python/resources/responses/methods/cancel/index.md 2026-05-02 05:57 UTC to 2026-05-05 23:00 UTC

Cancel a response

responses.cancel(strresponse_id) -> Response

post /responses/{response_id}/cancel

Cancels a model response with the given ID. Only responses created with the background parameter set to true can be cancelled. Learn more.

Parameters

• response_id: str

Returns

• class Response: …

  • id: str

    Unique identifier for this Response.

  • created_at: float

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

  • error: Optional[ResponseError]

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

    • code: Literal["server_error", "rate_limit_exceeded", "invalid_prompt", 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: str

      A human-readable description of the error.

  • incomplete_details: Optional[IncompleteDetails]

    Details about why the response is incomplete.

    • reason: Optional[Literal["max_output_tokens", "content_filter"]]

      The reason why the response is incomplete.

      • "max_output_tokens"

      • "content_filter"

  • instructions: Union[str, List[ResponseInputItem], null]

    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.

    • str

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

    • List[ResponseInputItem]

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

      • class EasyInputMessage: …

        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: Union[str, ResponseInputMessageContentList]

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

          • str

            A text input to the model.

          • List[ResponseInputContent]

            • class ResponseInputText: …

              A text input to the model.

              • text: str

                The text input to the model.

              • type: Literal["input_text"]

                The type of the input item. Always input_text.

                • "input_text"

            • class ResponseInputImage: …

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

              • detail: Literal["low", "high", "auto", "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: Literal["input_image"]

                The type of the input item. Always input_image.

                • "input_image"

              • file_id: Optional[str]

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

              • image_url: Optional[str]

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

            • class ResponseInputFile: …

              A file input to the model.

              • type: Literal["input_file"]

                The type of the input item. Always input_file.

                • "input_file"

              • detail: Optional[Literal["low", "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[str]

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

              • file_id: Optional[str]

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

              • file_url: Optional[str]

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

              • filename: Optional[str]

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

        • role: Literal["user", "assistant", "system", "developer"]

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

          • "user"

          • "assistant"

          • "system"

          • "developer"

        • phase: Optional[Literal["commentary", "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[Literal["message"]]

          The type of the message input. Always message.

          • "message"

      • class Message: …

        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.

          • class ResponseInputText: …

            A text input to the model.

          • class ResponseInputImage: …

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

          • class ResponseInputFile: …

            A file input to the model.

        • role: Literal["user", "system", "developer"]

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

          • "user"

          • "system"

          • "developer"

        • status: Optional[Literal["in_progress", "completed", "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[Literal["message"]]

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

          • "message"

      • class ResponseOutputMessage: …

        An output message from the model.

        • id: str

          The unique ID of the output message.

        • content: List[Content]

          The content of the output message.

          • class ResponseOutputText: …

            A text output from the model.

            • annotations: List[Annotation]

              The annotations of the text output.

              • class AnnotationFileCitation: …

                A citation to a file.

                • file_id: str

                  The ID of the file.

                • filename: str

                  The filename of the file cited.

                • index: int

                  The index of the file in the list of files.

                • type: Literal["file_citation"]

                  The type of the file citation. Always file_citation.

                  • "file_citation"

              • class AnnotationURLCitation: …

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

                • end_index: int

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

                • start_index: int

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

                • title: str

                  The title of the web resource.

                • type: Literal["url_citation"]

                  The type of the URL citation. Always url_citation.

                  • "url_citation"

                • url: str

                  The URL of the web resource.

              • class AnnotationContainerFileCitation: …

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

                • container_id: str

                  The ID of the container file.

                • end_index: int

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

                • file_id: str

                  The ID of the file.

                • filename: str

                  The filename of the container file cited.

                • start_index: int

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

                • type: Literal["container_file_citation"]

                  The type of the container file citation. Always container_file_citation.

                  • "container_file_citation"

              • class AnnotationFilePath: …

                A path to a file.

                • file_id: str

                  The ID of the file.

                • index: int

                  The index of the file in the list of files.

                • type: Literal["file_path"]

                  The type of the file path. Always file_path.

                  • "file_path"

            • text: str

              The text output from the model.

            • type: Literal["output_text"]

              The type of the output text. Always output_text.

              • "output_text"

            • logprobs: Optional[List[Logprob]]

              • token: str

              • bytes: List[int]

              • logprob: float

              • top_logprobs: List[LogprobTopLogprob]

                • token: str

                • bytes: List[int]

                • logprob: float

          • class ResponseOutputRefusal: …

            A refusal from the model.

            • refusal: str

              The refusal explanation from the model.

            • type: Literal["refusal"]

              The type of the refusal. Always refusal.

              • "refusal"

        • role: Literal["assistant"]

          The role of the output message. Always assistant.

          • "assistant"

        • status: Literal["in_progress", "completed", "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: Literal["message"]

          The type of the output message. Always message.

          • "message"

        • phase: Optional[Literal["commentary", "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"

      • class ResponseFileSearchToolCall: …

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

        • id: str

          The unique ID of the file search tool call.

        • queries: List[str]

          The queries used to search for files.

        • status: Literal["in_progress", "searching", "completed", 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: Literal["file_search_call"]

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

          • "file_search_call"

        • results: Optional[List[Result]]

          The results of the file search tool call.

          • attributes: Optional[Dict[str, Union[str, float, bool]]]

            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.

            • str

            • float

            • bool

          • file_id: Optional[str]

            The unique ID of the file.

          • filename: Optional[str]

            The name of the file.

          • score: Optional[float]

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

          • text: Optional[str]

            The text that was retrieved from the file.

      • class ResponseComputerToolCall: …

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

        • id: str

          The unique ID of the computer call.

        • call_id: str

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

        • pending_safety_checks: List[PendingSafetyCheck]

          The pending safety checks for the computer call.

          • id: str

            The ID of the pending safety check.

          • code: Optional[str]

            The type of the pending safety check.

          • message: Optional[str]

            Details about the pending safety check.

        • status: Literal["in_progress", "completed", "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: Literal["computer_call"]

          The type of the computer call. Always computer_call.

          • "computer_call"

        • action: Optional[Action]

          A click action.

          • class ActionClick: …

            A click action.

            • button: Literal["left", "right", "wheel", 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: Literal["click"]

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

              • "click"

            • x: int

              The x-coordinate where the click occurred.

            • y: int

              The y-coordinate where the click occurred.

            • keys: Optional[List[str]]

              The keys being held while clicking.

          • class ActionDoubleClick: …

            A double click action.

            • keys: Optional[List[str]]

              The keys being held while double-clicking.

            • type: Literal["double_click"]

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

              • "double_click"

            • x: int

              The x-coordinate where the double click occurred.

            • y: int

              The y-coordinate where the double click occurred.

          • class ActionDrag: …

            A drag action.

            • path: List[ActionDragPath]

              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: int

                The x-coordinate.

              • y: int

                The y-coordinate.

            • type: Literal["drag"]

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

              • "drag"

            • keys: Optional[List[str]]

              The keys being held while dragging the mouse.

          • class ActionKeypress: …

            A collection of keypresses the model would like to perform.

            • keys: List[str]

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

            • type: Literal["keypress"]

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

              • "keypress"

          • class ActionMove: …

            A mouse move action.

            • type: Literal["move"]

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

              • "move"

            • x: int

              The x-coordinate to move to.

            • y: int

              The y-coordinate to move to.

            • keys: Optional[List[str]]

              The keys being held while moving the mouse.

          • class ActionScreenshot: …

            A screenshot action.

            • type: Literal["screenshot"]

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

              • "screenshot"

          • class ActionScroll: …

            A scroll action.

            • scroll_x: int

              The horizontal scroll distance.

            • scroll_y: int

              The vertical scroll distance.

            • type: Literal["scroll"]

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

              • "scroll"

            • x: int

              The x-coordinate where the scroll occurred.

            • y: int

              The y-coordinate where the scroll occurred.

            • keys: Optional[List[str]]

              The keys being held while scrolling.

          • class ActionType: …

            An action to type in text.

            • text: str

              The text to type.

            • type: Literal["type"]

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

              • "type"

          • class ActionWait: …

            A wait action.

            • type: Literal["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.

          • class Click: …

            A click action.

            • button: Literal["left", "right", "wheel", 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: Literal["click"]

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

              • "click"

            • x: int

              The x-coordinate where the click occurred.

            • y: int

              The y-coordinate where the click occurred.

            • keys: Optional[List[str]]

              The keys being held while clicking.

          • class DoubleClick: …

            A double click action.

            • keys: Optional[List[str]]

              The keys being held while double-clicking.

            • type: Literal["double_click"]

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

              • "double_click"

            • x: int

              The x-coordinate where the double click occurred.

            • y: int

              The y-coordinate where the double click occurred.

          • class Drag: …

            A drag action.

            • path: List[DragPath]

              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: int

                The x-coordinate.

              • y: int

                The y-coordinate.

            • type: Literal["drag"]

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

              • "drag"

            • keys: Optional[List[str]]

              The keys being held while dragging the mouse.

          • class Keypress: …

            A collection of keypresses the model would like to perform.

            • keys: List[str]

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

            • type: Literal["keypress"]

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

              • "keypress"

          • class Move: …

            A mouse move action.

            • type: Literal["move"]

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

              • "move"

            • x: int

              The x-coordinate to move to.

            • y: int

              The y-coordinate to move to.

            • keys: Optional[List[str]]

              The keys being held while moving the mouse.

          • class Screenshot: …

            A screenshot action.

            • type: Literal["screenshot"]

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

              • "screenshot"

          • class Scroll: …

            A scroll action.

            • scroll_x: int

              The horizontal scroll distance.

            • scroll_y: int

              The vertical scroll distance.

            • type: Literal["scroll"]

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

              • "scroll"

            • x: int

              The x-coordinate where the scroll occurred.

            • y: int

              The y-coordinate where the scroll occurred.

            • keys: Optional[List[str]]

              The keys being held while scrolling.

          • class Type: …

            An action to type in text.

            • text: str

              The text to type.

            • type: Literal["type"]

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

              • "type"

          • class Wait: …

            A wait action.

            • type: Literal["wait"]

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

              • "wait"

      • class ComputerCallOutput: …

        The output of a computer tool call.

        • call_id: str

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

        • output: ResponseComputerToolCallOutputScreenshot

          A computer screenshot image used with the computer use tool.

          • type: Literal["computer_screenshot"]

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

            • "computer_screenshot"

          • file_id: Optional[str]

            The identifier of an uploaded file that contains the screenshot.

          • image_url: Optional[str]

            The URL of the screenshot image.

        • type: Literal["computer_call_output"]

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

          • "computer_call_output"

        • id: Optional[str]

          The ID of the computer tool call output.

        • acknowledged_safety_checks: Optional[List[ComputerCallOutputAcknowledgedSafetyCheck]]

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

          • id: str

            The ID of the pending safety check.

          • code: Optional[str]

            The type of the pending safety check.

          • message: Optional[str]

            Details about the pending safety check.

        • status: Optional[Literal["in_progress", "completed", "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"

      • class ResponseFunctionWebSearch: …

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

        • id: str

          The unique ID of the web search tool call.

        • action: Action

          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).

          • class ActionSearch: …

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

            • query: str

              [DEPRECATED] The search query.

            • type: Literal["search"]

              The action type.

              • "search"

            • queries: Optional[List[str]]

              The search queries.

            • sources: Optional[List[ActionSearchSource]]

              The sources used in the search.

              • type: Literal["url"]

                The type of source. Always url.

                • "url"

              • url: str

                The URL of the source.

          • class ActionOpenPage: …

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

            • type: Literal["open_page"]

              The action type.

              • "open_page"

            • url: Optional[str]

              The URL opened by the model.

          • class ActionFindInPage: …

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

            • pattern: str

              The pattern or text to search for within the page.

            • type: Literal["find_in_page"]

              The action type.

              • "find_in_page"

            • url: str

              The URL of the page searched for the pattern.

        • status: Literal["in_progress", "searching", "completed", "failed"]

          The status of the web search tool call.

          • "in_progress"

          • "searching"

          • "completed"

          • "failed"

        • type: Literal["web_search_call"]

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

          • "web_search_call"

      • class ResponseFunctionToolCall: …

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

        • arguments: str

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

        • call_id: str

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

        • name: str

          The name of the function to run.

        • type: Literal["function_call"]

          The type of the function tool call. Always function_call.

          • "function_call"

        • id: Optional[str]

          The unique ID of the function tool call.

        • namespace: Optional[str]

          The namespace of the function to run.

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • class FunctionCallOutput: …

        The output of a function tool call.

        • call_id: str

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

        • output: Union[str, ResponseFunctionCallOutputItemList]

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

          • str

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

          • List[ResponseFunctionCallOutputItem]

            • class ResponseInputTextContent: …

              A text input to the model.

              • text: str

                The text input to the model.

              • type: Literal["input_text"]

                The type of the input item. Always input_text.

                • "input_text"

            • class ResponseInputImageContent: …

              An image input to the model. Learn about image inputs

              • type: Literal["input_image"]

                The type of the input item. Always input_image.

                • "input_image"

              • detail: Optional[Literal["low", "high", "auto", "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[str]

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

              • image_url: Optional[str]

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

            • class ResponseInputFileContent: …

              A file input to the model.

              • type: Literal["input_file"]

                The type of the input item. Always input_file.

                • "input_file"

              • detail: Optional[Literal["low", "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[str]

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

              • file_id: Optional[str]

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

              • file_url: Optional[str]

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

              • filename: Optional[str]

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

        • type: Literal["function_call_output"]

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

          • "function_call_output"

        • id: Optional[str]

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

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ToolSearchCall: …

        • arguments: object

          The arguments supplied to the tool search call.

        • type: Literal["tool_search_call"]

          The item type. Always tool_search_call.

          • "tool_search_call"

        • id: Optional[str]

          The unique ID of this tool search call.

        • call_id: Optional[str]

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

        • execution: Optional[Literal["server", "client"]]

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

          • "server"

          • "client"

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

          The status of the tool search call.

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ResponseToolSearchOutputItemParam: …

        • tools: List[Tool]

          The loaded tool definitions returned by the tool search output.

          • class FunctionTool: …

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

            • name: str

              The name of the function to call.

            • parameters: Optional[Dict[str, object]]

              A JSON schema object describing the parameters of the function.

            • strict: Optional[bool]

              Whether to enforce strict parameter validation. Default true.

            • type: Literal["function"]

              The type of the function tool. Always function.

              • "function"

            • defer_loading: Optional[bool]

              Whether this function is deferred and loaded via tool search.

            • description: Optional[str]

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

          • class FileSearchTool: …

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

            • type: Literal["file_search"]

              The type of the file search tool. Always file_search.

              • "file_search"

            • vector_store_ids: List[str]

              The IDs of the vector stores to search.

            • filters: Optional[Filters]

              A filter to apply.

              • class ComparisonFilter: …

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

                • key: str

                  The key to compare against the value.

                • type: Literal["eq", "ne", "gt", 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: Union[str, float, bool, List[Union[str, float]]]

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

                  • str

                  • float

                  • bool

                  • List[Union[str, float]]

                    • str

                    • float

              • class CompoundFilter: …

                Combine multiple filters using and or or.

                • filters: List[Filter]

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

                  • class ComparisonFilter: …

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

                  • object

                • type: Literal["and", "or"]

                  Type of operation: and or or.

                  • "and"

                  • "or"

            • max_num_results: Optional[int]

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

            • ranking_options: Optional[RankingOptions]

              Ranking options for search.

              • hybrid_search: Optional[RankingOptionsHybridSearch]

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

                • embedding_weight: float

                  The weight of the embedding in the reciprocal ranking fusion.

                • text_weight: float

                  The weight of the text in the reciprocal ranking fusion.

              • ranker: Optional[Literal["auto", "default-2024-11-15"]]

                The ranker to use for the file search.

                • "auto"

                • "default-2024-11-15"

              • score_threshold: Optional[float]

                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.

          • class ComputerTool: …

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

            • type: Literal["computer"]

              The type of the computer tool. Always computer.

              • "computer"

          • class ComputerUsePreviewTool: …

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

            • display_height: int

              The height of the computer display.

            • display_width: int

              The width of the computer display.

            • environment: Literal["windows", "mac", "linux", 2 more]

              The type of computer environment to control.

              • "windows"

              • "mac"

              • "linux"

              • "ubuntu"

              • "browser"

            • type: Literal["computer_use_preview"]

              The type of the computer use tool. Always computer_use_preview.

              • "computer_use_preview"

          • class WebSearchTool: …

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

            • type: Literal["web_search", "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[Filters]

              Filters for the search.

              • allowed_domains: Optional[List[str]]

                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[Literal["low", "medium", "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[UserLocation]

              The approximate location of the user.

              • city: Optional[str]

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

              • country: Optional[str]

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

              • region: Optional[str]

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

              • timezone: Optional[str]

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

              • type: Optional[Literal["approximate"]]

                The type of location approximation. Always approximate.

                • "approximate"

          • class Mcp: …

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

            • server_label: str

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

            • type: Literal["mcp"]

              The type of the MCP tool. Always mcp.

              • "mcp"

            • allowed_tools: Optional[McpAllowedTools]

              List of allowed tool names or a filter object.

              • List[str]

                A string array of allowed tool names

              • class McpAllowedToolsMcpToolFilter: …

                A filter object to specify which tools are allowed.

                • read_only: Optional[bool]

                  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[List[str]]

                  List of allowed tool names.

            • authorization: Optional[str]

              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[Literal["connector_dropbox", "connector_gmail", "connector_googlecalendar", 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[bool]

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

            • headers: Optional[Dict[str, str]]

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

            • require_approval: Optional[McpRequireApproval]

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

              • class McpRequireApprovalMcpToolApprovalFilter: …

                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[McpRequireApprovalMcpToolApprovalFilterAlways]

                  A filter object to specify which tools are allowed.

                  • read_only: Optional[bool]

                    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[List[str]]

                    List of allowed tool names.

                • never: Optional[McpRequireApprovalMcpToolApprovalFilterNever]

                  A filter object to specify which tools are allowed.

                  • read_only: Optional[bool]

                    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[List[str]]

                    List of allowed tool names.

              • Literal["always", "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[str]

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

            • server_url: Optional[str]

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

          • class CodeInterpreter: …

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

            • container: CodeInterpreterContainer

              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.

              • str

                The container ID.

              • class CodeInterpreterContainerCodeInterpreterToolAuto: …

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

                • type: Literal["auto"]

                  Always auto.

                  • "auto"

                • file_ids: Optional[List[str]]

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

                • memory_limit: Optional[Literal["1g", "4g", "16g", "64g"]]

                  The memory limit for the code interpreter container.

                  • "1g"

                  • "4g"

                  • "16g"

                  • "64g"

                • network_policy: Optional[CodeInterpreterContainerCodeInterpreterToolAutoNetworkPolicy]

                  Network access policy for the container.

                  • class ContainerNetworkPolicyDisabled: …

                    • type: Literal["disabled"]

                      Disable outbound network access. Always disabled.

                      • "disabled"

                  • class ContainerNetworkPolicyAllowlist: …

                    • allowed_domains: List[str]

                      A list of allowed domains when type is allowlist.

                    • type: Literal["allowlist"]

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

                      • "allowlist"

                    • domain_secrets: Optional[List[ContainerNetworkPolicyDomainSecret]]

                      Optional domain-scoped secrets for allowlisted domains.

                      • domain: str

                        The domain associated with the secret.

                      • name: str

                        The name of the secret to inject for the domain.

                      • value: str

                        The secret value to inject for the domain.

            • type: Literal["code_interpreter"]

              The type of the code interpreter tool. Always code_interpreter.

              • "code_interpreter"

          • class ImageGeneration: …

            A tool that generates images using the GPT image models.

            • type: Literal["image_generation"]

              The type of the image generation tool. Always image_generation.

              • "image_generation"

            • action: Optional[Literal["generate", "edit", "auto"]]

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

              • "generate"

              • "edit"

              • "auto"

            • background: Optional[Literal["transparent", "opaque", "auto"]]

              Allows to set transparency for the background of the generated image(s). This parameter is only supported for GPT image models that support transparent backgrounds. Must be one of transparent, opaque, or auto (default value). When auto is used, the model will automatically determine the best background for the image.

              gpt-image-2 and gpt-image-2-2026-04-21 do not support transparent backgrounds. Requests with background set to transparent will return an error for these models; use opaque or auto instead.

              If transparent, the output format needs to support transparency, so it should be set to either png (default value) or webp.

              • "transparent"

              • "opaque"

              • "auto"

            • input_fidelity: Optional[Literal["high", "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[ImageGenerationInputImageMask]

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

              • file_id: Optional[str]

                File ID for the mask image.

              • image_url: Optional[str]

                Base64-encoded mask image.

            • model: Optional[Union[str, Literal["gpt-image-1", "gpt-image-1-mini", "gpt-image-2", 3 more], null]]

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

              • str

              • Literal["gpt-image-1", "gpt-image-1-mini", "gpt-image-2", 3 more]

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

                • "gpt-image-1"

                • "gpt-image-1-mini"

                • "gpt-image-2"

                • "gpt-image-2-2026-04-21"

                • "gpt-image-1.5"

                • "chatgpt-image-latest"

            • moderation: Optional[Literal["auto", "low"]]

              Moderation level for the generated image. Default: auto.

              • "auto"

              • "low"

            • output_compression: Optional[int]

              Compression level for the output image. Default: 100.

            • output_format: Optional[Literal["png", "webp", "jpeg"]]

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

              • "png"

              • "webp"

              • "jpeg"

            • partial_images: Optional[int]

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

            • quality: Optional[Literal["low", "medium", "high", "auto"]]

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

              • "low"

              • "medium"

              • "high"

              • "auto"

            • size: Optional[str]

              The size of the generated images. For gpt-image-2 and gpt-image-2-2026-04-21, arbitrary resolutions are supported as WIDTHxHEIGHT strings, for example 1536x864. Width and height must both be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1. Resolutions above 2560x1440 are experimental, and the maximum supported resolution is 3840x2160. The requested size must also satisfy the model's current pixel and edge limits. The standard sizes 1024x1024, 1536x1024, and 1024x1536 are supported by the GPT image models; auto is supported for models that allow automatic sizing. For dall-e-2, use one of 256x256, 512x512, or 1024x1024. For dall-e-3, use one of 1024x1024, 1792x1024, or 1024x1792.

          • class LocalShell: …

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

            • type: Literal["local_shell"]

              The type of the local shell tool. Always local_shell.

              • "local_shell"

          • class FunctionShellTool: …

            A tool that allows the model to execute shell commands.

            • type: Literal["shell"]

              The type of the shell tool. Always shell.

              • "shell"

            • environment: Optional[Environment]

              • class ContainerAuto: …

                • type: Literal["container_auto"]

                  Automatically creates a container for this request

                  • "container_auto"

                • file_ids: Optional[List[str]]

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

                • memory_limit: Optional[Literal["1g", "4g", "16g", "64g"]]

                  The memory limit for the container.

                  • "1g"

                  • "4g"

                  • "16g"

                  • "64g"

                • network_policy: Optional[NetworkPolicy]

                  Network access policy for the container.

                  • class ContainerNetworkPolicyDisabled: …

                  • class ContainerNetworkPolicyAllowlist: …

                • skills: Optional[List[Skill]]

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

                  • class SkillReference: …

                    • skill_id: str

                      The ID of the referenced skill.

                    • type: Literal["skill_reference"]

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

                      • "skill_reference"

                    • version: Optional[str]

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

                  • class InlineSkill: …

                    • description: str

                      The description of the skill.

                    • name: str

                      The name of the skill.

                    • source: InlineSkillSource

                      Inline skill payload

                      • data: str

                        Base64-encoded skill zip bundle.

                      • media_type: Literal["application/zip"]

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

                        • "application/zip"

                      • type: Literal["base64"]

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

                        • "base64"

                    • type: Literal["inline"]

                      Defines an inline skill for this request.

                      • "inline"

              • class LocalEnvironment: …

                • type: Literal["local"]

                  Use a local computer environment.

                  • "local"

                • skills: Optional[List[LocalSkill]]

                  An optional list of skills.

                  • description: str

                    The description of the skill.

                  • name: str

                    The name of the skill.

                  • path: str

                    The path to the directory containing the skill.

              • class ContainerReference: …

                • container_id: str

                  The ID of the referenced container.

                • type: Literal["container_reference"]

                  References a container created with the /v1/containers endpoint

                  • "container_reference"

          • class CustomTool: …

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

            • name: str

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

            • type: Literal["custom"]

              The type of the custom tool. Always custom.

              • "custom"

            • defer_loading: Optional[bool]

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

            • description: Optional[str]

              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.

              • class Text: …

                Unconstrained free-form text.

                • type: Literal["text"]

                  Unconstrained text format. Always text.

                  • "text"

              • class Grammar: …

                A grammar defined by the user.

                • definition: str

                  The grammar definition.

                • syntax: Literal["lark", "regex"]

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

                  • "lark"

                  • "regex"

                • type: Literal["grammar"]

                  Grammar format. Always grammar.

                  • "grammar"

          • class NamespaceTool: …

            Groups function/custom tools under a shared namespace.

            • description: str

              A description of the namespace shown to the model.

            • name: str

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

            • tools: List[Tool]

              The function/custom tools available inside this namespace.

              • class ToolFunction: …

                • name: str

                • type: Literal["function"]

                  • "function"

                • defer_loading: Optional[bool]

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

                • description: Optional[str]

                • parameters: Optional[object]

                • strict: Optional[bool]

              • class CustomTool: …

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

            • type: Literal["namespace"]

              The type of the tool. Always namespace.

              • "namespace"

          • class ToolSearchTool: …

            Hosted or BYOT tool search configuration for deferred tools.

            • type: Literal["tool_search"]

              The type of the tool. Always tool_search.

              • "tool_search"

            • description: Optional[str]

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

            • execution: Optional[Literal["server", "client"]]

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

              • "server"

              • "client"

            • parameters: Optional[object]

              Parameter schema for a client-executed tool search tool.

          • class WebSearchPreviewTool: …

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

            • type: Literal["web_search_preview", "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[List[Literal["text", "image"]]]

              • "text"

              • "image"

            • search_context_size: Optional[Literal["low", "medium", "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[UserLocation]

              The user's location.

              • type: Literal["approximate"]

                The type of location approximation. Always approximate.

                • "approximate"

              • city: Optional[str]

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

              • country: Optional[str]

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

              • region: Optional[str]

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

              • timezone: Optional[str]

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

          • class ApplyPatchTool: …

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

            • type: Literal["apply_patch"]

              The type of the tool. Always apply_patch.

              • "apply_patch"

        • type: Literal["tool_search_output"]

          The item type. Always tool_search_output.

          • "tool_search_output"

        • id: Optional[str]

          The unique ID of this tool search output.

        • call_id: Optional[str]

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

        • execution: Optional[Literal["server", "client"]]

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

          • "server"

          • "client"

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

          The status of the tool search output.

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ResponseReasoningItem: …

        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: str

          The unique identifier of the reasoning content.

        • summary: List[Summary]

          Reasoning summary content.

          • text: str

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

          • type: Literal["summary_text"]

            The type of the object. Always summary_text.

            • "summary_text"

        • type: Literal["reasoning"]

          The type of the object. Always reasoning.

          • "reasoning"

        • content: Optional[List[Content]]

          Reasoning text content.

          • text: str

            The reasoning text from the model.

          • type: Literal["reasoning_text"]

            The type of the reasoning text. Always reasoning_text.

            • "reasoning_text"

        • encrypted_content: Optional[str]

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

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ResponseCompactionItemParam: …

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

        • encrypted_content: str

          The encrypted content of the compaction summary.

        • type: Literal["compaction"]

          The type of the item. Always compaction.

          • "compaction"

        • id: Optional[str]

          The ID of the compaction item.

      • class ImageGenerationCall: …

        An image generation request made by the model.

        • id: str

          The unique ID of the image generation call.

        • result: Optional[str]

          The generated image encoded in base64.

        • status: Literal["in_progress", "completed", "generating", "failed"]

          The status of the image generation call.

          • "in_progress"

          • "completed"

          • "generating"

          • "failed"

        • type: Literal["image_generation_call"]

          The type of the image generation call. Always image_generation_call.

          • "image_generation_call"

      • class ResponseCodeInterpreterToolCall: …

        A tool call to run code.

        • id: str

          The unique ID of the code interpreter tool call.

        • code: Optional[str]

          The code to run, or null if not available.

        • container_id: str

          The ID of the container used to run the code.

        • outputs: Optional[List[Output]]

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

          • class OutputLogs: …

            The logs output from the code interpreter.

            • logs: str

              The logs output from the code interpreter.

            • type: Literal["logs"]

              The type of the output. Always logs.

              • "logs"

          • class OutputImage: …

            The image output from the code interpreter.

            • type: Literal["image"]

              The type of the output. Always image.

              • "image"

            • url: str

              The URL of the image output from the code interpreter.

        • status: Literal["in_progress", "completed", "incomplete", 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: Literal["code_interpreter_call"]

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

          • "code_interpreter_call"

      • class LocalShellCall: …

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

        • id: str

          The unique ID of the local shell call.

        • action: LocalShellCallAction

          Execute a shell command on the server.

          • command: List[str]

            The command to run.

          • env: Dict[str, str]

            Environment variables to set for the command.

          • type: Literal["exec"]

            The type of the local shell action. Always exec.

            • "exec"

          • timeout_ms: Optional[int]

            Optional timeout in milliseconds for the command.

          • user: Optional[str]

            Optional user to run the command as.

          • working_directory: Optional[str]

            Optional working directory to run the command in.

        • call_id: str

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

        • status: Literal["in_progress", "completed", "incomplete"]

          The status of the local shell call.

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: Literal["local_shell_call"]

          The type of the local shell call. Always local_shell_call.

          • "local_shell_call"

      • class LocalShellCallOutput: …

        The output of a local shell tool call.

        • id: str

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

        • output: str

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

        • type: Literal["local_shell_call_output"]

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

          • "local_shell_call_output"

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ShellCall: …

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

        • action: ShellCallAction

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

          • commands: List[str]

            Ordered shell commands for the execution environment to run.

          • max_output_length: Optional[int]

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

          • timeout_ms: Optional[int]

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

        • call_id: str

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

        • type: Literal["shell_call"]

          The type of the item. Always shell_call.

          • "shell_call"

        • id: Optional[str]

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

        • environment: Optional[ShellCallEnvironment]

          The environment to execute the shell commands in.

          • class LocalEnvironment: …

          • class ContainerReference: …

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ShellCallOutput: …

        The streamed output items emitted by a shell tool call.

        • call_id: str

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

        • output: List[ResponseFunctionShellCallOutputContent]

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

          • outcome: Outcome

            The exit or timeout outcome associated with this shell call.

            • class OutcomeTimeout: …

              Indicates that the shell call exceeded its configured time limit.

              • type: Literal["timeout"]

                The outcome type. Always timeout.

                • "timeout"

            • class OutcomeExit: …

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

              • exit_code: int

                The exit code returned by the shell process.

              • type: Literal["exit"]

                The outcome type. Always exit.

                • "exit"

          • stderr: str

            Captured stderr output for the shell call.

          • stdout: str

            Captured stdout output for the shell call.

        • type: Literal["shell_call_output"]

          The type of the item. Always shell_call_output.

          • "shell_call_output"

        • id: Optional[str]

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

        • max_output_length: Optional[int]

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

        • status: Optional[Literal["in_progress", "completed", "incomplete"]]

          The status of the shell call output.

          • "in_progress"

          • "completed"

          • "incomplete"

      • class ApplyPatchCall: …

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

        • call_id: str

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

        • operation: ApplyPatchCallOperation

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

          • class ApplyPatchCallOperationCreateFile: …

            Instruction for creating a new file via the apply_patch tool.

            • diff: str

              Unified diff content to apply when creating the file.

            • path: str

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

            • type: Literal["create_file"]

              The operation type. Always create_file.

              • "create_file"

          • class ApplyPatchCallOperationDeleteFile: …

            Instruction for deleting an existing file via the apply_patch tool.

            • path: str

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

            • type: Literal["delete_file"]

              The operation type. Always delete_file.

              • "delete_file"

          • class ApplyPatchCallOperationUpdateFile: …

            Instruction for updating an existing file via the apply_patch tool.

            • diff: str

              Unified diff content to apply to the existing file.

            • path: str

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

            • type: Literal["update_file"]

              The operation type. Always update_file.

              • "update_file"

        • status: Literal["in_progress", "completed"]

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

          • "in_progress"

          • "completed"

        • type: Literal["apply_patch_call"]

          The type of the item. Always apply_patch_call.

          • "apply_patch_call"

        • id: Optional[str]

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

      • class ApplyPatchCallOutput: …

        The streamed output emitted by an apply patch tool call.

        • call_id: str

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

        • status: Literal["completed", "failed"]

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

          • "completed"

          • "failed"

        • type: Literal["apply_patch_call_output"]

          The type of the item. Always apply_patch_call_output.

          • "apply_patch_call_output"

        • id: Optional[str]

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

        • output: Optional[str]

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

      • class McpListTools: …

        A list of tools available on an MCP server.

        • id: str

          The unique ID of the list.

        • server_label: str

          The label of the MCP server.

        • tools: List[McpListToolsTool]

          The tools available on the server.

          • input_schema: object

            The JSON schema describing the tool's input.

          • name: str

            The name of the tool.

          • annotations: Optional[object]

            Additional annotations about the tool.

          • description: Optional[str]

            The description of the tool.

        • type: Literal["mcp_list_tools"]

          The type of the item. Always mcp_list_tools.

          • "mcp_list_tools"

        • error: Optional[str]

          Error message if the server could not list tools.

      • class McpApprovalRequest: …

        A request for human approval of a tool invocation.

        • id: str

          The unique ID of the approval request.

        • arguments: str

          A JSON string of arguments for the tool.

        • name: str

          The name of the tool to run.

        • server_label: str

          The label of the MCP server making the request.

        • type: Literal["mcp_approval_request"]

          The type of the item. Always mcp_approval_request.

          • "mcp_approval_request"

      • class McpApprovalResponse: …

        A response to an MCP approval request.

        • approval_request_id: str

          The ID of the approval request being answered.

        • approve: bool

          Whether the request was approved.

        • type: Literal["mcp_approval_response"]

          The type of the item. Always mcp_approval_response.

          • "mcp_approval_response"

        • id: Optional[str]

          The unique ID of the approval response

        • reason: Optional[str]

          Optional reason for the decision.

      • class McpCall: …

        An invocation of a tool on an MCP server.

        • id: str

          The unique ID of the tool call.

        • arguments: str

          A JSON string of the arguments passed to the tool.

        • name: str

          The name of the tool that was run.

        • server_label: str

          The label of the MCP server running the tool.

        • type: Literal["mcp_call"]

          The type of the item. Always mcp_call.

          • "mcp_call"

        • approval_request_id: Optional[str]

          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[str]

          The error from the tool call, if any.

        • output: Optional[str]

          The output from the tool call.

        • status: Optional[Literal["in_progress", "completed", "incomplete", 2 more]]

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

          • "in_progress"

          • "completed"

          • "incomplete"

          • "calling"

          • "failed"

      • class ResponseCustomToolCallOutput: …

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

        • call_id: str

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

        • output: Union[str, List[OutputOutputContentList]]

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

          • str

            A string of the output of the custom tool call.

          • List[OutputOutputContentList]

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

            • class ResponseInputText: …

              A text input to the model.

            • class ResponseInputImage: …

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

            • class ResponseInputFile: …

              A file input to the model.

        • type: Literal["custom_tool_call_output"]

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

          • "custom_tool_call_output"

        • id: Optional[str]

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

      • class ResponseCustomToolCall: …

        A call to a custom tool created by the model.

        • call_id: str

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

        • input: str

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

        • name: str

          The name of the custom tool being called.

        • type: Literal["custom_tool_call"]

          The type of the custom tool call. Always custom_tool_call.

          • "custom_tool_call"

        • id: Optional[str]

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

        • namespace: Optional[str]

          The namespace of the custom tool being called.

      • class ItemReference: …

        An internal identifier for an item to reference.

        • id: str

          The ID of the item to reference.

        • type: Optional[Literal["item_reference"]]

          The type of item to reference. Always item_reference.

          • "item_reference"

  • 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: 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.

    • str

    • Literal["gpt-5.4", "gpt-5.4-mini", "gpt-5.4-nano", 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"

    • Literal["o1-pro", "o1-pro-2025-03-19", "o3-pro", 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: Literal["response"]

    The object type of this resource - always set to response.

    • "response"

  • output: List[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.

    • class ResponseOutputMessage: …

      An output message from the model.

    • class ResponseFileSearchToolCall: …

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

    • class ResponseFunctionToolCall: …

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

    • class ResponseFunctionToolCallOutputItem: …

      • id: str

        The unique ID of the function call tool output.

      • call_id: str

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

      • output: Union[str, List[OutputOutputContentList]]

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

        • str

          A string of the output of the function call.

        • List[OutputOutputContentList]

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

          • class ResponseInputText: …

            A text input to the model.

          • class ResponseInputImage: …

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

          • class ResponseInputFile: …

            A file input to the model.

      • status: Literal["in_progress", "completed", "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: Literal["function_call_output"]

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

        • "function_call_output"

      • created_by: Optional[str]

        The identifier of the actor that created the item.

    • class ResponseFunctionWebSearch: …

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

    • class ResponseComputerToolCall: …

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

    • class ResponseComputerToolCallOutputItem: …

      • id: str

        The unique ID of the computer call tool output.

      • call_id: str

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

      • output: ResponseComputerToolCallOutputScreenshot

        A computer screenshot image used with the computer use tool.

      • status: Literal["completed", "incomplete", "failed", "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: Literal["computer_call_output"]

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

        • "computer_call_output"

      • acknowledged_safety_checks: Optional[List[AcknowledgedSafetyCheck]]

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

        • id: str

          The ID of the pending safety check.

        • code: Optional[str]

          The type of the pending safety check.

        • message: Optional[str]

          Details about the pending safety check.

      • created_by: Optional[str]

        The identifier of the actor that created the item.

    • class ResponseReasoningItem: …

      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.

    • class ResponseToolSearchCall: …

      • id: str

        The unique ID of the tool search call item.

      • arguments: object

        Arguments used for the tool search call.

      • call_id: Optional[str]

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

      • execution: Literal["server", "client"]

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

        • "server"

        • "client"

      • status: Literal["in_progress", "completed", "incomplete"]

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: Literal["tool_search_call"]

        The type of the item. Always tool_search_call.

        • "tool_search_call"

      • created_by: Optional[str]

        The identifier of the actor that created the item.

    • class ResponseToolSearchOutputItem: …

      • id: str

        The unique ID of the tool search output item.

      • call_id: Optional[str]

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

      • execution: Literal["server", "client"]

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

        • "server"

        • "client"

      • status: Literal["in_progress", "completed", "incomplete"]

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • tools: List[Tool]

        The loaded tool definitions returned by tool search.

        • class FunctionTool: …

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

        • class FileSearchTool: …

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

        • class ComputerTool: …

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

        • class ComputerUsePreviewTool: …

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

        • class WebSearchTool: …

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

        • class Mcp: …

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

        • class CodeInterpreter: …

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

        • class ImageGeneration: …

          A tool that generates images using the GPT image models.

        • class LocalShell: …

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

        • class FunctionShellTool: …

          A tool that allows the model to execute shell commands.

        • class CustomTool: …

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

        • class NamespaceTool: …

          Groups function/custom tools under a shared namespace.

        • class ToolSearchTool: …

          Hosted or BYOT tool search configuration for deferred tools.

        • class WebSearchPreviewTool: …

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

        • class ApplyPatchTool: …

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

      • type: Literal["tool_search_output"]

        The type of the item. Always tool_search_output.

        • "tool_search_output"

      • created_by: Optional[str]

        The identifier of the actor that created the item.

    • class ResponseCompactionItem: …

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

      • id: str

        The unique ID of the compaction item.

      • encrypted_content: str

        The encrypted content that was produced by compaction.

      • type: Literal["compaction"]

        The type of the item. Always compaction.

        • "compaction"

      • created_by: Optional[str]

        The identifier of the actor that created the item.

    • class ImageGenerationCall: …

      An image generation request made by the model.

      • id: str

        The unique ID of the image generation call.

      • result: Optional[str]

        The generated image encoded in base64.

      • status: Literal["in_progress", "completed", "generating", "failed"]

        The status of the image generation call.

        • "in_progress"

        • "completed"

        • "generating"

        • "failed"

      • type: Literal["image_generation_call"]

        The type of the image generation call. Always image_generation_call.

        • "image_generation_call"

    • class ResponseCodeInterpreterToolCall: …

      A tool call to run code.

    • class LocalShellCall: …

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

      • id: str

        The unique ID of the local shell call.

      • action: LocalShellCallAction

        Execute a shell command on the server.

        • command: List[str]

          The command to run.

        • env: Dict[str, str]

          Environment variables to set for the command.

        • type: Literal["exec"]

          The type of the local shell action. Always exec.

          • "exec"

        • timeout_ms: Optional[int]

          Optional timeout in milliseconds for the command.

        • user: Optional[str]

          Optional user to run the command as.

        • working_directory: Optional[str]

          Optional working directory to run the command in.

      • call_id: str

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

      • status: Literal["in_progress", "completed", "incomplete"]

        The status of the local shell call.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: Literal["local_shell_call"]

        The type of the local shell call. Always local_shell_call.

        • "local_shell_call"

    • class LocalShellCallOutput: …

      The output of a local shell tool call.

      • id: str

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

      • output: str

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

      • type: Literal["local_shell_call_output"]

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

        • "local_shell_call_output"

      • status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

        • "in_progress"

        • "completed"

        • "incomplete"

    • class ResponseFunctionShellToolCall: …

      A tool call that executes one or more shell commands in a managed environment.

      • id: str

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

      • action: Action

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

        • commands: List[str]

        • max_output_length: Optional[int]

          Optional maximum number of characters to return from each command.

        • timeout_ms: Optional[int]

          Optional timeout in milliseconds for the commands.

      • call_id: str

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

      • environment: Optional[Environment]

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

        • class ResponseLocalEnvironment: …

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

          • type: Literal["local"]

            The environment type. Always local.

            • "local"

        • class ResponseContainerReference: …

          Represents a container created with /v1/containers.

          • container_id: str

          • type: Literal["container_reference"]

            The environment type. Always container_reference.

            • "container_reference"

      • status: Literal["in_progress", "completed", "incomplete"]

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: Literal["shell_call"]

        The type of the item. Always shell_call.

        • "shell_call"

      • created_by: Optional[str]

        The ID of the entity that created this tool call.

    • class ResponseFunctionShellToolCallOutput: …

      The output of a shell tool call that was emitted.

      • id: str

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

      • call_id: str

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

      • max_output_length: Optional[int]

        The maximum length of the shell command output. This is generated by the model and should be passed back with the raw output.

      • output: List[Output]

        An array of shell call output contents

        • outcome: OutputOutcome

          Represents either an exit outcome (with an exit code) or a timeout outcome for a shell call output chunk.

          • class OutputOutcomeTimeout: …

            Indicates that the shell call exceeded its configured time limit.

            • type: Literal["timeout"]

              The outcome type. Always timeout.

              • "timeout"

          • class OutputOutcomeExit: …

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

            • exit_code: int

              Exit code from the shell process.

            • type: Literal["exit"]

              The outcome type. Always exit.

              • "exit"

        • stderr: str

          The standard error output that was captured.

        • stdout: str

          The standard output that was captured.

        • created_by: Optional[str]

          The identifier of the actor that created the item.

      • status: Literal["in_progress", "completed", "incomplete"]

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: Literal["shell_call_output"]

        The type of the shell call output. Always shell_call_output.

        • "shell_call_output"

      • created_by: Optional[str]

        The identifier of the actor that created the item.

    • class ResponseApplyPatchToolCall: …

      A tool call that applies file diffs by creating, deleting, or updating files.

      • id: str

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

      • call_id: str

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

      • operation: Operation

        One of the create_file, delete_file, or update_file operations applied via apply_patch.

        • class OperationCreateFile: …

          Instruction describing how to create a file via the apply_patch tool.

          • diff: str

            Diff to apply.

          • path: str

            Path of the file to create.

          • type: Literal["create_file"]

            Create a new file with the provided diff.

            • "create_file"

        • class OperationDeleteFile: …

          Instruction describing how to delete a file via the apply_patch tool.

          • path: str

            Path of the file to delete.

          • type: Literal["delete_file"]

            Delete the specified file.

            • "delete_file"

        • class OperationUpdateFile: …

          Instruction describing how to update a file via the apply_patch tool.

          • diff: str

            Diff to apply.

          • path: str

            Path of the file to update.

          • type: Literal["update_file"]

            Update an existing file with the provided diff.

            • "update_file"

      • status: Literal["in_progress", "completed"]

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

        • "in_progress"

        • "completed"

      • type: Literal["apply_patch_call"]

        The type of the item. Always apply_patch_call.

        • "apply_patch_call"

      • created_by: Optional[str]

        The ID of the entity that created this tool call.

    • class ResponseApplyPatchToolCallOutput: …

      The output emitted by an apply patch tool call.

      • id: str

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

      • call_id: str

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

      • status: Literal["completed", "failed"]

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

        • "completed"

        • "failed"

      • type: Literal["apply_patch_call_output"]

        The type of the item. Always apply_patch_call_output.

        • "apply_patch_call_output"

      • created_by: Optional[str]

        The ID of the entity that created this tool call output.

      • output: Optional[str]

        Optional textual output returned by the apply patch tool.

    • class McpCall: …

      An invocation of a tool on an MCP server.

      • id: str

        The unique ID of the tool call.

      • arguments: str

        A JSON string of the arguments passed to the tool.

      • name: str

        The name of the tool that was run.

      • server_label: str

        The label of the MCP server running the tool.

      • type: Literal["mcp_call"]

        The type of the item. Always mcp_call.

        • "mcp_call"

      • approval_request_id: Optional[str]

        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[str]

        The error from the tool call, if any.

      • output: Optional[str]

        The output from the tool call.

      • status: Optional[Literal["in_progress", "completed", "incomplete", 2 more]]

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

        • "in_progress"

        • "completed"

        • "incomplete"

        • "calling"

        • "failed"

    • class McpListTools: …

      A list of tools available on an MCP server.

      • id: str

        The unique ID of the list.

      • server_label: str

        The label of the MCP server.

      • tools: List[McpListToolsTool]

        The tools available on the server.

        • input_schema: object

          The JSON schema describing the tool's input.

        • name: str

          The name of the tool.

        • annotations: Optional[object]

          Additional annotations about the tool.

        • description: Optional[str]

          The description of the tool.

      • type: Literal["mcp_list_tools"]

        The type of the item. Always mcp_list_tools.

        • "mcp_list_tools"

      • error: Optional[str]

        Error message if the server could not list tools.

    • class McpApprovalRequest: …

      A request for human approval of a tool invocation.

      • id: str

        The unique ID of the approval request.

      • arguments: str

        A JSON string of arguments for the tool.

      • name: str

        The name of the tool to run.

      • server_label: str

        The label of the MCP server making the request.

      • type: Literal["mcp_approval_request"]

        The type of the item. Always mcp_approval_request.

        • "mcp_approval_request"

    • class McpApprovalResponse: …

      A response to an MCP approval request.

      • id: str

        The unique ID of the approval response

      • approval_request_id: str

        The ID of the approval request being answered.

      • approve: bool

        Whether the request was approved.

      • type: Literal["mcp_approval_response"]

        The type of the item. Always mcp_approval_response.

        • "mcp_approval_response"

      • reason: Optional[str]

        Optional reason for the decision.

    • class ResponseCustomToolCall: …

      A call to a custom tool created by the model.

    • class ResponseCustomToolCallOutputItem: …

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

      • id: str

        The unique ID of the custom tool call output item.

      • status: Literal["in_progress", "completed", "incomplete"]

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • created_by: Optional[str]

        The identifier of the actor that created the item.

  • parallel_tool_calls: bool

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

  • temperature: Optional[float]

    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: ToolChoice

    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.

    • Literal["none", "auto", "required"]

      • "none"

      • "auto"

      • "required"

    • class ToolChoiceAllowed: …

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

      • mode: Literal["auto", "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: List[Dict[str, object]]

        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: Literal["allowed_tools"]

        Allowed tool configuration type. Always allowed_tools.

        • "allowed_tools"

    • class ToolChoiceTypes: …

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

      • type: Literal["file_search", "web_search_preview", "computer", 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"

    • class ToolChoiceFunction: …

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

      • name: str

        The name of the function to call.

      • type: Literal["function"]

        For function calling, the type is always function.

        • "function"

    • class ToolChoiceMcp: …

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

      • server_label: str

        The label of the MCP server to use.

      • type: Literal["mcp"]

        For MCP tools, the type is always mcp.

        • "mcp"

      • name: Optional[str]

        The name of the tool to call on the server.

    • class ToolChoiceCustom: …

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

      • name: str

        The name of the custom tool to call.

      • type: Literal["custom"]

        For custom tool calling, the type is always custom.

        • "custom"

    • class ToolChoiceApplyPatch: …

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

      • type: Literal["apply_patch"]

        The tool to call. Always apply_patch.

        • "apply_patch"

    • class ToolChoiceShell: …

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

      • type: Literal["shell"]

        The tool to call. Always shell.

        • "shell"

  • tools: List[Tool]

    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.

    • class FunctionTool: …

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

    • class FileSearchTool: …

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

    • class ComputerTool: …

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

    • class ComputerUsePreviewTool: …

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

    • class WebSearchTool: …

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

    • class Mcp: …

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

    • class CodeInterpreter: …

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

    • class ImageGeneration: …

      A tool that generates images using the GPT image models.

    • class LocalShell: …

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

    • class FunctionShellTool: …

      A tool that allows the model to execute shell commands.

    • class CustomTool: …

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

    • class NamespaceTool: …

      Groups function/custom tools under a shared namespace.

    • class ToolSearchTool: …

      Hosted or BYOT tool search configuration for deferred tools.

    • class WebSearchPreviewTool: …

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

    • class ApplyPatchTool: …

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

  • top_p: Optional[float]

    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[bool]

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

  • completed_at: Optional[float]

    Unix timestamp (in seconds) of when this Response was completed. Only present when the status is completed.

  • conversation: Optional[Conversation]

    The conversation that this response belonged to. Input items and output items from this response were automatically added to this conversation.

    • id: str

      The unique ID of the conversation that this response was associated with.

  • max_output_tokens: Optional[int]

    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[int]

    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.

  • previous_response_id: Optional[str]

    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: str

      The unique identifier of the prompt template to use.

    • variables: Optional[Dict[str, Variables]]

      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.

      • str

      • class ResponseInputText: …

        A text input to the model.

      • class ResponseInputImage: …

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

      • class ResponseInputFile: …

        A file input to the model.

    • version: Optional[str]

      Optional version of the prompt template.

  • prompt_cache_key: Optional[str]

    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[Literal["in_memory", "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[Literal["auto", "concise", "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[Literal["auto", "concise", "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[str]

    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[Literal["auto", "default", "flex", 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.

      • class ResponseFormatText: …

        Default response format. Used to generate text responses.

        • type: Literal["text"]

          The type of response format being defined. Always text.

          • "text"

      • class ResponseFormatTextJSONSchemaConfig: …

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

        • name: str

          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: Dict[str, object]

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

        • type: Literal["json_schema"]

          The type of response format being defined. Always json_schema.

          • "json_schema"

        • description: Optional[str]

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

        • strict: Optional[bool]

          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.

      • class ResponseFormatJSONObject: …

        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: Literal["json_object"]

          The type of response format being defined. Always json_object.

          • "json_object"

    • verbosity: Optional[Literal["low", "medium", "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[int]

    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[Literal["auto", "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: int

      The number of input tokens.

    • input_tokens_details: InputTokensDetails

      A detailed breakdown of the input tokens.

      • cached_tokens: int

        The number of tokens that were retrieved from the cache. More on prompt caching.

    • output_tokens: int

      The number of output tokens.

    • output_tokens_details: OutputTokensDetails

      A detailed breakdown of the output tokens.

      • reasoning_tokens: int

        The number of reasoning tokens.

    • total_tokens: int

      The total number of tokens used.

  • user: Optional[str]

    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

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
)
response = client.responses.cancel(
    "resp_677efb5139a88190b512bc3fef8e535d",
)
print(response.id)

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"
            }
          ],
          "text": "text",
          "type": "output_text",
          "logprobs": [
            {
              "token": "token",
              "bytes": [
                0
              ],
              "logprob": 0,
              "top_logprobs": [
                {
                  "token": "token",
                  "bytes": [
                    0
                  ],
                  "logprob": 0
                }
              ]
            }
          ]
        }
      ],
      "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"
}

Example

from openai import OpenAI
client = OpenAI()

response = client.responses.cancel("resp_123")
print(response)

Response

{
  "id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
  "object": "response",
  "created_at": 1741386163,
  "status": "cancelled",
  "background": true,
  "completed_at": null,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-4o-2024-08-06",
  "output": [
    {
      "type": "message",
      "id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
      "status": "in_progress",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "Silent circuits hum,  \nThoughts emerge in data streams—  \nDigital dawn breaks.",
          "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": null,
  "user": null,
  "metadata": {}
}