## Compact a response `beta.responses.compact(ResponseCompactParams**kwargs) -> BetaCompactedResponse` **post** `/responses/compact?beta=true` Compact a conversation. Returns a compacted response object. Learn when and how to compact long-running conversations in the [conversation state guide](https://platform.openai.com/docs/guides/conversation-state#managing-the-context-window). For ZDR-compatible compaction details, see [Compaction (advanced)](https://platform.openai.com/docs/guides/conversation-state#compaction-advanced). ### Parameters - `model: Union[Literal["gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna", 92 more], str, null]` Model ID used to generate the response, like `gpt-5` or `o3`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models) to browse and compare available models. - `Literal["gpt-5.6-sol", "gpt-5.6-terra", "gpt-5.6-luna", 92 more]` Model ID used to generate the response, like `gpt-5` or `o3`. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the [model guide](https://platform.openai.com/docs/models) to browse and compare available models. - `"gpt-5.6-sol"` - `"gpt-5.6-terra"` - `"gpt-5.6-luna"` - `"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"` - `"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"` - `str` - `input: Optional[Union[str, Iterable[BetaResponseInputItemParam], null]]` Text, image, or file inputs to the model, used to generate a response - `str` A text input to the model, equivalent to a text input with the `user` role. - `Iterable[BetaResponseInputItemParam]` A list of one or many input items to the model, containing different content types. - `class BetaEasyInputMessage: …` 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, BetaResponseInputMessageContentList]` 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[BetaResponseInputContent]` - `class BetaResponseInputText: …` 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"` - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputImage: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision). - `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. - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputFile: …` A file input to the model. - `type: Literal["input_file"]` The type of the input item. Always `input_file`. - `"input_file"` - `detail: Optional[Literal["auto", "low", "high"]]` The detail level of the file to be sent to the model. Use `auto` to let the system select the detail level; for GPT-5.6 and later models, `auto` uses high-quality rendering, which may increase input token usage. Use `low` for lower-cost rendering, or `high` to render the file at higher quality. Defaults to `auto`. - `"auto"` - `"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. - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `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: BetaResponseInputMessageContentList` A list of one or many input items to the model, containing different content types. - `class BetaResponseInputText: …` A text input to the model. - `class BetaResponseInputImage: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision). - `class BetaResponseInputFile: …` 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"` - `agent: Optional[MessageAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseOutputMessage: …` 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 BetaResponseOutputText: …` 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 BetaResponseOutputRefusal: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseFileSearchToolCall: …` The results of a file search tool call. See the [file search guide](https://platform.openai.com/docs/guides/tools-file-search) 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseComputerToolCall: …` A tool call to a computer use tool. See the [computer use guide](https://platform.openai.com/docs/guides/tools-computer-use) 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[BetaComputerAction]` A click action. - `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"` - `actions: Optional[BetaComputerActionList]` Flattened batched actions for `computer_use`. Each action includes an `type` discriminator and action-specific fields. - `class Click: …` A click action. - `class DoubleClick: …` A double click action. - `class Drag: …` A drag action. - `class Keypress: …` A collection of keypresses the model would like to perform. - `class Move: …` A mouse move action. - `class Screenshot: …` A screenshot action. - `class Scroll: …` A scroll action. - `class Type: …` An action to type in text. - `class Wait: …` A wait action. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class ComputerCallOutput: …` The output of a computer tool call. - `call_id: str` The ID of the computer tool call that produced the output. - `output: BetaResponseComputerToolCallOutputScreenshot` 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. - `agent: Optional[ComputerCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseFunctionWebSearch: …` The results of a web search tool call. See the [web search guide](https://platform.openai.com/docs/guides/tools-web-search) 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. - `type: Literal["search"]` The action type. - `"search"` - `queries: Optional[List[str]]` The search queries. - `query: Optional[str]` The search query. - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseFunctionToolCall: …` A tool call to run a function. See the [function calling guide](https://platform.openai.com/docs/guides/function-calling) 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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `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, BetaResponseFunctionCallOutputItemList]` Text, image, or file output of the function tool call. - `str` A JSON string of the output of the function tool call. - `List[BetaResponseFunctionCallOutputItem]` - `class BetaResponseInputTextContent: …` 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"` - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputImageContent: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision) - `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. - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputFileContent: …` A file input to the model. - `type: Literal["input_file"]` The type of the input item. Always `input_file`. - `"input_file"` - `detail: Optional[Literal["auto", "low", "high"]]` The detail level of the file to be sent to the model. Use `auto` to let the system select the detail level; for GPT-5.6 and later models, `auto` uses high-quality rendering, which may increase input token usage. Use `low` for lower-cost rendering, or `high` to render the file at higher quality. Defaults to `auto`. - `"auto"` - `"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. - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `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. - `agent: Optional[FunctionCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[FunctionCallOutputCaller]` The execution context that produced this tool call. - `class FunctionCallOutputCallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class FunctionCallOutputCallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `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 AgentMessage: …` A message routed between agents. - `author: str` The sending agent identity. - `content: List[AgentMessageContent]` Plaintext, image, or encrypted content sent between agents. - `class BetaResponseInputTextContent: …` A text input to the model. - `class BetaResponseInputImageContent: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision) - `class AgentMessageContentEncryptedContent: …` Opaque encrypted content that Responses API decrypts inside trusted model execution. - `encrypted_content: str` Opaque encrypted content. - `type: Literal["encrypted_content"]` The type of the input item. Always `encrypted_content`. - `"encrypted_content"` - `recipient: str` The destination agent identity. - `type: Literal["agent_message"]` The item type. Always `agent_message`. - `"agent_message"` - `id: Optional[str]` The unique ID of this agent message item. - `agent: Optional[AgentMessageAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class MultiAgentCall: …` - `action: Literal["spawn_agent", "interrupt_agent", "list_agents", 3 more]` The multi-agent action that was executed. - `"spawn_agent"` - `"interrupt_agent"` - `"list_agents"` - `"send_message"` - `"followup_task"` - `"wait_agent"` - `arguments: str` The action arguments as a JSON string. - `call_id: str` The unique ID linking this call to its output. - `type: Literal["multi_agent_call"]` The item type. Always `multi_agent_call`. - `"multi_agent_call"` - `id: Optional[str]` The unique ID of this multi-agent call. - `agent: Optional[MultiAgentCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class MultiAgentCallOutput: …` - `action: Literal["spawn_agent", "interrupt_agent", "list_agents", 3 more]` The multi-agent action that produced this result. - `"spawn_agent"` - `"interrupt_agent"` - `"list_agents"` - `"send_message"` - `"followup_task"` - `"wait_agent"` - `call_id: str` The unique ID of the multi-agent call. - `output: List[MultiAgentCallOutputOutput]` Text output returned by the multi-agent action. - `text: str` The text content. - `type: Literal["output_text"]` The content type. Always `output_text`. - `"output_text"` - `annotations: Optional[List[MultiAgentCallOutputOutputAnnotation]]` Citations associated with the text content. - `class MultiAgentCallOutputOutputAnnotationFileCitation: …` - `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 citation type. Always `file_citation`. - `"file_citation"` - `class MultiAgentCallOutputOutputAnnotationURLCitation: …` - `end_index: int` The index of the last character of the citation in the message. - `start_index: int` The index of the first character of the citation in the message. - `title: str` The title of the cited resource. - `type: Literal["url_citation"]` The citation type. Always `url_citation`. - `"url_citation"` - `url: str` The URL of the cited resource. - `class MultiAgentCallOutputOutputAnnotationContainerFileCitation: …` - `container_id: str` The ID of the container. - `end_index: int` The index of the last character of the citation in the message. - `file_id: str` The ID of the container file. - `filename: str` The filename of the container file cited. - `start_index: int` The index of the first character of the citation in the message. - `type: Literal["container_file_citation"]` The citation type. Always `container_file_citation`. - `"container_file_citation"` - `type: Literal["multi_agent_call_output"]` The item type. Always `multi_agent_call_output`. - `"multi_agent_call_output"` - `id: Optional[str]` The unique ID of this multi-agent call output. - `agent: Optional[MultiAgentCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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. - `agent: Optional[ToolSearchCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseToolSearchOutputItemParam: …` - `tools: List[BetaTool]` The loaded tool definitions returned by the tool search output. - `class BetaFunctionTool: …` Defines a function in your own code the model can choose to call. Learn more about [function calling](https://platform.openai.com/docs/guides/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 strict parameter validation is enforced for this function tool. - `type: Literal["function"]` The type of the function tool. Always `function`. - `"function"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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. - `output_schema: Optional[Dict[str, object]]` A JSON schema object describing the JSON value encoded in string outputs for this function. - `class BetaFileSearchTool: …` A tool that searches for relevant content from uploaded files. Learn more about the [file search tool](https://platform.openai.com/docs/guides/tools-file-search). - `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 FiltersComparisonFilter: …` 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 FiltersCompoundFilter: …` Combine multiple filters using `and` or `or`. - `filters: List[FiltersCompoundFilterFilter]` Array of filters to combine. Items can be `ComparisonFilter` or `CompoundFilter`. - `class FiltersCompoundFilterFilterComparisonFilter: …` 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` - `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 BetaComputerTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `type: Literal["computer"]` The type of the computer tool. Always `computer`. - `"computer"` - `class BetaComputerUsePreviewTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `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 BetaWebSearchTool: …` Search the Internet for sources related to the prompt. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `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](https://en.wikipedia.org/wiki/ISO_3166-1) 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](https://timeapi.io/documentation/iana-timezones) 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](https://platform.openai.com/docs/guides/tools-remote-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_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-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`, `connector_id`, or `tunnel_id` must be provided. Learn more about service connectors [here](https://platform.openai.com/docs/guides/tools-remote-mcp#connectors). 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`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-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`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-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`, `connector_id`, or `tunnel_id` must be provided. - `tunnel_id: Optional[str]` The Secure MCP Tunnel ID to use instead of a direct server URL. One of `server_url`, `connector_id`, or `tunnel_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 BetaContainerNetworkPolicyDisabled: …` - `type: Literal["disabled"]` Disable outbound network access. Always `disabled`. - `"disabled"` - `class BetaContainerNetworkPolicyAllowlist: …` - `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[BetaContainerNetworkPolicyDomainSecret]]` 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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `class ProgrammaticToolCalling: …` - `type: Literal["programmatic_tool_calling"]` The type of the tool. Always `programmatic_tool_calling`. - `"programmatic_tool_calling"` - `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[Union[str, Literal["1024x1024", "1024x1536", "1536x1024", "auto"], null]]` 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`. - `str` - `Literal["1024x1024", "1024x1536", "1536x1024", "auto"]` 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`. - `"1024x1024"` - `"1024x1536"` - `"1536x1024"` - `"auto"` - `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 BetaFunctionShellTool: …` A tool that allows the model to execute shell commands. - `type: Literal["shell"]` The type of the shell tool. Always `shell`. - `"shell"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `environment: Optional[Environment]` - `class BetaContainerAuto: …` - `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 BetaContainerNetworkPolicyDisabled: …` - `class BetaContainerNetworkPolicyAllowlist: …` - `skills: Optional[List[Skill]]` An optional list of skills referenced by id or inline data. - `class BetaSkillReference: …` - `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 BetaInlineSkill: …` - `description: str` The description of the skill. - `name: str` The name of the skill. - `source: BetaInlineSkillSource` 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 BetaLocalEnvironment: …` - `type: Literal["local"]` Use a local computer environment. - `"local"` - `skills: Optional[List[BetaLocalSkill]]` 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 BetaContainerReference: …` - `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 BetaCustomTool: …` A custom tool that processes input using a specified format. Learn more about [custom tools](https://platform.openai.com/docs/guides/function-calling#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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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[Format]` The input format for the custom tool. Default is unconstrained text. - `class FormatText: …` Unconstrained free-form text. - `type: Literal["text"]` Unconstrained text format. Always `text`. - `"text"` - `class FormatGrammar: …` 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 BetaNamespaceTool: …` 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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `defer_loading: Optional[bool]` Whether this function should be deferred and discovered via tool search. - `description: Optional[str]` - `output_schema: Optional[Dict[str, object]]` A JSON Schema describing the JSON value encoded in string outputs for this function tool. This does not describe content-array outputs. - `parameters: Optional[object]` - `strict: Optional[bool]` Whether to enforce strict parameter validation. If omitted, Responses attempts to use strict validation when the schema is compatible, and falls back to non-strict validation otherwise. - `class BetaCustomTool: …` A custom tool that processes input using a specified format. Learn more about [custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) - `type: Literal["namespace"]` The type of the tool. Always `namespace`. - `"namespace"` - `class BetaToolSearchTool: …` 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 BetaWebSearchPreviewTool: …` This tool searches the web for relevant results to use in a response. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `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](https://en.wikipedia.org/wiki/ISO_3166-1) 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](https://timeapi.io/documentation/iana-timezones) of the user, e.g. `America/Los_Angeles`. - `class BetaApplyPatchTool: …` 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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 AdditionalTools: …` - `role: Literal["developer"]` The role that provided the additional tools. Only `developer` is supported. - `"developer"` - `tools: List[BetaTool]` A list of additional tools made available at this item. - `class BetaFunctionTool: …` Defines a function in your own code the model can choose to call. Learn more about [function calling](https://platform.openai.com/docs/guides/function-calling). - `class BetaFileSearchTool: …` A tool that searches for relevant content from uploaded files. Learn more about the [file search tool](https://platform.openai.com/docs/guides/tools-file-search). - `class BetaComputerTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `class BetaComputerUsePreviewTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `class BetaWebSearchTool: …` Search the Internet for sources related to the prompt. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `class Mcp: …` Give the model access to additional tools via remote Model Context Protocol (MCP) servers. [Learn more about MCP](https://platform.openai.com/docs/guides/tools-remote-mcp). - `class CodeInterpreter: …` A tool that runs Python code to help generate a response to a prompt. - `class ProgrammaticToolCalling: …` - `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 BetaFunctionShellTool: …` A tool that allows the model to execute shell commands. - `class BetaCustomTool: …` A custom tool that processes input using a specified format. Learn more about [custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) - `class BetaNamespaceTool: …` Groups function/custom tools under a shared namespace. - `class BetaToolSearchTool: …` Hosted or BYOT tool search configuration for deferred tools. - `class BetaWebSearchPreviewTool: …` This tool searches the web for relevant results to use in a response. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `class BetaApplyPatchTool: …` Allows the assistant to create, delete, or update files using unified diffs. - `type: Literal["additional_tools"]` The item type. Always `additional_tools`. - `"additional_tools"` - `id: Optional[str]` The unique ID of this additional tools item. - `agent: Optional[AdditionalToolsAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseReasoningItem: …` 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](https://platform.openai.com/docs/guides/conversation-state). - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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. This is populated by default for reasoning items returned by `POST /v1/responses` and WebSocket `response.create` requests. - `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 BetaResponseCompactionItemParam: …` A compaction item generated by the [`v1/responses/compact` API](https://platform.openai.com/docs/api-reference/responses/compact). - `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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this 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"` - `agent: Optional[ImageGenerationCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseCodeInterpreterToolCall: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[LocalShellCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[LocalShellCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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. - `agent: Optional[ShellCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[ShellCallCaller]` The execution context that produced this tool call. - `class ShellCallCallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class ShellCallCallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `environment: Optional[ShellCallEnvironment]` The environment to execute the shell commands in. - `class BetaLocalEnvironment: …` - `class BetaContainerReference: …` - `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[BetaResponseFunctionShellCallOutputContent]` 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. - `agent: Optional[ShellCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[ShellCallOutputCaller]` The execution context that produced this tool call. - `class ShellCallOutputCallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class ShellCallOutputCallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `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. - `agent: Optional[ApplyPatchCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[ApplyPatchCallCaller]` The execution context that produced this tool call. - `class ApplyPatchCallCallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class ApplyPatchCallCallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `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. - `agent: Optional[ApplyPatchCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[ApplyPatchCallOutputCaller]` The execution context that produced this tool call. - `class ApplyPatchCallOutputCallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class ApplyPatchCallOutputCallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `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"` - `agent: Optional[McpListToolsAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[McpApprovalRequestAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 - `agent: Optional[McpApprovalResponseAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[McpCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseCustomToolCallOutput: …` 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 BetaResponseInputText: …` A text input to the model. - `class BetaResponseInputImage: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision). - `class BetaResponseInputFile: …` 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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `class BetaResponseCustomToolCall: …` 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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `namespace: Optional[str]` The namespace of the custom tool being called. - `class CompactionTrigger: …` Compacts the current context. Must be the final input item. - `type: Literal["compaction_trigger"]` The type of the item. Always `compaction_trigger`. - `"compaction_trigger"` - `agent: Optional[CompactionTriggerAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class ItemReference: …` An internal identifier for an item to reference. - `id: str` The ID of the item to reference. - `agent: Optional[ItemReferenceAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `type: Optional[Literal["item_reference"]]` The type of item to reference. Always `item_reference`. - `"item_reference"` - `class Program: …` - `id: str` The unique ID of this program item. - `call_id: str` The stable call ID of the program item. - `code: str` The JavaScript source executed by programmatic tool calling. - `fingerprint: str` Opaque program replay fingerprint that must be round-tripped. - `type: Literal["program"]` The item type. Always `program`. - `"program"` - `agent: Optional[ProgramAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class ProgramOutput: …` - `id: str` The unique ID of this program output item. - `call_id: str` The call ID of the program item. - `result: str` The result produced by the program item. - `status: Literal["completed", "incomplete"]` The terminal status of the program output. - `"completed"` - `"incomplete"` - `type: Literal["program_output"]` The item type. Always `program_output`. - `"program_output"` - `agent: Optional[ProgramOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `instructions: Optional[str]` A system (or developer) message inserted into the model's context. When used 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. - `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](https://platform.openai.com/docs/guides/conversation-state). Cannot be used in conjunction with `conversation`. - `prompt_cache_key: Optional[str]` A key to use when reading from or writing to the prompt cache. - `prompt_cache_options: Optional[PromptCacheOptions]` Options for prompt caching. Supported for `gpt-5.6` and later models. By default, OpenAI automatically chooses one implicit cache breakpoint. You can add explicit breakpoints to content blocks with `prompt_cache_breakpoint`. Each request can write up to four breakpoints. For cache matching, OpenAI considers up to the latest 80 breakpoints in the conversation, without a content-block lookback limit. Set `mode` to `explicit` to disable the implicit breakpoint. The `ttl` defaults to `30m`, which is currently the only supported value. See the [prompt caching guide](https://platform.openai.com/docs/guides/prompt-caching) for current details. - `mode: Optional[Literal["implicit", "explicit"]]` Controls whether OpenAI automatically creates an implicit cache breakpoint. Defaults to `implicit`. With `implicit`, OpenAI creates one implicit breakpoint and writes up to the latest three explicit breakpoints in the request. With `explicit`, OpenAI does not create an implicit breakpoint and writes up to the latest four explicit breakpoints. If there are no explicit breakpoints, the request does not use prompt caching. - `"implicit"` - `"explicit"` - `ttl: Optional[Literal["30m"]]` The minimum lifetime applied to every implicit and explicit cache breakpoint written by the request. Defaults to `30m`, which is currently the only supported value. The backend may retain cache entries for longer. - `"30m"` - `prompt_cache_retention: Optional[Literal["in_memory", "24h"]]` How long to retain a prompt cache entry created by this request. - `"in_memory"` - `"24h"` - `service_tier: Optional[Literal["auto", "default", "flex", "priority"]]` The service tier to use for this request. - `"auto"` - `"default"` - `"flex"` - `"priority"` - `betas: Optional[List[Literal["responses_multi_agent=v1"]]]` - `"responses_multi_agent=v1"` ### Returns - `class BetaCompactedResponse: …` - `id: str` The unique identifier for the compacted response. - `created_at: int` Unix timestamp (in seconds) when the compacted conversation was created. - `object: Literal["response.compaction"]` The object type. Always `response.compaction`. - `"response.compaction"` - `output: List[BetaResponseOutputItem]` The compacted list of output items. This is a list of all user messages, followed by a single compaction item. - `class BetaResponseOutputMessage: …` 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 BetaResponseOutputText: …` 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 BetaResponseOutputRefusal: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseFileSearchToolCall: …` The results of a file search tool call. See the [file search guide](https://platform.openai.com/docs/guides/tools-file-search) 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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 BetaResponseFunctionToolCall: …` A tool call to run a function. See the [function calling guide](https://platform.openai.com/docs/guides/function-calling) 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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `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 BetaResponseFunctionToolCallOutputItem: …` - `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 BetaResponseInputText: …` 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"` - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputImage: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision). - `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. - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputFile: …` A file input to the model. - `type: Literal["input_file"]` The type of the input item. Always `input_file`. - `"input_file"` - `detail: Optional[Literal["auto", "low", "high"]]` The detail level of the file to be sent to the model. Use `auto` to let the system select the detail level; for GPT-5.6 and later models, `auto` uses high-quality rendering, which may increase input token usage. Use `low` for lower-cost rendering, or `high` to render the file at higher quality. Defaults to `auto`. - `"auto"` - `"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. - `prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` The caller type. Always `direct`. - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` The caller type. Always `program`. - `"program"` - `created_by: Optional[str]` The identifier of the actor that created the item. - `class AgentMessage: …` - `id: str` The unique ID of the agent message. - `author: str` The sending agent identity. - `content: List[AgentMessageContent]` Encrypted content sent between agents. - `class BetaResponseInputText: …` A text input to the model. - `class BetaResponseOutputText: …` A text output from the model. - `class AgentMessageContentText: …` A text content. - `text: str` - `type: Literal["text"]` - `"text"` - `class AgentMessageContentSummaryText: …` A summary text from the model. - `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"` - `class AgentMessageContentReasoningText: …` Reasoning text from the model. - `text: str` The reasoning text from the model. - `type: Literal["reasoning_text"]` The type of the reasoning text. Always `reasoning_text`. - `"reasoning_text"` - `class BetaResponseOutputRefusal: …` A refusal from the model. - `class BetaResponseInputImage: …` An image input to the model. Learn about [image inputs](https://platform.openai.com/docs/guides/vision). - `class AgentMessageContentComputerScreenshot: …` A screenshot of a computer. - `detail: Literal["low", "high", "auto", "original"]` The detail level of the screenshot 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 identifier of an uploaded file that contains the screenshot. - `image_url: Optional[str]` The URL of the screenshot image. - `type: Literal["computer_screenshot"]` Specifies the event type. For a computer screenshot, this property is always set to `computer_screenshot`. - `"computer_screenshot"` - `prompt_cache_breakpoint: Optional[AgentMessageContentComputerScreenshotPromptCacheBreakpoint]` Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. - `mode: Literal["explicit"]` The breakpoint mode. Always `explicit`. - `"explicit"` - `class BetaResponseInputFile: …` A file input to the model. - `class AgentMessageContentEncryptedContent: …` Opaque encrypted content that Responses API decrypts inside trusted model execution. - `encrypted_content: str` Opaque encrypted content. - `type: Literal["encrypted_content"]` The type of the input item. Always `encrypted_content`. - `"encrypted_content"` - `recipient: str` The destination agent identity. - `type: Literal["agent_message"]` The type of the item. Always `agent_message`. - `"agent_message"` - `agent: Optional[AgentMessageAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class MultiAgentCall: …` - `id: str` The unique ID of the multi-agent call item. - `action: Literal["spawn_agent", "interrupt_agent", "list_agents", 3 more]` The multi-agent action to execute. - `"spawn_agent"` - `"interrupt_agent"` - `"list_agents"` - `"send_message"` - `"followup_task"` - `"wait_agent"` - `arguments: str` The JSON string of arguments generated for the action. - `call_id: str` The unique ID linking this call to its output. - `type: Literal["multi_agent_call"]` The type of the multi-agent call. Always `multi_agent_call`. - `"multi_agent_call"` - `agent: Optional[MultiAgentCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class MultiAgentCallOutput: …` - `id: str` The unique ID of the multi-agent call output item. - `action: Literal["spawn_agent", "interrupt_agent", "list_agents", 3 more]` The multi-agent action that produced this result. - `"spawn_agent"` - `"interrupt_agent"` - `"list_agents"` - `"send_message"` - `"followup_task"` - `"wait_agent"` - `call_id: str` The unique ID of the multi-agent call. - `output: List[BetaResponseOutputText]` Text output returned by the multi-agent action. - `annotations: List[Annotation]` The annotations of the text output. - `text: str` The text output from the model. - `type: Literal["output_text"]` The type of the output text. Always `output_text`. - `logprobs: Optional[List[Logprob]]` - `type: Literal["multi_agent_call_output"]` The type of the multi-agent result. Always `multi_agent_call_output`. - `"multi_agent_call_output"` - `agent: Optional[MultiAgentCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseFunctionWebSearch: …` The results of a web search tool call. See the [web search guide](https://platform.openai.com/docs/guides/tools-web-search) 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. - `type: Literal["search"]` The action type. - `"search"` - `queries: Optional[List[str]]` The search queries. - `query: Optional[str]` The search query. - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseComputerToolCall: …` A tool call to a computer use tool. See the [computer use guide](https://platform.openai.com/docs/guides/tools-computer-use) 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[BetaComputerAction]` A click action. - `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"` - `actions: Optional[BetaComputerActionList]` Flattened batched actions for `computer_use`. Each action includes an `type` discriminator and action-specific fields. - `class Click: …` A click action. - `class DoubleClick: …` A double click action. - `class Drag: …` A drag action. - `class Keypress: …` A collection of keypresses the model would like to perform. - `class Move: …` A mouse move action. - `class Screenshot: …` A screenshot action. - `class Scroll: …` A scroll action. - `class Type: …` An action to type in text. - `class Wait: …` A wait action. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseComputerToolCallOutputItem: …` - `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: BetaResponseComputerToolCallOutputScreenshot` 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. - `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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `created_by: Optional[str]` The identifier of the actor that created the item. - `class BetaResponseReasoningItem: …` 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](https://platform.openai.com/docs/guides/conversation-state). - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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. This is populated by default for reasoning items returned by `POST /v1/responses` and WebSocket `response.create` requests. - `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 Program: …` - `id: str` The unique ID of the program item. - `call_id: str` The stable call ID of the program item. - `code: str` The JavaScript source executed by programmatic tool calling. - `fingerprint: str` Opaque program replay fingerprint that must be round-tripped. - `type: Literal["program"]` The type of the item. Always `program`. - `"program"` - `agent: Optional[ProgramAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class ProgramOutput: …` - `id: str` The unique ID of the program output item. - `call_id: str` The call ID of the program item. - `result: str` The result produced by the program item. - `status: Literal["completed", "incomplete"]` The terminal status of the program output item. - `"completed"` - `"incomplete"` - `type: Literal["program_output"]` The type of the item. Always `program_output`. - `"program_output"` - `agent: Optional[ProgramOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseToolSearchCall: …` - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `created_by: Optional[str]` The identifier of the actor that created the item. - `class BetaResponseToolSearchOutputItem: …` - `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[BetaTool]` The loaded tool definitions returned by tool search. - `class BetaFunctionTool: …` Defines a function in your own code the model can choose to call. Learn more about [function calling](https://platform.openai.com/docs/guides/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 strict parameter validation is enforced for this function tool. - `type: Literal["function"]` The type of the function tool. Always `function`. - `"function"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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. - `output_schema: Optional[Dict[str, object]]` A JSON schema object describing the JSON value encoded in string outputs for this function. - `class BetaFileSearchTool: …` A tool that searches for relevant content from uploaded files. Learn more about the [file search tool](https://platform.openai.com/docs/guides/tools-file-search). - `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 FiltersComparisonFilter: …` 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 FiltersCompoundFilter: …` Combine multiple filters using `and` or `or`. - `filters: List[FiltersCompoundFilterFilter]` Array of filters to combine. Items can be `ComparisonFilter` or `CompoundFilter`. - `class FiltersCompoundFilterFilterComparisonFilter: …` 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` - `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 BetaComputerTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `type: Literal["computer"]` The type of the computer tool. Always `computer`. - `"computer"` - `class BetaComputerUsePreviewTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `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 BetaWebSearchTool: …` Search the Internet for sources related to the prompt. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `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](https://en.wikipedia.org/wiki/ISO_3166-1) 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](https://timeapi.io/documentation/iana-timezones) 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](https://platform.openai.com/docs/guides/tools-remote-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_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-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`, `connector_id`, or `tunnel_id` must be provided. Learn more about service connectors [here](https://platform.openai.com/docs/guides/tools-remote-mcp#connectors). 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`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-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`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-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`, `connector_id`, or `tunnel_id` must be provided. - `tunnel_id: Optional[str]` The Secure MCP Tunnel ID to use instead of a direct server URL. One of `server_url`, `connector_id`, or `tunnel_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 BetaContainerNetworkPolicyDisabled: …` - `type: Literal["disabled"]` Disable outbound network access. Always `disabled`. - `"disabled"` - `class BetaContainerNetworkPolicyAllowlist: …` - `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[BetaContainerNetworkPolicyDomainSecret]]` 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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `class ProgrammaticToolCalling: …` - `type: Literal["programmatic_tool_calling"]` The type of the tool. Always `programmatic_tool_calling`. - `"programmatic_tool_calling"` - `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[Union[str, Literal["1024x1024", "1024x1536", "1536x1024", "auto"], null]]` 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`. - `str` - `Literal["1024x1024", "1024x1536", "1536x1024", "auto"]` 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`. - `"1024x1024"` - `"1024x1536"` - `"1536x1024"` - `"auto"` - `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 BetaFunctionShellTool: …` A tool that allows the model to execute shell commands. - `type: Literal["shell"]` The type of the shell tool. Always `shell`. - `"shell"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `environment: Optional[Environment]` - `class BetaContainerAuto: …` - `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 BetaContainerNetworkPolicyDisabled: …` - `class BetaContainerNetworkPolicyAllowlist: …` - `skills: Optional[List[Skill]]` An optional list of skills referenced by id or inline data. - `class BetaSkillReference: …` - `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 BetaInlineSkill: …` - `description: str` The description of the skill. - `name: str` The name of the skill. - `source: BetaInlineSkillSource` 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 BetaLocalEnvironment: …` - `type: Literal["local"]` Use a local computer environment. - `"local"` - `skills: Optional[List[BetaLocalSkill]]` 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 BetaContainerReference: …` - `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 BetaCustomTool: …` A custom tool that processes input using a specified format. Learn more about [custom tools](https://platform.openai.com/docs/guides/function-calling#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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `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[Format]` The input format for the custom tool. Default is unconstrained text. - `class FormatText: …` Unconstrained free-form text. - `type: Literal["text"]` Unconstrained text format. Always `text`. - `"text"` - `class FormatGrammar: …` 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 BetaNamespaceTool: …` 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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `defer_loading: Optional[bool]` Whether this function should be deferred and discovered via tool search. - `description: Optional[str]` - `output_schema: Optional[Dict[str, object]]` A JSON Schema describing the JSON value encoded in string outputs for this function tool. This does not describe content-array outputs. - `parameters: Optional[object]` - `strict: Optional[bool]` Whether to enforce strict parameter validation. If omitted, Responses attempts to use strict validation when the schema is compatible, and falls back to non-strict validation otherwise. - `class BetaCustomTool: …` A custom tool that processes input using a specified format. Learn more about [custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) - `type: Literal["namespace"]` The type of the tool. Always `namespace`. - `"namespace"` - `class BetaToolSearchTool: …` 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 BetaWebSearchPreviewTool: …` This tool searches the web for relevant results to use in a response. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `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](https://en.wikipedia.org/wiki/ISO_3166-1) 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](https://timeapi.io/documentation/iana-timezones) of the user, e.g. `America/Los_Angeles`. - `class BetaApplyPatchTool: …` 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"` - `allowed_callers: Optional[List[Literal["direct", "programmatic"]]]` The tool invocation context(s). - `"direct"` - `"programmatic"` - `type: Literal["tool_search_output"]` The type of the item. Always `tool_search_output`. - `"tool_search_output"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `created_by: Optional[str]` The identifier of the actor that created the item. - `class AdditionalTools: …` - `id: str` The unique ID of the additional tools item. - `role: Literal["unknown", "user", "assistant", 5 more]` The role that provided the additional tools. - `"unknown"` - `"user"` - `"assistant"` - `"system"` - `"critic"` - `"discriminator"` - `"developer"` - `"tool"` - `tools: List[BetaTool]` The additional tool definitions made available at this item. - `class BetaFunctionTool: …` Defines a function in your own code the model can choose to call. Learn more about [function calling](https://platform.openai.com/docs/guides/function-calling). - `class BetaFileSearchTool: …` A tool that searches for relevant content from uploaded files. Learn more about the [file search tool](https://platform.openai.com/docs/guides/tools-file-search). - `class BetaComputerTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `class BetaComputerUsePreviewTool: …` A tool that controls a virtual computer. Learn more about the [computer tool](https://platform.openai.com/docs/guides/tools-computer-use). - `class BetaWebSearchTool: …` Search the Internet for sources related to the prompt. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `class Mcp: …` Give the model access to additional tools via remote Model Context Protocol (MCP) servers. [Learn more about MCP](https://platform.openai.com/docs/guides/tools-remote-mcp). - `class CodeInterpreter: …` A tool that runs Python code to help generate a response to a prompt. - `class ProgrammaticToolCalling: …` - `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 BetaFunctionShellTool: …` A tool that allows the model to execute shell commands. - `class BetaCustomTool: …` A custom tool that processes input using a specified format. Learn more about [custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) - `class BetaNamespaceTool: …` Groups function/custom tools under a shared namespace. - `class BetaToolSearchTool: …` Hosted or BYOT tool search configuration for deferred tools. - `class BetaWebSearchPreviewTool: …` This tool searches the web for relevant results to use in a response. Learn more about the [web search tool](https://platform.openai.com/docs/guides/tools-web-search). - `class BetaApplyPatchTool: …` Allows the assistant to create, delete, or update files using unified diffs. - `type: Literal["additional_tools"]` The type of the item. Always `additional_tools`. - `"additional_tools"` - `agent: Optional[AdditionalToolsAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseCompactionItem: …` A compaction item generated by the [`v1/responses/compact` API](https://platform.openai.com/docs/api-reference/responses/compact). - `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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[ImageGenerationCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `class BetaResponseCodeInterpreterToolCall: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[LocalShellCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[LocalShellCallOutputAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `status: Optional[Literal["in_progress", "completed", "incomplete"]]` The status of the item. One of `in_progress`, `completed`, or `incomplete`. - `"in_progress"` - `"completed"` - `"incomplete"` - `class BetaResponseFunctionShellToolCall: …` 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 BetaResponseLocalEnvironment: …` Represents the use of a local environment to perform shell actions. - `type: Literal["local"]` The environment type. Always `local`. - `"local"` - `class BetaResponseContainerReference: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `created_by: Optional[str]` The ID of the entity that created this tool call. - `class BetaResponseFunctionShellToolCallOutput: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `created_by: Optional[str]` The identifier of the actor that created the item. - `class BetaResponseApplyPatchToolCall: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `created_by: Optional[str]` The ID of the entity that created this tool call. - `class BetaResponseApplyPatchToolCallOutput: …` 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"` - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `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"` - `agent: Optional[McpCallAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[McpListToolsAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[McpApprovalRequestAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `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"` - `agent: Optional[McpApprovalResponseAgent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `reason: Optional[str]` Optional reason for the decision. - `class BetaResponseCustomToolCall: …` 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. - `agent: Optional[Agent]` The agent that produced this item. - `agent_name: str` The canonical name of the agent that produced this item. - `caller: Optional[Caller]` The execution context that produced this tool call. - `class CallerDirect: …` - `type: Literal["direct"]` - `"direct"` - `class CallerProgram: …` - `caller_id: str` The call ID of the program item that produced this tool call. - `type: Literal["program"]` - `"program"` - `namespace: Optional[str]` The namespace of the custom tool being called. - `class BetaResponseCustomToolCallOutputItem: …` 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. - `usage: BetaResponseUsage` Token accounting for the compaction pass, including cached, reasoning, and total tokens. - `input_tokens: int` The number of input tokens. - `input_tokens_details: InputTokensDetails` A detailed breakdown of the input tokens. - `cache_write_tokens: int` The number of input tokens that were written to the cache. - `cached_tokens: int` The number of tokens that were retrieved from the cache. [More on prompt caching](https://platform.openai.com/docs/guides/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. ### Example ```python import os from openai import OpenAI client = OpenAI( api_key=os.environ.get("OPENAI_API_KEY"), # This is the default and can be omitted ) beta_compacted_response = client.beta.responses.compact( model="gpt-5.6-sol", ) print(beta_compacted_response.id) ``` #### Response ```json { "id": "id", "created_at": 0, "object": "response.compaction", "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", "agent": { "agent_name": "agent_name" }, "phase": "commentary" } ], "usage": { "input_tokens": 0, "input_tokens_details": { "cache_write_tokens": 0, "cached_tokens": 0 }, "output_tokens": 0, "output_tokens_details": { "reasoning_tokens": 0 }, "total_tokens": 0 } } ``` ### Example ```python from openai import OpenAI client = OpenAI() compacted_response = client.responses.compact( model="gpt-5.1-codex-max", input=[ { "role": "user", "content": "Create a simple landing page for a dog petting cafe.", }, # All items returned from previous requests are included here, like reasoning, message, function call, etc. { "id": "msg_001", "type": "message", "status": "completed", "content": [ { "type": "output_text", "annotations": [], "logprobs": [], "text": "Below is a single file, ready-to-use landing page for a dog petting café:...", }, ], "role": "assistant", }, ] ) # Pass the compacted_response.output as input to the next request print(compacted_response) ``` #### Response ```json { "id": "resp_001", "object": "response.compaction", "created_at": 1764967971, "output": [ { "id": "msg_000", "type": "message", "status": "completed", "content": [ { "type": "input_text", "text": "Create a simple landing page for a dog petting cafe." } ], "role": "user" }, { "id": "cmp_001", "type": "compaction", "encrypted_content": "gAAAAABpM0Yj-...=" } ], "usage": { "input_tokens": 139, "input_tokens_details": { "cached_tokens": 0, "cache_write_tokens": 0 }, "output_tokens": 438, "output_tokens_details": { "reasoning_tokens": 64 }, "total_tokens": 577 } } ```