LearnInAI/ResponseOpenAI_API.md

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 Parameters

• 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.

• conversation: optional string or ResponseConversationParam

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.

• 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).

• "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 or object { content, role, status, type } or ResponseOutputMessage or 25 more

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

Learn more:

• Text inputs and outputs
• Image inputs
• File inputs
• Conversation state

• Function calling

• TextInput = string

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

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

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

  • 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.

    • 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.

    • 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.

      • "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.

      • "low"

      • "high"

      • "auto"

      • "original"

      • type: "input_image"

      The type of the input item. Always input_image.

      • "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, detail, file_data, 3 more }

      A file input to the model.

      • type: "input_file"

      The type of the input item. Always input_file.

      • "input_file"

      • detail: optional "low" or "high"

      The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

      • "low"

      • "high"

      • 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.

    • "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.

    • "commentary"

    • "final_answer"

  • type: optional "message"

    The type of the message input. Always message.

    • "message"

  • Message object { content, role, status, 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.

  • content: ResponseInputMessageContentList

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

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

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

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: optional "message"

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

    • "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 or ResponseOutputRefusal

    The content of the output message.

    • 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.

      • 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.

        • "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_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.

        • "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.

        • "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.

      • "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.

      • "refusal"

  • role: "assistant"

    The role of the output message. Always assistant.

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "message"

    The type of the output message. Always message.

    • "message"

  • 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.

    • "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,

    • "in_progress"

    • "searching"

    • "completed"

    • "incomplete"

    • "failed"

  • type: "file_search_call"

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

    • "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.

    • 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.

    • 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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "computer_call"

    The type of the computer call. Always computer_call.

    • "computer_call"

  • action: optional ComputerAction

    A click action.

    • 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.

      • "left"

      • "right"

      • "wheel"

      • "back"

      • "forward"

    • type: "click"

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

      • "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.

      • "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.

      • "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.

      • "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.

      • "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.

      • "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.

      • "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.

      • "type"

    • Wait object { type }

    A wait action.

    • type: "wait"

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

      • "wait"

  • actions: optional ComputerActionList

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

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

    A click action.

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

    A double click action.

    • Drag object { path, type, keys }

    A drag action.

    • Keypress object { keys, type }

    A collection of keypresses the model would like to perform.

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

    A mouse move action.

    • Screenshot object { type }

    A screenshot action.

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

    A scroll action.

    • Type object { text, type }

    An action to type in text.

    • Wait object { type }

    A wait action.

  • 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.

  • output: ResponseComputerToolCallOutputScreenshot

    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.

    • "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.

    • "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.

    • "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).

    • 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.

      • "search"

    • 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"

      • 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.

      • "open_page"

    • url: optional string

      The URL opened by the model.

    • 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.

      • "find_in_page"

    • url: string

      The URL of the page searched for the pattern.

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

    The status of the web search tool call.

    • "in_progress"

    • "searching"

    • "completed"

    • "failed"

  • type: "web_search_call"

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

    • "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.

  • name: string

    The name of the function to run.

  • type: "function_call"

    The type of the function tool call. Always function_call.

    • "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.

    • "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.

  • output: string or array of ResponseInputTextContent or ResponseInputImageContent or ResponseInputFileContent

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

    • string

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

    • array of ResponseInputTextContent or ResponseInputImageContent or ResponseInputFileContent

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

    • ResponseInputTextContent 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.

      • "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.

      • "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.

      • "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.

    • ResponseInputFileContent object { type, detail, file_data, 3 more }

      A file input to the model.

      • type: "input_file"

      The type of the input item. Always input_file.

      • "input_file"

      • detail: optional "low" or "high"

      The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

      • "low"

      • "high"

      • file_data: optional string

      The base64-encoded data 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: "function_call_output"

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

    • "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.

    • "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.

    • "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.

    • execution: optional "server" or "client"

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

    • "server"

    • "client"

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

    The status of the tool search call.

    • "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.

    • 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.

    • name: string

      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.

      • "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.

      • "file_search"

    • vector_store_ids: array of string

      The IDs of the vector stores to search.

    • filters: optional ComparisonFilter or CompoundFilter

      A filter to apply.

      • 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

        • "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.

        • string

        • number

        • boolean

        • array of string or number

          • string

          • number

      • CompoundFilter object { filters, type }

      Combine multiple filters using and or or.

      • filters: array of ComparisonFilter or unknown

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

        • ComparisonFilter object { key, type, value }

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

        • unknown

      • type: "and" or "or"

        Type of operation: and or or.

        • "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.

      • "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.

      • "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.

      • "windows"

      • "mac"

      • "linux"

      • "ubuntu"

      • "browser"

    • type: "computer_use_preview"

      The type of the computer use tool. Always computer_use_preview.

      • "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.

      • "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.

      • "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.

      • "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.

      • "mcp"

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

      List of allowed tool names or a filter object.

      • 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

      • "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.

      • 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.

      • "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.

      • 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.

        • "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.

        • "1g"

        • "4g"

        • "16g"

        • "64g"

      • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

        Network access policy for the container.

        • ContainerNetworkPolicyDisabled object { type }

          • type: "disabled"

          Disable outbound network access. Always disabled.

          • "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.

          • "allowlist"

          • domain_secrets: optional array of ContainerNetworkPolicyDomainSecret

          Optional domain-scoped secrets for allowlisted domains.

          • domain: string

          The domain associated with the secret.

          • name: string

          The name of the secret to inject for the domain.

          • value: string

          The secret value to inject for the domain.

    • type: "code_interpreter"

      The type of the code interpreter tool. Always code_interpreter.

      • "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.

      • "image_generation"

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

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

      • "generate"

      • "edit"

      • "auto"

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

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

      • "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.

      • "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.

      • string

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

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

      • "gpt-image-1"

      • "gpt-image-1-mini"

      • "gpt-image-1.5"

    • moderation: optional "auto" or "low"

      Moderation level for the generated image. Default: auto.

      • "auto"

      • "low"

    • output_compression: optional number

      Compression level for the output image. Default: 100.

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

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

      • "png"

      • "webp"

      • "jpeg"

    • partial_images: optional number

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

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

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

      • "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.

      • "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.

      • "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.

      • "shell"

    • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

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

        • type: "container_auto"

        Automatically creates a container for this request

        • "container_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 container.

        • "1g"

        • "4g"

        • "16g"

        • "64g"

        • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

        Network access policy for the container.

        • ContainerNetworkPolicyDisabled object { type }

        • ContainerNetworkPolicyAllowlist object { allowed_domains, type, domain_secrets }

        • skills: optional array of SkillReference or InlineSkill

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

        • SkillReference object { skill_id, type, version }

          • skill_id: string

          The ID of the referenced skill.

          • type: "skill_reference"

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

          • "skill_reference"

          • 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.

          • name: string

          The name of the skill.

          • source: InlineSkillSource

          Inline skill payload

          • data: string

          Base64-encoded skill zip bundle.

          • media_type: "application/zip"

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

          • "application/zip"

          • type: "base64"

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

          • "base64"

          • type: "inline"

          Defines an inline skill for this request.

          • "inline"

      • LocalEnvironment object { type, skills }

        • type: "local"

        Use a local computer environment.

        • "local"

        • skills: optional array of LocalSkill

        An optional list of skills.

        • description: string

        The description of the skill.

        • name: string

        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

        • "container_reference"

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

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

    • name: string

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

    • type: "custom"

      The type of the custom tool. Always custom.

      • "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.

      • Text object { type }

      Unconstrained free-form text.

      • type: "text"

        Unconstrained text format. Always text.

        • "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.

        • "lark"

        • "regex"

      • type: "grammar"

        Grammar format. Always grammar.

        • "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.

    • name: string

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

    • 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.

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

        • name: string

        • type: "function"

        • "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

      • name: string

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

      • type: "custom"

        The type of the custom tool. Always custom.

        • "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.

    • type: "namespace"

      The type of the tool. Always namespace.

      • "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.

      • "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.

      • "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.

      • "web_search_preview"

      • "web_search_preview_2025_03_11"

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

      • "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.

      • "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.

      • "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.

      • "apply_patch"

    • type: "tool_search_output"

    The item type. Always tool_search_output.

    • "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.

    • execution: optional "server" or "client"

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

    • "server"

    • "client"

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

    The status of the tool search output.

    • "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

    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.

    • "summary_text"

  • type: "reasoning"

    The type of the object. Always reasoning.

    • "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.

    • "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.

    • "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.

  • type: "compaction"

    The type of the item. Always compaction.

    • "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.

    • "in_progress"

    • "completed"

    • "generating"

    • "failed"

  • type: "image_generation_call"

    The type of the image generation call. Always image_generation_call.

    • "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.

    • 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.

      • "logs"

    • Image object { type, url }

    The image output from the code interpreter.

    • type: "image"

      The type of the output. Always image.

      • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • "interpreting"

    • "failed"

  • type: "code_interpreter_call"

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

    • "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.

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "local_shell_call"

    The type of the local shell call. Always local_shell_call.

    • "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.

    • "local_shell_call_output"

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

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

    • "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.

  • type: "shell_call"

    The type of the item. Always shell_call.

    • "shell_call"

  • id: optional string

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

  • environment: optional LocalEnvironment or ContainerReference

    The environment to execute the shell commands in.

    • LocalEnvironment object { type, skills }

    • ContainerReference object { container_id, type }

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

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

    • "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.

  • output: array of ResponseFunctionShellCallOutputContent

    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.

    • Timeout object { type }

      Indicates that the shell call exceeded its configured time limit.

      • type: "timeout"

      The outcome type. Always timeout.

      • "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.

      • "exit"

    • stderr: string

    Captured stderr output for the shell call.

    • stdout: string

    Captured stdout output for the shell call.

  • type: "shell_call_output"

    The type of the item. Always shell_call_output.

    • "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.

    • "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.

  • 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.

    • 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.

    • path: string

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

    • type: "create_file"

      The operation type. Always create_file.

      • "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.

    • type: "delete_file"

      The operation type. Always delete_file.

      • "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.

    • path: string

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

    • type: "update_file"

      The operation type. Always update_file.

      • "update_file"

  • status: "in_progress" or "completed"

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

    • "in_progress"

    • "completed"

  • type: "apply_patch_call"

    The type of the item. Always apply_patch_call.

    • "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.

  • status: "completed" or "failed"

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

    • "completed"

    • "failed"

  • type: "apply_patch_call_output"

    The type of the item. Always apply_patch_call_output.

    • "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).

  • 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.

    • name: string

    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.

    • "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.

  • name: string

    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.

    • "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.

    • "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.

  • name: string

    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.

    • "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.

    • "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 or ResponseInputImage or ResponseInputFile

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

    • StringOutput = string

    A string of the output of the custom tool call.

    • OutputContentList = array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

    • ResponseInputText object { text, type }

      A text input to the model.

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

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

    • ResponseInputFile object { type, detail, file_data, 3 more }

      A file input to the model.

  • type: "custom_tool_call_output"

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

    • "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.

  • name: string

    The name of the custom tool being called.

  • type: "custom_tool_call"

    The type of the custom tool call. Always custom_tool_call.

    • "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.

    • "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

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.

• 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.

• string

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

  • "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

  • "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

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 or ResponseInputImage or ResponseInputFile]

  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.

  • string

  • ResponseInputText object { text, type }

  A text input to the model.

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

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

  • ResponseInputFile object { type, detail, file_data, 3 more }

  A file input 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.

• "in_memory"

• "24h"

• reasoning: optional Reasoning

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.

  • "none"

  • "minimal"

  • "low"

  • "medium"

  • "high"

  • "xhigh"

• generate_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.

  • "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.

  • "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.

• 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.

• "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.

• text: optional ResponseTextConfig

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

• Text inputs and outputs

• Structured Outputs

• 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.

  • ResponseFormatText object { type }

  Default response format. Used to generate text responses.

  • type: "text"

    The type of response format being defined. Always text.

    • "text"

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

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

  • name: string

    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.

    • "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.

    • "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.

  • "low"

  • "medium"

  • "high"

• tool_choice: optional ToolChoiceOptions or ToolChoiceAllowed or ToolChoiceTypes 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.

• 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.

  • "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.

  • "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.

  • "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

  • "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.

  • name: string

  The name of the function to call.

  • type: "function"

  For function calling, the type is always function.

  • "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.

  • "mcp"

  • name: optional string

  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.

  • name: string

  The name of the custom tool to call.

  • type: "custom"

  For custom tool calling, the type is always custom.

  • "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.

  • "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.

  • "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.

• 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.

  • name: string

  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.

  • "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.

  • "file_search"

  • vector_store_ids: array of string

  The IDs of the vector stores to search.

  • filters: optional ComparisonFilter or CompoundFilter

  A filter to apply.

  • ComparisonFilter object { key, type, value }

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

  • CompoundFilter object { filters, type }

    Combine multiple filters using and or 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.

    • "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.

  • "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.

  • "windows"

  • "mac"

  • "linux"

  • "ubuntu"

  • "browser"

  • type: "computer_use_preview"

  The type of the computer use tool. Always computer_use_preview.

  • "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.

  • "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.

  • "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.

    • "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.

  • "mcp"

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

  List of allowed tool names or a filter object.

  • 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

  • "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.

  • 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.

    • "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.

  • 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.

    • "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.

    • "1g"

    • "4g"

    • "16g"

    • "64g"

    • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

    Network access policy for the container.

    • ContainerNetworkPolicyDisabled object { type }

    • ContainerNetworkPolicyAllowlist object { allowed_domains, type, domain_secrets }

  • type: "code_interpreter"

  The type of the code interpreter tool. Always code_interpreter.

  • "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.

  • "image_generation"

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

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

  • "generate"

  • "edit"

  • "auto"

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

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

  • "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.

  • "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.

  • string

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

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

    • "gpt-image-1"

    • "gpt-image-1-mini"

    • "gpt-image-1.5"

  • moderation: optional "auto" or "low"

  Moderation level for the generated image. Default: auto.

  • "auto"

  • "low"

  • output_compression: optional number

  Compression level for the output image. Default: 100.

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

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

  • "png"

  • "webp"

  • "jpeg"

  • partial_images: optional number

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

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

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

  • "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.

  • "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.

  • "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.

  • "shell"

  • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

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

    • LocalEnvironment object { type, skills }

    • ContainerReference object { container_id, type }

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

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

  • name: string

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

  • type: "custom"

  The type of the custom tool. Always custom.

  • "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.

• 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.

  • name: string

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

  • 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.

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

    • name: string

    • type: "function"

      • "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

    • name: string

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

    • type: "custom"

    The type of the custom tool. Always custom.

    • "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.

  • type: "namespace"

  The type of the tool. Always namespace.

  • "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.

  • "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.

  • "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.

  • "web_search_preview"

  • "web_search_preview_2025_03_11"

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

    • "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.

  • "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.

    • "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.

  • "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.

• 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.

• 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.

• "auto"

• "disabled"

• user: 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.

Returns

• 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

  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.

  • "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.

  • "max_output_tokens"

  • "content_filter"

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

  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.

  • string

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

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

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

  • 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.

    • 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.

      • 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.

        • "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.

        • "low"

        • "high"

        • "auto"

        • "original"

      • type: "input_image"

        The type of the input item. Always input_image.

        • "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, detail, file_data, 3 more }

      A file input to the model.

      • type: "input_file"

        The type of the input item. Always input_file.

        • "input_file"

      • detail: optional "low" or "high"

        The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

        • "low"

        • "high"

      • 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.

    • "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.

    • "commentary"

    • "final_answer"

    • type: optional "message"

    The type of the message input. Always message.

    • "message"

  • Message object { content, role, status, 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.

    • content: ResponseInputMessageContentList

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

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

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

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: optional "message"

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

    • "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 or ResponseOutputRefusal

    The content of the output message.

    • 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.

      • 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.

        • "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_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.

        • "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.

        • "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.

      • "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.

      • "refusal"

    • role: "assistant"

    The role of the output message. Always assistant.

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: "message"

    The type of the output message. Always message.

    • "message"

    • 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.

    • "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,

    • "in_progress"

    • "searching"

    • "completed"

    • "incomplete"

    • "failed"

    • type: "file_search_call"

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

    • "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.

      • 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.

    • 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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: "computer_call"

    The type of the computer call. Always computer_call.

    • "computer_call"

    • action: optional ComputerAction

    A click action.

    • 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.

      • "left"

      • "right"

      • "wheel"

      • "back"

      • "forward"

      • type: "click"

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

      • "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.

      • "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.

      • "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.

      • "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.

      • "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.

      • "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.

      • "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.

      • "type"

    • Wait object { type }

      A wait action.

      • type: "wait"

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

      • "wait"

    • actions: optional ComputerActionList

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

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

      A click action.

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

      A double click action.

    • Drag object { path, type, keys }

      A drag action.

    • Keypress object { keys, type }

      A collection of keypresses the model would like to perform.

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

      A mouse move action.

    • Screenshot object { type }

      A screenshot action.

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

      A scroll action.

    • Type object { text, type }

      An action to type in text.

    • Wait object { type }

      A wait action.

  • 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.

    • output: ResponseComputerToolCallOutputScreenshot

    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.

      • "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.

    • "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.

    • "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).

    • 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.

      • "search"

      • 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"

      • 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.

      • "open_page"

      • url: optional string

      The URL opened by the model.

    • 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.

      • "find_in_page"

      • url: string

      The URL of the page searched for the pattern.

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

    The status of the web search tool call.

    • "in_progress"

    • "searching"

    • "completed"

    • "failed"

    • type: "web_search_call"

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

    • "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.

    • name: string

    The name of the function to run.

    • type: "function_call"

    The type of the function tool call. Always function_call.

    • "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.

    • "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.

    • output: string or array of ResponseInputTextContent or ResponseInputImageContent or ResponseInputFileContent

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

    • string

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

    • array of ResponseInputTextContent or ResponseInputImageContent or ResponseInputFileContent

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

      • ResponseInputTextContent 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.

        • "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.

        • "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.

        • "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.

      • ResponseInputFileContent object { type, detail, file_data, 3 more }

      A file input to the model.

      • type: "input_file"

        The type of the input item. Always input_file.

        • "input_file"

      • detail: optional "low" or "high"

        The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

        • "low"

        • "high"

      • file_data: optional string

        The base64-encoded data 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: "function_call_output"

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

    • "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.

    • "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.

    • "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.

    • execution: optional "server" or "client"

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

    • "server"

    • "client"

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

    The status of the tool search call.

    • "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.

    • 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.

      • name: string

      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.

      • "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.

      • "file_search"

      • vector_store_ids: array of string

      The IDs of the vector stores to search.

      • filters: optional ComparisonFilter or CompoundFilter

      A filter to apply.

      • 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

        • "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.

        • string

        • number

        • boolean

        • array of string or number

          • string

          • number

      • CompoundFilter object { filters, type }

        Combine multiple filters using and or or.

        • filters: array of ComparisonFilter or unknown

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

        • ComparisonFilter object { key, type, value }

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

        • unknown

        • type: "and" or "or"

        Type of operation: and or or.

        • "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.

        • "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.

      • "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.

      • "windows"

      • "mac"

      • "linux"

      • "ubuntu"

      • "browser"

      • type: "computer_use_preview"

      The type of the computer use tool. Always computer_use_preview.

      • "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.

      • "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.

      • "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.

        • "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.

      • "mcp"

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

      List of allowed tool names or a filter object.

      • 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

      • "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.

      • 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.

        • "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.

      • 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.

        • "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.

        • "1g"

        • "4g"

        • "16g"

        • "64g"

        • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

        Network access policy for the container.

        • ContainerNetworkPolicyDisabled object { type }

          • type: "disabled"

          Disable outbound network access. Always disabled.

          • "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.

          • "allowlist"

          • domain_secrets: optional array of ContainerNetworkPolicyDomainSecret

          Optional domain-scoped secrets for allowlisted domains.

          • domain: string

            The domain associated with the secret.

          • name: string

            The name of the secret to inject for the domain.

          • value: string

            The secret value to inject for the domain.

      • type: "code_interpreter"

      The type of the code interpreter tool. Always code_interpreter.

      • "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.

      • "image_generation"

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

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

      • "generate"

      • "edit"

      • "auto"

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

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

      • "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.

      • "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.

      • string

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

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

        • "gpt-image-1"

        • "gpt-image-1-mini"

        • "gpt-image-1.5"

      • moderation: optional "auto" or "low"

      Moderation level for the generated image. Default: auto.

      • "auto"

      • "low"

      • output_compression: optional number

      Compression level for the output image. Default: 100.

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

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

      • "png"

      • "webp"

      • "jpeg"

      • partial_images: optional number

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

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

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

      • "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.

      • "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.

      • "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.

      • "shell"

      • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

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

        • type: "container_auto"

        Automatically creates a container for this request

        • "container_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 container.

        • "1g"

        • "4g"

        • "16g"

        • "64g"

        • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

        Network access policy for the container.

        • ContainerNetworkPolicyDisabled object { type }

        • ContainerNetworkPolicyAllowlist object { allowed_domains, type, domain_secrets }

        • skills: optional array of SkillReference or InlineSkill

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

        • SkillReference object { skill_id, type, version }

          • skill_id: string

          The ID of the referenced skill.

          • type: "skill_reference"

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

          • "skill_reference"

          • 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.

          • name: string

          The name of the skill.

          • source: InlineSkillSource

          Inline skill payload

          • data: string

            Base64-encoded skill zip bundle.

          • media_type: "application/zip"

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

            • "application/zip"

          • type: "base64"

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

            • "base64"

          • type: "inline"

          Defines an inline skill for this request.

          • "inline"

        • LocalEnvironment object { type, skills }

        • type: "local"

        Use a local computer environment.

        • "local"

        • skills: optional array of LocalSkill

        An optional list of skills.

        • description: string

          The description of the skill.

        • name: string

          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

        • "container_reference"

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

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

      • name: string

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

      • type: "custom"

      The type of the custom tool. Always custom.

      • "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.

      • Text object { type }

        Unconstrained free-form text.

        • type: "text"

        Unconstrained text format. Always text.

        • "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.

        • "lark"

        • "regex"

        • type: "grammar"

        Grammar format. Always grammar.

        • "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.

      • name: string

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

      • 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.

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

        • name: string

        • type: "function"

          • "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

        • name: string

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

        • type: "custom"

        The type of the custom tool. Always custom.

        • "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.

      • type: "namespace"

      The type of the tool. Always namespace.

      • "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.

      • "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.

      • "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.

      • "web_search_preview"

      • "web_search_preview_2025_03_11"

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

        • "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.

      • "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.

        • "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.

      • "apply_patch"

    • type: "tool_search_output"

    The item type. Always tool_search_output.

    • "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.

    • execution: optional "server" or "client"

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

    • "server"

    • "client"

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

    The status of the tool search output.

    • "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

    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.

      • "summary_text"

    • type: "reasoning"

    The type of the object. Always reasoning.

    • "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.

      • "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.

    • "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.

    • type: "compaction"

    The type of the item. Always compaction.

    • "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.

    • "in_progress"

    • "completed"

    • "generating"

    • "failed"

    • type: "image_generation_call"

    The type of the image generation call. Always image_generation_call.

    • "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.

    • 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.

      • "logs"

    • Image object { type, url }

      The image output from the code interpreter.

      • type: "image"

      The type of the output. Always image.

      • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • "interpreting"

    • "failed"

    • type: "code_interpreter_call"

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

    • "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.

      • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: "local_shell_call"

    The type of the local shell call. Always local_shell_call.

    • "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.

    • "local_shell_call_output"

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

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

    • "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.

    • type: "shell_call"

    The type of the item. Always shell_call.

    • "shell_call"

    • id: optional string

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

    • environment: optional LocalEnvironment or ContainerReference

    The environment to execute the shell commands in.

    • LocalEnvironment object { type, skills }

    • ContainerReference object { container_id, type }

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

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

    • "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.

    • output: array of ResponseFunctionShellCallOutputContent

    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.

      • Timeout object { type }

      Indicates that the shell call exceeded its configured time limit.

      • type: "timeout"

        The outcome type. Always timeout.

        • "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.

        • "exit"

    • stderr: string

      Captured stderr output for the shell call.

    • stdout: string

      Captured stdout output for the shell call.

    • type: "shell_call_output"

    The type of the item. Always shell_call_output.

    • "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.

    • "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.

    • 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.

    • 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.

      • path: string

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

      • type: "create_file"

      The operation type. Always create_file.

      • "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.

      • type: "delete_file"

      The operation type. Always delete_file.

      • "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.

      • path: string

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

      • type: "update_file"

      The operation type. Always update_file.

      • "update_file"

    • status: "in_progress" or "completed"

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

    • "in_progress"

    • "completed"

    • type: "apply_patch_call"

    The type of the item. Always apply_patch_call.

    • "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.

    • status: "completed" or "failed"

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

    • "completed"

    • "failed"

    • type: "apply_patch_call_output"

    The type of the item. Always apply_patch_call_output.

    • "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).

  • 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.

    • name: string

      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.

    • "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.

    • name: string

    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.

    • "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.

    • "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.

    • name: string

    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.

    • "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.

    • "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 or ResponseInputImage or ResponseInputFile

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

    • StringOutput = string

      A string of the output of the custom tool call.

    • OutputContentList = array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

      • ResponseInputText object { text, type }

      A text input to the model.

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

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

      • ResponseInputFile object { type, detail, file_data, 3 more }

      A file input to the model.

    • type: "custom_tool_call_output"

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

    • "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.

    • name: string

    The name of the custom tool being called.

    • type: "custom_tool_call"

    The type of the custom tool call. Always custom_tool_call.

    • "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.

    • "item_reference"

  • metadata: Metadata

  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.

  • model: 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.

  • string

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

    • "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

    • "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.

  • "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.

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

  An output message from the model.

  • 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,

    • "in_progress"

    • "searching"

    • "completed"

    • "incomplete"

    • "failed"

  • type: "file_search_call"

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

    • "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.

    • 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.

    • 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.

  • name: string

    The name of the function to run.

  • type: "function_call"

    The type of the function tool call. Always function_call.

    • "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.

    • "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 or ResponseInputImage or ResponseInputFile

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

    • StringOutput = string

    A string of the output of the function call.

    • OutputContentList = array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

    • ResponseInputText object { text, type }

      A text input to the model.

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

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

    • ResponseInputFile object { type, detail, file_data, 3 more }

      A file input 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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: "function_call_output"

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

    • "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).

    • 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.

      • "search"

    • 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"

      • 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.

      • "open_page"

    • url: optional string

      The URL opened by the model.

    • 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.

      • "find_in_page"

    • url: string

      The URL of the page searched for the pattern.

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

    The status of the web search tool call.

    • "in_progress"

    • "searching"

    • "completed"

    • "failed"

  • type: "web_search_call"

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

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "computer_call"

    The type of the computer call. Always computer_call.

    • "computer_call"

  • action: optional ComputerAction

    A click action.

  • actions: optional ComputerActionList

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

  • 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

    A computer screenshot image used with the computer use tool.

    • 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.

    • "completed"

    • "incomplete"

    • "failed"

    • "in_progress"

    • type: "computer_call_output"

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

    • "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 }

  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

    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.

    • "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.

    • "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.

    • "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.

    • "server"

    • "client"

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

    The status of the tool search call item that was recorded.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: "tool_search_call"

    The type of the item. Always tool_search_call.

    • "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.

    • "server"

    • "client"

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

    The status of the tool search output item that was recorded.

    • "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.

    • 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.

    • name: string

      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.

      • "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.

      • "file_search"

    • vector_store_ids: array of string

      The IDs of the vector stores to search.

    • filters: optional ComparisonFilter or CompoundFilter

      A filter to apply.

      • ComparisonFilter object { key, type, value }

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

      • CompoundFilter object { filters, type }

      Combine multiple filters using and or 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.

      • "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.

      • "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.

      • "windows"

      • "mac"

      • "linux"

      • "ubuntu"

      • "browser"

    • type: "computer_use_preview"

      The type of the computer use tool. Always computer_use_preview.

      • "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.

      • "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.

      • "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.

      • "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.

      • "mcp"

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

      List of allowed tool names or a filter object.

      • 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

      • "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.

      • 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.

      • "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.

      • 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.

        • "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.

        • "1g"

        • "4g"

        • "16g"

        • "64g"

      • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

        Network access policy for the container.

        • ContainerNetworkPolicyDisabled object { type }

        • ContainerNetworkPolicyAllowlist object { allowed_domains, type, domain_secrets }

    • type: "code_interpreter"

      The type of the code interpreter tool. Always code_interpreter.

      • "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.

      • "image_generation"

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

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

      • "generate"

      • "edit"

      • "auto"

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

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

      • "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.

      • "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.

      • string

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

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

      • "gpt-image-1"

      • "gpt-image-1-mini"

      • "gpt-image-1.5"

    • moderation: optional "auto" or "low"

      Moderation level for the generated image. Default: auto.

      • "auto"

      • "low"

    • output_compression: optional number

      Compression level for the output image. Default: 100.

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

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

      • "png"

      • "webp"

      • "jpeg"

    • partial_images: optional number

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

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

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

      • "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.

      • "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.

      • "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.

      • "shell"

    • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

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

      • LocalEnvironment object { type, skills }

      • ContainerReference object { container_id, type }

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

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

    • name: string

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

    • type: "custom"

      The type of the custom tool. Always custom.

      • "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.

    • 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.

    • name: string

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

    • 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.

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

        • name: string

        • type: "function"

        • "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

      • name: string

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

      • type: "custom"

        The type of the custom tool. Always custom.

        • "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.

    • type: "namespace"

      The type of the tool. Always namespace.

      • "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.

      • "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.

      • "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.

      • "web_search_preview"

      • "web_search_preview_2025_03_11"

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

      • "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.

      • "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.

      • "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.

      • "apply_patch"

    • type: "tool_search_output"

    The type of the item. Always tool_search_output.

    • "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.

    • "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.

    • "in_progress"

    • "completed"

    • "generating"

    • "failed"

  • type: "image_generation_call"

    The type of the image generation call. Always image_generation_call.

    • "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.

    • 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.

      • "logs"

    • Image object { type, url }

    The image output from the code interpreter.

    • type: "image"

      The type of the output. Always image.

      • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • "interpreting"

    • "failed"

  • type: "code_interpreter_call"

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

    • "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.

    • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "local_shell_call"

    The type of the local shell call. Always local_shell_call.

    • "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.

    • "local_shell_call_output"

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

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

    • "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 or ResponseContainerReference

    Represents the use of a local environment to perform shell actions.

    • ResponseLocalEnvironment object { type }

    Represents the use of a local environment to perform shell actions.

    • type: "local"

      The environment type. Always local.

      • "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.

      • "container_reference"

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

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

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "shell_call"

    The type of the item. Always shell_call.

    • "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.

    • Timeout object { type }

      Indicates that the shell call exceeded its configured time limit.

      • type: "timeout"

      The outcome type. Always timeout.

      • "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.

      • "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.

    • "in_progress"

    • "completed"

    • "incomplete"

  • type: "shell_call_output"

    The type of the shell call output. Always shell_call_output.

    • "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.

    • 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.

      • "create_file"

    • 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.

      • "delete_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.

      • "update_file"

  • status: "in_progress" or "completed"

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

    • "in_progress"

    • "completed"

  • type: "apply_patch_call"

    The type of the item. Always apply_patch_call.

    • "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.

    • "completed"

    • "failed"

  • type: "apply_patch_call_output"

    The type of the item. Always apply_patch_call_output.

    • "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.

  • name: string

    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.

    • "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.

    • "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.

    • name: string

    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.

    • "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.

  • name: string

    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.

    • "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.

    • "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.

  • name: string

    The name of the custom tool being called.

  • type: "custom_tool_call"

    The type of the custom tool call. Always custom_tool_call.

    • "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 or ResponseInputImage or ResponseInputFile

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

    • StringOutput = string

    A string of the output of the custom tool call.

    • OutputContentList = array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

    • ResponseInputText object { text, type }

      A text input to the model.

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

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

    • ResponseInputFile object { type, detail, file_data, 3 more }

      A file input 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.

    • "in_progress"

    • "completed"

    • "incomplete"

    • type: "custom_tool_call_output"

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

    • "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

  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.

  • tool_choice: ToolChoiceOptions or ToolChoiceAllowed or ToolChoiceTypes 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.

  • 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.

  • "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.

    • "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.

    • "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

    • "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.

  • name: string

    The name of the function to call.

  • type: "function"

    For function calling, the type is always function.

    • "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.

    • "mcp"

  • name: optional string

    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.

  • name: string

    The name of the custom tool to call.

  • type: "custom"

    For custom tool calling, the type is always custom.

    • "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.

    • "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.

    • "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.

  • 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.

  • name: string

    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.

    • "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.

    • "file_search"

  • vector_store_ids: array of string

    The IDs of the vector stores to search.

  • filters: optional ComparisonFilter or CompoundFilter

    A filter to apply.

    • ComparisonFilter object { key, type, value }

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

    • CompoundFilter object { filters, type }

    Combine multiple filters using and or 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.

    • "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.

    • "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.

    • "windows"

    • "mac"

    • "linux"

    • "ubuntu"

    • "browser"

  • type: "computer_use_preview"

    The type of the computer use tool. Always computer_use_preview.

    • "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.

    • "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.

    • "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.

    • "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.

    • "mcp"

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

    List of allowed tool names or a filter object.

    • 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

    • "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.

    • 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.

    • "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.

    • 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.

      • "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.

      • "1g"

      • "4g"

      • "16g"

      • "64g"

    • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

      Network access policy for the container.

      • ContainerNetworkPolicyDisabled object { type }

      • ContainerNetworkPolicyAllowlist object { allowed_domains, type, domain_secrets }

  • type: "code_interpreter"

    The type of the code interpreter tool. Always code_interpreter.

    • "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.

    • "image_generation"

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

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

    • "generate"

    • "edit"

    • "auto"

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

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

    • "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.

    • "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.

    • string

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

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

    • "gpt-image-1"

    • "gpt-image-1-mini"

    • "gpt-image-1.5"

  • moderation: optional "auto" or "low"

    Moderation level for the generated image. Default: auto.

    • "auto"

    • "low"

  • output_compression: optional number

    Compression level for the output image. Default: 100.

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

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

    • "png"

    • "webp"

    • "jpeg"

  • partial_images: optional number

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

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

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

    • "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.

    • "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.

    • "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.

    • "shell"

  • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

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

    • LocalEnvironment object { type, skills }

    • ContainerReference object { container_id, type }

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

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

  • name: string

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

  • type: "custom"

    The type of the custom tool. Always custom.

    • "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.

  • 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.

  • name: string

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

  • 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.

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

      • name: string

      • type: "function"

      • "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

    • name: string

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

    • type: "custom"

      The type of the custom tool. Always custom.

      • "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.

  • type: "namespace"

    The type of the tool. Always namespace.

    • "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.

    • "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.

    • "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.

    • "web_search_preview"

    • "web_search_preview_2025_03_11"

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

    • "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.

    • "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.

    • "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.

    • "apply_patch"

  • top_p: 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.

  • 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

  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.

  • 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

  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 or ResponseInputImage or ResponseInputFile]

  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.

  • string

  • ResponseInputText object { text, type }

    A text input to the model.

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

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

  • ResponseInputFile object { type, detail, file_data, 3 more }

    A file input 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.

  • "in_memory"

  • "24h"

  • reasoning: optional Reasoning

  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.

  • "none"

  • "minimal"

  • "low"

  • "medium"

  • "high"

  • "xhigh"

  • generate_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.

  • "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.

  • "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.

  • 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.

  • "auto"

  • "default"

  • "flex"

  • "scale"

  • "priority"

  • status: optional ResponseStatus

  The status of the response generation. One of completed, failed, in_progress, cancelled, queued, or incomplete.

  • "completed"

  • "failed"

  • "in_progress"

  • "cancelled"

  • "queued"

  • "incomplete"

  • text: optional ResponseTextConfig

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

  • Text inputs and outputs

  • Structured Outputs

  • 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.

  • ResponseFormatText object { type }

    Default response format. Used to generate text responses.

    • type: "text"

    The type of response format being defined. Always text.

    • "text"

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

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

    • name: string

    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.

    • "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.

    • "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.

  • "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.

  • 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.

  • "auto"

  • "disabled"

  • usage: optional ResponseUsage

  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.

  • user: 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.

Example

curl https://api.openai.com/v1/responses \
    -H 'Content-Type: application/json' \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -d '{
          "model": "gpt-5.1",
          "prompt_cache_key": "prompt-cache-key-1234",
          "safety_identifier": "safety-identifier-1234",
          "temperature": 1,
          "top_p": 1,
          "user": "user-1234"
        }'

Response

{
  "id": "id",
  "created_at": 0,
  "error": {
    "code": "server_error",
    "message": "message"
  },
  "incomplete_details": {
    "reason": "max_output_tokens"
  },
  "instructions": "string",
  "metadata": {
    "foo": "string"
  },
  "model": "gpt-5.1",
  "object": "response",
  "output": [
    {
      "id": "id",
      "content": [
        {
          "annotations": [
            {
              "file_id": "file_id",
              "filename": "filename",
              "index": 0,
              "type": "file_citation"
            }
          ],
          "logprobs": [
            {
              "token": "token",
              "bytes": [
                0
              ],
              "logprob": 0,
              "top_logprobs": [
                {
                  "token": "token",
                  "bytes": [
                    0
                  ],
                  "logprob": 0
                }
              ]
            }
          ],
          "text": "text",
          "type": "output_text"
        }
      ],
      "role": "assistant",
      "status": "in_progress",
      "type": "message",
      "phase": "commentary"
    }
  ],
  "parallel_tool_calls": true,
  "temperature": 1,
  "tool_choice": "none",
  "tools": [
    {
      "name": "name",
      "parameters": {
        "foo": "bar"
      },
      "strict": true,
      "type": "function",
      "defer_loading": true,
      "description": "description"
    }
  ],
  "top_p": 1,
  "background": true,
  "completed_at": 0,
  "conversation": {
    "id": "id"
  },
  "max_output_tokens": 0,
  "max_tool_calls": 0,
  "output_text": "output_text",
  "previous_response_id": "previous_response_id",
  "prompt": {
    "id": "id",
    "variables": {
      "foo": "string"
    },
    "version": "version"
  },
  "prompt_cache_key": "prompt-cache-key-1234",
  "prompt_cache_retention": "in_memory",
  "reasoning": {
    "effort": "none",
    "generate_summary": "auto",
    "summary": "auto"
  },
  "safety_identifier": "safety-identifier-1234",
  "service_tier": "auto",
  "status": "completed",
  "text": {
    "format": {
      "type": "text"
    },
    "verbosity": "low"
  },
  "top_logprobs": 0,
  "truncation": "auto",
  "usage": {
    "input_tokens": 0,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 0,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 0
  },
  "user": "user-1234"
}

Text input

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "input": "Tell me a three sentence bedtime story about a unicorn."
  }'

Response

{
  "id": "resp_67ccd2bed1ec8190b14f964abc0542670bb6a6b452d3795b",
  "object": "response",
  "created_at": 1741476542,
  "status": "completed",
  "completed_at": 1741476543,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-5.4",
  "output": [
    {
      "type": "message",
      "id": "msg_67ccd2bf17f0819081ff3bb2cf6508e60bb6a6b452d3795b",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "In a peaceful grove beneath a silver moon, a unicorn named Lumina discovered a hidden pool that reflected the stars. As she dipped her horn into the water, the pool began to shimmer, revealing a pathway to a magical realm of endless night skies. Filled with wonder, Lumina whispered a wish for all who dream to find their own hidden magic, and as she glanced back, her hoofprints sparkled like stardust.",
          "annotations": []
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 36,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 87,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 123
  },
  "user": null,
  "metadata": {}
}

Image input

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "input": [
      {
        "role": "user",
        "content": [
          {"type": "input_text", "text": "what is in this image?"},
          {
            "type": "input_image",
            "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
          }
        ]
      }
    ]
  }'

Response

{
  "id": "resp_67ccd3a9da748190baa7f1570fe91ac604becb25c45c1d41",
  "object": "response",
  "created_at": 1741476777,
  "status": "completed",
  "completed_at": 1741476778,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-5.4",
  "output": [
    {
      "type": "message",
      "id": "msg_67ccd3acc8d48190a77525dc6de64b4104becb25c45c1d41",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "The image depicts a scenic landscape with a wooden boardwalk or pathway leading through lush, green grass under a blue sky with some clouds. The setting suggests a peaceful natural area, possibly a park or nature reserve. There are trees and shrubs in the background.",
          "annotations": []
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 328,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 52,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 380
  },
  "user": null,
  "metadata": {}
}

File input

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "input": [
      {
        "role": "user",
        "content": [
          {"type": "input_text", "text": "what is in this file?"},
          {
            "type": "input_file",
            "file_url": "https://www.berkshirehathaway.com/letters/2024ltr.pdf"
          }
        ]
      }
    ]
  }'

Response

{
  "id": "resp_686eef60237881a2bd1180bb8b13de430e34c516d176ff86",
  "object": "response",
  "created_at": 1752100704,
  "status": "completed",
  "completed_at": 1752100705,
  "background": false,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "max_tool_calls": null,
  "model": "gpt-5.4",
  "output": [
    {
      "id": "msg_686eef60d3e081a29283bdcbc4322fd90e34c516d176ff86",
      "type": "message",
      "status": "completed",
      "content": [
        {
          "type": "output_text",
          "annotations": [],
          "logprobs": [],
          "text": "The file seems to contain excerpts from a letter to the shareholders of Berkshire Hathaway Inc., likely written by Warren Buffett. It covers several topics:\n\n1. **Communication Philosophy**: Buffett emphasizes the importance of transparency and candidness in reporting mistakes and successes to shareholders.\n\n2. **Mistakes and Learnings**: The letter acknowledges past mistakes in business assessments and management hires, highlighting the importance of correcting errors promptly.\n\n3. **CEO Succession**: Mention of Greg Abel stepping in as the new CEO and continuing the tradition of honest communication.\n\n4. **Pete Liegl Story**: A detailed account of acquiring Forest River and the relationship with its founder, highlighting trust and effective business decisions.\n\n5. **2024 Performance**: Overview of business performance, particularly in insurance and investment activities, with a focus on GEICO's improvement.\n\n6. **Tax Contributions**: Discussion of significant tax payments to the U.S. Treasury, credited to shareholders' reinvestments.\n\n7. **Investment Strategy**: A breakdown of Berkshire\u2019s investments in both controlled subsidiaries and marketable equities, along with a focus on long-term holding strategies.\n\n8. **American Capitalism**: Reflections on America\u2019s economic development and Berkshire\u2019s role within it.\n\n9. **Property-Casualty Insurance**: Insights into the P/C insurance business model and its challenges and benefits.\n\n10. **Japanese Investments**: Information about Berkshire\u2019s investments in Japanese companies and future plans.\n\n11. **Annual Meeting**: Details about the upcoming annual gathering in Omaha, including schedule changes and new book releases.\n\n12. **Personal Anecdotes**: Light-hearted stories about family and interactions, conveying Buffett's personable approach.\n\n13. **Financial Performance Data**: Tables comparing Berkshire\u2019s annual performance to the S&P 500, showing impressive long-term gains.\n\nOverall, the letter reinforces Berkshire Hathaway's commitment to transparency, investment in both its businesses and the wider economy, and emphasizes strong leadership and prudent financial management."
        }
      ],
      "role": "assistant"
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "service_tier": "default",
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [],
  "top_logprobs": 0,
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 8438,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 398,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 8836
  },
  "user": null,
  "metadata": {}
}

Web search

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "tools": [{ "type": "web_search_preview" }],
    "input": "What was a positive news story from today?"
  }'

Response

{
  "id": "resp_67ccf18ef5fc8190b16dbee19bc54e5f087bb177ab789d5c",
  "object": "response",
  "created_at": 1741484430,
  "status": "completed",
  "completed_at": 1741484431,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-5.4",
  "output": [
    {
      "type": "web_search_call",
      "id": "ws_67ccf18f64008190a39b619f4c8455ef087bb177ab789d5c",
      "status": "completed"
    },
    {
      "type": "message",
      "id": "msg_67ccf190ca3881909d433c50b1f6357e087bb177ab789d5c",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "As of today, March 9, 2025, one notable positive news story...",
          "annotations": [
            {
              "type": "url_citation",
              "start_index": 442,
              "end_index": 557,
              "url": "https://.../?utm_source=chatgpt.com",
              "title": "..."
            },
            {
              "type": "url_citation",
              "start_index": 962,
              "end_index": 1077,
              "url": "https://.../?utm_source=chatgpt.com",
              "title": "..."
            },
            {
              "type": "url_citation",
              "start_index": 1336,
              "end_index": 1451,
              "url": "https://.../?utm_source=chatgpt.com",
              "title": "..."
            }
          ]
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [
    {
      "type": "web_search_preview",
      "domains": [],
      "search_context_size": "medium",
      "user_location": {
        "type": "approximate",
        "city": null,
        "country": "US",
        "region": null,
        "timezone": null
      }
    }
  ],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 328,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 356,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 684
  },
  "user": null,
  "metadata": {}
}

File search

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "tools": [{
      "type": "file_search",
      "vector_store_ids": ["vs_1234567890"],
      "max_num_results": 20
    }],
    "input": "What are the attributes of an ancient brown dragon?"
  }'

Response

{
  "id": "resp_67ccf4c55fc48190b71bd0463ad3306d09504fb6872380d7",
  "object": "response",
  "created_at": 1741485253,
  "status": "completed",
  "completed_at": 1741485254,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-5.4",
  "output": [
    {
      "type": "file_search_call",
      "id": "fs_67ccf4c63cd08190887ef6464ba5681609504fb6872380d7",
      "status": "completed",
      "queries": [
        "attributes of an ancient brown dragon"
      ],
      "results": null
    },
    {
      "type": "message",
      "id": "msg_67ccf4c93e5c81909d595b369351a9d309504fb6872380d7",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "The attributes of an ancient brown dragon include...",
          "annotations": [
            {
              "type": "file_citation",
              "index": 320,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 576,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 815,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 815,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 1030,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 1030,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 1156,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            },
            {
              "type": "file_citation",
              "index": 1225,
              "file_id": "file-4wDz5b167pAf72nx1h9eiN",
              "filename": "dragons.pdf"
            }
          ]
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [
    {
      "type": "file_search",
      "filters": null,
      "max_num_results": 20,
      "ranking_options": {
        "ranker": "auto",
        "score_threshold": 0.0
      },
      "vector_store_ids": [
        "vs_1234567890"
      ]
    }
  ],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 18307,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 348,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 18655
  },
  "user": null,
  "metadata": {}
}

Streaming

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "instructions": "You are a helpful assistant.",
    "input": "Hello!",
    "stream": true
  }'

Response

event: response.created
data: {"type":"response.created","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"in_progress","error":null,"incomplete_details":null,"instructions":"You are a helpful assistant.","max_output_tokens":null,"model":"gpt-5.4","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}

event: response.in_progress
data: {"type":"response.in_progress","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"in_progress","error":null,"incomplete_details":null,"instructions":"You are a helpful assistant.","max_output_tokens":null,"model":"gpt-5.4","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}

event: response.output_item.added
data: {"type":"response.output_item.added","output_index":0,"item":{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"in_progress","role":"assistant","content":[]}}

event: response.content_part.added
data: {"type":"response.content_part.added","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}

event: response.output_text.delta
data: {"type":"response.output_text.delta","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"delta":"Hi"}

...

event: response.output_text.done
data: {"type":"response.output_text.done","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"text":"Hi there! How can I assist you today?"}

event: response.content_part.done
data: {"type":"response.content_part.done","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hi there! How can I assist you today?","annotations":[]}}

event: response.output_item.done
data: {"type":"response.output_item.done","output_index":0,"item":{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hi there! How can I assist you today?","annotations":[]}]}}

event: response.completed
data: {"type":"response.completed","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"completed","error":null,"incomplete_details":null,"instructions":"You are a helpful assistant.","max_output_tokens":null,"model":"gpt-5.4","output":[{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hi there! How can I assist you today?","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":37,"output_tokens":11,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":48},"user":null,"metadata":{}}}

Functions

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "gpt-5.4",
    "input": "What is the weather like in Boston today?",
    "tools": [
      {
        "type": "function",
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {
              "type": "string",
              "description": "The city and state, e.g. San Francisco, CA"
            },
            "unit": {
              "type": "string",
              "enum": ["celsius", "fahrenheit"]
            }
          },
          "required": ["location", "unit"]
        }
      }
    ],
    "tool_choice": "auto"
  }'

Response

{
  "id": "resp_67ca09c5efe0819096d0511c92b8c890096610f474011cc0",
  "object": "response",
  "created_at": 1741294021,
  "status": "completed",
  "completed_at": 1741294022,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-5.4",
  "output": [
    {
      "type": "function_call",
      "id": "fc_67ca09c6bedc8190a7abfec07b1a1332096610f474011cc0",
      "call_id": "call_unLAR8MvFNptuiZK6K6HCy5k",
      "name": "get_current_weather",
      "arguments": "{\"location\":\"Boston, MA\",\"unit\":\"celsius\"}",
      "status": "completed"
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [
    {
      "type": "function",
      "description": "Get the current weather in a given location",
      "name": "get_current_weather",
      "parameters": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "The city and state, e.g. San Francisco, CA"
          },
          "unit": {
            "type": "string",
            "enum": [
              "celsius",
              "fahrenheit"
            ]
          }
        },
        "required": [
          "location",
          "unit"
        ]
      },
      "strict": true
    }
  ],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 291,
    "output_tokens": 23,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 314
  },
  "user": null,
  "metadata": {}
}

Reasoning

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "model": "o3-mini",
    "input": "How much wood would a woodchuck chuck?",
    "reasoning": {
      "effort": "high"
    }
  }'

Response

{
  "id": "resp_67ccd7eca01881908ff0b5146584e408072912b2993db808",
  "object": "response",
  "created_at": 1741477868,
  "status": "completed",
  "completed_at": 1741477869,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "o1-2024-12-17",
  "output": [
    {
      "type": "message",
      "id": "msg_67ccd7f7b5848190a6f3e95d809f6b44072912b2993db808",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "The classic tongue twister...",
          "annotations": []
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": "high",
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 81,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens": 1035,
    "output_tokens_details": {
      "reasoning_tokens": 832
    },
    "total_tokens": 1116
  },
  "user": null,
  "metadata": {}
}