.

y: number

The y-coordinate to move to.

keys: optional array of string

The keys being held while moving the mouse.

Screenshot = object { type }

A screenshot action.

type: "screenshot"

Specifies the event type. For a screenshot action, this property is always set to screenshot.

Scroll = object { scroll_x, scroll_y, type, 3 more }

A scroll action.

scroll_x: number

The horizontal scroll distance.

scroll_y: number

The vertical scroll distance.

type: "scroll"

Specifies the event type. For a scroll action, this property is always set to scroll.

x: number

The x-coordinate where the scroll occurred.

y: number

The y-coordinate where the scroll occurred.

keys: optional array of string

The keys being held while scrolling.

Type = object { text, type }

An action to type in text.

text: string

The text to type.

type: "type"

Specifies the event type. For a type action, this property is always set to type.

Wait = object { type }

A wait action.

type: "wait"

Specifies the event type. For a wait action, this property is always set to wait.

ComputerCallOutput = object { call_id, output, type, 3 more }

The output of a computer tool call.

call_id: string

The ID of the computer tool call that produced the output.

maxLength64

minLength1

output: ResponseComputerToolCallOutputScreenshot { type, file_id, image_url }

A computer screenshot image used with the computer use tool.

type: "computer_screenshot"

Specifies the event type. For a computer screenshot, this property is always set to computer_screenshot.

file_id: optional string

The identifier of an uploaded file that contains the screenshot.

image_url: optional string

The URL of the screenshot image.

type: "computer_call_output"

The type of the computer tool call output. Always computer_call_output.

id: optional string

The ID of the computer tool call output.

acknowledged_safety_checks: optional array of object { id, code, message }

The safety checks reported by the API that have been acknowledged by the developer.

id: string

The ID of the pending safety check.

code: optional string

The type of the pending safety check.

message: optional string

Details about the pending safety check.

status: optional "in_progress" or "completed" or "incomplete"

The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

WebSearchCall = object { id, action, status, type }

The results of a web search tool call. See the web search guide for more information.

id: string

The unique ID of the web search tool call.

action: object { query, type, queries, sources } or object { type, url } or object { pattern, type, url }

An object describing the specific action taken in this web search call. Includes details on how the model used the web (search, open_page, find_in_page).

One of the following:

Search = object { query, type, queries, sources }

Action type "search" - Performs a web search query.

query: string

[DEPRECATED] The search query.

type: "search"

The action type.

queries: optional array of string

The search queries.

sources: optional array of object { type, url }

The sources used in the search.

type: "url"

The type of source. Always url.

url: string

The URL of the source.

OpenPage = object { type, url }

Action type "open_page" - Opens a specific URL from search results.

type: "open_page"

The action type.

url: optional string

The URL opened by the model.

formaturi

FindInPage = object { pattern, type, url }

Action type "find_in_page": Searches for a pattern within a loaded page.

pattern: string

The pattern or text to search for within the page.

type: "find_in_page"

The action type.

url: string

The URL of the page searched for the pattern.

formaturi

status: "in_progress" or "searching" or "completed" or "failed"

The status of the web search tool call.

One of the following:

"in_progress"

"searching"

"completed"

"failed"

type: "web_search_call"

The type of the web search tool call. Always web_search_call.

FunctionCall = object { arguments, call_id, name, 4 more }

A tool call to run a function. See the function calling guide for more information.

arguments: string

A JSON string of the arguments to pass to the function.

call_id: string

The unique ID of the function tool call generated by the model.

The name of the function to run.

type: "function_call"

The type of the function tool call. Always function_call.

id: optional string

The unique ID of the function tool call.

namespace: optional string

The namespace of the function to run.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

FunctionCallOutput = object { call_id, output, type, 2 more }

The output of a function tool call.

call_id: string

The unique ID of the function tool call generated by the model.

maxLength64

minLength1

output: string or array of ResponseInputTextContent { text, type } or ResponseInputImageContent { type, detail, file_id, image_url } or ResponseInputFileContent { type, file_data, file_id, 2 more }

Text, image, or file output of the function tool call.

One of the following:

string

A JSON string of the output of the function tool call.

array of ResponseInputTextContent { text, type } or ResponseInputImageContent { type, detail, file_id, image_url } or ResponseInputFileContent { type, file_data, file_id, 2 more }

An array of content outputs (text, image, file) for the function tool call.

One of the following:

ResponseInputTextContent = object { text, type }

A text input to the model.

text: string

The text input to the model.

maxLength10485760

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImageContent = object { type, detail, file_id, image_url }

An image input to the model. Learn about image inputs

type: "input_image"

The type of the input item. Always input_image.

detail: optional "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

maxLength20971520

ResponseInputFileContent = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The base64-encoded data of the file to be sent to the model.

maxLength33554432

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

type: "function_call_output"

The type of the function tool call output. Always function_call_output.

id: optional string

The unique ID of the function tool call output. Populated when this item is returned via API.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

ToolSearchCall = object { arguments, type, id, 3 more }

arguments: unknown

The arguments supplied to the tool search call.

type: "tool_search_call"

The item type. Always tool_search_call.

id: optional string

The unique ID of this tool search call.

call_id: optional string

The unique ID of the tool search call generated by the model.

maxLength64

minLength1

execution: optional "server" or "client"

Whether tool search was executed by the server or by the client.

One of the following:

"server"

"client"

status: optional "in_progress" or "completed" or "incomplete"

The status of the tool search call.

One of the following:

"in_progress"

"completed"

"incomplete"

ToolSearchOutput = object { tools, type, id, 3 more }

tools: array of object { name, parameters, strict, 3 more } or object { type, vector_store_ids, filters, 2 more } or object { type } or 12 more

The loaded tool definitions returned by the tool search output.

One of the following:

Function = object { name, parameters, strict, 3 more }

Defines a function in your own code the model can choose to call. Learn more about function calling.

The name of the function to call.

parameters: map[unknown]

A JSON schema object describing the parameters of the function.

strict: boolean

Whether to enforce strict parameter validation. Default true.

type: "function"

The type of the function tool. Always function.

defer_loading: optional boolean

Whether this function is deferred and loaded via tool search.

description: optional string

A description of the function. Used by the model to determine whether or not to call the function.

FileSearch = object { type, vector_store_ids, filters, 2 more }

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: "file_search"

The type of the file search tool. Always file_search.

vector_store_ids: array of string

The IDs of the vector stores to search.

filters: optional ComparisonFilter { key, type, value } or CompoundFilter { filters, type }

A filter to apply.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

CompoundFilter = object { filters, type }

Combine multiple filters using and or or.

filters: array of ComparisonFilter { key, type, value } or unknown

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

unknown

type: "and" or "or"

Type of operation: and or or.

One of the following:

"and"

"or"

max_num_results: optional number

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: optional object { hybrid_search, ranker, score_threshold }

Ranking options for search.

hybrid_search: optional object { embedding_weight, text_weight }

Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled.

embedding_weight: number

The weight of the embedding in the reciprocal ranking fusion.

text_weight: number

The weight of the text in the reciprocal ranking fusion.

ranker: optional "auto" or "default-2024-11-15"

The ranker to use for the file search.

One of the following:

"auto"

"default-2024-11-15"

score_threshold: optional number

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

Computer = object { type }

A tool that controls a virtual computer. Learn more about the computer tool.

type: "computer"

The type of the computer tool. Always computer.

ComputerUsePreview = object { display_height, display_width, environment, type }

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: number

The height of the computer display.

display_width: number

The width of the computer display.

environment: "windows" or "mac" or "linux" or 2 more

The type of computer environment to control.

One of the following:

"windows"

"mac"

"linux"

"ubuntu"

"browser"

type: "computer_use_preview"

The type of the computer use tool. Always computer_use_preview.

WebSearch = object { type, filters, search_context_size, user_location }

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: "web_search" or "web_search_2025_08_26"

The type of the web search tool. One of web_search or web_search_2025_08_26.

One of the following:

"web_search"

"web_search_2025_08_26"

filters: optional object { allowed_domains }

Filters for the search.

allowed_domains: optional array of string

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { city, country, region, 2 more }

The approximate location of the user.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

type: optional "approximate"

The type of location approximation. Always approximate.

Mcp = object { server_label, type, allowed_tools, 7 more }

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: string

A label for this MCP server, used to identify it in tool calls.

type: "mcp"

The type of the MCP tool. Always mcp.

allowed_tools: optional array of string or object { read_only, tool_names }

List of allowed tool names or a filter object.

One of the following:

McpAllowedTools = array of string

A string array of allowed tool names

McpToolFilter = object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

authorization: optional string

An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

connector_id: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more

Identifier for service connectors, like those available in ChatGPT. One of server_url or connector_id must be provided. Learn more about service connectors here.

Currently supported connector_id values are:

Dropbox: connector_dropbox
Gmail: connector_gmail
Google Calendar: connector_googlecalendar
Google Drive: connector_googledrive
Microsoft Teams: connector_microsoftteams
Outlook Calendar: connector_outlookcalendar
Outlook Email: connector_outlookemail
SharePoint: connector_sharepoint

One of the following:

"connector_dropbox"

"connector_gmail"

"connector_googlecalendar"

"connector_googledrive"

"connector_microsoftteams"

"connector_outlookcalendar"

"connector_outlookemail"

"connector_sharepoint"

defer_loading: optional boolean

Whether this MCP tool is deferred and discovered via tool search.

headers: optional map[string]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: optional object { always, never } or "always" or "never"

Specify which of the MCP server's tools require approval.

One of the following:

McpToolApprovalFilter = object { always, never }

Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

never: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

McpToolApprovalSetting = "always" or "never"

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

One of the following:

"always"

"never"

server_description: optional string

Optional description of the MCP server, used to provide more context.

server_url: optional string

The URL for the MCP server. One of server_url or connector_id must be provided.

CodeInterpreter = object { container, type }

A tool that runs Python code to help generate a response to a prompt.

container: string or object { type, file_ids, memory_limit, network_policy }

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

One of the following:

string

The container ID.

CodeInterpreterToolAuto = object { type, file_ids, memory_limit, network_policy }

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: "auto"

Always auto.

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the code interpreter container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

type: "code_interpreter"

The type of the code interpreter tool. Always code_interpreter.

ImageGeneration = object { type, action, background, 9 more }

A tool that generates images using the GPT image models.

type: "image_generation"

The type of the image generation tool. Always image_generation.

action: optional "generate" or "edit" or "auto"

Whether to generate a new image or edit an existing image. Default: auto.

One of the following:

"generate"

"edit"

"auto"

background: optional "transparent" or "opaque" or "auto"

Background type for the generated image. One of transparent, opaque, or auto. Default: auto.

One of the following:

"transparent"

"opaque"

"auto"

input_fidelity: optional "high" or "low"

Control how much effort the model will exert to match the style and features, especially facial features, of input images. This parameter is only supported for gpt-image-1 and gpt-image-1.5 and later models, unsupported for gpt-image-1-mini. Supports high and low. Defaults to low.

One of the following:

"high"

"low"

input_image_mask: optional object { file_id, image_url }

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: optional string

File ID for the mask image.

image_url: optional string

Base64-encoded mask image.

model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

string

"gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

"gpt-image-1"

"gpt-image-1-mini"

"gpt-image-1.5"

moderation: optional "auto" or "low"

Moderation level for the generated image. Default: auto.

One of the following:

"auto"

"low"

output_compression: optional number

Compression level for the output image. Default: 100.

minimum0

maximum100

output_format: optional "png" or "webp" or "jpeg"

The output format of the generated image. One of png, webp, or jpeg. Default: png.

One of the following:

"png"

"webp"

"jpeg"

partial_images: optional number

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0

maximum3

quality: optional "low" or "medium" or "high" or "auto"

The quality of the generated image. One of low, medium, high, or auto. Default: auto.

One of the following:

"low"

"medium"

"high"

"auto"

size: optional "1024x1024" or "1024x1536" or "1536x1024" or "auto"

The size of the generated image. One of 1024x1024, 1024x1536, 1536x1024, or auto. Default: auto.

One of the following:

"1024x1024"

"1024x1536"

"1536x1024"

"auto"

LocalShell = object { type }

A tool that allows the model to execute shell commands in a local environment.

type: "local_shell"

The type of the local shell tool. Always local_shell.

Shell = object { type, environment }

A tool that allows the model to execute shell commands.

type: "shell"

The type of the shell tool. Always shell.

environment: optional ContainerAuto { type, file_ids, memory_limit, 2 more } or LocalEnvironment { type, skills } or ContainerReference { container_id, type }

One of the following:

ContainerAuto = object { type, file_ids, memory_limit, 2 more }

type: "container_auto"

Automatically creates a container for this request

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

skills: optional array of SkillReference { skill_id, type, version } or InlineSkill { description, name, source, type }

An optional list of skills referenced by id or inline data.

One of the following:

SkillReference = object { skill_id, type, version }

skill_id: string

The ID of the referenced skill.

maxLength64

minLength1

type: "skill_reference"

References a skill created with the /v1/skills endpoint.

version: optional string

Optional skill version. Use a positive integer or 'latest'. Omit for default.

InlineSkill = object { description, name, source, type }

description: string

The description of the skill.

The name of the skill.

source: InlineSkillSource { data, media_type, type }

Inline skill payload

data: string

Base64-encoded skill zip bundle.

maxLength70254592

minLength1

media_type: "application/zip"

The media type of the inline skill payload. Must be application/zip.

type: "base64"

The type of the inline skill source. Must be base64.

type: "inline"

Defines an inline skill for this request.

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

Namespace = object { description, name, tools, type }

Groups function/custom tools under a shared namespace.

description: string

A description of the namespace shown to the model.

minLength1

The namespace name used in tool calls (for example, crm).

minLength1

tools: array of object { name, type, defer_loading, 3 more } or object { name, type, defer_loading, 2 more }

The function/custom tools available inside this namespace.

One of the following:

Function = object { name, type, defer_loading, 3 more }

maxLength128

minLength1

type: "function"

defer_loading: optional boolean

Whether this function should be deferred and discovered via tool search.

description: optional string

parameters: optional unknown

strict: optional boolean

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "namespace"

The type of the tool. Always namespace.

ToolSearch = object { type, description, execution, parameters }

Hosted or BYOT tool search configuration for deferred tools.

type: "tool_search"

The type of the tool. Always tool_search.

description: optional string

Description shown to the model for a client-executed tool search tool.

execution: optional "server" or "client"

Whether tool search is executed by the server or by the client.

One of the following:

"server"

"client"

parameters: optional unknown

Parameter schema for a client-executed tool search tool.

WebSearchPreview = object { type, search_content_types, search_context_size, user_location }

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: "web_search_preview" or "web_search_preview_2025_03_11"

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

One of the following:

"web_search_preview"

"web_search_preview_2025_03_11"

search_content_types: optional array of "text" or "image"

One of the following:

"text"

"image"

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { type, city, country, 2 more }

The user's location.

type: "approximate"

The type of location approximation. Always approximate.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

ApplyPatch = object { type }

Allows the assistant to create, delete, or update files using unified diffs.

type: "apply_patch"

The type of the tool. Always apply_patch.

type: "tool_search_output"

The item type. Always tool_search_output.

id: optional string

The unique ID of this tool search output.

call_id: optional string

The unique ID of the tool search call generated by the model.

maxLength64

minLength1

execution: optional "server" or "client"

Whether tool search was executed by the server or by the client.

One of the following:

"server"

"client"

status: optional "in_progress" or "completed" or "incomplete"

The status of the tool search output.

One of the following:

"in_progress"

"completed"

"incomplete"

Reasoning = object { id, summary, type, 3 more }

A description of the chain of thought used by a reasoning model while generating a response. Be sure to include these items in your input to the Responses API for subsequent turns of a conversation if you are manually managing context.

id: string

The unique identifier of the reasoning content.

summary: array of SummaryTextContent { text, type }

Reasoning summary content.

text: string

A summary of the reasoning output from the model so far.

type: "summary_text"

The type of the object. Always summary_text.

type: "reasoning"

The type of the object. Always reasoning.

content: optional array of object { text, type }

Reasoning text content.

text: string

The reasoning text from the model.

type: "reasoning_text"

The type of the reasoning text. Always reasoning_text.

encrypted_content: optional string

The encrypted content of the reasoning item - populated when a response is generated with reasoning.encrypted_content in the include parameter.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

Compaction = object { encrypted_content, type, id }

A compaction item generated by the v1/responses/compact API.

encrypted_content: string

The encrypted content of the compaction summary.

maxLength10485760

type: "compaction"

The type of the item. Always compaction.

id: optional string

The ID of the compaction item.

ImageGenerationCall = object { id, result, status, type }

An image generation request made by the model.

id: string

The unique ID of the image generation call.

result: string

The generated image encoded in base64.

status: "in_progress" or "completed" or "generating" or "failed"

The status of the image generation call.

One of the following:

"in_progress"

"completed"

"generating"

"failed"

type: "image_generation_call"

The type of the image generation call. Always image_generation_call.

CodeInterpreterCall = object { id, code, container_id, 3 more }

A tool call to run code.

id: string

The unique ID of the code interpreter tool call.

code: string

The code to run, or null if not available.

container_id: string

The ID of the container used to run the code.

outputs: array of object { logs, type } or object { type, url }

The outputs generated by the code interpreter, such as logs or images. Can be null if no outputs are available.

One of the following:

Logs = object { logs, type }

The logs output from the code interpreter.

logs: string

The logs output from the code interpreter.

type: "logs"

The type of the output. Always logs.

Image = object { type, url }

The image output from the code interpreter.

type: "image"

The type of the output. Always image.

url: string

The URL of the image output from the code interpreter.

status: "in_progress" or "completed" or "incomplete" or 2 more

The status of the code interpreter tool call. Valid values are in_progress, completed, incomplete, interpreting, and failed.

One of the following:

"in_progress"

"completed"

"incomplete"

"interpreting"

"failed"

type: "code_interpreter_call"

The type of the code interpreter tool call. Always code_interpreter_call.

LocalShellCall = object { id, action, call_id, 2 more }

A tool call to run a command on the local shell.

id: string

The unique ID of the local shell call.

action: object { command, env, type, 3 more }

Execute a shell command on the server.

command: array of string

The command to run.

env: map[string]

Environment variables to set for the command.

type: "exec"

The type of the local shell action. Always exec.

timeout_ms: optional number

Optional timeout in milliseconds for the command.

user: optional string

Optional user to run the command as.

working_directory: optional string

Optional working directory to run the command in.

call_id: string

The unique ID of the local shell tool call generated by the model.

status: "in_progress" or "completed" or "incomplete"

The status of the local shell call.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "local_shell_call"

The type of the local shell call. Always local_shell_call.

LocalShellCallOutput = object { id, output, type, status }

The output of a local shell tool call.

id: string

The unique ID of the local shell tool call generated by the model.

output: string

A JSON string of the output of the local shell tool call.

type: "local_shell_call_output"

The type of the local shell tool call output. Always local_shell_call_output.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

ShellCall = object { action, call_id, type, 3 more }

A tool representing a request to execute one or more shell commands.

action: object { commands, max_output_length, timeout_ms }

The shell commands and limits that describe how to run the tool call.

commands: array of string

Ordered shell commands for the execution environment to run.

max_output_length: optional number

Maximum number of UTF-8 characters to capture from combined stdout and stderr output.

timeout_ms: optional number

Maximum wall-clock time in milliseconds to allow the shell commands to run.

call_id: string

The unique ID of the shell tool call generated by the model.

maxLength64

minLength1

type: "shell_call"

The type of the item. Always shell_call.

id: optional string

The unique ID of the shell tool call. Populated when this item is returned via API.

environment: optional LocalEnvironment { type, skills } or ContainerReference { container_id, type }

The environment to execute the shell commands in.

One of the following:

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

status: optional "in_progress" or "completed" or "incomplete"

The status of the shell call. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

ShellCallOutput = object { call_id, output, type, 3 more }

The streamed output items emitted by a shell tool call.

call_id: string

The unique ID of the shell tool call generated by the model.

maxLength64

minLength1

output: array of ResponseFunctionShellCallOutputContent { outcome, stderr, stdout }

Captured chunks of stdout and stderr output, along with their associated outcomes.

outcome: object { type } or object { exit_code, type }

The exit or timeout outcome associated with this shell call.

One of the following:

Timeout = object { type }

Indicates that the shell call exceeded its configured time limit.

type: "timeout"

The outcome type. Always timeout.

Exit = object { exit_code, type }

Indicates that the shell commands finished and returned an exit code.

exit_code: number

The exit code returned by the shell process.

type: "exit"

The outcome type. Always exit.

stderr: string

Captured stderr output for the shell call.

maxLength10485760

stdout: string

Captured stdout output for the shell call.

maxLength10485760

type: "shell_call_output"

The type of the item. Always shell_call_output.

id: optional string

The unique ID of the shell tool call output. Populated when this item is returned via API.

max_output_length: optional number

The maximum number of UTF-8 characters captured for this shell call's combined output.

status: optional "in_progress" or "completed" or "incomplete"

The status of the shell call output.

One of the following:

"in_progress"

"completed"

"incomplete"

ApplyPatchCall = object { call_id, operation, status, 2 more }

A tool call representing a request to create, delete, or update files using diff patches.

call_id: string

The unique ID of the apply patch tool call generated by the model.

maxLength64

minLength1

operation: object { diff, path, type } or object { path, type } or object { diff, path, type }

The specific create, delete, or update instruction for the apply_patch tool call.

One of the following:

CreateFile = object { diff, path, type }

Instruction for creating a new file via the apply_patch tool.

diff: string

Unified diff content to apply when creating the file.

maxLength10485760

path: string

Path of the file to create relative to the workspace root.

minLength1

type: "create_file"

The operation type. Always create_file.

DeleteFile = object { path, type }

Instruction for deleting an existing file via the apply_patch tool.

path: string

Path of the file to delete relative to the workspace root.

minLength1

type: "delete_file"

The operation type. Always delete_file.

UpdateFile = object { diff, path, type }

Instruction for updating an existing file via the apply_patch tool.

diff: string

Unified diff content to apply to the existing file.

maxLength10485760

path: string

Path of the file to update relative to the workspace root.

minLength1

type: "update_file"

The operation type. Always update_file.

status: "in_progress" or "completed"

The status of the apply patch tool call. One of in_progress or completed.

One of the following:

"in_progress"

"completed"

type: "apply_patch_call"

The type of the item. Always apply_patch_call.

id: optional string

The unique ID of the apply patch tool call. Populated when this item is returned via API.

ApplyPatchCallOutput = object { call_id, status, type, 2 more }

The streamed output emitted by an apply patch tool call.

call_id: string

The unique ID of the apply patch tool call generated by the model.

maxLength64

minLength1

status: "completed" or "failed"

The status of the apply patch tool call output. One of completed or failed.

One of the following:

"completed"

"failed"

type: "apply_patch_call_output"

The type of the item. Always apply_patch_call_output.

id: optional string

The unique ID of the apply patch tool call output. Populated when this item is returned via API.

output: optional string

Optional human-readable log text from the apply patch tool (e.g., patch results or errors).

maxLength10485760

McpListTools = object { id, server_label, tools, 2 more }

A list of tools available on an MCP server.

id: string

The unique ID of the list.

server_label: string

The label of the MCP server.

tools: array of object { input_schema, name, annotations, description }

The tools available on the server.

input_schema: unknown

The JSON schema describing the tool's input.

The name of the tool.

annotations: optional unknown

Additional annotations about the tool.

description: optional string

The description of the tool.

type: "mcp_list_tools"

The type of the item. Always mcp_list_tools.

error: optional string

Error message if the server could not list tools.

McpApprovalRequest = object { id, arguments, name, 2 more }

A request for human approval of a tool invocation.

id: string

The unique ID of the approval request.

arguments: string

A JSON string of arguments for the tool.

The name of the tool to run.

server_label: string

The label of the MCP server making the request.

type: "mcp_approval_request"

The type of the item. Always mcp_approval_request.

McpApprovalResponse = object { approval_request_id, approve, type, 2 more }

A response to an MCP approval request.

approval_request_id: string

The ID of the approval request being answered.

approve: boolean

Whether the request was approved.

type: "mcp_approval_response"

The type of the item. Always mcp_approval_response.

id: optional string

The unique ID of the approval response

reason: optional string

Optional reason for the decision.

McpCall = object { id, arguments, name, 6 more }

An invocation of a tool on an MCP server.

id: string

The unique ID of the tool call.

arguments: string

A JSON string of the arguments passed to the tool.

The name of the tool that was run.

server_label: string

The label of the MCP server running the tool.

type: "mcp_call"

The type of the item. Always mcp_call.

approval_request_id: optional string

Unique identifier for the MCP tool call approval request. Include this value in a subsequent mcp_approval_response input to approve or reject the corresponding tool call.

error: optional string

The error from the tool call, if any.

output: optional string

The output from the tool call.

status: optional "in_progress" or "completed" or "incomplete" or 2 more

The status of the tool call. One of in_progress, completed, incomplete, calling, or failed.

One of the following:

"in_progress"

"completed"

"incomplete"

"calling"

"failed"

CustomToolCallOutput = object { call_id, output, type, id }

The output of a custom tool call from your code, being sent back to the model.

call_id: string

The call ID, used to map this custom tool call output to a custom tool call.

output: string or array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

The output from the custom tool call generated by your code. Can be a string or an list of output content.

One of the following:

StringOutput = string

A string of the output of the custom tool call.

OutputContentList = array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

Text, image, or file output of the custom tool call.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

type: "custom_tool_call_output"

The type of the custom tool call output. Always custom_tool_call_output.

id: optional string

The unique ID of the custom tool call output in the OpenAI platform.

CustomToolCall = object { call_id, input, name, 3 more }

A call to a custom tool created by the model.

call_id: string

An identifier used to map this custom tool call to a tool call output.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool being called.

type: "custom_tool_call"

The type of the custom tool call. Always custom_tool_call.

id: optional string

The unique ID of the custom tool call in the OpenAI platform.

namespace: optional string

The namespace of the custom tool being called.

ItemReference = object { id, type }

An internal identifier for an item to reference.

id: string

The ID of the item to reference.

type: optional "item_reference"

The type of item to reference. Always item_reference.

instructions: optional string

A system (or developer) message inserted into the model's context.

When using along with previous_response_id, the instructions from a previous response will not be carried over to the next response. This makes it simple to swap out system (or developer) messages in new responses.

max_output_tokens: optional number

An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.

max_tool_calls: optional number

The maximum number of total calls to built-in tools that can be processed in a response. This maximum number applies across all built-in tool calls, not per individual tool. Any further attempts to call a tool by the model will be ignored.

metadata: optional Metadata

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

model: optional ResponsesModel

Model ID used to generate the response, like gpt-4o or o3. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.

One of the following:

string

"gpt-5.4" or "gpt-5.4-mini" or "gpt-5.4-nano" or 75 more

One of the following:

"gpt-5.4"

"gpt-5.4-mini"

"gpt-5.4-nano"

"gpt-5.4-mini-2026-03-17"

"gpt-5.4-nano-2026-03-17"

"gpt-5.3-chat-latest"

"gpt-5.2"

"gpt-5.2-2025-12-11"

"gpt-5.2-chat-latest"

"gpt-5.2-pro"

"gpt-5.2-pro-2025-12-11"

"gpt-5.1"

"gpt-5.1-2025-11-13"

"gpt-5.1-codex"

"gpt-5.1-mini"

"gpt-5.1-chat-latest"

"gpt-5"

"gpt-5-mini"

"gpt-5-nano"

"gpt-5-2025-08-07"

"gpt-5-mini-2025-08-07"

"gpt-5-nano-2025-08-07"

"gpt-5-chat-latest"

"gpt-4.1"

"gpt-4.1-mini"

"gpt-4.1-nano"

"gpt-4.1-2025-04-14"

"gpt-4.1-mini-2025-04-14"

"gpt-4.1-nano-2025-04-14"

"o4-mini"

"o4-mini-2025-04-16"

"o3"

"o3-2025-04-16"

"o3-mini"

"o3-mini-2025-01-31"

"o1"

"o1-2024-12-17"

"o1-preview"

"o1-preview-2024-09-12"

"o1-mini"

"o1-mini-2024-09-12"

"gpt-4o"

"gpt-4o-2024-11-20"

"gpt-4o-2024-08-06"

"gpt-4o-2024-05-13"

"gpt-4o-audio-preview"

"gpt-4o-audio-preview-2024-10-01"

"gpt-4o-audio-preview-2024-12-17"

"gpt-4o-audio-preview-2025-06-03"

"gpt-4o-mini-audio-preview"

"gpt-4o-mini-audio-preview-2024-12-17"

"gpt-4o-search-preview"

"gpt-4o-mini-search-preview"

"gpt-4o-search-preview-2025-03-11"

"gpt-4o-mini-search-preview-2025-03-11"

"chatgpt-4o-latest"

"codex-mini-latest"

"gpt-4o-mini"

"gpt-4o-mini-2024-07-18"

"gpt-4-turbo"

"gpt-4-turbo-2024-04-09"

"gpt-4-0125-preview"

"gpt-4-turbo-preview"

"gpt-4-1106-preview"

"gpt-4-vision-preview"

"gpt-4"

"gpt-4-0314"

"gpt-4-0613"

"gpt-4-32k"

"gpt-4-32k-0314"

"gpt-4-32k-0613"

"gpt-3.5-turbo"

"gpt-3.5-turbo-16k"

"gpt-3.5-turbo-0301"

"gpt-3.5-turbo-0613"

"gpt-3.5-turbo-1106"

"gpt-3.5-turbo-0125"

"gpt-3.5-turbo-16k-0613"

ResponsesOnlyModel = "o1-pro" or "o1-pro-2025-03-19" or "o3-pro" or 11 more

One of the following:

"o1-pro"

"o1-pro-2025-03-19"

"o3-pro"

"o3-pro-2025-06-10"

"o3-deep-research"

"o3-deep-research-2025-06-26"

"o4-mini-deep-research"

"o4-mini-deep-research-2025-06-26"

"computer-use-preview"

"computer-use-preview-2025-03-11"

"gpt-5-codex"

"gpt-5-pro"

"gpt-5-pro-2025-10-06"

"gpt-5.1-codex-max"

parallel_tool_calls: optional boolean

Whether to allow the model to run tool calls in parallel.

previous_response_id: optional string

The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state. Cannot be used in conjunction with conversation.

prompt: optional ResponsePrompt { id, variables, version }

Reference to a prompt template and its variables. Learn more.

id: string

The unique identifier of the prompt template to use.

variables: optional map[string or ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more } ]

Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

One of the following:

string

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

version: optional string

Optional version of the prompt template.

prompt_cache_key: optional string

Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.

prompt_cache_retention: optional "in-memory" or "24h"

The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more.

One of the following:

"in-memory"

"24h"

reasoning: optional Reasoning { effort, generate_summary, summary }

gpt-5 and o-series models only

Configuration options for reasoning models.

effort: optional ReasoningEffort

Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
All models before gpt-5.1 default to medium reasoning effort, and do not support none.
The gpt-5-pro model defaults to (and only supports) high reasoning effort.
xhigh is supported for all models after gpt-5.1-codex-max.

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

Deprecatedgenerate_summary: optional "auto" or "concise" or "detailed"

Deprecated: use summary instead.

A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

One of the following:

"auto"

"concise"

"detailed"

summary: optional "auto" or "concise" or "detailed"

A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

concise is supported for computer-use-preview models and all reasoning models after gpt-5.

One of the following:

"auto"

"concise"

"detailed"

safety_identifier: optional string

A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies. The IDs should be a string that uniquely identifies each user, with a maximum length of 64 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.

maxLength64

service_tier: optional "auto" or "default" or "flex" or 2 more

Specifies the processing type used for serving the request.

If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier.
When not set, the default behavior is 'auto'.

When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

One of the following:

"auto"

"default"

"flex"

"scale"

"priority"

store: optional boolean

Whether to store the generated model response for later retrieval via API.

stream: optional boolean

If set to true, the model response data will be streamed to the client as it is generated using server-sent events. See the Streaming section below for more information.

stream_options: optional object { include_obfuscation }

Options for streaming responses. Only set this when you set stream: true.

include_obfuscation: optional boolean

When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an obfuscation field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set include_obfuscation to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API.

temperature: optional number

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. We generally recommend altering this or top_p but not both.

minimum0

maximum2

text: optional ResponseTextConfig { format, verbosity }

Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more:

format: optional ResponseFormatTextConfig

An object specifying the format that the model must output.

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

The default format is { "type": "text" } with no additional options.

Not recommended for gpt-4o and newer models:

Setting to { "type": "json_object" } enables the older JSON mode, which ensures the message the model generates is valid JSON. Using json_schema is preferred for models that support it.

One of the following:

ResponseFormatText = object { type }

Default response format. Used to generate text responses.

type: "text"

The type of response format being defined. Always text.

ResponseFormatTextJSONSchemaConfig = object { name, schema, type, 2 more }

JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

schema: map[unknown]

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

type: "json_schema"

The type of response format being defined. Always json_schema.

description: optional string

A description of what the response format is for, used by the model to determine how to respond in the format.

strict: optional boolean

Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the schema field. Only a subset of JSON Schema is supported when strict is true. To learn more, read the Structured Outputs guide.

ResponseFormatJSONObject = object { type }

JSON object response format. An older method of generating JSON responses. Using json_schema is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.

type: "json_object"

The type of response format being defined. Always json_object.

verbosity: optional "low" or "medium" or "high"

Constrains the verbosity of the model's response. Lower values will result in more concise responses, while higher values will result in more verbose responses. Currently supported values are low, medium, and high.

One of the following:

"low"

"medium"

"high"

tool_choice: optional ToolChoiceOptions or ToolChoiceAllowed { mode, tools, type } or ToolChoiceTypes { type } or 5 more

How the model should select which tool (or tools) to use when generating a response. See the tools parameter to see how to specify which tools the model can call.

One of the following:

ToolChoiceOptions = "none" or "auto" or "required"

Controls which (if any) tool is called by the model.

none means the model will not call any tool and instead generates a message.

auto 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.

One of the following:

"none"

"auto"

"required"

ToolChoiceAllowed = object { mode, tools, type }

Constrains the tools available to the model to a pre-defined set.

mode: "auto" or "required"

Constrains the tools available to the model to a pre-defined set.

auto allows the model to pick from among the allowed tools and generate a message.

required requires the model to call one or more of the allowed tools.

One of the following:

"auto"

"required"

tools: array of map[unknown]

A list of tool definitions that the model should be allowed to call.

For the Responses API, the list of tool definitions might look like:

[
  { "type": "function", "name": "get_weather" },
  { "type": "mcp", "server_label": "deepwiki" },
  { "type": "image_generation" }
]

type: "allowed_tools"

Allowed tool configuration type. Always allowed_tools.

ToolChoiceTypes = object { type }

Indicates that the model should use a built-in tool to generate a response. Learn more about built-in tools.

type: "file_search" or "web_search_preview" or "computer" or 5 more

The type of hosted tool the model should to use. Learn more about built-in tools.

Allowed values are:

file_search
web_search_preview
computer
computer_use_preview
computer_use
code_interpreter
image_generation

One of the following:

"file_search"

"web_search_preview"

"computer"

"computer_use_preview"

"computer_use"

"web_search_preview_2025_03_11"

"image_generation"

"code_interpreter"

ToolChoiceFunction = object { name, type }

Use this option to force the model to call a specific function.

The name of the function to call.

type: "function"

For function calling, the type is always function.

ToolChoiceMcp = object { server_label, type, name }

Use this option to force the model to call a specific tool on a remote MCP server.

server_label: string

The label of the MCP server to use.

type: "mcp"

For MCP tools, the type is always mcp.

The name of the tool to call on the server.

ToolChoiceCustom = object { name, type }

Use this option to force the model to call a specific custom tool.

The name of the custom tool to call.

type: "custom"

For custom tool calling, the type is always custom.

ToolChoiceApplyPatch = object { type }

Forces the model to call the apply_patch tool when executing a tool call.

type: "apply_patch"

The tool to call. Always apply_patch.

ToolChoiceShell = object { type }

Forces the model to call the shell tool when a tool call is required.

type: "shell"

The tool to call. Always shell.

tools: optional array of object { name, parameters, strict, 3 more } or object { type, vector_store_ids, filters, 2 more } or object { type } or 12 more

An array of tools the model may call while generating a response. You can specify which tool to use by setting the tool_choice parameter.

We support the following categories of tools:

Built-in tools: Tools that are provided by OpenAI that extend the model's capabilities, like web search or file search. Learn more about built-in tools.
MCP Tools: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about MCP Tools.
Function calls (custom tools): Functions that are defined by you, enabling the model to call your own code with strongly typed arguments and outputs. Learn more about function calling. You can also use custom tools to call your own code.

One of the following:

Function = object { name, parameters, strict, 3 more }

Defines a function in your own code the model can choose to call. Learn more about function calling.

The name of the function to call.

parameters: map[unknown]

A JSON schema object describing the parameters of the function.

strict: boolean

Whether to enforce strict parameter validation. Default true.

type: "function"

The type of the function tool. Always function.

defer_loading: optional boolean

Whether this function is deferred and loaded via tool search.

description: optional string

A description of the function. Used by the model to determine whether or not to call the function.

FileSearch = object { type, vector_store_ids, filters, 2 more }

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: "file_search"

The type of the file search tool. Always file_search.

vector_store_ids: array of string

The IDs of the vector stores to search.

filters: optional ComparisonFilter { key, type, value } or CompoundFilter { filters, type }

A filter to apply.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

CompoundFilter = object { filters, type }

Combine multiple filters using and or or.

filters: array of ComparisonFilter { key, type, value } or unknown

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

unknown

type: "and" or "or"

Type of operation: and or or.

One of the following:

"and"

"or"

max_num_results: optional number

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: optional object { hybrid_search, ranker, score_threshold }

Ranking options for search.

hybrid_search: optional object { embedding_weight, text_weight }

Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled.

embedding_weight: number

The weight of the embedding in the reciprocal ranking fusion.

text_weight: number

The weight of the text in the reciprocal ranking fusion.

ranker: optional "auto" or "default-2024-11-15"

The ranker to use for the file search.

One of the following:

"auto"

"default-2024-11-15"

score_threshold: optional number

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

Computer = object { type }

A tool that controls a virtual computer. Learn more about the computer tool.

type: "computer"

The type of the computer tool. Always computer.

ComputerUsePreview = object { display_height, display_width, environment, type }

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: number

The height of the computer display.

display_width: number

The width of the computer display.

environment: "windows" or "mac" or "linux" or 2 more

The type of computer environment to control.

One of the following:

"windows"

"mac"

"linux"

"ubuntu"

"browser"

type: "computer_use_preview"

The type of the computer use tool. Always computer_use_preview.

WebSearch = object { type, filters, search_context_size, user_location }

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: "web_search" or "web_search_2025_08_26"

The type of the web search tool. One of web_search or web_search_2025_08_26.

One of the following:

"web_search"

"web_search_2025_08_26"

filters: optional object { allowed_domains }

Filters for the search.

allowed_domains: optional array of string

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { city, country, region, 2 more }

The approximate location of the user.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

type: optional "approximate"

The type of location approximation. Always approximate.

Mcp = object { server_label, type, allowed_tools, 7 more }

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: string

A label for this MCP server, used to identify it in tool calls.

type: "mcp"

The type of the MCP tool. Always mcp.

allowed_tools: optional array of string or object { read_only, tool_names }

List of allowed tool names or a filter object.

One of the following:

McpAllowedTools = array of string

A string array of allowed tool names

McpToolFilter = object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

authorization: optional string

connector_id: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more

Identifier for service connectors, like those available in ChatGPT. One of server_url or connector_id must be provided. Learn more about service connectors here.

Currently supported connector_id values are:

Dropbox: connector_dropbox
Gmail: connector_gmail
Google Calendar: connector_googlecalendar
Google Drive: connector_googledrive
Microsoft Teams: connector_microsoftteams
Outlook Calendar: connector_outlookcalendar
Outlook Email: connector_outlookemail
SharePoint: connector_sharepoint

One of the following:

"connector_dropbox"

"connector_gmail"

"connector_googlecalendar"

"connector_googledrive"

"connector_microsoftteams"

"connector_outlookcalendar"

"connector_outlookemail"

"connector_sharepoint"

defer_loading: optional boolean

Whether this MCP tool is deferred and discovered via tool search.

headers: optional map[string]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: optional object { always, never } or "always" or "never"

Specify which of the MCP server's tools require approval.

One of the following:

McpToolApprovalFilter = object { always, never }

Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

never: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

McpToolApprovalSetting = "always" or "never"

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

One of the following:

"always"

"never"

server_description: optional string

Optional description of the MCP server, used to provide more context.

server_url: optional string

The URL for the MCP server. One of server_url or connector_id must be provided.

CodeInterpreter = object { container, type }

A tool that runs Python code to help generate a response to a prompt.

container: string or object { type, file_ids, memory_limit, network_policy }

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

One of the following:

string

The container ID.

CodeInterpreterToolAuto = object { type, file_ids, memory_limit, network_policy }

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: "auto"

Always auto.

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the code interpreter container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

type: "code_interpreter"

The type of the code interpreter tool. Always code_interpreter.

ImageGeneration = object { type, action, background, 9 more }

A tool that generates images using the GPT image models.

type: "image_generation"

The type of the image generation tool. Always image_generation.

action: optional "generate" or "edit" or "auto"

Whether to generate a new image or edit an existing image. Default: auto.

One of the following:

"generate"

"edit"

"auto"

background: optional "transparent" or "opaque" or "auto"

Background type for the generated image. One of transparent, opaque, or auto. Default: auto.

One of the following:

"transparent"

"opaque"

"auto"

input_fidelity: optional "high" or "low"

One of the following:

"high"

"low"

input_image_mask: optional object { file_id, image_url }

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: optional string

File ID for the mask image.

image_url: optional string

Base64-encoded mask image.

model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

string

"gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

"gpt-image-1"

"gpt-image-1-mini"

"gpt-image-1.5"

moderation: optional "auto" or "low"

Moderation level for the generated image. Default: auto.

One of the following:

"auto"

"low"

output_compression: optional number

Compression level for the output image. Default: 100.

minimum0

maximum100

output_format: optional "png" or "webp" or "jpeg"

The output format of the generated image. One of png, webp, or jpeg. Default: png.

One of the following:

"png"

"webp"

"jpeg"

partial_images: optional number

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0

maximum3

quality: optional "low" or "medium" or "high" or "auto"

The quality of the generated image. One of low, medium, high, or auto. Default: auto.

One of the following:

"low"

"medium"

"high"

"auto"

size: optional "1024x1024" or "1024x1536" or "1536x1024" or "auto"

The size of the generated image. One of 1024x1024, 1024x1536, 1536x1024, or auto. Default: auto.

One of the following:

"1024x1024"

"1024x1536"

"1536x1024"

"auto"

LocalShell = object { type }

A tool that allows the model to execute shell commands in a local environment.

type: "local_shell"

The type of the local shell tool. Always local_shell.

Shell = object { type, environment }

A tool that allows the model to execute shell commands.

type: "shell"

The type of the shell tool. Always shell.

environment: optional ContainerAuto { type, file_ids, memory_limit, 2 more } or LocalEnvironment { type, skills } or ContainerReference { container_id, type }

One of the following:

ContainerAuto = object { type, file_ids, memory_limit, 2 more }

type: "container_auto"

Automatically creates a container for this request

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

skills: optional array of SkillReference { skill_id, type, version } or InlineSkill { description, name, source, type }

An optional list of skills referenced by id or inline data.

One of the following:

SkillReference = object { skill_id, type, version }

skill_id: string

The ID of the referenced skill.

maxLength64

minLength1

type: "skill_reference"

References a skill created with the /v1/skills endpoint.

version: optional string

Optional skill version. Use a positive integer or 'latest'. Omit for default.

InlineSkill = object { description, name, source, type }

description: string

The description of the skill.

The name of the skill.

source: InlineSkillSource { data, media_type, type }

Inline skill payload

data: string

Base64-encoded skill zip bundle.

maxLength70254592

minLength1

media_type: "application/zip"

The media type of the inline skill payload. Must be application/zip.

type: "base64"

The type of the inline skill source. Must be base64.

type: "inline"

Defines an inline skill for this request.

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

Namespace = object { description, name, tools, type }

Groups function/custom tools under a shared namespace.

description: string

A description of the namespace shown to the model.

minLength1

The namespace name used in tool calls (for example, crm).

minLength1

tools: array of object { name, type, defer_loading, 3 more } or object { name, type, defer_loading, 2 more }

The function/custom tools available inside this namespace.

One of the following:

Function = object { name, type, defer_loading, 3 more }

maxLength128

minLength1

type: "function"

defer_loading: optional boolean

Whether this function should be deferred and discovered via tool search.

description: optional string

parameters: optional unknown

strict: optional boolean

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "namespace"

The type of the tool. Always namespace.

ToolSearch = object { type, description, execution, parameters }

Hosted or BYOT tool search configuration for deferred tools.

type: "tool_search"

The type of the tool. Always tool_search.

description: optional string

Description shown to the model for a client-executed tool search tool.

execution: optional "server" or "client"

Whether tool search is executed by the server or by the client.

One of the following:

"server"

"client"

parameters: optional unknown

Parameter schema for a client-executed tool search tool.

WebSearchPreview = object { type, search_content_types, search_context_size, user_location }

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: "web_search_preview" or "web_search_preview_2025_03_11"

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

One of the following:

"web_search_preview"

"web_search_preview_2025_03_11"

search_content_types: optional array of "text" or "image"

One of the following:

"text"

"image"

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { type, city, country, 2 more }

The user's location.

type: "approximate"

The type of location approximation. Always approximate.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

ApplyPatch = object { type }

Allows the assistant to create, delete, or update files using unified diffs.

type: "apply_patch"

The type of the tool. Always apply_patch.

top_logprobs: optional number

An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.

minimum0

maximum20

top_p: optional number

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.

minimum0

maximum1

truncation: optional "auto" or "disabled"

The truncation strategy to use for the model response.

auto: If the input to this Response exceeds the model's context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation.
disabled (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error.

One of the following:

"auto"

"disabled"

Deprecateduser: optional string

This field is being replaced by safety_identifier and prompt_cache_key. Use prompt_cache_key instead to maintain caching optimizations. A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. Learn more.

ReturnsExpand Collapse

Response = object { id, created_at, error, 30 more }

id: string

Unique identifier for this Response.

created_at: number

Unix timestamp (in seconds) of when this Response was created.

error: ResponseError { code, message }

An error object returned when the model fails to generate a Response.

code: "server_error" or "rate_limit_exceeded" or "invalid_prompt" or 15 more

The error code for the response.

One of the following:

"server_error"

"rate_limit_exceeded"

"invalid_prompt"

"vector_store_timeout"

"invalid_image"

"invalid_image_format"

"invalid_base64_image"

"invalid_image_url"

"image_too_large"

"image_too_small"

"image_parse_error"

"image_content_policy_violation"

"invalid_image_mode"

"image_file_too_large"

"unsupported_image_media_type"

"empty_image_file"

"failed_to_download_image"

"image_file_not_found"

message: string

A human-readable description of the error.

incomplete_details: object { reason }

Details about why the response is incomplete.

reason: optional "max_output_tokens" or "content_filter"

The reason why the response is incomplete.

One of the following:

"max_output_tokens"

"content_filter"

instructions: string or array of EasyInputMessage { content, role, phase, type } or object { content, role, status, type } or ResponseOutputMessage { id, content, role, 3 more } or 25 more

A system (or developer) message inserted into the model's context.

One of the following:

string

A text input to the model, equivalent to a text input with the developer role.

InputItemList = array of EasyInputMessage { content, role, phase, type } or object { content, role, status, type } or ResponseOutputMessage { id, content, role, 3 more } or 25 more

A list of one or many input items to the model, containing different content types.

One of the following:

EasyInputMessage = object { content, role, phase, type }

content: string or ResponseInputMessageContentList { , , }

Text, image, or audio input to the model, used to generate a response. Can also contain previous assistant responses.

One of the following:

TextInput = string

A text input to the model.

ResponseInputMessageContentList = array of ResponseInputContent

A list of one or many input items to the model, containing different content types.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

role: "user" or "assistant" or "system" or "developer"

The role of the message input. One of user, assistant, system, or developer.

One of the following:

"user"

"assistant"

"system"

"developer"

phase: optional "commentary" or "final_answer"

One of the following:

"commentary"

"final_answer"

type: optional "message"

The type of the message input. Always message.

Message = object { content, role, status, type }

content: ResponseInputMessageContentList { , , }

A list of one or many input items to the model, containing different content types.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

role: "user" or "system" or "developer"

The role of the message input. One of user, system, or developer.

One of the following:

"user"

"system"

"developer"

status: optional "in_progress" or "completed" or "incomplete"

The status of item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: optional "message"

The type of the message input. Always set to message.

ResponseOutputMessage = object { id, content, role, 3 more }

An output message from the model.

id: string

The unique ID of the output message.

content: array of ResponseOutputText { annotations, logprobs, text, type } or ResponseOutputRefusal { refusal, type }

The content of the output message.

One of the following:

ResponseOutputText = object { annotations, logprobs, text, type }

A text output from the model.

The annotations of the text output.

One of the following:

FileCitation = object { file_id, filename, index, type }

A citation to a file.

file_id: string

The ID of the file.

filename: string

The filename of the file cited.

index: number

The index of the file in the list of files.

type: "file_citation"

The type of the file citation. Always file_citation.

URLCitation = object { end_index, start_index, title, 2 more }

A citation for a web resource used to generate a model response.

end_index: number

The index of the last character of the URL citation in the message.

start_index: number

The index of the first character of the URL citation in the message.

title: string

The title of the web resource.

type: "url_citation"

The type of the URL citation. Always url_citation.

url: string

The URL of the web resource.

ContainerFileCitation = object { container_id, end_index, file_id, 3 more }

A citation for a container file used to generate a model response.

container_id: string

The ID of the container file.

end_index: number

The index of the last character of the container file citation in the message.

file_id: string

The ID of the file.

filename: string

The filename of the container file cited.

start_index: number

The index of the first character of the container file citation in the message.

type: "container_file_citation"

The type of the container file citation. Always container_file_citation.

FilePath = object { file_id, index, type }

A path to a file.

file_id: string

The ID of the file.

index: number

The index of the file in the list of files.

type: "file_path"

The type of the file path. Always file_path.

logprobs: array of object { token, bytes, logprob, top_logprobs }

token: string

bytes: array of number

logprob: number

top_logprobs: array of object { token, bytes, logprob }

token: string

bytes: array of number

logprob: number

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

ResponseOutputRefusal = object { refusal, type }

A refusal from the model.

refusal: string

The refusal explanation from the model.

type: "refusal"

The type of the refusal. Always refusal.

role: "assistant"

The role of the output message. Always assistant.

status: "in_progress" or "completed" or "incomplete"

The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "message"

The type of the output message. Always message.

phase: optional "commentary" or "final_answer"

One of the following:

"commentary"

"final_answer"

FileSearchCall = object { id, queries, status, 2 more }

The results of a file search tool call. See the file search guide for more information.

id: string

The unique ID of the file search tool call.

queries: array of string

The queries used to search for files.

status: "in_progress" or "searching" or "completed" or 2 more

The status of the file search tool call. One of in_progress, searching, incomplete or failed,

One of the following:

"in_progress"

"searching"

"completed"

"incomplete"

"failed"

type: "file_search_call"

The type of the file search tool call. Always file_search_call.

results: optional array of object { attributes, file_id, filename, 2 more }

The results of the file search tool call.

attributes: optional map[string or number or boolean]

One of the following:

string

number

boolean

file_id: optional string

The unique ID of the file.

filename: optional string

The name of the file.

score: optional number

The relevance score of the file - a value between 0 and 1.

formatfloat

text: optional string

The text that was retrieved from the file.

ComputerCall = object { id, call_id, pending_safety_checks, 4 more }

A tool call to a computer use tool. See the computer use guide for more information.

id: string

The unique ID of the computer call.

call_id: string

An identifier used when responding to the tool call with output.

pending_safety_checks: array of object { id, code, message }

The pending safety checks for the computer call.

id: string

The ID of the pending safety check.

code: optional string

The type of the pending safety check.

message: optional string

Details about the pending safety check.

status: "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "computer_call"

The type of the computer call. Always computer_call.

action: optional ComputerAction

A click action.

One of the following:

Click = object { button, type, x, 2 more }

A click action.

button: "left" or "right" or "wheel" or 2 more

Indicates which mouse button was pressed during the click. One of left, right, wheel, back, or forward.

One of the following:

"left"

"right"

"wheel"

"back"

"forward"

type: "click"

Specifies the event type. For a click action, this property is always click.

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys: optional array of string

The keys being held while clicking.

DoubleClick = object { keys, type, x, y }

A double click action.

keys: array of string

The keys being held while double-clicking.

type: "double_click"

Specifies the event type. For a double click action, this property is always set to double_click.

x: number

The x-coordinate where the double click occurred.

y: number

The y-coordinate where the double click occurred.

Drag = object { path, type, keys }

A drag action.

path: array of object { x, y }

An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg

[
  { x: 100, y: 200 },
  { x: 200, y: 300 }
]

x: number

The x-coordinate.

y: number

The y-coordinate.

type: "drag"

Specifies the event type. For a drag action, this property is always set to drag.

keys: optional array of string

The keys being held while dragging the mouse.

Keypress = object { keys, type }

A collection of keypresses the model would like to perform.

keys: array of string

The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key.

type: "keypress"

Specifies the event type. For a keypress action, this property is always set to keypress.

Move = object { type, x, y, keys }

A mouse move action.

type: "move"

Specifies the event type. For a move action, this property is always set to move.

x: number

The x-coordinate to move to.

y: number

The y-coordinate to move to.

keys: optional array of string

The keys being held while moving the mouse.

Screenshot = object { type }

A screenshot action.

type: "screenshot"

Specifies the event type. For a screenshot action, this property is always set to screenshot.

Scroll = object { scroll_x, scroll_y, type, 3 more }

A scroll action.

scroll_x: number

The horizontal scroll distance.

scroll_y: number

The vertical scroll distance.

type: "scroll"

Specifies the event type. For a scroll action, this property is always set to scroll.

x: number

The x-coordinate where the scroll occurred.

y: number

The y-coordinate where the scroll occurred.

keys: optional array of string

The keys being held while scrolling.

Type = object { text, type }

An action to type in text.

text: string

The text to type.

type: "type"

Specifies the event type. For a type action, this property is always set to type.

Wait = object { type }

A wait action.

type: "wait"

Specifies the event type. For a wait action, this property is always set to wait.

actions: optional ComputerActionList { Click, DoubleClick, Drag, 6 more }

Flattened batched actions for computer_use. Each action includes an type discriminator and action-specific fields.

One of the following:

Click = object { button, type, x, 2 more }

A click action.

button: "left" or "right" or "wheel" or 2 more

Indicates which mouse button was pressed during the click. One of left, right, wheel, back, or forward.

One of the following:

"left"

"right"

"wheel"

"back"

"forward"

type: "click"

Specifies the event type. For a click action, this property is always click.

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys: optional array of string

The keys being held while clicking.

DoubleClick = object { keys, type, x, y }

A double click action.

keys: array of string

The keys being held while double-clicking.

type: "double_click"

Specifies the event type. For a double click action, this property is always set to double_click.

x: number

The x-coordinate where the double click occurred.

y: number

The y-coordinate where the double click occurred.

Drag = object { path, type, keys }

A drag action.

path: array of object { x, y }

An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg

[
  { x: 100, y: 200 },
  { x: 200, y: 300 }
]

x: number

The x-coordinate.

y: number

The y-coordinate.

type: "drag"

Specifies the event type. For a drag action, this property is always set to drag.

keys: optional array of string

The keys being held while dragging the mouse.

Keypress = object { keys, type }

A collection of keypresses the model would like to perform.

keys: array of string

The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key.

type: "keypress"

Specifies the event type. For a keypress action, this property is always set to keypress.

Move = object { type, x, y, keys }

A mouse move action.

type: "move"

Specifies the event type. For a move action, this property is always set to move.

x: number

The x-coordinate to move to.

y: number

The y-coordinate to move to.

keys: optional array of string

The keys being held while moving the mouse.

Screenshot = object { type }

A screenshot action.

type: "screenshot"

Specifies the event type. For a screenshot action, this property is always set to screenshot.

Scroll = object { scroll_x, scroll_y, type, 3 more }

A scroll action.

scroll_x: number

The horizontal scroll distance.

scroll_y: number

The vertical scroll distance.

type: "scroll"

Specifies the event type. For a scroll action, this property is always set to scroll.

x: number

The x-coordinate where the scroll occurred.

y: number

The y-coordinate where the scroll occurred.

keys: optional array of string

The keys being held while scrolling.

Type = object { text, type }

An action to type in text.

text: string

The text to type.

type: "type"

Specifies the event type. For a type action, this property is always set to type.

Wait = object { type }

A wait action.

type: "wait"

Specifies the event type. For a wait action, this property is always set to wait.

ComputerCallOutput = object { call_id, output, type, 3 more }

The output of a computer tool call.

call_id: string

The ID of the computer tool call that produced the output.

maxLength64

minLength1

output: ResponseComputerToolCallOutputScreenshot { type, file_id, image_url }

A computer screenshot image used with the computer use tool.

type: "computer_screenshot"

Specifies the event type. For a computer screenshot, this property is always set to computer_screenshot.

file_id: optional string

The identifier of an uploaded file that contains the screenshot.

image_url: optional string

The URL of the screenshot image.

type: "computer_call_output"

The type of the computer tool call output. Always computer_call_output.

id: optional string

The ID of the computer tool call output.

acknowledged_safety_checks: optional array of object { id, code, message }

The safety checks reported by the API that have been acknowledged by the developer.

id: string

The ID of the pending safety check.

code: optional string

The type of the pending safety check.

message: optional string

Details about the pending safety check.

status: optional "in_progress" or "completed" or "incomplete"

The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

WebSearchCall = object { id, action, status, type }

The results of a web search tool call. See the web search guide for more information.

id: string

The unique ID of the web search tool call.

action: object { query, type, queries, sources } or object { type, url } or object { pattern, type, url }

An object describing the specific action taken in this web search call. Includes details on how the model used the web (search, open_page, find_in_page).

One of the following:

Search = object { query, type, queries, sources }

Action type "search" - Performs a web search query.

query: string

[DEPRECATED] The search query.

type: "search"

The action type.

queries: optional array of string

The search queries.

sources: optional array of object { type, url }

The sources used in the search.

type: "url"

The type of source. Always url.

url: string

The URL of the source.

OpenPage = object { type, url }

Action type "open_page" - Opens a specific URL from search results.

type: "open_page"

The action type.

url: optional string

The URL opened by the model.

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FindInPage = object { pattern, type, url }

Action type "find_in_page": Searches for a pattern within a loaded page.

pattern: string

The pattern or text to search for within the page.

type: "find_in_page"

The action type.

url: string

The URL of the page searched for the pattern.

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status: "in_progress" or "searching" or "completed" or "failed"

The status of the web search tool call.

One of the following:

"in_progress"

"searching"

"completed"

"failed"

type: "web_search_call"

The type of the web search tool call. Always web_search_call.

FunctionCall = object { arguments, call_id, name, 4 more }

A tool call to run a function. See the function calling guide for more information.

arguments: string

A JSON string of the arguments to pass to the function.

call_id: string

The unique ID of the function tool call generated by the model.

The name of the function to run.

type: "function_call"

The type of the function tool call. Always function_call.

id: optional string

The unique ID of the function tool call.

namespace: optional string

The namespace of the function to run.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

FunctionCallOutput = object { call_id, output, type, 2 more }

The output of a function tool call.

call_id: string

The unique ID of the function tool call generated by the model.

maxLength64

minLength1

output: string or array of ResponseInputTextContent { text, type } or ResponseInputImageContent { type, detail, file_id, image_url } or ResponseInputFileContent { type, file_data, file_id, 2 more }

Text, image, or file output of the function tool call.

One of the following:

string

A JSON string of the output of the function tool call.

array of ResponseInputTextContent { text, type } or ResponseInputImageContent { type, detail, file_id, image_url } or ResponseInputFileContent { type, file_data, file_id, 2 more }

An array of content outputs (text, image, file) for the function tool call.

One of the following:

ResponseInputTextContent = object { text, type }

A text input to the model.

text: string

The text input to the model.

maxLength10485760

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImageContent = object { type, detail, file_id, image_url }

An image input to the model. Learn about image inputs

type: "input_image"

The type of the input item. Always input_image.

detail: optional "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

maxLength20971520

ResponseInputFileContent = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The base64-encoded data of the file to be sent to the model.

maxLength33554432

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

type: "function_call_output"

The type of the function tool call output. Always function_call_output.

id: optional string

The unique ID of the function tool call output. Populated when this item is returned via API.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

ToolSearchCall = object { arguments, type, id, 3 more }

arguments: unknown

The arguments supplied to the tool search call.

type: "tool_search_call"

The item type. Always tool_search_call.

id: optional string

The unique ID of this tool search call.

call_id: optional string

The unique ID of the tool search call generated by the model.

maxLength64

minLength1

execution: optional "server" or "client"

Whether tool search was executed by the server or by the client.

One of the following:

"server"

"client"

status: optional "in_progress" or "completed" or "incomplete"

The status of the tool search call.

One of the following:

"in_progress"

"completed"

"incomplete"

ToolSearchOutput = object { tools, type, id, 3 more }

tools: array of object { name, parameters, strict, 3 more } or object { type, vector_store_ids, filters, 2 more } or object { type } or 12 more

The loaded tool definitions returned by the tool search output.

One of the following:

Function = object { name, parameters, strict, 3 more }

Defines a function in your own code the model can choose to call. Learn more about function calling.

The name of the function to call.

parameters: map[unknown]

A JSON schema object describing the parameters of the function.

strict: boolean

Whether to enforce strict parameter validation. Default true.

type: "function"

The type of the function tool. Always function.

defer_loading: optional boolean

Whether this function is deferred and loaded via tool search.

description: optional string

A description of the function. Used by the model to determine whether or not to call the function.

FileSearch = object { type, vector_store_ids, filters, 2 more }

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: "file_search"

The type of the file search tool. Always file_search.

vector_store_ids: array of string

The IDs of the vector stores to search.

filters: optional ComparisonFilter { key, type, value } or CompoundFilter { filters, type }

A filter to apply.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

CompoundFilter = object { filters, type }

Combine multiple filters using and or or.

filters: array of ComparisonFilter { key, type, value } or unknown

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

unknown

type: "and" or "or"

Type of operation: and or or.

One of the following:

"and"

"or"

max_num_results: optional number

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: optional object { hybrid_search, ranker, score_threshold }

Ranking options for search.

hybrid_search: optional object { embedding_weight, text_weight }

Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled.

embedding_weight: number

The weight of the embedding in the reciprocal ranking fusion.

text_weight: number

The weight of the text in the reciprocal ranking fusion.

ranker: optional "auto" or "default-2024-11-15"

The ranker to use for the file search.

One of the following:

"auto"

"default-2024-11-15"

score_threshold: optional number

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

Computer = object { type }

A tool that controls a virtual computer. Learn more about the computer tool.

type: "computer"

The type of the computer tool. Always computer.

ComputerUsePreview = object { display_height, display_width, environment, type }

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: number

The height of the computer display.

display_width: number

The width of the computer display.

environment: "windows" or "mac" or "linux" or 2 more

The type of computer environment to control.

One of the following:

"windows"

"mac"

"linux"

"ubuntu"

"browser"

type: "computer_use_preview"

The type of the computer use tool. Always computer_use_preview.

WebSearch = object { type, filters, search_context_size, user_location }

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: "web_search" or "web_search_2025_08_26"

The type of the web search tool. One of web_search or web_search_2025_08_26.

One of the following:

"web_search"

"web_search_2025_08_26"

filters: optional object { allowed_domains }

Filters for the search.

allowed_domains: optional array of string

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { city, country, region, 2 more }

The approximate location of the user.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

type: optional "approximate"

The type of location approximation. Always approximate.

Mcp = object { server_label, type, allowed_tools, 7 more }

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: string

A label for this MCP server, used to identify it in tool calls.

type: "mcp"

The type of the MCP tool. Always mcp.

allowed_tools: optional array of string or object { read_only, tool_names }

List of allowed tool names or a filter object.

One of the following:

McpAllowedTools = array of string

A string array of allowed tool names

McpToolFilter = object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

authorization: optional string

connector_id: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more

Identifier for service connectors, like those available in ChatGPT. One of server_url or connector_id must be provided. Learn more about service connectors here.

Currently supported connector_id values are:

Dropbox: connector_dropbox
Gmail: connector_gmail
Google Calendar: connector_googlecalendar
Google Drive: connector_googledrive
Microsoft Teams: connector_microsoftteams
Outlook Calendar: connector_outlookcalendar
Outlook Email: connector_outlookemail
SharePoint: connector_sharepoint

One of the following:

"connector_dropbox"

"connector_gmail"

"connector_googlecalendar"

"connector_googledrive"

"connector_microsoftteams"

"connector_outlookcalendar"

"connector_outlookemail"

"connector_sharepoint"

defer_loading: optional boolean

Whether this MCP tool is deferred and discovered via tool search.

headers: optional map[string]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: optional object { always, never } or "always" or "never"

Specify which of the MCP server's tools require approval.

One of the following:

McpToolApprovalFilter = object { always, never }

Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

never: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

McpToolApprovalSetting = "always" or "never"

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

One of the following:

"always"

"never"

server_description: optional string

Optional description of the MCP server, used to provide more context.

server_url: optional string

The URL for the MCP server. One of server_url or connector_id must be provided.

CodeInterpreter = object { container, type }

A tool that runs Python code to help generate a response to a prompt.

container: string or object { type, file_ids, memory_limit, network_policy }

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

One of the following:

string

The container ID.

CodeInterpreterToolAuto = object { type, file_ids, memory_limit, network_policy }

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: "auto"

Always auto.

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the code interpreter container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

type: "code_interpreter"

The type of the code interpreter tool. Always code_interpreter.

ImageGeneration = object { type, action, background, 9 more }

A tool that generates images using the GPT image models.

type: "image_generation"

The type of the image generation tool. Always image_generation.

action: optional "generate" or "edit" or "auto"

Whether to generate a new image or edit an existing image. Default: auto.

One of the following:

"generate"

"edit"

"auto"

background: optional "transparent" or "opaque" or "auto"

Background type for the generated image. One of transparent, opaque, or auto. Default: auto.

One of the following:

"transparent"

"opaque"

"auto"

input_fidelity: optional "high" or "low"

One of the following:

"high"

"low"

input_image_mask: optional object { file_id, image_url }

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: optional string

File ID for the mask image.

image_url: optional string

Base64-encoded mask image.

model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

string

"gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

"gpt-image-1"

"gpt-image-1-mini"

"gpt-image-1.5"

moderation: optional "auto" or "low"

Moderation level for the generated image. Default: auto.

One of the following:

"auto"

"low"

output_compression: optional number

Compression level for the output image. Default: 100.

minimum0

maximum100

output_format: optional "png" or "webp" or "jpeg"

The output format of the generated image. One of png, webp, or jpeg. Default: png.

One of the following:

"png"

"webp"

"jpeg"

partial_images: optional number

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0

maximum3

quality: optional "low" or "medium" or "high" or "auto"

The quality of the generated image. One of low, medium, high, or auto. Default: auto.

One of the following:

"low"

"medium"

"high"

"auto"

size: optional "1024x1024" or "1024x1536" or "1536x1024" or "auto"

The size of the generated image. One of 1024x1024, 1024x1536, 1536x1024, or auto. Default: auto.

One of the following:

"1024x1024"

"1024x1536"

"1536x1024"

"auto"

LocalShell = object { type }

A tool that allows the model to execute shell commands in a local environment.

type: "local_shell"

The type of the local shell tool. Always local_shell.

Shell = object { type, environment }

A tool that allows the model to execute shell commands.

type: "shell"

The type of the shell tool. Always shell.

environment: optional ContainerAuto { type, file_ids, memory_limit, 2 more } or LocalEnvironment { type, skills } or ContainerReference { container_id, type }

One of the following:

ContainerAuto = object { type, file_ids, memory_limit, 2 more }

type: "container_auto"

Automatically creates a container for this request

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

skills: optional array of SkillReference { skill_id, type, version } or InlineSkill { description, name, source, type }

An optional list of skills referenced by id or inline data.

One of the following:

SkillReference = object { skill_id, type, version }

skill_id: string

The ID of the referenced skill.

maxLength64

minLength1

type: "skill_reference"

References a skill created with the /v1/skills endpoint.

version: optional string

Optional skill version. Use a positive integer or 'latest'. Omit for default.

InlineSkill = object { description, name, source, type }

description: string

The description of the skill.

The name of the skill.

source: InlineSkillSource { data, media_type, type }

Inline skill payload

data: string

Base64-encoded skill zip bundle.

maxLength70254592

minLength1

media_type: "application/zip"

The media type of the inline skill payload. Must be application/zip.

type: "base64"

The type of the inline skill source. Must be base64.

type: "inline"

Defines an inline skill for this request.

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

Namespace = object { description, name, tools, type }

Groups function/custom tools under a shared namespace.

description: string

A description of the namespace shown to the model.

minLength1

The namespace name used in tool calls (for example, crm).

minLength1

tools: array of object { name, type, defer_loading, 3 more } or object { name, type, defer_loading, 2 more }

The function/custom tools available inside this namespace.

One of the following:

Function = object { name, type, defer_loading, 3 more }

maxLength128

minLength1

type: "function"

defer_loading: optional boolean

Whether this function should be deferred and discovered via tool search.

description: optional string

parameters: optional unknown

strict: optional boolean

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "namespace"

The type of the tool. Always namespace.

ToolSearch = object { type, description, execution, parameters }

Hosted or BYOT tool search configuration for deferred tools.

type: "tool_search"

The type of the tool. Always tool_search.

description: optional string

Description shown to the model for a client-executed tool search tool.

execution: optional "server" or "client"

Whether tool search is executed by the server or by the client.

One of the following:

"server"

"client"

parameters: optional unknown

Parameter schema for a client-executed tool search tool.

WebSearchPreview = object { type, search_content_types, search_context_size, user_location }

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: "web_search_preview" or "web_search_preview_2025_03_11"

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

One of the following:

"web_search_preview"

"web_search_preview_2025_03_11"

search_content_types: optional array of "text" or "image"

One of the following:

"text"

"image"

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { type, city, country, 2 more }

The user's location.

type: "approximate"

The type of location approximation. Always approximate.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

ApplyPatch = object { type }

Allows the assistant to create, delete, or update files using unified diffs.

type: "apply_patch"

The type of the tool. Always apply_patch.

type: "tool_search_output"

The item type. Always tool_search_output.

id: optional string

The unique ID of this tool search output.

call_id: optional string

The unique ID of the tool search call generated by the model.

maxLength64

minLength1

execution: optional "server" or "client"

Whether tool search was executed by the server or by the client.

One of the following:

"server"

"client"

status: optional "in_progress" or "completed" or "incomplete"

The status of the tool search output.

One of the following:

"in_progress"

"completed"

"incomplete"

Reasoning = object { id, summary, type, 3 more }

id: string

The unique identifier of the reasoning content.

summary: array of SummaryTextContent { text, type }

Reasoning summary content.

text: string

A summary of the reasoning output from the model so far.

type: "summary_text"

The type of the object. Always summary_text.

type: "reasoning"

The type of the object. Always reasoning.

content: optional array of object { text, type }

Reasoning text content.

text: string

The reasoning text from the model.

type: "reasoning_text"

The type of the reasoning text. Always reasoning_text.

encrypted_content: optional string

The encrypted content of the reasoning item - populated when a response is generated with reasoning.encrypted_content in the include parameter.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

Compaction = object { encrypted_content, type, id }

A compaction item generated by the v1/responses/compact API.

encrypted_content: string

The encrypted content of the compaction summary.

maxLength10485760

type: "compaction"

The type of the item. Always compaction.

id: optional string

The ID of the compaction item.

ImageGenerationCall = object { id, result, status, type }

An image generation request made by the model.

id: string

The unique ID of the image generation call.

result: string

The generated image encoded in base64.

status: "in_progress" or "completed" or "generating" or "failed"

The status of the image generation call.

One of the following:

"in_progress"

"completed"

"generating"

"failed"

type: "image_generation_call"

The type of the image generation call. Always image_generation_call.

CodeInterpreterCall = object { id, code, container_id, 3 more }

A tool call to run code.

id: string

The unique ID of the code interpreter tool call.

code: string

The code to run, or null if not available.

container_id: string

The ID of the container used to run the code.

outputs: array of object { logs, type } or object { type, url }

The outputs generated by the code interpreter, such as logs or images. Can be null if no outputs are available.

One of the following:

Logs = object { logs, type }

The logs output from the code interpreter.

logs: string

The logs output from the code interpreter.

type: "logs"

The type of the output. Always logs.

Image = object { type, url }

The image output from the code interpreter.

type: "image"

The type of the output. Always image.

url: string

The URL of the image output from the code interpreter.

status: "in_progress" or "completed" or "incomplete" or 2 more

The status of the code interpreter tool call. Valid values are in_progress, completed, incomplete, interpreting, and failed.

One of the following:

"in_progress"

"completed"

"incomplete"

"interpreting"

"failed"

type: "code_interpreter_call"

The type of the code interpreter tool call. Always code_interpreter_call.

LocalShellCall = object { id, action, call_id, 2 more }

A tool call to run a command on the local shell.

id: string

The unique ID of the local shell call.

action: object { command, env, type, 3 more }

Execute a shell command on the server.

command: array of string

The command to run.

env: map[string]

Environment variables to set for the command.

type: "exec"

The type of the local shell action. Always exec.

timeout_ms: optional number

Optional timeout in milliseconds for the command.

user: optional string

Optional user to run the command as.

working_directory: optional string

Optional working directory to run the command in.

call_id: string

The unique ID of the local shell tool call generated by the model.

status: "in_progress" or "completed" or "incomplete"

The status of the local shell call.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "local_shell_call"

The type of the local shell call. Always local_shell_call.

LocalShellCallOutput = object { id, output, type, status }

The output of a local shell tool call.

id: string

The unique ID of the local shell tool call generated by the model.

output: string

A JSON string of the output of the local shell tool call.

type: "local_shell_call_output"

The type of the local shell tool call output. Always local_shell_call_output.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

ShellCall = object { action, call_id, type, 3 more }

A tool representing a request to execute one or more shell commands.

action: object { commands, max_output_length, timeout_ms }

The shell commands and limits that describe how to run the tool call.

commands: array of string

Ordered shell commands for the execution environment to run.

max_output_length: optional number

Maximum number of UTF-8 characters to capture from combined stdout and stderr output.

timeout_ms: optional number

Maximum wall-clock time in milliseconds to allow the shell commands to run.

call_id: string

The unique ID of the shell tool call generated by the model.

maxLength64

minLength1

type: "shell_call"

The type of the item. Always shell_call.

id: optional string

The unique ID of the shell tool call. Populated when this item is returned via API.

environment: optional LocalEnvironment { type, skills } or ContainerReference { container_id, type }

The environment to execute the shell commands in.

One of the following:

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

status: optional "in_progress" or "completed" or "incomplete"

The status of the shell call. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

ShellCallOutput = object { call_id, output, type, 3 more }

The streamed output items emitted by a shell tool call.

call_id: string

The unique ID of the shell tool call generated by the model.

maxLength64

minLength1

output: array of ResponseFunctionShellCallOutputContent { outcome, stderr, stdout }

Captured chunks of stdout and stderr output, along with their associated outcomes.

outcome: object { type } or object { exit_code, type }

The exit or timeout outcome associated with this shell call.

One of the following:

Timeout = object { type }

Indicates that the shell call exceeded its configured time limit.

type: "timeout"

The outcome type. Always timeout.

Exit = object { exit_code, type }

Indicates that the shell commands finished and returned an exit code.

exit_code: number

The exit code returned by the shell process.

type: "exit"

The outcome type. Always exit.

stderr: string

Captured stderr output for the shell call.

maxLength10485760

stdout: string

Captured stdout output for the shell call.

maxLength10485760

type: "shell_call_output"

The type of the item. Always shell_call_output.

id: optional string

The unique ID of the shell tool call output. Populated when this item is returned via API.

max_output_length: optional number

The maximum number of UTF-8 characters captured for this shell call's combined output.

status: optional "in_progress" or "completed" or "incomplete"

The status of the shell call output.

One of the following:

"in_progress"

"completed"

"incomplete"

ApplyPatchCall = object { call_id, operation, status, 2 more }

A tool call representing a request to create, delete, or update files using diff patches.

call_id: string

The unique ID of the apply patch tool call generated by the model.

maxLength64

minLength1

operation: object { diff, path, type } or object { path, type } or object { diff, path, type }

The specific create, delete, or update instruction for the apply_patch tool call.

One of the following:

CreateFile = object { diff, path, type }

Instruction for creating a new file via the apply_patch tool.

diff: string

Unified diff content to apply when creating the file.

maxLength10485760

path: string

Path of the file to create relative to the workspace root.

minLength1

type: "create_file"

The operation type. Always create_file.

DeleteFile = object { path, type }

Instruction for deleting an existing file via the apply_patch tool.

path: string

Path of the file to delete relative to the workspace root.

minLength1

type: "delete_file"

The operation type. Always delete_file.

UpdateFile = object { diff, path, type }

Instruction for updating an existing file via the apply_patch tool.

diff: string

Unified diff content to apply to the existing file.

maxLength10485760

path: string

Path of the file to update relative to the workspace root.

minLength1

type: "update_file"

The operation type. Always update_file.

status: "in_progress" or "completed"

The status of the apply patch tool call. One of in_progress or completed.

One of the following:

"in_progress"

"completed"

type: "apply_patch_call"

The type of the item. Always apply_patch_call.

id: optional string

The unique ID of the apply patch tool call. Populated when this item is returned via API.

ApplyPatchCallOutput = object { call_id, status, type, 2 more }

The streamed output emitted by an apply patch tool call.

call_id: string

The unique ID of the apply patch tool call generated by the model.

maxLength64

minLength1

status: "completed" or "failed"

The status of the apply patch tool call output. One of completed or failed.

One of the following:

"completed"

"failed"

type: "apply_patch_call_output"

The type of the item. Always apply_patch_call_output.

id: optional string

The unique ID of the apply patch tool call output. Populated when this item is returned via API.

output: optional string

Optional human-readable log text from the apply patch tool (e.g., patch results or errors).

maxLength10485760

McpListTools = object { id, server_label, tools, 2 more }

A list of tools available on an MCP server.

id: string

The unique ID of the list.

server_label: string

The label of the MCP server.

tools: array of object { input_schema, name, annotations, description }

The tools available on the server.

input_schema: unknown

The JSON schema describing the tool's input.

The name of the tool.

annotations: optional unknown

Additional annotations about the tool.

description: optional string

The description of the tool.

type: "mcp_list_tools"

The type of the item. Always mcp_list_tools.

error: optional string

Error message if the server could not list tools.

McpApprovalRequest = object { id, arguments, name, 2 more }

A request for human approval of a tool invocation.

id: string

The unique ID of the approval request.

arguments: string

A JSON string of arguments for the tool.

The name of the tool to run.

server_label: string

The label of the MCP server making the request.

type: "mcp_approval_request"

The type of the item. Always mcp_approval_request.

McpApprovalResponse = object { approval_request_id, approve, type, 2 more }

A response to an MCP approval request.

approval_request_id: string

The ID of the approval request being answered.

approve: boolean

Whether the request was approved.

type: "mcp_approval_response"

The type of the item. Always mcp_approval_response.

id: optional string

The unique ID of the approval response

reason: optional string

Optional reason for the decision.

McpCall = object { id, arguments, name, 6 more }

An invocation of a tool on an MCP server.

id: string

The unique ID of the tool call.

arguments: string

A JSON string of the arguments passed to the tool.

The name of the tool that was run.

server_label: string

The label of the MCP server running the tool.

type: "mcp_call"

The type of the item. Always mcp_call.

approval_request_id: optional string

Unique identifier for the MCP tool call approval request. Include this value in a subsequent mcp_approval_response input to approve or reject the corresponding tool call.

error: optional string

The error from the tool call, if any.

output: optional string

The output from the tool call.

status: optional "in_progress" or "completed" or "incomplete" or 2 more

The status of the tool call. One of in_progress, completed, incomplete, calling, or failed.

One of the following:

"in_progress"

"completed"

"incomplete"

"calling"

"failed"

CustomToolCallOutput = object { call_id, output, type, id }

The output of a custom tool call from your code, being sent back to the model.

call_id: string

The call ID, used to map this custom tool call output to a custom tool call.

output: string or array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

The output from the custom tool call generated by your code. Can be a string or an list of output content.

One of the following:

StringOutput = string

A string of the output of the custom tool call.

OutputContentList = array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

Text, image, or file output of the custom tool call.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

type: "custom_tool_call_output"

The type of the custom tool call output. Always custom_tool_call_output.

id: optional string

The unique ID of the custom tool call output in the OpenAI platform.

CustomToolCall = object { call_id, input, name, 3 more }

A call to a custom tool created by the model.

call_id: string

An identifier used to map this custom tool call to a tool call output.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool being called.

type: "custom_tool_call"

The type of the custom tool call. Always custom_tool_call.

id: optional string

The unique ID of the custom tool call in the OpenAI platform.

namespace: optional string

The namespace of the custom tool being called.

ItemReference = object { id, type }

An internal identifier for an item to reference.

id: string

The ID of the item to reference.

type: optional "item_reference"

The type of item to reference. Always item_reference.

metadata: Metadata

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

model: ResponsesModel

One of the following:

string

"gpt-5.4" or "gpt-5.4-mini" or "gpt-5.4-nano" or 75 more

One of the following:

"gpt-5.4"

"gpt-5.4-mini"

"gpt-5.4-nano"

"gpt-5.4-mini-2026-03-17"

"gpt-5.4-nano-2026-03-17"

"gpt-5.3-chat-latest"

"gpt-5.2"

"gpt-5.2-2025-12-11"

"gpt-5.2-chat-latest"

"gpt-5.2-pro"

"gpt-5.2-pro-2025-12-11"

"gpt-5.1"

"gpt-5.1-2025-11-13"

"gpt-5.1-codex"

"gpt-5.1-mini"

"gpt-5.1-chat-latest"

"gpt-5"

"gpt-5-mini"

"gpt-5-nano"

"gpt-5-2025-08-07"

"gpt-5-mini-2025-08-07"

"gpt-5-nano-2025-08-07"

"gpt-5-chat-latest"

"gpt-4.1"

"gpt-4.1-mini"

"gpt-4.1-nano"

"gpt-4.1-2025-04-14"

"gpt-4.1-mini-2025-04-14"

"gpt-4.1-nano-2025-04-14"

"o4-mini"

"o4-mini-2025-04-16"

"o3"

"o3-2025-04-16"

"o3-mini"

"o3-mini-2025-01-31"

"o1"

"o1-2024-12-17"

"o1-preview"

"o1-preview-2024-09-12"

"o1-mini"

"o1-mini-2024-09-12"

"gpt-4o"

"gpt-4o-2024-11-20"

"gpt-4o-2024-08-06"

"gpt-4o-2024-05-13"

"gpt-4o-audio-preview"

"gpt-4o-audio-preview-2024-10-01"

"gpt-4o-audio-preview-2024-12-17"

"gpt-4o-audio-preview-2025-06-03"

"gpt-4o-mini-audio-preview"

"gpt-4o-mini-audio-preview-2024-12-17"

"gpt-4o-search-preview"

"gpt-4o-mini-search-preview"

"gpt-4o-search-preview-2025-03-11"

"gpt-4o-mini-search-preview-2025-03-11"

"chatgpt-4o-latest"

"codex-mini-latest"

"gpt-4o-mini"

"gpt-4o-mini-2024-07-18"

"gpt-4-turbo"

"gpt-4-turbo-2024-04-09"

"gpt-4-0125-preview"

"gpt-4-turbo-preview"

"gpt-4-1106-preview"

"gpt-4-vision-preview"

"gpt-4"

"gpt-4-0314"

"gpt-4-0613"

"gpt-4-32k"

"gpt-4-32k-0314"

"gpt-4-32k-0613"

"gpt-3.5-turbo"

"gpt-3.5-turbo-16k"

"gpt-3.5-turbo-0301"

"gpt-3.5-turbo-0613"

"gpt-3.5-turbo-1106"

"gpt-3.5-turbo-0125"

"gpt-3.5-turbo-16k-0613"

ResponsesOnlyModel = "o1-pro" or "o1-pro-2025-03-19" or "o3-pro" or 11 more

One of the following:

"o1-pro"

"o1-pro-2025-03-19"

"o3-pro"

"o3-pro-2025-06-10"

"o3-deep-research"

"o3-deep-research-2025-06-26"

"o4-mini-deep-research"

"o4-mini-deep-research-2025-06-26"

"computer-use-preview"

"computer-use-preview-2025-03-11"

"gpt-5-codex"

"gpt-5-pro"

"gpt-5-pro-2025-10-06"

"gpt-5.1-codex-max"

object: "response"

The object type of this resource - always set to response.

output: array of ResponseOutputItem

An array of content items generated by the model.

The length and order of items in the output array is dependent on the model's response.
Rather than accessing the first item in the output array and assuming it's an assistant message with the content generated by the model, you might consider using the output_text property where supported in SDKs.

One of the following:

ResponseOutputMessage = object { id, content, role, 3 more }

An output message from the model.

id: string

The unique ID of the output message.

content: array of ResponseOutputText { annotations, logprobs, text, type } or ResponseOutputRefusal { refusal, type }

The content of the output message.

One of the following:

ResponseOutputText = object { annotations, logprobs, text, type }

A text output from the model.

The annotations of the text output.

One of the following:

FileCitation = object { file_id, filename, index, type }

A citation to a file.

file_id: string

The ID of the file.

filename: string

The filename of the file cited.

index: number

The index of the file in the list of files.

type: "file_citation"

The type of the file citation. Always file_citation.

URLCitation = object { end_index, start_index, title, 2 more }

A citation for a web resource used to generate a model response.

end_index: number

The index of the last character of the URL citation in the message.

start_index: number

The index of the first character of the URL citation in the message.

title: string

The title of the web resource.

type: "url_citation"

The type of the URL citation. Always url_citation.

url: string

The URL of the web resource.

ContainerFileCitation = object { container_id, end_index, file_id, 3 more }

A citation for a container file used to generate a model response.

container_id: string

The ID of the container file.

end_index: number

The index of the last character of the container file citation in the message.

file_id: string

The ID of the file.

filename: string

The filename of the container file cited.

start_index: number

The index of the first character of the container file citation in the message.

type: "container_file_citation"

The type of the container file citation. Always container_file_citation.

FilePath = object { file_id, index, type }

A path to a file.

file_id: string

The ID of the file.

index: number

The index of the file in the list of files.

type: "file_path"

The type of the file path. Always file_path.

logprobs: array of object { token, bytes, logprob, top_logprobs }

token: string

bytes: array of number

logprob: number

top_logprobs: array of object { token, bytes, logprob }

token: string

bytes: array of number

logprob: number

text: string

The text output from the model.

type: "output_text"

The type of the output text. Always output_text.

ResponseOutputRefusal = object { refusal, type }

A refusal from the model.

refusal: string

The refusal explanation from the model.

type: "refusal"

The type of the refusal. Always refusal.

role: "assistant"

The role of the output message. Always assistant.

status: "in_progress" or "completed" or "incomplete"

The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "message"

The type of the output message. Always message.

phase: optional "commentary" or "final_answer"

One of the following:

"commentary"

"final_answer"

FileSearchCall = object { id, queries, status, 2 more }

The results of a file search tool call. See the file search guide for more information.

id: string

The unique ID of the file search tool call.

queries: array of string

The queries used to search for files.

status: "in_progress" or "searching" or "completed" or 2 more

The status of the file search tool call. One of in_progress, searching, incomplete or failed,

One of the following:

"in_progress"

"searching"

"completed"

"incomplete"

"failed"

type: "file_search_call"

The type of the file search tool call. Always file_search_call.

results: optional array of object { attributes, file_id, filename, 2 more }

The results of the file search tool call.

attributes: optional map[string or number or boolean]

One of the following:

string

number

boolean

file_id: optional string

The unique ID of the file.

filename: optional string

The name of the file.

score: optional number

The relevance score of the file - a value between 0 and 1.

formatfloat

text: optional string

The text that was retrieved from the file.

FunctionCall = object { arguments, call_id, name, 4 more }

A tool call to run a function. See the function calling guide for more information.

arguments: string

A JSON string of the arguments to pass to the function.

call_id: string

The unique ID of the function tool call generated by the model.

The name of the function to run.

type: "function_call"

The type of the function tool call. Always function_call.

id: optional string

The unique ID of the function tool call.

namespace: optional string

The namespace of the function to run.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

FunctionCallOutput = object { id, call_id, output, 3 more }

id: string

The unique ID of the function call tool output.

call_id: string

The unique ID of the function tool call generated by the model.

output: string or array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

The output from the function call generated by your code. Can be a string or an list of output content.

One of the following:

StringOutput = string

A string of the output of the function call.

OutputContentList = array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

Text, image, or file output of the function call.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

status: "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "function_call_output"

The type of the function tool call output. Always function_call_output.

created_by: optional string

The identifier of the actor that created the item.

WebSearchCall = object { id, action, status, type }

The results of a web search tool call. See the web search guide for more information.

id: string

The unique ID of the web search tool call.

action: object { query, type, queries, sources } or object { type, url } or object { pattern, type, url }

An object describing the specific action taken in this web search call. Includes details on how the model used the web (search, open_page, find_in_page).

One of the following:

Search = object { query, type, queries, sources }

Action type "search" - Performs a web search query.

query: string

[DEPRECATED] The search query.

type: "search"

The action type.

queries: optional array of string

The search queries.

sources: optional array of object { type, url }

The sources used in the search.

type: "url"

The type of source. Always url.

url: string

The URL of the source.

OpenPage = object { type, url }

Action type "open_page" - Opens a specific URL from search results.

type: "open_page"

The action type.

url: optional string

The URL opened by the model.

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FindInPage = object { pattern, type, url }

Action type "find_in_page": Searches for a pattern within a loaded page.

pattern: string

The pattern or text to search for within the page.

type: "find_in_page"

The action type.

url: string

The URL of the page searched for the pattern.

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status: "in_progress" or "searching" or "completed" or "failed"

The status of the web search tool call.

One of the following:

"in_progress"

"searching"

"completed"

"failed"

type: "web_search_call"

The type of the web search tool call. Always web_search_call.

ComputerCall = object { id, call_id, pending_safety_checks, 4 more }

A tool call to a computer use tool. See the computer use guide for more information.

id: string

The unique ID of the computer call.

call_id: string

An identifier used when responding to the tool call with output.

pending_safety_checks: array of object { id, code, message }

The pending safety checks for the computer call.

id: string

The ID of the pending safety check.

code: optional string

The type of the pending safety check.

message: optional string

Details about the pending safety check.

status: "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "computer_call"

The type of the computer call. Always computer_call.

action: optional ComputerAction

A click action.

One of the following:

Click = object { button, type, x, 2 more }

A click action.

button: "left" or "right" or "wheel" or 2 more

Indicates which mouse button was pressed during the click. One of left, right, wheel, back, or forward.

One of the following:

"left"

"right"

"wheel"

"back"

"forward"

type: "click"

Specifies the event type. For a click action, this property is always click.

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys: optional array of string

The keys being held while clicking.

DoubleClick = object { keys, type, x, y }

A double click action.

keys: array of string

The keys being held while double-clicking.

type: "double_click"

Specifies the event type. For a double click action, this property is always set to double_click.

x: number

The x-coordinate where the double click occurred.

y: number

The y-coordinate where the double click occurred.

Drag = object { path, type, keys }

A drag action.

path: array of object { x, y }

An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg

[
  { x: 100, y: 200 },
  { x: 200, y: 300 }
]

x: number

The x-coordinate.

y: number

The y-coordinate.

type: "drag"

Specifies the event type. For a drag action, this property is always set to drag.

keys: optional array of string

The keys being held while dragging the mouse.

Keypress = object { keys, type }

A collection of keypresses the model would like to perform.

keys: array of string

The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key.

type: "keypress"

Specifies the event type. For a keypress action, this property is always set to keypress.

Move = object { type, x, y, keys }

A mouse move action.

type: "move"

Specifies the event type. For a move action, this property is always set to move.

x: number

The x-coordinate to move to.

y: number

The y-coordinate to move to.

keys: optional array of string

The keys being held while moving the mouse.

Screenshot = object { type }

A screenshot action.

type: "screenshot"

Specifies the event type. For a screenshot action, this property is always set to screenshot.

Scroll = object { scroll_x, scroll_y, type, 3 more }

A scroll action.

scroll_x: number

The horizontal scroll distance.

scroll_y: number

The vertical scroll distance.

type: "scroll"

Specifies the event type. For a scroll action, this property is always set to scroll.

x: number

The x-coordinate where the scroll occurred.

y: number

The y-coordinate where the scroll occurred.

keys: optional array of string

The keys being held while scrolling.

Type = object { text, type }

An action to type in text.

text: string

The text to type.

type: "type"

Specifies the event type. For a type action, this property is always set to type.

Wait = object { type }

A wait action.

type: "wait"

Specifies the event type. For a wait action, this property is always set to wait.

actions: optional ComputerActionList { Click, DoubleClick, Drag, 6 more }

Flattened batched actions for computer_use. Each action includes an type discriminator and action-specific fields.

One of the following:

Click = object { button, type, x, 2 more }

A click action.

button: "left" or "right" or "wheel" or 2 more

Indicates which mouse button was pressed during the click. One of left, right, wheel, back, or forward.

One of the following:

"left"

"right"

"wheel"

"back"

"forward"

type: "click"

Specifies the event type. For a click action, this property is always click.

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys: optional array of string

The keys being held while clicking.

DoubleClick = object { keys, type, x, y }

A double click action.

keys: array of string

The keys being held while double-clicking.

type: "double_click"

Specifies the event type. For a double click action, this property is always set to double_click.

x: number

The x-coordinate where the double click occurred.

y: number

The y-coordinate where the double click occurred.

Drag = object { path, type, keys }

A drag action.

path: array of object { x, y }

An array of coordinates representing the path of the drag action. Coordinates will appear as an array of objects, eg

[
  { x: 100, y: 200 },
  { x: 200, y: 300 }
]

x: number

The x-coordinate.

y: number

The y-coordinate.

type: "drag"

Specifies the event type. For a drag action, this property is always set to drag.

keys: optional array of string

The keys being held while dragging the mouse.

Keypress = object { keys, type }

A collection of keypresses the model would like to perform.

keys: array of string

The combination of keys the model is requesting to be pressed. This is an array of strings, each representing a key.

type: "keypress"

Specifies the event type. For a keypress action, this property is always set to keypress.

Move = object { type, x, y, keys }

A mouse move action.

type: "move"

Specifies the event type. For a move action, this property is always set to move.

x: number

The x-coordinate to move to.

y: number

The y-coordinate to move to.

keys: optional array of string

The keys being held while moving the mouse.

Screenshot = object { type }

A screenshot action.

type: "screenshot"

Specifies the event type. For a screenshot action, this property is always set to screenshot.

Scroll = object { scroll_x, scroll_y, type, 3 more }

A scroll action.

scroll_x: number

The horizontal scroll distance.

scroll_y: number

The vertical scroll distance.

type: "scroll"

Specifies the event type. For a scroll action, this property is always set to scroll.

x: number

The x-coordinate where the scroll occurred.

y: number

The y-coordinate where the scroll occurred.

keys: optional array of string

The keys being held while scrolling.

Type = object { text, type }

An action to type in text.

text: string

The text to type.

type: "type"

Specifies the event type. For a type action, this property is always set to type.

Wait = object { type }

A wait action.

type: "wait"

Specifies the event type. For a wait action, this property is always set to wait.

ComputerCallOutput = object { id, call_id, output, 4 more }

id: string

The unique ID of the computer call tool output.

call_id: string

The ID of the computer tool call that produced the output.

output: ResponseComputerToolCallOutputScreenshot { type, file_id, image_url }

A computer screenshot image used with the computer use tool.

type: "computer_screenshot"

Specifies the event type. For a computer screenshot, this property is always set to computer_screenshot.

file_id: optional string

The identifier of an uploaded file that contains the screenshot.

image_url: optional string

The URL of the screenshot image.

status: "completed" or "incomplete" or "failed" or "in_progress"

The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

One of the following:

"completed"

"incomplete"

"failed"

"in_progress"

type: "computer_call_output"

The type of the computer tool call output. Always computer_call_output.

acknowledged_safety_checks: optional array of object { id, code, message }

The safety checks reported by the API that have been acknowledged by the developer.

id: string

The ID of the pending safety check.

code: optional string

The type of the pending safety check.

message: optional string

Details about the pending safety check.

created_by: optional string

The identifier of the actor that created the item.

Reasoning = object { id, summary, type, 3 more }

id: string

The unique identifier of the reasoning content.

summary: array of SummaryTextContent { text, type }

Reasoning summary content.

text: string

A summary of the reasoning output from the model so far.

type: "summary_text"

The type of the object. Always summary_text.

type: "reasoning"

The type of the object. Always reasoning.

content: optional array of object { text, type }

Reasoning text content.

text: string

The reasoning text from the model.

type: "reasoning_text"

The type of the reasoning text. Always reasoning_text.

encrypted_content: optional string

The encrypted content of the reasoning item - populated when a response is generated with reasoning.encrypted_content in the include parameter.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

ToolSearchCall = object { id, arguments, call_id, 4 more }

id: string

The unique ID of the tool search call item.

arguments: unknown

Arguments used for the tool search call.

call_id: string

The unique ID of the tool search call generated by the model.

execution: "server" or "client"

Whether tool search was executed by the server or by the client.

One of the following:

"server"

"client"

status: "in_progress" or "completed" or "incomplete"

The status of the tool search call item that was recorded.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "tool_search_call"

The type of the item. Always tool_search_call.

created_by: optional string

The identifier of the actor that created the item.

ToolSearchOutput = object { id, call_id, execution, 4 more }

id: string

The unique ID of the tool search output item.

call_id: string

The unique ID of the tool search call generated by the model.

execution: "server" or "client"

Whether tool search was executed by the server or by the client.

One of the following:

"server"

"client"

status: "in_progress" or "completed" or "incomplete"

The status of the tool search output item that was recorded.

One of the following:

"in_progress"

"completed"

"incomplete"

tools: array of object { name, parameters, strict, 3 more } or object { type, vector_store_ids, filters, 2 more } or object { type } or 12 more

The loaded tool definitions returned by tool search.

One of the following:

Function = object { name, parameters, strict, 3 more }

Defines a function in your own code the model can choose to call. Learn more about function calling.

The name of the function to call.

parameters: map[unknown]

A JSON schema object describing the parameters of the function.

strict: boolean

Whether to enforce strict parameter validation. Default true.

type: "function"

The type of the function tool. Always function.

defer_loading: optional boolean

Whether this function is deferred and loaded via tool search.

description: optional string

A description of the function. Used by the model to determine whether or not to call the function.

FileSearch = object { type, vector_store_ids, filters, 2 more }

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: "file_search"

The type of the file search tool. Always file_search.

vector_store_ids: array of string

The IDs of the vector stores to search.

filters: optional ComparisonFilter { key, type, value } or CompoundFilter { filters, type }

A filter to apply.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

CompoundFilter = object { filters, type }

Combine multiple filters using and or or.

filters: array of ComparisonFilter { key, type, value } or unknown

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

unknown

type: "and" or "or"

Type of operation: and or or.

One of the following:

"and"

"or"

max_num_results: optional number

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: optional object { hybrid_search, ranker, score_threshold }

Ranking options for search.

hybrid_search: optional object { embedding_weight, text_weight }

Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled.

embedding_weight: number

The weight of the embedding in the reciprocal ranking fusion.

text_weight: number

The weight of the text in the reciprocal ranking fusion.

ranker: optional "auto" or "default-2024-11-15"

The ranker to use for the file search.

One of the following:

"auto"

"default-2024-11-15"

score_threshold: optional number

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

Computer = object { type }

A tool that controls a virtual computer. Learn more about the computer tool.

type: "computer"

The type of the computer tool. Always computer.

ComputerUsePreview = object { display_height, display_width, environment, type }

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: number

The height of the computer display.

display_width: number

The width of the computer display.

environment: "windows" or "mac" or "linux" or 2 more

The type of computer environment to control.

One of the following:

"windows"

"mac"

"linux"

"ubuntu"

"browser"

type: "computer_use_preview"

The type of the computer use tool. Always computer_use_preview.

WebSearch = object { type, filters, search_context_size, user_location }

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: "web_search" or "web_search_2025_08_26"

The type of the web search tool. One of web_search or web_search_2025_08_26.

One of the following:

"web_search"

"web_search_2025_08_26"

filters: optional object { allowed_domains }

Filters for the search.

allowed_domains: optional array of string

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { city, country, region, 2 more }

The approximate location of the user.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

type: optional "approximate"

The type of location approximation. Always approximate.

Mcp = object { server_label, type, allowed_tools, 7 more }

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: string

A label for this MCP server, used to identify it in tool calls.

type: "mcp"

The type of the MCP tool. Always mcp.

allowed_tools: optional array of string or object { read_only, tool_names }

List of allowed tool names or a filter object.

One of the following:

McpAllowedTools = array of string

A string array of allowed tool names

McpToolFilter = object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

authorization: optional string

connector_id: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more

Identifier for service connectors, like those available in ChatGPT. One of server_url or connector_id must be provided. Learn more about service connectors here.

Currently supported connector_id values are:

Dropbox: connector_dropbox
Gmail: connector_gmail
Google Calendar: connector_googlecalendar
Google Drive: connector_googledrive
Microsoft Teams: connector_microsoftteams
Outlook Calendar: connector_outlookcalendar
Outlook Email: connector_outlookemail
SharePoint: connector_sharepoint

One of the following:

"connector_dropbox"

"connector_gmail"

"connector_googlecalendar"

"connector_googledrive"

"connector_microsoftteams"

"connector_outlookcalendar"

"connector_outlookemail"

"connector_sharepoint"

defer_loading: optional boolean

Whether this MCP tool is deferred and discovered via tool search.

headers: optional map[string]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: optional object { always, never } or "always" or "never"

Specify which of the MCP server's tools require approval.

One of the following:

McpToolApprovalFilter = object { always, never }

Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

never: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

McpToolApprovalSetting = "always" or "never"

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

One of the following:

"always"

"never"

server_description: optional string

Optional description of the MCP server, used to provide more context.

server_url: optional string

The URL for the MCP server. One of server_url or connector_id must be provided.

CodeInterpreter = object { container, type }

A tool that runs Python code to help generate a response to a prompt.

container: string or object { type, file_ids, memory_limit, network_policy }

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

One of the following:

string

The container ID.

CodeInterpreterToolAuto = object { type, file_ids, memory_limit, network_policy }

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: "auto"

Always auto.

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the code interpreter container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

type: "code_interpreter"

The type of the code interpreter tool. Always code_interpreter.

ImageGeneration = object { type, action, background, 9 more }

A tool that generates images using the GPT image models.

type: "image_generation"

The type of the image generation tool. Always image_generation.

action: optional "generate" or "edit" or "auto"

Whether to generate a new image or edit an existing image. Default: auto.

One of the following:

"generate"

"edit"

"auto"

background: optional "transparent" or "opaque" or "auto"

Background type for the generated image. One of transparent, opaque, or auto. Default: auto.

One of the following:

"transparent"

"opaque"

"auto"

input_fidelity: optional "high" or "low"

One of the following:

"high"

"low"

input_image_mask: optional object { file_id, image_url }

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: optional string

File ID for the mask image.

image_url: optional string

Base64-encoded mask image.

model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

string

"gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

"gpt-image-1"

"gpt-image-1-mini"

"gpt-image-1.5"

moderation: optional "auto" or "low"

Moderation level for the generated image. Default: auto.

One of the following:

"auto"

"low"

output_compression: optional number

Compression level for the output image. Default: 100.

minimum0

maximum100

output_format: optional "png" or "webp" or "jpeg"

The output format of the generated image. One of png, webp, or jpeg. Default: png.

One of the following:

"png"

"webp"

"jpeg"

partial_images: optional number

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0

maximum3

quality: optional "low" or "medium" or "high" or "auto"

The quality of the generated image. One of low, medium, high, or auto. Default: auto.

One of the following:

"low"

"medium"

"high"

"auto"

size: optional "1024x1024" or "1024x1536" or "1536x1024" or "auto"

The size of the generated image. One of 1024x1024, 1024x1536, 1536x1024, or auto. Default: auto.

One of the following:

"1024x1024"

"1024x1536"

"1536x1024"

"auto"

LocalShell = object { type }

A tool that allows the model to execute shell commands in a local environment.

type: "local_shell"

The type of the local shell tool. Always local_shell.

Shell = object { type, environment }

A tool that allows the model to execute shell commands.

type: "shell"

The type of the shell tool. Always shell.

environment: optional ContainerAuto { type, file_ids, memory_limit, 2 more } or LocalEnvironment { type, skills } or ContainerReference { container_id, type }

One of the following:

ContainerAuto = object { type, file_ids, memory_limit, 2 more }

type: "container_auto"

Automatically creates a container for this request

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

skills: optional array of SkillReference { skill_id, type, version } or InlineSkill { description, name, source, type }

An optional list of skills referenced by id or inline data.

One of the following:

SkillReference = object { skill_id, type, version }

skill_id: string

The ID of the referenced skill.

maxLength64

minLength1

type: "skill_reference"

References a skill created with the /v1/skills endpoint.

version: optional string

Optional skill version. Use a positive integer or 'latest'. Omit for default.

InlineSkill = object { description, name, source, type }

description: string

The description of the skill.

The name of the skill.

source: InlineSkillSource { data, media_type, type }

Inline skill payload

data: string

Base64-encoded skill zip bundle.

maxLength70254592

minLength1

media_type: "application/zip"

The media type of the inline skill payload. Must be application/zip.

type: "base64"

The type of the inline skill source. Must be base64.

type: "inline"

Defines an inline skill for this request.

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

Namespace = object { description, name, tools, type }

Groups function/custom tools under a shared namespace.

description: string

A description of the namespace shown to the model.

minLength1

The namespace name used in tool calls (for example, crm).

minLength1

tools: array of object { name, type, defer_loading, 3 more } or object { name, type, defer_loading, 2 more }

The function/custom tools available inside this namespace.

One of the following:

Function = object { name, type, defer_loading, 3 more }

maxLength128

minLength1

type: "function"

defer_loading: optional boolean

Whether this function should be deferred and discovered via tool search.

description: optional string

parameters: optional unknown

strict: optional boolean

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "namespace"

The type of the tool. Always namespace.

ToolSearch = object { type, description, execution, parameters }

Hosted or BYOT tool search configuration for deferred tools.

type: "tool_search"

The type of the tool. Always tool_search.

description: optional string

Description shown to the model for a client-executed tool search tool.

execution: optional "server" or "client"

Whether tool search is executed by the server or by the client.

One of the following:

"server"

"client"

parameters: optional unknown

Parameter schema for a client-executed tool search tool.

WebSearchPreview = object { type, search_content_types, search_context_size, user_location }

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: "web_search_preview" or "web_search_preview_2025_03_11"

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

One of the following:

"web_search_preview"

"web_search_preview_2025_03_11"

search_content_types: optional array of "text" or "image"

One of the following:

"text"

"image"

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { type, city, country, 2 more }

The user's location.

type: "approximate"

The type of location approximation. Always approximate.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

ApplyPatch = object { type }

Allows the assistant to create, delete, or update files using unified diffs.

type: "apply_patch"

The type of the tool. Always apply_patch.

type: "tool_search_output"

The type of the item. Always tool_search_output.

created_by: optional string

The identifier of the actor that created the item.

Compaction = object { id, encrypted_content, type, created_by }

A compaction item generated by the v1/responses/compact API.

id: string

The unique ID of the compaction item.

encrypted_content: string

The encrypted content that was produced by compaction.

type: "compaction"

The type of the item. Always compaction.

created_by: optional string

The identifier of the actor that created the item.

ImageGenerationCall = object { id, result, status, type }

An image generation request made by the model.

id: string

The unique ID of the image generation call.

result: string

The generated image encoded in base64.

status: "in_progress" or "completed" or "generating" or "failed"

The status of the image generation call.

One of the following:

"in_progress"

"completed"

"generating"

"failed"

type: "image_generation_call"

The type of the image generation call. Always image_generation_call.

CodeInterpreterCall = object { id, code, container_id, 3 more }

A tool call to run code.

id: string

The unique ID of the code interpreter tool call.

code: string

The code to run, or null if not available.

container_id: string

The ID of the container used to run the code.

outputs: array of object { logs, type } or object { type, url }

The outputs generated by the code interpreter, such as logs or images. Can be null if no outputs are available.

One of the following:

Logs = object { logs, type }

The logs output from the code interpreter.

logs: string

The logs output from the code interpreter.

type: "logs"

The type of the output. Always logs.

Image = object { type, url }

The image output from the code interpreter.

type: "image"

The type of the output. Always image.

url: string

The URL of the image output from the code interpreter.

status: "in_progress" or "completed" or "incomplete" or 2 more

The status of the code interpreter tool call. Valid values are in_progress, completed, incomplete, interpreting, and failed.

One of the following:

"in_progress"

"completed"

"incomplete"

"interpreting"

"failed"

type: "code_interpreter_call"

The type of the code interpreter tool call. Always code_interpreter_call.

LocalShellCall = object { id, action, call_id, 2 more }

A tool call to run a command on the local shell.

id: string

The unique ID of the local shell call.

action: object { command, env, type, 3 more }

Execute a shell command on the server.

command: array of string

The command to run.

env: map[string]

Environment variables to set for the command.

type: "exec"

The type of the local shell action. Always exec.

timeout_ms: optional number

Optional timeout in milliseconds for the command.

user: optional string

Optional user to run the command as.

working_directory: optional string

Optional working directory to run the command in.

call_id: string

The unique ID of the local shell tool call generated by the model.

status: "in_progress" or "completed" or "incomplete"

The status of the local shell call.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "local_shell_call"

The type of the local shell call. Always local_shell_call.

LocalShellCallOutput = object { id, output, type, status }

The output of a local shell tool call.

id: string

The unique ID of the local shell tool call generated by the model.

output: string

A JSON string of the output of the local shell tool call.

type: "local_shell_call_output"

The type of the local shell tool call output. Always local_shell_call_output.

status: optional "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

ShellCall = object { id, action, call_id, 4 more }

A tool call that executes one or more shell commands in a managed environment.

id: string

The unique ID of the shell tool call. Populated when this item is returned via API.

action: object { commands, max_output_length, timeout_ms }

The shell commands and limits that describe how to run the tool call.

commands: array of string

max_output_length: number

Optional maximum number of characters to return from each command.

timeout_ms: number

Optional timeout in milliseconds for the commands.

call_id: string

The unique ID of the shell tool call generated by the model.

environment: ResponseLocalEnvironment { type } or ResponseContainerReference { container_id, type }

Represents the use of a local environment to perform shell actions.

One of the following:

ResponseLocalEnvironment = object { type }

Represents the use of a local environment to perform shell actions.

type: "local"

The environment type. Always local.

ResponseContainerReference = object { container_id, type }

Represents a container created with /v1/containers.

container_id: string

type: "container_reference"

The environment type. Always container_reference.

status: "in_progress" or "completed" or "incomplete"

The status of the shell call. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "shell_call"

The type of the item. Always shell_call.

created_by: optional string

The ID of the entity that created this tool call.

ShellCallOutput = object { id, call_id, max_output_length, 4 more }

The output of a shell tool call that was emitted.

id: string

The unique ID of the shell call output. Populated when this item is returned via API.

call_id: string

The unique ID of the shell tool call generated by the model.

max_output_length: number

The maximum length of the shell command output. This is generated by the model and should be passed back with the raw output.

output: array of object { outcome, stderr, stdout, created_by }

An array of shell call output contents

outcome: object { type } or object { exit_code, type }

Represents either an exit outcome (with an exit code) or a timeout outcome for a shell call output chunk.

One of the following:

Timeout = object { type }

Indicates that the shell call exceeded its configured time limit.

type: "timeout"

The outcome type. Always timeout.

Exit = object { exit_code, type }

Indicates that the shell commands finished and returned an exit code.

exit_code: number

Exit code from the shell process.

type: "exit"

The outcome type. Always exit.

stderr: string

The standard error output that was captured.

stdout: string

The standard output that was captured.

created_by: optional string

The identifier of the actor that created the item.

status: "in_progress" or "completed" or "incomplete"

The status of the shell call output. One of in_progress, completed, or incomplete.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "shell_call_output"

The type of the shell call output. Always shell_call_output.

created_by: optional string

The identifier of the actor that created the item.

ApplyPatchCall = object { id, call_id, operation, 3 more }

A tool call that applies file diffs by creating, deleting, or updating files.

id: string

The unique ID of the apply patch tool call. Populated when this item is returned via API.

call_id: string

The unique ID of the apply patch tool call generated by the model.

operation: object { diff, path, type } or object { path, type } or object { diff, path, type }

One of the create_file, delete_file, or update_file operations applied via apply_patch.

One of the following:

CreateFile = object { diff, path, type }

Instruction describing how to create a file via the apply_patch tool.

diff: string

Diff to apply.

path: string

Path of the file to create.

type: "create_file"

Create a new file with the provided diff.

DeleteFile = object { path, type }

Instruction describing how to delete a file via the apply_patch tool.

path: string

Path of the file to delete.

type: "delete_file"

Delete the specified file.

UpdateFile = object { diff, path, type }

Instruction describing how to update a file via the apply_patch tool.

diff: string

Diff to apply.

path: string

Path of the file to update.

type: "update_file"

Update an existing file with the provided diff.

status: "in_progress" or "completed"

The status of the apply patch tool call. One of in_progress or completed.

One of the following:

"in_progress"

"completed"

type: "apply_patch_call"

The type of the item. Always apply_patch_call.

created_by: optional string

The ID of the entity that created this tool call.

ApplyPatchCallOutput = object { id, call_id, status, 3 more }

The output emitted by an apply patch tool call.

id: string

The unique ID of the apply patch tool call output. Populated when this item is returned via API.

call_id: string

The unique ID of the apply patch tool call generated by the model.

status: "completed" or "failed"

The status of the apply patch tool call output. One of completed or failed.

One of the following:

"completed"

"failed"

type: "apply_patch_call_output"

The type of the item. Always apply_patch_call_output.

created_by: optional string

The ID of the entity that created this tool call output.

output: optional string

Optional textual output returned by the apply patch tool.

McpCall = object { id, arguments, name, 6 more }

An invocation of a tool on an MCP server.

id: string

The unique ID of the tool call.

arguments: string

A JSON string of the arguments passed to the tool.

The name of the tool that was run.

server_label: string

The label of the MCP server running the tool.

type: "mcp_call"

The type of the item. Always mcp_call.

approval_request_id: optional string

Unique identifier for the MCP tool call approval request. Include this value in a subsequent mcp_approval_response input to approve or reject the corresponding tool call.

error: optional string

The error from the tool call, if any.

output: optional string

The output from the tool call.

status: optional "in_progress" or "completed" or "incomplete" or 2 more

The status of the tool call. One of in_progress, completed, incomplete, calling, or failed.

One of the following:

"in_progress"

"completed"

"incomplete"

"calling"

"failed"

McpListTools = object { id, server_label, tools, 2 more }

A list of tools available on an MCP server.

id: string

The unique ID of the list.

server_label: string

The label of the MCP server.

tools: array of object { input_schema, name, annotations, description }

The tools available on the server.

input_schema: unknown

The JSON schema describing the tool's input.

The name of the tool.

annotations: optional unknown

Additional annotations about the tool.

description: optional string

The description of the tool.

type: "mcp_list_tools"

The type of the item. Always mcp_list_tools.

error: optional string

Error message if the server could not list tools.

McpApprovalRequest = object { id, arguments, name, 2 more }

A request for human approval of a tool invocation.

id: string

The unique ID of the approval request.

arguments: string

A JSON string of arguments for the tool.

The name of the tool to run.

server_label: string

The label of the MCP server making the request.

type: "mcp_approval_request"

The type of the item. Always mcp_approval_request.

McpApprovalResponse = object { id, approval_request_id, approve, 2 more }

A response to an MCP approval request.

id: string

The unique ID of the approval response

approval_request_id: string

The ID of the approval request being answered.

approve: boolean

Whether the request was approved.

type: "mcp_approval_response"

The type of the item. Always mcp_approval_response.

reason: optional string

Optional reason for the decision.

CustomToolCall = object { call_id, input, name, 3 more }

A call to a custom tool created by the model.

call_id: string

An identifier used to map this custom tool call to a tool call output.

input: string

The input for the custom tool call generated by the model.

The name of the custom tool being called.

type: "custom_tool_call"

The type of the custom tool call. Always custom_tool_call.

id: optional string

The unique ID of the custom tool call in the OpenAI platform.

namespace: optional string

The namespace of the custom tool being called.

CustomToolCallOutput = object { id, call_id, output, 3 more }

id: string

The unique ID of the custom tool call output item.

call_id: string

The call ID, used to map this custom tool call output to a custom tool call.

output: string or array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

The output from the custom tool call generated by your code. Can be a string or an list of output content.

One of the following:

StringOutput = string

A string of the output of the custom tool call.

OutputContentList = array of ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more }

Text, image, or file output of the custom tool call.

One of the following:

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

status: "in_progress" or "completed" or "incomplete"

The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

One of the following:

"in_progress"

"completed"

"incomplete"

type: "custom_tool_call_output"

The type of the custom tool call output. Always custom_tool_call_output.

created_by: optional string

The identifier of the actor that created the item.

parallel_tool_calls: boolean

Whether to allow the model to run tool calls in parallel.

temperature: number

minimum0

maximum2

tool_choice: ToolChoiceOptions or ToolChoiceAllowed { mode, tools, type } or ToolChoiceTypes { type } or 5 more

How the model should select which tool (or tools) to use when generating a response. See the tools parameter to see how to specify which tools the model can call.

One of the following:

ToolChoiceOptions = "none" or "auto" or "required"

Controls which (if any) tool is called by the model.

none means the model will not call any tool and instead generates a message.

auto 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.

One of the following:

"none"

"auto"

"required"

ToolChoiceAllowed = object { mode, tools, type }

Constrains the tools available to the model to a pre-defined set.

mode: "auto" or "required"

Constrains the tools available to the model to a pre-defined set.

auto allows the model to pick from among the allowed tools and generate a message.

required requires the model to call one or more of the allowed tools.

One of the following:

"auto"

"required"

tools: array of map[unknown]

A list of tool definitions that the model should be allowed to call.

For the Responses API, the list of tool definitions might look like:

[
  { "type": "function", "name": "get_weather" },
  { "type": "mcp", "server_label": "deepwiki" },
  { "type": "image_generation" }
]

type: "allowed_tools"

Allowed tool configuration type. Always allowed_tools.

ToolChoiceTypes = object { type }

Indicates that the model should use a built-in tool to generate a response. Learn more about built-in tools.

type: "file_search" or "web_search_preview" or "computer" or 5 more

The type of hosted tool the model should to use. Learn more about built-in tools.

Allowed values are:

file_search
web_search_preview
computer
computer_use_preview
computer_use
code_interpreter
image_generation

One of the following:

"file_search"

"web_search_preview"

"computer"

"computer_use_preview"

"computer_use"

"web_search_preview_2025_03_11"

"image_generation"

"code_interpreter"

ToolChoiceFunction = object { name, type }

Use this option to force the model to call a specific function.

The name of the function to call.

type: "function"

For function calling, the type is always function.

ToolChoiceMcp = object { server_label, type, name }

Use this option to force the model to call a specific tool on a remote MCP server.

server_label: string

The label of the MCP server to use.

type: "mcp"

For MCP tools, the type is always mcp.

The name of the tool to call on the server.

ToolChoiceCustom = object { name, type }

Use this option to force the model to call a specific custom tool.

The name of the custom tool to call.

type: "custom"

For custom tool calling, the type is always custom.

ToolChoiceApplyPatch = object { type }

Forces the model to call the apply_patch tool when executing a tool call.

type: "apply_patch"

The tool to call. Always apply_patch.

ToolChoiceShell = object { type }

Forces the model to call the shell tool when a tool call is required.

type: "shell"

The tool to call. Always shell.

tools: array of object { name, parameters, strict, 3 more } or object { type, vector_store_ids, filters, 2 more } or object { type } or 12 more

An array of tools the model may call while generating a response. You can specify which tool to use by setting the tool_choice parameter.

We support the following categories of tools:

Built-in tools: Tools that are provided by OpenAI that extend the model's capabilities, like web search or file search. Learn more about built-in tools.
MCP Tools: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about MCP Tools.
Function calls (custom tools): Functions that are defined by you, enabling the model to call your own code with strongly typed arguments and outputs. Learn more about function calling. You can also use custom tools to call your own code.

One of the following:

Function = object { name, parameters, strict, 3 more }

Defines a function in your own code the model can choose to call. Learn more about function calling.

The name of the function to call.

parameters: map[unknown]

A JSON schema object describing the parameters of the function.

strict: boolean

Whether to enforce strict parameter validation. Default true.

type: "function"

The type of the function tool. Always function.

defer_loading: optional boolean

Whether this function is deferred and loaded via tool search.

description: optional string

A description of the function. Used by the model to determine whether or not to call the function.

FileSearch = object { type, vector_store_ids, filters, 2 more }

A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

type: "file_search"

The type of the file search tool. Always file_search.

vector_store_ids: array of string

The IDs of the vector stores to search.

filters: optional ComparisonFilter { key, type, value } or CompoundFilter { filters, type }

A filter to apply.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

CompoundFilter = object { filters, type }

Combine multiple filters using and or or.

filters: array of ComparisonFilter { key, type, value } or unknown

Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.

One of the following:

ComparisonFilter = object { key, type, value }

A filter used to compare a specified attribute key to a given value using a defined comparison operation.

key: string

The key to compare against the value.

type: "eq" or "ne" or "gt" or 5 more

Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.

eq: equals
ne: not equal
gt: greater than
gte: greater than or equal
lt: less than
lte: less than or equal
in: in
nin: not in

One of the following:

"eq"

"ne"

"gt"

"gte"

"lt"

"lte"

"in"

"nin"

value: string or number or boolean or array of string or number

The value to compare against the attribute key; supports string, number, or boolean types.

One of the following:

string

number

boolean

array of string or number

One of the following:

string

number

unknown

type: "and" or "or"

Type of operation: and or or.

One of the following:

"and"

"or"

max_num_results: optional number

The maximum number of results to return. This number should be between 1 and 50 inclusive.

ranking_options: optional object { hybrid_search, ranker, score_threshold }

Ranking options for search.

hybrid_search: optional object { embedding_weight, text_weight }

Weights that control how reciprocal rank fusion balances semantic embedding matches versus sparse keyword matches when hybrid search is enabled.

embedding_weight: number

The weight of the embedding in the reciprocal ranking fusion.

text_weight: number

The weight of the text in the reciprocal ranking fusion.

ranker: optional "auto" or "default-2024-11-15"

The ranker to use for the file search.

One of the following:

"auto"

"default-2024-11-15"

score_threshold: optional number

The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will attempt to return only the most relevant results, but may return fewer results.

Computer = object { type }

A tool that controls a virtual computer. Learn more about the computer tool.

type: "computer"

The type of the computer tool. Always computer.

ComputerUsePreview = object { display_height, display_width, environment, type }

A tool that controls a virtual computer. Learn more about the computer tool.

display_height: number

The height of the computer display.

display_width: number

The width of the computer display.

environment: "windows" or "mac" or "linux" or 2 more

The type of computer environment to control.

One of the following:

"windows"

"mac"

"linux"

"ubuntu"

"browser"

type: "computer_use_preview"

The type of the computer use tool. Always computer_use_preview.

WebSearch = object { type, filters, search_context_size, user_location }

Search the Internet for sources related to the prompt. Learn more about the web search tool.

type: "web_search" or "web_search_2025_08_26"

The type of the web search tool. One of web_search or web_search_2025_08_26.

One of the following:

"web_search"

"web_search_2025_08_26"

filters: optional object { allowed_domains }

Filters for the search.

allowed_domains: optional array of string

Allowed domains for the search. If not provided, all domains are allowed. Subdomains of the provided domains are allowed as well.

Example: ["pubmed.ncbi.nlm.nih.gov"]

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { city, country, region, 2 more }

The approximate location of the user.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

type: optional "approximate"

The type of location approximation. Always approximate.

Mcp = object { server_label, type, allowed_tools, 7 more }

Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

server_label: string

A label for this MCP server, used to identify it in tool calls.

type: "mcp"

The type of the MCP tool. Always mcp.

allowed_tools: optional array of string or object { read_only, tool_names }

List of allowed tool names or a filter object.

One of the following:

McpAllowedTools = array of string

A string array of allowed tool names

McpToolFilter = object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

authorization: optional string

connector_id: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more

Identifier for service connectors, like those available in ChatGPT. One of server_url or connector_id must be provided. Learn more about service connectors here.

Currently supported connector_id values are:

Dropbox: connector_dropbox
Gmail: connector_gmail
Google Calendar: connector_googlecalendar
Google Drive: connector_googledrive
Microsoft Teams: connector_microsoftteams
Outlook Calendar: connector_outlookcalendar
Outlook Email: connector_outlookemail
SharePoint: connector_sharepoint

One of the following:

"connector_dropbox"

"connector_gmail"

"connector_googlecalendar"

"connector_googledrive"

"connector_microsoftteams"

"connector_outlookcalendar"

"connector_outlookemail"

"connector_sharepoint"

defer_loading: optional boolean

Whether this MCP tool is deferred and discovered via tool search.

headers: optional map[string]

Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

require_approval: optional object { always, never } or "always" or "never"

Specify which of the MCP server's tools require approval.

One of the following:

McpToolApprovalFilter = object { always, never }

Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

always: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

never: optional object { read_only, tool_names }

A filter object to specify which tools are allowed.

read_only: optional boolean

Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

tool_names: optional array of string

List of allowed tool names.

McpToolApprovalSetting = "always" or "never"

Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

One of the following:

"always"

"never"

server_description: optional string

Optional description of the MCP server, used to provide more context.

server_url: optional string

The URL for the MCP server. One of server_url or connector_id must be provided.

CodeInterpreter = object { container, type }

A tool that runs Python code to help generate a response to a prompt.

container: string or object { type, file_ids, memory_limit, network_policy }

The code interpreter container. Can be a container ID or an object that specifies uploaded file IDs to make available to your code, along with an optional memory_limit setting.

One of the following:

string

The container ID.

CodeInterpreterToolAuto = object { type, file_ids, memory_limit, network_policy }

Configuration for a code interpreter container. Optionally specify the IDs of the files to run the code on.

type: "auto"

Always auto.

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the code interpreter container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

type: "code_interpreter"

The type of the code interpreter tool. Always code_interpreter.

ImageGeneration = object { type, action, background, 9 more }

A tool that generates images using the GPT image models.

type: "image_generation"

The type of the image generation tool. Always image_generation.

action: optional "generate" or "edit" or "auto"

Whether to generate a new image or edit an existing image. Default: auto.

One of the following:

"generate"

"edit"

"auto"

background: optional "transparent" or "opaque" or "auto"

Background type for the generated image. One of transparent, opaque, or auto. Default: auto.

One of the following:

"transparent"

"opaque"

"auto"

input_fidelity: optional "high" or "low"

One of the following:

"high"

"low"

input_image_mask: optional object { file_id, image_url }

Optional mask for inpainting. Contains image_url (string, optional) and file_id (string, optional).

file_id: optional string

File ID for the mask image.

image_url: optional string

Base64-encoded mask image.

model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

string

"gpt-image-1" or "gpt-image-1-mini" or "gpt-image-1.5"

The image generation model to use. Default: gpt-image-1.

One of the following:

"gpt-image-1"

"gpt-image-1-mini"

"gpt-image-1.5"

moderation: optional "auto" or "low"

Moderation level for the generated image. Default: auto.

One of the following:

"auto"

"low"

output_compression: optional number

Compression level for the output image. Default: 100.

minimum0

maximum100

output_format: optional "png" or "webp" or "jpeg"

The output format of the generated image. One of png, webp, or jpeg. Default: png.

One of the following:

"png"

"webp"

"jpeg"

partial_images: optional number

Number of partial images to generate in streaming mode, from 0 (default value) to 3.

minimum0

maximum3

quality: optional "low" or "medium" or "high" or "auto"

The quality of the generated image. One of low, medium, high, or auto. Default: auto.

One of the following:

"low"

"medium"

"high"

"auto"

size: optional "1024x1024" or "1024x1536" or "1536x1024" or "auto"

The size of the generated image. One of 1024x1024, 1024x1536, 1536x1024, or auto. Default: auto.

One of the following:

"1024x1024"

"1024x1536"

"1536x1024"

"auto"

LocalShell = object { type }

A tool that allows the model to execute shell commands in a local environment.

type: "local_shell"

The type of the local shell tool. Always local_shell.

Shell = object { type, environment }

A tool that allows the model to execute shell commands.

type: "shell"

The type of the shell tool. Always shell.

environment: optional ContainerAuto { type, file_ids, memory_limit, 2 more } or LocalEnvironment { type, skills } or ContainerReference { container_id, type }

One of the following:

ContainerAuto = object { type, file_ids, memory_limit, 2 more }

type: "container_auto"

Automatically creates a container for this request

file_ids: optional array of string

An optional list of uploaded files to make available to your code.

memory_limit: optional "1g" or "4g" or "16g" or "64g"

The memory limit for the container.

One of the following:

"1g"

"4g"

"16g"

"64g"

network_policy: optional ContainerNetworkPolicyDisabled { type } or ContainerNetworkPolicyAllowlist { allowed_domains, type, domain_secrets }

Network access policy for the container.

One of the following:

ContainerNetworkPolicyDisabled = object { type }

type: "disabled"

Disable outbound network access. Always disabled.

ContainerNetworkPolicyAllowlist = object { allowed_domains, type, domain_secrets }

allowed_domains: array of string

A list of allowed domains when type is allowlist.

type: "allowlist"

Allow outbound network access only to specified domains. Always allowlist.

domain_secrets: optional array of ContainerNetworkPolicyDomainSecret { domain, name, value }

Optional domain-scoped secrets for allowlisted domains.

domain: string

The domain associated with the secret.

minLength1

The name of the secret to inject for the domain.

minLength1

value: string

The secret value to inject for the domain.

maxLength10485760

minLength1

skills: optional array of SkillReference { skill_id, type, version } or InlineSkill { description, name, source, type }

An optional list of skills referenced by id or inline data.

One of the following:

SkillReference = object { skill_id, type, version }

skill_id: string

The ID of the referenced skill.

maxLength64

minLength1

type: "skill_reference"

References a skill created with the /v1/skills endpoint.

version: optional string

Optional skill version. Use a positive integer or 'latest'. Omit for default.

InlineSkill = object { description, name, source, type }

description: string

The description of the skill.

The name of the skill.

source: InlineSkillSource { data, media_type, type }

Inline skill payload

data: string

Base64-encoded skill zip bundle.

maxLength70254592

minLength1

media_type: "application/zip"

The media type of the inline skill payload. Must be application/zip.

type: "base64"

The type of the inline skill source. Must be base64.

type: "inline"

Defines an inline skill for this request.

LocalEnvironment = object { type, skills }

type: "local"

Use a local computer environment.

skills: optional array of LocalSkill { description, name, path }

An optional list of skills.

description: string

The description of the skill.

The name of the skill.

path: string

The path to the directory containing the skill.

ContainerReference = object { container_id, type }

container_id: string

The ID of the referenced container.

type: "container_reference"

References a container created with the /v1/containers endpoint

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

Namespace = object { description, name, tools, type }

Groups function/custom tools under a shared namespace.

description: string

A description of the namespace shown to the model.

minLength1

The namespace name used in tool calls (for example, crm).

minLength1

tools: array of object { name, type, defer_loading, 3 more } or object { name, type, defer_loading, 2 more }

The function/custom tools available inside this namespace.

One of the following:

Function = object { name, type, defer_loading, 3 more }

maxLength128

minLength1

type: "function"

defer_loading: optional boolean

Whether this function should be deferred and discovered via tool search.

description: optional string

parameters: optional unknown

strict: optional boolean

Custom = object { name, type, defer_loading, 2 more }

A custom tool that processes input using a specified format. Learn more about custom tools

The name of the custom tool, used to identify it in tool calls.

type: "custom"

The type of the custom tool. Always custom.

defer_loading: optional boolean

Whether this tool should be deferred and discovered via tool search.

description: optional string

Optional description of the custom tool, used to provide more context.

format: optional CustomToolInputFormat

The input format for the custom tool. Default is unconstrained text.

One of the following:

Text = object { type }

Unconstrained free-form text.

type: "text"

Unconstrained text format. Always text.

Grammar = object { definition, syntax, type }

A grammar defined by the user.

definition: string

The grammar definition.

syntax: "lark" or "regex"

The syntax of the grammar definition. One of lark or regex.

One of the following:

"lark"

"regex"

type: "grammar"

Grammar format. Always grammar.

type: "namespace"

The type of the tool. Always namespace.

ToolSearch = object { type, description, execution, parameters }

Hosted or BYOT tool search configuration for deferred tools.

type: "tool_search"

The type of the tool. Always tool_search.

description: optional string

Description shown to the model for a client-executed tool search tool.

execution: optional "server" or "client"

Whether tool search is executed by the server or by the client.

One of the following:

"server"

"client"

parameters: optional unknown

Parameter schema for a client-executed tool search tool.

WebSearchPreview = object { type, search_content_types, search_context_size, user_location }

This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

type: "web_search_preview" or "web_search_preview_2025_03_11"

The type of the web search tool. One of web_search_preview or web_search_preview_2025_03_11.

One of the following:

"web_search_preview"

"web_search_preview_2025_03_11"

search_content_types: optional array of "text" or "image"

One of the following:

"text"

"image"

search_context_size: optional "low" or "medium" or "high"

High level guidance for the amount of context window space to use for the search. One of low, medium, or high. medium is the default.

One of the following:

"low"

"medium"

"high"

user_location: optional object { type, city, country, 2 more }

The user's location.

type: "approximate"

The type of location approximation. Always approximate.

city: optional string

Free text input for the city of the user, e.g. San Francisco.

country: optional string

The two-letter ISO country code of the user, e.g. US.

region: optional string

Free text input for the region of the user, e.g. California.

timezone: optional string

The IANA timezone of the user, e.g. America/Los_Angeles.

ApplyPatch = object { type }

Allows the assistant to create, delete, or update files using unified diffs.

type: "apply_patch"

The type of the tool. Always apply_patch.

top_p: number

We generally recommend altering this or temperature but not both.

minimum0

maximum1

background: optional boolean

Whether to run the model response in the background. Learn more.

completed_at: optional number

Unix timestamp (in seconds) of when this Response was completed. Only present when the status is completed.

conversation: optional object { id }

The conversation that this response belonged to. Input items and output items from this response were automatically added to this conversation.

id: string

The unique ID of the conversation that this response was associated with.

max_output_tokens: optional number

An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.

max_tool_calls: optional number

output_text: optional string

SDK-only convenience property that contains the aggregated text output from all output_text items in the output array, if any are present. Supported in the Python and JavaScript SDKs.

previous_response_id: optional string

The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state. Cannot be used in conjunction with conversation.

prompt: optional ResponsePrompt { id, variables, version }

Reference to a prompt template and its variables. Learn more.

id: string

The unique identifier of the prompt template to use.

variables: optional map[string or ResponseInputText { text, type } or ResponseInputImage { detail, type, file_id, image_url } or ResponseInputFile { type, file_data, file_id, 2 more } ]

Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

One of the following:

string

ResponseInputText = object { text, type }

A text input to the model.

text: string

The text input to the model.

type: "input_text"

The type of the input item. Always input_text.

ResponseInputImage = object { detail, type, file_id, image_url }

An image input to the model. Learn about image inputs.

detail: "low" or "high" or "auto" or "original"

The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

One of the following:

"low"

"high"

"auto"

"original"

type: "input_image"

The type of the input item. Always input_image.

file_id: optional string

The ID of the file to be sent to the model.

image_url: optional string

The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

ResponseInputFile = object { type, file_data, file_id, 2 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

file_data: optional string

The content of the file to be sent to the model.

file_id: optional string

The ID of the file to be sent to the model.

file_url: optional string

The URL of the file to be sent to the model.

filename: optional string

The name of the file to be sent to the model.

version: optional string

Optional version of the prompt template.

prompt_cache_key: optional string

Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.

prompt_cache_retention: optional "in-memory" or "24h"

The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more.

One of the following:

"in-memory"

"24h"

reasoning: optional Reasoning { effort, generate_summary, summary }

gpt-5 and o-series models only

Configuration options for reasoning models.

effort: optional ReasoningEffort

gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
All models before gpt-5.1 default to medium reasoning effort, and do not support none.
The gpt-5-pro model defaults to (and only supports) high reasoning effort.
xhigh is supported for all models after gpt-5.1-codex-max.

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

Deprecatedgenerate_summary: optional "auto" or "concise" or "detailed"

Deprecated: use summary instead.

A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

One of the following:

"auto"

"concise"

"detailed"

summary: optional "auto" or "concise" or "detailed"

A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

concise is supported for computer-use-preview models and all reasoning models after gpt-5.

One of the following:

"auto"

"concise"

"detailed"

safety_identifier: optional string

maxLength64

service_tier: optional "auto" or "default" or "flex" or 2 more

Specifies the processing type used for serving the request.

If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier.
When not set, the default behavior is 'auto'.

One of the following:

"auto"

"default"

"flex"

"scale"

"priority"

status: optional ResponseStatus

The status of the response generation. One of completed, failed, in_progress, cancelled, queued, or incomplete.

One of the following:

"completed"

"failed"

"in_progress"

"cancelled"

"queued"

"incomplete"

text: optional ResponseTextConfig { format, verbosity }

Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more:

format: optional ResponseFormatTextConfig

An object specifying the format that the model must output.

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

The default format is { "type": "text" } with no additional options.

Not recommended for gpt-4o and newer models:

Setting to { "type": "json_object" } enables the older JSON mode, which ensures the message the model generates is valid JSON. Using json_schema is preferred for models that support it.

One of the following:

ResponseFormatText = object { type }

Default response format. Used to generate text responses.

type: "text"

The type of response format being defined. Always text.

ResponseFormatTextJSONSchemaConfig = object { name, schema, type, 2 more }

JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

schema: map[unknown]

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

type: "json_schema"

The type of response format being defined. Always json_schema.

description: optional string

A description of what the response format is for, used by the model to determine how to respond in the format.

strict: optional boolean

ResponseFormatJSONObject = object { type }

type: "json_object"

The type of response format being defined. Always json_object.

verbosity: optional "low" or "medium" or "high"

One of the following:

"low"

"medium"

"high"

top_logprobs: optional number

An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.

minimum0

maximum20

truncation: optional "auto" or "disabled"

The truncation strategy to use for the model response.

auto: If the input to this Response exceeds the model's context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation.
disabled (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error.

One of the following:

"auto"

"disabled"

usage: optional ResponseUsage { input_tokens, input_tokens_details, output_tokens, 2 more }

Represents token usage details including input tokens, output tokens, a breakdown of output tokens, and the total tokens used.

input_tokens: number

The number of input tokens.

input_tokens_details: object { cached_tokens }

A detailed breakdown of the input tokens.

cached_tokens: number

The number of tokens that were retrieved from the cache. More on prompt caching.

output_tokens: number

The number of output tokens.

output_tokens_details: object { reasoning_tokens }

A detailed breakdown of the output tokens.

reasoning_tokens: number

The number of reasoning tokens.

total_tokens: number

The total number of tokens used.

Deprecateduser: optional string