Responses

Create a model response

$ openai responses create

post /responses

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

Parameters

• --background: optional boolean

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

• --context-management: optional array of object { type, compact_threshold }

  Context management configuration for this request.

• --conversation: optional string or ResponseConversationParam

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

• --include: optional array of ResponseIncludable

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

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

• --input: optional string or ResponseInput

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

  Learn more:

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

• --instructions: optional string

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

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

• --max-output-tokens: optional number

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

• --max-tool-calls: optional number

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

• --metadata: optional map[string]

  Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

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

• --model: optional string or ChatModel or "o1-pro" or "o1-pro-2025-03-19" or "o3-pro" or 11 more

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

• --moderation: optional object { model }

  Configuration for running moderation on the input and output of this response.

• --parallel-tool-calls: optional boolean

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

• --previous-response-id: optional string

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

• --prompt: optional object { id, variables, version }

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

• --prompt-cache-key: optional string

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

• --prompt-cache-retention: optional "in_memory" or "24h"

  The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more. For gpt-5.5, gpt-5.5-pro, and future models, only 24h is supported.

  For older models that support both in_memory and 24h, the default depends on your organization's data retention policy:

  • Organizations without ZDR enabled default to 24h.
  • Organizations with ZDR enabled default to in_memory when prompt_cache_retention is not specified.

• --reasoning: optional object { context, effort, generate_summary, summary }

  gpt-5 and o-series models only

  Configuration options for reasoning models.

• --safety-identifier: optional string

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

• --service-tier: optional "auto" or "default" or "flex" or 2 more

  Specifies the processing type used for serving the request.

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

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

• --store: optional boolean

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

• --stream-options: optional object { include_obfuscation }

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

• --temperature: optional number

  What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.

• --text: optional object { format, verbosity }

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

  • Text inputs and outputs
  • Structured Outputs

• --tool-choice: optional ToolChoiceOptions or ToolChoiceAllowed or ToolChoiceTypes or 5 more

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

• --tool: optional array of Tool

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

  We support the following categories of tools:

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

• --top-logprobs: optional number

  An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested.

• --top-p: optional number

  An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

  We generally recommend altering this or temperature but not both.

• --truncation: optional "auto" or "disabled"

  The truncation strategy to use for the model response.

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

• --user: optional string

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

Returns

• response: object { id, created_at, error, 30 more }

  • id: string

    Unique identifier for this Response.

  • created_at: number

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

  • error: object { code, message }

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

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

      The error code for the response.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

      • "vector_store_timeout"

      • "invalid_image"

      • "invalid_image_format"

      • "invalid_base64_image"

      • "invalid_image_url"

      • "image_too_large"

      • "image_too_small"

      • "image_parse_error"

      • "image_content_policy_violation"

      • "invalid_image_mode"

      • "image_file_too_large"

      • "unsupported_image_media_type"

      • "empty_image_file"

      • "failed_to_download_image"

      • "image_file_not_found"

    • message: string

      A human-readable description of the error.

  • incomplete_details: object { reason }

    Details about why the response is incomplete.

    • reason: optional "max_output_tokens" or "content_filter"

      The reason why the response is incomplete.

      • "max_output_tokens"

      • "content_filter"

  • instructions: string or array of ResponseInputItem

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

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

    • union_member_0: string

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

    • Input item list: array of ResponseInputItem

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

      • easy_input_message: object { content, role, phase, type }

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

        • content: string or ResponseInputMessageContentList

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

          • Text input: string

            A text input to the model.

          • response_input_message_content_list: array of ResponseInputContent

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

            • response_input_text: object { text, type }

              A text input to the model.

              • text: string

                The text input to the model.

              • type: "input_text"

                The type of the input item. Always input_text.

            • response_input_image: object { detail, type, file_id, image_url }

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

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

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

                • "low"

                • "high"

                • "auto"

                • "original"

              • type: "input_image"

                The type of the input item. Always input_image.

              • file_id: optional string

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

              • image_url: optional string

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

            • response_input_file: object { type, detail, file_data, 3 more }

              A file input to the model.

              • type: "input_file"

                The type of the input item. Always input_file.

              • detail: optional "low" or "high"

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

                • "low"

                • "high"

              • file_data: optional string

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

              • file_id: optional string

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

              • file_url: optional string

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

              • filename: optional string

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

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

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

          • "user"

          • "assistant"

          • "system"

          • "developer"

        • phase: optional "commentary" or "final_answer"

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

          • "commentary"

          • "final_answer"

        • type: optional "message"

          The type of the message input. Always message.

          • "message"

      • message: object { content, role, status, type }

        A message input to the model with a role indicating instruction following hierarchy. Instructions given with the developer or system role take precedence over instructions given with the user role.

        • content: array of ResponseInputContent

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

          • response_input_text: object { text, type }

            A text input to the model.

          • response_input_image: object { detail, type, file_id, image_url }

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

          • response_input_file: object { type, detail, file_data, 3 more }

            A file input to the model.

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

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

          • "user"

          • "system"

          • "developer"

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: optional "message"

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

          • "message"

      • response_output_message: object { id, content, role, 3 more }

        An output message from the model.

        • id: string

          The unique ID of the output message.

        • content: array of ResponseOutputText or ResponseOutputRefusal

          The content of the output message.

          • response_output_text: object { annotations, text, type, logprobs }

            A text output from the model.

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

              The annotations of the text output.

              • file_citation: object { file_id, filename, index, type }

                A citation to a file.

                • file_id: string

                  The ID of the file.

                • filename: string

                  The filename of the file cited.

                • index: number

                  The index of the file in the list of files.

                • type: "file_citation"

                  The type of the file citation. Always file_citation.

              • url_citation: object { end_index, start_index, title, 2 more }

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

                • end_index: number

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

                • start_index: number

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

                • title: string

                  The title of the web resource.

                • type: "url_citation"

                  The type of the URL citation. Always url_citation.

                • url: string

                  The URL of the web resource.

              • container_file_citation: object { container_id, end_index, file_id, 3 more }

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

                • container_id: string

                  The ID of the container file.

                • end_index: number

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

                • file_id: string

                  The ID of the file.

                • filename: string

                  The filename of the container file cited.

                • start_index: number

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

                • type: "container_file_citation"

                  The type of the container file citation. Always container_file_citation.

              • file_path: object { file_id, index, type }

                A path to a file.

                • file_id: string

                  The ID of the file.

                • index: number

                  The index of the file in the list of files.

                • type: "file_path"

                  The type of the file path. Always file_path.

            • text: string

              The text output from the model.

            • type: "output_text"

              The type of the output text. Always output_text.

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

              • token: string

              • bytes: array of number

              • logprob: number

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

                • token: string

                • bytes: array of number

                • logprob: number

          • response_output_refusal: object { refusal, type }

            A refusal from the model.

            • refusal: string

              The refusal explanation from the model.

            • type: "refusal"

              The type of the refusal. Always refusal.

        • role: "assistant"

          The role of the output message. Always assistant.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: "message"

          The type of the output message. Always message.

        • phase: optional "commentary" or "final_answer"

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

          • "commentary"

          • "final_answer"

      • response_file_search_tool_call: object { id, queries, status, 2 more }

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

        • id: string

          The unique ID of the file search tool call.

        • queries: array of string

          The queries used to search for files.

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

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

          • "in_progress"

          • "searching"

          • "completed"

          • "incomplete"

          • "failed"

        • type: "file_search_call"

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

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

          The results of the file search tool call.

          • attributes: optional map[string or number or boolean]

            Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

            • union_member_0: string

            • union_member_1: number

            • union_member_2: boolean

          • file_id: optional string

            The unique ID of the file.

          • filename: optional string

            The name of the file.

          • score: optional number

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

          • text: optional string

            The text that was retrieved from the file.

      • response_computer_tool_call: object { id, call_id, pending_safety_checks, 4 more }

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

        • id: string

          The unique ID of the computer call.

        • call_id: string

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

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

          The pending safety checks for the computer call.

          • id: string

            The ID of the pending safety check.

          • code: optional string

            The type of the pending safety check.

          • message: optional string

            Details about the pending safety check.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: "computer_call"

          The type of the computer call. Always computer_call.

          • "computer_call"

        • action: optional object { button, type, x, 2 more } or object { keys, type, x, y } or object { path, type, keys } or 6 more

          A click action.

          • click: object { button, type, x, 2 more }

            A click action.

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

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

              • "left"

              • "right"

              • "wheel"

              • "back"

              • "forward"

            • type: "click"

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

            • x: number

              The x-coordinate where the click occurred.

            • y: number

              The y-coordinate where the click occurred.

            • keys: optional array of string

              The keys being held while clicking.

          • double_click: object { keys, type, x, y }

            A double click action.

            • keys: array of string

              The keys being held while double-clicking.

            • type: "double_click"

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

            • x: number

              The x-coordinate where the double click occurred.

            • y: number

              The y-coordinate where the double click occurred.

          • drag: object { path, type, keys }

            A drag action.

            • path: array of object { x, y }

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

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

              • x: number

                The x-coordinate.

              • y: number

                The y-coordinate.

            • type: "drag"

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

            • keys: optional array of string

              The keys being held while dragging the mouse.

          • keypress: object { keys, type }

            A collection of keypresses the model would like to perform.

            • keys: array of string

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

            • type: "keypress"

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

          • move: object { type, x, y, keys }

            A mouse move action.

            • type: "move"

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

            • x: number

              The x-coordinate to move to.

            • y: number

              The y-coordinate to move to.

            • keys: optional array of string

              The keys being held while moving the mouse.

          • screenshot: object { type }

            A screenshot action.

          • scroll: object { scroll_x, scroll_y, type, 3 more }

            A scroll action.

            • scroll_x: number

              The horizontal scroll distance.

            • scroll_y: number

              The vertical scroll distance.

            • type: "scroll"

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

            • x: number

              The x-coordinate where the scroll occurred.

            • y: number

              The y-coordinate where the scroll occurred.

            • keys: optional array of string

              The keys being held while scrolling.

          • type: object { text, type }

            An action to type in text.

            • text: string

              The text to type.

            • type: "type"

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

          • wait: object { type }

            A wait action.

        • actions: optional array of ComputerAction

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

          • click: object { button, type, x, 2 more }

            A click action.

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

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

              • "left"

              • "right"

              • "wheel"

              • "back"

              • "forward"

            • type: "click"

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

            • x: number

              The x-coordinate where the click occurred.

            • y: number

              The y-coordinate where the click occurred.

            • keys: optional array of string

              The keys being held while clicking.

          • double_click: object { keys, type, x, y }

            A double click action.

            • keys: array of string

              The keys being held while double-clicking.

            • type: "double_click"

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

            • x: number

              The x-coordinate where the double click occurred.

            • y: number

              The y-coordinate where the double click occurred.

          • drag: object { path, type, keys }

            A drag action.

            • path: array of object { x, y }

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

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

              • x: number

                The x-coordinate.

              • y: number

                The y-coordinate.

            • type: "drag"

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

            • keys: optional array of string

              The keys being held while dragging the mouse.

          • keypress: object { keys, type }

            A collection of keypresses the model would like to perform.

            • keys: array of string

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

            • type: "keypress"

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

          • move: object { type, x, y, keys }

            A mouse move action.

            • type: "move"

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

            • x: number

              The x-coordinate to move to.

            • y: number

              The y-coordinate to move to.

            • keys: optional array of string

              The keys being held while moving the mouse.

          • screenshot: object { type }

            A screenshot action.

          • scroll: object { scroll_x, scroll_y, type, 3 more }

            A scroll action.

            • scroll_x: number

              The horizontal scroll distance.

            • scroll_y: number

              The vertical scroll distance.

            • type: "scroll"

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

            • x: number

              The x-coordinate where the scroll occurred.

            • y: number

              The y-coordinate where the scroll occurred.

            • keys: optional array of string

              The keys being held while scrolling.

          • type: object { text, type }

            An action to type in text.

            • text: string

              The text to type.

            • type: "type"

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

          • wait: object { type }

            A wait action.

      • computer_call_output: object { call_id, output, type, 3 more }

        The output of a computer tool call.

        • call_id: string

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

        • output: object { type, file_id, image_url }

          A computer screenshot image used with the computer use tool.

          • type: "computer_screenshot"

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

          • file_id: optional string

            The identifier of an uploaded file that contains the screenshot.

          • image_url: optional string

            The URL of the screenshot image.

        • type: "computer_call_output"

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

        • id: optional string

          The ID of the computer tool call output.

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

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

          • id: string

            The ID of the pending safety check.

          • code: optional string

            The type of the pending safety check.

          • message: optional string

            Details about the pending safety check.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • response_function_web_search: object { id, action, status, type }

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

        • id: string

          The unique ID of the web search tool call.

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

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

          • search: object { type, queries, query, sources }

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

            • type: "search"

              The action type.

            • queries: optional array of string

              The search queries.

            • query: optional string

              The search query.

            • sources: optional array of object { type, url }

              The sources used in the search.

              • type: "url"

                The type of source. Always url.

              • url: string

                The URL of the source.

          • open_page: object { type, url }

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

            • type: "open_page"

              The action type.

            • url: optional string

              The URL opened by the model.

          • find_in_page: object { pattern, type, url }

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

            • pattern: string

              The pattern or text to search for within the page.

            • type: "find_in_page"

              The action type.

            • url: string

              The URL of the page searched for the pattern.

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

          The status of the web search tool call.

          • "in_progress"

          • "searching"

          • "completed"

          • "failed"

        • type: "web_search_call"

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

      • response_function_tool_call: object { arguments, call_id, name, 4 more }

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

        • arguments: string

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

        • call_id: string

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

        • name: string

          The name of the function to run.

        • type: "function_call"

          The type of the function tool call. Always function_call.

        • id: optional string

          The unique ID of the function tool call.

        • namespace: optional string

          The namespace of the function to run.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • function_call_output: object { call_id, output, type, 2 more }

        The output of a function tool call.

        • call_id: string

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

        • output: string or ResponseFunctionCallOutputItemList

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

          • union_member_0: string

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

          • response_function_call_output_item_list: array of ResponseFunctionCallOutputItem

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

            • response_input_text_content: object { text, type }

              A text input to the model.

              • text: string

                The text input to the model.

              • type: "input_text"

                The type of the input item. Always input_text.

            • response_input_image_content: object { type, detail, file_id, image_url }

              An image input to the model. Learn about image inputs

              • type: "input_image"

                The type of the input item. Always input_image.

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

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

                • "low"

                • "high"

                • "auto"

                • "original"

              • file_id: optional string

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

              • image_url: optional string

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

            • response_input_file_content: object { type, detail, file_data, 3 more }

              A file input to the model.

              • type: "input_file"

                The type of the input item. Always input_file.

              • detail: optional "low" or "high"

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

                • "low"

                • "high"

              • file_data: optional string

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

              • file_id: optional string

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

              • file_url: optional string

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

              • filename: optional string

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

        • type: "function_call_output"

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

        • id: optional string

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

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • tool_search_call: object { arguments, type, id, 3 more }

        • arguments: unknown

          The arguments supplied to the tool search call.

        • type: "tool_search_call"

          The item type. Always tool_search_call.

        • id: optional string

          The unique ID of this tool search call.

        • call_id: optional string

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

        • execution: optional "server" or "client"

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

          • "server"

          • "client"

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

          The status of the tool search call.

          • "in_progress"

          • "completed"

          • "incomplete"

      • response_tool_search_output_item_param: object { tools, type, id, 3 more }

        • tools: array of Tool

          The loaded tool definitions returned by the tool search output.

          • function_tool: object { name, parameters, strict, 3 more }

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

            • name: string

              The name of the function to call.

            • parameters: map[unknown]

              A JSON schema object describing the parameters of the function.

            • strict: boolean

              Whether to enforce strict parameter validation. Default true.

            • type: "function"

              The type of the function tool. Always function.

            • defer_loading: optional boolean

              Whether this function is deferred and loaded via tool search.

            • description: optional string

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

          • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

            • type: "file_search"

              The type of the file search tool. Always file_search.

            • vector_store_ids: array of string

              The IDs of the vector stores to search.

            • filters: optional ComparisonFilter or CompoundFilter

              A filter to apply.

              • comparison_filter: object { key, type, value }

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

                • key: string

                  The key to compare against the value.

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

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

                  • eq: equals

                  • ne: not equal

                  • gt: greater than

                  • gte: greater than or equal

                  • lt: less than

                  • lte: less than or equal

                  • in: in

                  • nin: not in

                  • "eq"

                  • "ne"

                  • "gt"

                  • "gte"

                  • "lt"

                  • "lte"

                  • "in"

                  • "nin"

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

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

                  • union_member_0: string

                  • union_member_1: number

                  • union_member_2: boolean

                  • union_member_3: array of string or number

                    • union_member_0: string

                    • union_member_1: number

              • compound_filter: object { filters, type }

                Combine multiple filters using and or or.

                • filters: array of ComparisonFilter or unknown

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

                  • comparison_filter: object { key, type, value }

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

                  • union_member_1: unknown

                • type: "and" or "or"

                  Type of operation: and or or.

                  • "and"

                  • "or"

            • max_num_results: optional number

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

            • ranking_options: optional object { hybrid_search, ranker, score_threshold }

              Ranking options for search.

              • hybrid_search: optional object { embedding_weight, text_weight }

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

                • embedding_weight: number

                  The weight of the embedding in the reciprocal ranking fusion.

                • text_weight: number

                  The weight of the text in the reciprocal ranking fusion.

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

                The ranker to use for the file search.

                • "auto"

                • "default-2024-11-15"

              • score_threshold: optional number

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

          • computer_tool: object { type }

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

            • type: "computer"

              The type of the computer tool. Always computer.

          • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

            • display_height: number

              The height of the computer display.

            • display_width: number

              The width of the computer display.

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

              The type of computer environment to control.

              • "windows"

              • "mac"

              • "linux"

              • "ubuntu"

              • "browser"

            • type: "computer_use_preview"

              The type of the computer use tool. Always computer_use_preview.

          • web_search_tool: object { type, filters, search_context_size, user_location }

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

            • type: "web_search" or "web_search_2025_08_26"

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

              • "web_search"

              • "web_search_2025_08_26"

            • filters: optional object { allowed_domains }

              Filters for the search.

              • allowed_domains: optional array of string

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

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

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

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

              • "low"

              • "medium"

              • "high"

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

              The approximate location of the user.

              • city: optional string

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

              • country: optional string

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

              • region: optional string

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

              • timezone: optional string

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

              • type: optional "approximate"

                The type of location approximation. Always approximate.

                • "approximate"

          • mcp: object { server_label, type, allowed_tools, 8 more }

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

            • server_label: string

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

            • type: "mcp"

              The type of the MCP tool. Always mcp.

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

              List of allowed tool names or a filter object.

              • MCP allowed tools: array of string

                A string array of allowed tool names

              • MCP tool filter: object { read_only, tool_names }

                A filter object to specify which tools are allowed.

                • read_only: optional boolean

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

                • tool_names: optional array of string

                  List of allowed tool names.

            • authorization: optional string

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

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

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

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • "connector_dropbox"

              • "connector_gmail"

              • "connector_googlecalendar"

              • "connector_googledrive"

              • "connector_microsoftteams"

              • "connector_outlookcalendar"

              • "connector_outlookemail"

              • "connector_sharepoint"

            • defer_loading: optional boolean

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

            • headers: optional map[string]

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

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

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

              • MCP tool approval filter: object { always, never }

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

                • always: optional object { read_only, tool_names }

                  A filter object to specify which tools are allowed.

                  • read_only: optional boolean

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

                  • tool_names: optional array of string

                    List of allowed tool names.

                • never: optional object { read_only, tool_names }

                  A filter object to specify which tools are allowed.

                  • read_only: optional boolean

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

                  • tool_names: optional array of string

                    List of allowed tool names.

              • MCP tool approval setting: "always" or "never"

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

                • "always"

                • "never"

            • server_description: optional string

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

            • server_url: optional string

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

            • tunnel_id: optional string

              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.

          • code_interpreter: object { container, type }

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

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

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

              • union_member_0: string

                The container ID.

              • CodeInterpreterToolAuto: object { type, file_ids, memory_limit, network_policy }

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

                • type: "auto"

                  Always auto.

                • file_ids: optional array of string

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

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

                  The memory limit for the code interpreter container.

                  • "1g"

                  • "4g"

                  • "16g"

                  • "64g"

                • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

                  Network access policy for the container.

                  • container_network_policy_disabled: object { type }

                    • type: "disabled"

                      Disable outbound network access. Always disabled.

                  • container_network_policy_allowlist: object { allowed_domains, type, domain_secrets }

                    • allowed_domains: array of string

                      A list of allowed domains when type is allowlist.

                    • type: "allowlist"

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

                    • domain_secrets: optional array of ContainerNetworkPolicyDomainSecret

                      Optional domain-scoped secrets for allowlisted domains.

                      • domain: string

                        The domain associated with the secret.

                      • name: string

                        The name of the secret to inject for the domain.

                      • value: string

                        The secret value to inject for the domain.

            • type: "code_interpreter"

              The type of the code interpreter tool. Always code_interpreter.

          • image_generation: object { type, action, background, 9 more }

            A tool that generates images using the GPT image models.

            • type: "image_generation"

              The type of the image generation tool. Always image_generation.

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

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

              • "generate"

              • "edit"

              • "auto"

            • background: optional "transparent" or "opaque" or "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 "high" or "low"

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

              • "high"

              • "low"

            • input_image_mask: optional object { file_id, image_url }

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

              • file_id: optional string

                File ID for the mask image.

              • image_url: optional string

                Base64-encoded mask image.

            • model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-2" or 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 "auto" or "low"

              Moderation level for the generated image. Default: auto.

              • "auto"

              • "low"

            • output_compression: optional number

              Compression level for the output image. Default: 100.

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

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

              • "png"

              • "webp"

              • "jpeg"

            • partial_images: optional number

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

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

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

              • "low"

              • "medium"

              • "high"

              • "auto"

            • size: optional string or "1024x1024" or "1024x1536" or "1536x1024" or "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"

          • local_shell: object { type }

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

          • function_shell_tool: object { type, environment }

            A tool that allows the model to execute shell commands.

            • type: "shell"

              The type of the shell tool. Always shell.

            • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

              • container_auto: object { type, file_ids, memory_limit, 2 more }

                • type: "container_auto"

                  Automatically creates a container for this request

                • file_ids: optional array of string

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

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

                  The memory limit for the container.

                  • "1g"

                  • "4g"

                  • "16g"

                  • "64g"

                • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

                  Network access policy for the container.

                  • container_network_policy_disabled: object { type }

                  • container_network_policy_allowlist: object { allowed_domains, type, domain_secrets }

                • skills: optional array of SkillReference or InlineSkill

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

                  • skill_reference: object { skill_id, type, version }

                    • skill_id: string

                      The ID of the referenced skill.

                    • type: "skill_reference"

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

                    • version: optional string

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

                  • inline_skill: object { description, name, source, type }

                    • description: string

                      The description of the skill.

                    • name: string

                      The name of the skill.

                    • source: object { data, media_type, type }

                      Inline skill payload

                      • data: string

                        Base64-encoded skill zip bundle.

                      • media_type: "application/zip"

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

                      • type: "base64"

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

                    • type: "inline"

                      Defines an inline skill for this request.

              • local_environment: object { type, skills }

                • type: "local"

                  Use a local computer environment.

                • skills: optional array of LocalSkill

                  An optional list of skills.

                  • description: string

                    The description of the skill.

                  • name: string

                    The name of the skill.

                  • path: string

                    The path to the directory containing the skill.

              • container_reference: object { container_id, type }

                • container_id: string

                  The ID of the referenced container.

                • type: "container_reference"

                  References a container created with the /v1/containers endpoint

          • custom_tool: object { name, type, defer_loading, 2 more }

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

            • name: string

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

            • type: "custom"

              The type of the custom tool. Always custom.

            • defer_loading: optional boolean

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

            • description: optional string

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

            • format: optional object { type } or object { definition, syntax, type }

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

              • text: object { type }

                Unconstrained free-form text.

              • grammar: object { definition, syntax, type }

                A grammar defined by the user.

                • definition: string

                  The grammar definition.

                • syntax: "lark" or "regex"

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

                  • "lark"

                  • "regex"

                • type: "grammar"

                  Grammar format. Always grammar.

          • namespace_tool: object { description, name, tools, type }

            Groups function/custom tools under a shared namespace.

            • description: string

              A description of the namespace shown to the model.

            • name: string

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

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

              The function/custom tools available inside this namespace.

              • function: object { name, type, defer_loading, 3 more }

                • name: string

                • type: "function"

                • defer_loading: optional boolean

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

                • description: optional string

                • parameters: optional unknown

                • strict: optional boolean

              • custom_tool: object { name, type, defer_loading, 2 more }

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

                • name: string

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

                • type: "custom"

                  The type of the custom tool. Always custom.

                • defer_loading: optional boolean

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

                • description: optional string

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

                • format: optional object { type } or object { definition, syntax, type }

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

            • type: "namespace"

              The type of the tool. Always namespace.

          • tool_search_tool: object { type, description, execution, parameters }

            Hosted or BYOT tool search configuration for deferred tools.

            • type: "tool_search"

              The type of the tool. Always tool_search.

            • description: optional string

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

            • execution: optional "server" or "client"

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

              • "server"

              • "client"

            • parameters: optional unknown

              Parameter schema for a client-executed tool search tool.

          • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

            • type: "web_search_preview" or "web_search_preview_2025_03_11"

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

              • "web_search_preview"

              • "web_search_preview_2025_03_11"

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

              • "text"

              • "image"

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

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

              • "low"

              • "medium"

              • "high"

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

              The user's location.

              • type: "approximate"

                The type of location approximation. Always approximate.

              • city: optional string

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

              • country: optional string

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

              • region: optional string

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

              • timezone: optional string

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

          • apply_patch_tool: object { type }

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

            • type: "apply_patch"

              The type of the tool. Always apply_patch.

        • type: "tool_search_output"

          The item type. Always tool_search_output.

        • id: optional string

          The unique ID of this tool search output.

        • call_id: optional string

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

        • execution: optional "server" or "client"

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

          • "server"

          • "client"

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

          The status of the tool search output.

          • "in_progress"

          • "completed"

          • "incomplete"

      • additional_tools: object { role, tools, type, id }

        • role: "developer"

          The role that provided the additional tools. Only developer is supported.

        • tools: array of Tool

          A list of additional tools made available at this item.

          • function_tool: object { name, parameters, strict, 3 more }

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

          • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

          • computer_tool: object { type }

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

          • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

          • web_search_tool: object { type, filters, search_context_size, user_location }

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

          • mcp: object { server_label, type, allowed_tools, 8 more }

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

          • code_interpreter: object { container, type }

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

          • image_generation: object { type, action, background, 9 more }

            A tool that generates images using the GPT image models.

          • local_shell: object { type }

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

          • function_shell_tool: object { type, environment }

            A tool that allows the model to execute shell commands.

          • custom_tool: object { name, type, defer_loading, 2 more }

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

          • namespace_tool: object { description, name, tools, type }

            Groups function/custom tools under a shared namespace.

          • tool_search_tool: object { type, description, execution, parameters }

            Hosted or BYOT tool search configuration for deferred tools.

          • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

          • apply_patch_tool: object { type }

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

        • type: "additional_tools"

          The item type. Always additional_tools.

        • id: optional string

          The unique ID of this additional tools item.

      • response_reasoning_item: object { id, summary, type, 3 more }

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

        • id: string

          The unique identifier of the reasoning content.

        • summary: array of object { text, type }

          Reasoning summary content.

          • text: string

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

          • type: "summary_text"

            The type of the object. Always summary_text.

        • type: "reasoning"

          The type of the object. Always reasoning.

        • content: optional array of object { text, type }

          Reasoning text content.

          • text: string

            The reasoning text from the model.

          • type: "reasoning_text"

            The type of the reasoning text. Always reasoning_text.

        • encrypted_content: optional string

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

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • response_compaction_item_param: object { encrypted_content, type, id }

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

        • encrypted_content: string

          The encrypted content of the compaction summary.

        • type: "compaction"

          The type of the item. Always compaction.

        • id: optional string

          The ID of the compaction item.

      • image_generation_call: object { id, result, status, type }

        An image generation request made by the model.

        • id: string

          The unique ID of the image generation call.

        • result: string

          The generated image encoded in base64.

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

          The status of the image generation call.

          • "in_progress"

          • "completed"

          • "generating"

          • "failed"

        • type: "image_generation_call"

          The type of the image generation call. Always image_generation_call.

      • response_code_interpreter_tool_call: object { id, code, container_id, 3 more }

        A tool call to run code.

        • id: string

          The unique ID of the code interpreter tool call.

        • code: string

          The code to run, or null if not available.

        • container_id: string

          The ID of the container used to run the code.

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

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

          • logs: object { logs, type }

            The logs output from the code interpreter.

            • logs: string

              The logs output from the code interpreter.

            • type: "logs"

              The type of the output. Always logs.

          • image: object { type, url }

            The image output from the code interpreter.

            • type: "image"

              The type of the output. Always image.

            • url: string

              The URL of the image output from the code interpreter.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

          • "interpreting"

          • "failed"

        • type: "code_interpreter_call"

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

      • local_shell_call: object { id, action, call_id, 2 more }

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

        • id: string

          The unique ID of the local shell call.

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

          Execute a shell command on the server.

          • command: array of string

            The command to run.

          • env: map[string]

            Environment variables to set for the command.

          • type: "exec"

            The type of the local shell action. Always exec.

          • timeout_ms: optional number

            Optional timeout in milliseconds for the command.

          • user: optional string

            Optional user to run the command as.

          • working_directory: optional string

            Optional working directory to run the command in.

        • call_id: string

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

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

          The status of the local shell call.

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: "local_shell_call"

          The type of the local shell call. Always local_shell_call.

      • local_shell_call_output: object { id, output, type, status }

        The output of a local shell tool call.

        • id: string

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

        • output: string

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

        • type: "local_shell_call_output"

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

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • shell_call: object { action, call_id, type, 3 more }

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

        • action: object { commands, max_output_length, timeout_ms }

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

          • commands: array of string

            Ordered shell commands for the execution environment to run.

          • max_output_length: optional number

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

          • timeout_ms: optional number

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

        • call_id: string

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

        • type: "shell_call"

          The type of the item. Always shell_call.

        • id: optional string

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

        • environment: optional LocalEnvironment or ContainerReference

          The environment to execute the shell commands in.

          • local_environment: object { type, skills }

          • container_reference: object { container_id, type }

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • shell_call_output: object { call_id, output, type, 3 more }

        The streamed output items emitted by a shell tool call.

        • call_id: string

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

        • output: array of ResponseFunctionShellCallOutputContent

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

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

            The exit or timeout outcome associated with this shell call.

            • timeout: object { type }

              Indicates that the shell call exceeded its configured time limit.

            • exit: object { exit_code, type }

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

              • exit_code: number

                The exit code returned by the shell process.

              • type: "exit"

                The outcome type. Always exit.

          • stderr: string

            Captured stderr output for the shell call.

          • stdout: string

            Captured stdout output for the shell call.

        • type: "shell_call_output"

          The type of the item. Always shell_call_output.

        • id: optional string

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

        • max_output_length: optional number

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

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

          The status of the shell call output.

          • "in_progress"

          • "completed"

          • "incomplete"

      • apply_patch_call: object { call_id, operation, status, 2 more }

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

        • call_id: string

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

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

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

          • create_file: object { diff, path, type }

            Instruction for creating a new file via the apply_patch tool.

            • diff: string

              Unified diff content to apply when creating the file.

            • path: string

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

            • type: "create_file"

              The operation type. Always create_file.

          • delete_file: object { path, type }

            Instruction for deleting an existing file via the apply_patch tool.

            • path: string

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

            • type: "delete_file"

              The operation type. Always delete_file.

          • update_file: object { diff, path, type }

            Instruction for updating an existing file via the apply_patch tool.

            • diff: string

              Unified diff content to apply to the existing file.

            • path: string

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

            • type: "update_file"

              The operation type. Always update_file.

        • status: "in_progress" or "completed"

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

          • "in_progress"

          • "completed"

        • type: "apply_patch_call"

          The type of the item. Always apply_patch_call.

        • id: optional string

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

      • apply_patch_call_output: object { call_id, status, type, 2 more }

        The streamed output emitted by an apply patch tool call.

        • call_id: string

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

        • status: "completed" or "failed"

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

          • "completed"

          • "failed"

        • type: "apply_patch_call_output"

          The type of the item. Always apply_patch_call_output.

        • id: optional string

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

        • output: optional string

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

      • mcp_list_tools: object { id, server_label, tools, 2 more }

        A list of tools available on an MCP server.

        • id: string

          The unique ID of the list.

        • server_label: string

          The label of the MCP server.

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

          The tools available on the server.

          • input_schema: unknown

            The JSON schema describing the tool's input.

          • name: string

            The name of the tool.

          • annotations: optional unknown

            Additional annotations about the tool.

          • description: optional string

            The description of the tool.

        • type: "mcp_list_tools"

          The type of the item. Always mcp_list_tools.

        • error: optional string

          Error message if the server could not list tools.

      • mcp_approval_request: object { id, arguments, name, 2 more }

        A request for human approval of a tool invocation.

        • id: string

          The unique ID of the approval request.

        • arguments: string

          A JSON string of arguments for the tool.

        • name: string

          The name of the tool to run.

        • server_label: string

          The label of the MCP server making the request.

        • type: "mcp_approval_request"

          The type of the item. Always mcp_approval_request.

      • mcp_approval_response: object { approval_request_id, approve, type, 2 more }

        A response to an MCP approval request.

        • approval_request_id: string

          The ID of the approval request being answered.

        • approve: boolean

          Whether the request was approved.

        • type: "mcp_approval_response"

          The type of the item. Always mcp_approval_response.

        • id: optional string

          The unique ID of the approval response

        • reason: optional string

          Optional reason for the decision.

      • mcp_call: object { id, arguments, name, 6 more }

        An invocation of a tool on an MCP server.

        • id: string

          The unique ID of the tool call.

        • arguments: string

          A JSON string of the arguments passed to the tool.

        • name: string

          The name of the tool that was run.

        • server_label: string

          The label of the MCP server running the tool.

        • type: "mcp_call"

          The type of the item. Always mcp_call.

        • approval_request_id: optional string

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

        • error: optional string

          The error from the tool call, if any.

        • output: optional string

          The output from the tool call.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

          • "calling"

          • "failed"

      • response_custom_tool_call_output: object { call_id, output, type, id }

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

        • call_id: string

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

        • output: string or array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

          • string output: string

            A string of the output of the custom tool call.

          • output content list: array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

            • response_input_text: object { text, type }

              A text input to the model.

              • text: string

                The text input to the model.

              • type: "input_text"

                The type of the input item. Always input_text.

            • response_input_image: object { detail, type, file_id, image_url }

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

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

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

              • type: "input_image"

                The type of the input item. Always input_image.

              • file_id: optional string

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

              • image_url: optional string

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

            • response_input_file: object { type, detail, file_data, 3 more }

              A file input to the model.

              • type: "input_file"

                The type of the input item. Always input_file.

              • detail: optional "low" or "high"

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

              • file_data: optional string

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

              • file_id: optional string

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

              • file_url: optional string

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

              • filename: optional string

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

        • type: "custom_tool_call_output"

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

        • id: optional string

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

      • response_custom_tool_call: object { call_id, input, name, 3 more }

        A call to a custom tool created by the model.

        • call_id: string

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

        • input: string

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

        • name: string

          The name of the custom tool being called.

        • type: "custom_tool_call"

          The type of the custom tool call. Always custom_tool_call.

        • id: optional string

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

        • namespace: optional string

          The namespace of the custom tool being called.

      • compaction_trigger: object { type }

        Compacts the current context. Must be the final input item.

      • item_reference: object { id, type }

        An internal identifier for an item to reference.

        • id: string

          The ID of the item to reference.

        • type: optional "item_reference"

          The type of item to reference. Always item_reference.

          • "item_reference"

  • metadata: map[string]

    Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

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

  • model: string or ChatModel or "o1-pro" or "o1-pro-2025-03-19" or "o3-pro" or 11 more

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

    • union_member_0: string

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

      • "gpt-5.4"

      • "gpt-5.4-mini"

      • "gpt-5.4-nano"

      • "gpt-5.4-mini-2026-03-17"

      • "gpt-5.4-nano-2026-03-17"

      • "gpt-5.3-chat-latest"

      • "gpt-5.2"

      • "gpt-5.2-2025-12-11"

      • "gpt-5.2-chat-latest"

      • "gpt-5.2-pro"

      • "gpt-5.2-pro-2025-12-11"

      • "gpt-5.1"

      • "gpt-5.1-2025-11-13"

      • "gpt-5.1-codex"

      • "gpt-5.1-mini"

      • "gpt-5.1-chat-latest"

      • "gpt-5"

      • "gpt-5-mini"

      • "gpt-5-nano"

      • "gpt-5-2025-08-07"

      • "gpt-5-mini-2025-08-07"

      • "gpt-5-nano-2025-08-07"

      • "gpt-5-chat-latest"

      • "gpt-4.1"

      • "gpt-4.1-mini"

      • "gpt-4.1-nano"

      • "gpt-4.1-2025-04-14"

      • "gpt-4.1-mini-2025-04-14"

      • "gpt-4.1-nano-2025-04-14"

      • "o4-mini"

      • "o4-mini-2025-04-16"

      • "o3"

      • "o3-2025-04-16"

      • "o3-mini"

      • "o3-mini-2025-01-31"

      • "o1"

      • "o1-2024-12-17"

      • "o1-preview"

      • "o1-preview-2024-09-12"

      • "o1-mini"

      • "o1-mini-2024-09-12"

      • "gpt-4o"

      • "gpt-4o-2024-11-20"

      • "gpt-4o-2024-08-06"

      • "gpt-4o-2024-05-13"

      • "gpt-4o-audio-preview"

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

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

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

      • "gpt-4o-mini-audio-preview"

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

      • "gpt-4o-search-preview"

      • "gpt-4o-mini-search-preview"

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

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

      • "chatgpt-4o-latest"

      • "codex-mini-latest"

      • "gpt-4o-mini"

      • "gpt-4o-mini-2024-07-18"

      • "gpt-4-turbo"

      • "gpt-4-turbo-2024-04-09"

      • "gpt-4-0125-preview"

      • "gpt-4-turbo-preview"

      • "gpt-4-1106-preview"

      • "gpt-4-vision-preview"

      • "gpt-4"

      • "gpt-4-0314"

      • "gpt-4-0613"

      • "gpt-4-32k"

      • "gpt-4-32k-0314"

      • "gpt-4-32k-0613"

      • "gpt-3.5-turbo"

      • "gpt-3.5-turbo-16k"

      • "gpt-3.5-turbo-0301"

      • "gpt-3.5-turbo-0613"

      • "gpt-3.5-turbo-1106"

      • "gpt-3.5-turbo-0125"

      • "gpt-3.5-turbo-16k-0613"

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

      • "o1-pro"

      • "o1-pro-2025-03-19"

      • "o3-pro"

      • "o3-pro-2025-06-10"

      • "o3-deep-research"

      • "o3-deep-research-2025-06-26"

      • "o4-mini-deep-research"

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

      • "computer-use-preview"

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

      • "gpt-5-codex"

      • "gpt-5-pro"

      • "gpt-5-pro-2025-10-06"

      • "gpt-5.1-codex-max"

  • object: "response"

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

  • output: array of ResponseOutputItem

    An array of content items generated by the model.

    • The length and order of items in the output array is dependent on the model's response.

    • Rather than accessing the first item in the output array and assuming it's an assistant message with the content generated by the model, you might consider using the output_text property where supported in SDKs.

    • response_output_message: object { id, content, role, 3 more }

      An output message from the model.

      • id: string

        The unique ID of the output message.

      • content: array of ResponseOutputText or ResponseOutputRefusal

        The content of the output message.

      • role: "assistant"

        The role of the output message. Always assistant.

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

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

      • type: "message"

        The type of the output message. Always message.

      • phase: optional "commentary" or "final_answer"

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

    • response_file_search_tool_call: object { id, queries, status, 2 more }

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

      • id: string

        The unique ID of the file search tool call.

      • queries: array of string

        The queries used to search for files.

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

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

      • type: "file_search_call"

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

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

        The results of the file search tool call.

    • response_function_tool_call: object { arguments, call_id, name, 4 more }

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

      • arguments: string

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

      • call_id: string

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

      • name: string

        The name of the function to run.

      • type: "function_call"

        The type of the function tool call. Always function_call.

      • id: optional string

        The unique ID of the function tool call.

      • namespace: optional string

        The namespace of the function to run.

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

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

    • response_function_tool_call_output_item: object { id, call_id, output, 3 more }

      • id: string

        The unique ID of the function call tool output.

      • call_id: string

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

      • output: string or array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

        • string output: string

          A string of the output of the function call.

        • output content list: array of ResponseInputText or ResponseInputImage or ResponseInputFile

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

          • response_input_text: object { text, type }

            A text input to the model.

          • response_input_image: object { detail, type, file_id, image_url }

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

          • response_input_file: object { type, detail, file_data, 3 more }

            A file input to the model.

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "function_call_output"

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

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_function_web_search: object { id, action, status, type }

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

      • id: string

        The unique ID of the web search tool call.

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

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

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

        The status of the web search tool call.

      • type: "web_search_call"

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

    • response_computer_tool_call: object { id, call_id, pending_safety_checks, 4 more }

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

      • id: string

        The unique ID of the computer call.

      • call_id: string

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

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

        The pending safety checks for the computer call.

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

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

      • type: "computer_call"

        The type of the computer call. Always computer_call.

      • action: optional object { button, type, x, 2 more } or object { keys, type, x, y } or object { path, type, keys } or 6 more

        A click action.

      • actions: optional array of ComputerAction

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

    • response_computer_tool_call_output_item: object { id, call_id, output, 4 more }

      • id: string

        The unique ID of the computer call tool output.

      • call_id: string

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

      • output: object { type, file_id, image_url }

        A computer screenshot image used with the computer use tool.

        • type: "computer_screenshot"

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

        • file_id: optional string

          The identifier of an uploaded file that contains the screenshot.

        • image_url: optional string

          The URL of the screenshot image.

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

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

        • "completed"

        • "incomplete"

        • "failed"

        • "in_progress"

      • type: "computer_call_output"

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

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

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

        • id: string

          The ID of the pending safety check.

        • code: optional string

          The type of the pending safety check.

        • message: optional string

          Details about the pending safety check.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_reasoning_item: object { id, summary, type, 3 more }

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

      • id: string

        The unique identifier of the reasoning content.

      • summary: array of object { text, type }

        Reasoning summary content.

      • type: "reasoning"

        The type of the object. Always reasoning.

      • content: optional array of object { text, type }

        Reasoning text content.

      • encrypted_content: optional string

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

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

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

    • response_tool_search_call: object { id, arguments, call_id, 4 more }

      • id: string

        The unique ID of the tool search call item.

      • arguments: unknown

        Arguments used for the tool search call.

      • call_id: string

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

      • execution: "server" or "client"

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

        • "server"

        • "client"

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "tool_search_call"

        The type of the item. Always tool_search_call.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_tool_search_output_item: object { id, call_id, execution, 4 more }

      • id: string

        The unique ID of the tool search output item.

      • call_id: string

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

      • execution: "server" or "client"

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

        • "server"

        • "client"

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • tools: array of Tool

        The loaded tool definitions returned by tool search.

        • function_tool: object { name, parameters, strict, 3 more }

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

        • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

        • computer_tool: object { type }

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

        • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

        • web_search_tool: object { type, filters, search_context_size, user_location }

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

        • mcp: object { server_label, type, allowed_tools, 8 more }

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

        • code_interpreter: object { container, type }

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

        • image_generation: object { type, action, background, 9 more }

          A tool that generates images using the GPT image models.

        • local_shell: object { type }

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

        • function_shell_tool: object { type, environment }

          A tool that allows the model to execute shell commands.

        • custom_tool: object { name, type, defer_loading, 2 more }

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

        • namespace_tool: object { description, name, tools, type }

          Groups function/custom tools under a shared namespace.

        • tool_search_tool: object { type, description, execution, parameters }

          Hosted or BYOT tool search configuration for deferred tools.

        • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

        • apply_patch_tool: object { type }

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

      • type: "tool_search_output"

        The type of the item. Always tool_search_output.

      • created_by: optional string

        The identifier of the actor that created the item.

    • additional_tools: object { id, role, tools, type }

      • id: string

        The unique ID of the additional tools item.

      • role: "unknown" or "user" or "assistant" or 5 more

        The role that provided the additional tools.

        • "unknown"

        • "user"

        • "assistant"

        • "system"

        • "critic"

        • "discriminator"

        • "developer"

        • "tool"

      • tools: array of Tool

        The additional tool definitions made available at this item.

        • function_tool: object { name, parameters, strict, 3 more }

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

        • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

        • computer_tool: object { type }

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

        • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

        • web_search_tool: object { type, filters, search_context_size, user_location }

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

        • mcp: object { server_label, type, allowed_tools, 8 more }

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

        • code_interpreter: object { container, type }

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

        • image_generation: object { type, action, background, 9 more }

          A tool that generates images using the GPT image models.

        • local_shell: object { type }

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

        • function_shell_tool: object { type, environment }

          A tool that allows the model to execute shell commands.

        • custom_tool: object { name, type, defer_loading, 2 more }

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

        • namespace_tool: object { description, name, tools, type }

          Groups function/custom tools under a shared namespace.

        • tool_search_tool: object { type, description, execution, parameters }

          Hosted or BYOT tool search configuration for deferred tools.

        • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

        • apply_patch_tool: object { type }

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

      • type: "additional_tools"

        The type of the item. Always additional_tools.

    • response_compaction_item: object { id, encrypted_content, type, created_by }

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

      • id: string

        The unique ID of the compaction item.

      • encrypted_content: string

        The encrypted content that was produced by compaction.

      • type: "compaction"

        The type of the item. Always compaction.

      • created_by: optional string

        The identifier of the actor that created the item.

    • image_generation_call: object { id, result, status, type }

      An image generation request made by the model.

      • id: string

        The unique ID of the image generation call.

      • result: string

        The generated image encoded in base64.

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

        The status of the image generation call.

        • "in_progress"

        • "completed"

        • "generating"

        • "failed"

      • type: "image_generation_call"

        The type of the image generation call. Always image_generation_call.

    • response_code_interpreter_tool_call: object { id, code, container_id, 3 more }

      A tool call to run code.

      • id: string

        The unique ID of the code interpreter tool call.

      • code: string

        The code to run, or null if not available.

      • container_id: string

        The ID of the container used to run the code.

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

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

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

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

      • type: "code_interpreter_call"

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

    • local_shell_call: object { id, action, call_id, 2 more }

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

      • id: string

        The unique ID of the local shell call.

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

        Execute a shell command on the server.

        • command: array of string

          The command to run.

        • env: map[string]

          Environment variables to set for the command.

        • type: "exec"

          The type of the local shell action. Always exec.

        • timeout_ms: optional number

          Optional timeout in milliseconds for the command.

        • user: optional string

          Optional user to run the command as.

        • working_directory: optional string

          Optional working directory to run the command in.

      • call_id: string

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

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

        The status of the local shell call.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "local_shell_call"

        The type of the local shell call. Always local_shell_call.

    • local_shell_call_output: object { id, output, type, status }

      The output of a local shell tool call.

      • id: string

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

      • output: string

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

      • type: "local_shell_call_output"

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

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

    • response_function_shell_tool_call: object { id, action, call_id, 4 more }

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

      • id: string

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

      • action: object { commands, max_output_length, timeout_ms }

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

        • commands: array of string

        • max_output_length: number

          Optional maximum number of characters to return from each command.

        • timeout_ms: number

          Optional timeout in milliseconds for the commands.

      • call_id: string

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

      • environment: ResponseLocalEnvironment or ResponseContainerReference

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

        • response_local_environment: object { type }

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

          • type: "local"

            The environment type. Always local.

        • response_container_reference: object { container_id, type }

          Represents a container created with /v1/containers.

          • container_id: string

          • type: "container_reference"

            The environment type. Always container_reference.

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "shell_call"

        The type of the item. Always shell_call.

      • created_by: optional string

        The ID of the entity that created this tool call.

    • response_function_shell_tool_call_output: object { id, call_id, max_output_length, 4 more }

      The output of a shell tool call that was emitted.

      • id: string

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

      • call_id: string

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

      • max_output_length: number

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

      • output: array of object { outcome, stderr, stdout, created_by }

        An array of shell call output contents

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

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

          • timeout: object { type }

            Indicates that the shell call exceeded its configured time limit.

          • exit: object { exit_code, type }

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

            • exit_code: number

              Exit code from the shell process.

            • type: "exit"

              The outcome type. Always exit.

        • stderr: string

          The standard error output that was captured.

        • stdout: string

          The standard output that was captured.

        • created_by: optional string

          The identifier of the actor that created the item.

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "shell_call_output"

        The type of the shell call output. Always shell_call_output.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_apply_patch_tool_call: object { id, call_id, operation, 3 more }

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

      • id: string

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

      • call_id: string

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

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

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

        • create_file: object { diff, path, type }

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

          • diff: string

            Diff to apply.

          • path: string

            Path of the file to create.

          • type: "create_file"

            Create a new file with the provided diff.

        • delete_file: object { path, type }

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

          • path: string

            Path of the file to delete.

          • type: "delete_file"

            Delete the specified file.

        • update_file: object { diff, path, type }

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

          • diff: string

            Diff to apply.

          • path: string

            Path of the file to update.

          • type: "update_file"

            Update an existing file with the provided diff.

      • status: "in_progress" or "completed"

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

        • "in_progress"

        • "completed"

      • type: "apply_patch_call"

        The type of the item. Always apply_patch_call.

      • created_by: optional string

        The ID of the entity that created this tool call.

    • response_apply_patch_tool_call_output: object { id, call_id, status, 3 more }

      The output emitted by an apply patch tool call.

      • id: string

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

      • call_id: string

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

      • status: "completed" or "failed"

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

        • "completed"

        • "failed"

      • type: "apply_patch_call_output"

        The type of the item. Always apply_patch_call_output.

      • created_by: optional string

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

      • output: optional string

        Optional textual output returned by the apply patch tool.

    • mcp_call: object { id, arguments, name, 6 more }

      An invocation of a tool on an MCP server.

      • id: string

        The unique ID of the tool call.

      • arguments: string

        A JSON string of the arguments passed to the tool.

      • name: string

        The name of the tool that was run.

      • server_label: string

        The label of the MCP server running the tool.

      • type: "mcp_call"

        The type of the item. Always mcp_call.

      • approval_request_id: optional string

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

      • error: optional string

        The error from the tool call, if any.

      • output: optional string

        The output from the tool call.

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

        • "calling"

        • "failed"

    • mcp_list_tools: object { id, server_label, tools, 2 more }

      A list of tools available on an MCP server.

      • id: string

        The unique ID of the list.

      • server_label: string

        The label of the MCP server.

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

        The tools available on the server.

        • input_schema: unknown

          The JSON schema describing the tool's input.

        • name: string

          The name of the tool.

        • annotations: optional unknown

          Additional annotations about the tool.

        • description: optional string

          The description of the tool.

      • type: "mcp_list_tools"

        The type of the item. Always mcp_list_tools.

      • error: optional string

        Error message if the server could not list tools.

    • mcp_approval_request: object { id, arguments, name, 2 more }

      A request for human approval of a tool invocation.

      • id: string

        The unique ID of the approval request.

      • arguments: string

        A JSON string of arguments for the tool.

      • name: string

        The name of the tool to run.

      • server_label: string

        The label of the MCP server making the request.

      • type: "mcp_approval_request"

        The type of the item. Always mcp_approval_request.

    • mcp_approval_response: object { id, approval_request_id, approve, 2 more }

      A response to an MCP approval request.

      • id: string

        The unique ID of the approval response

      • approval_request_id: string

        The ID of the approval request being answered.

      • approve: boolean

        Whether the request was approved.

      • type: "mcp_approval_response"

        The type of the item. Always mcp_approval_response.

      • reason: optional string

        Optional reason for the decision.

    • response_custom_tool_call: object { call_id, input, name, 3 more }

      A call to a custom tool created by the model.

      • call_id: string

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

      • input: string

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

      • name: string

        The name of the custom tool being called.

      • type: "custom_tool_call"

        The type of the custom tool call. Always custom_tool_call.

      • id: optional string

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

      • namespace: optional string

        The namespace of the custom tool being called.

    • response_custom_tool_call_output_item: ResponseCustomToolCallOutput

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

      • id: string

        The unique ID of the custom tool call output item.

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

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

        • "in_progress"

        • "completed"

        • "incomplete"

      • created_by: optional string

        The identifier of the actor that created the item.

  • parallel_tool_calls: boolean

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

  • temperature: number

    What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.

  • tool_choice: ToolChoiceOptions or ToolChoiceAllowed or ToolChoiceTypes or 5 more

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

    • tool_choice_options: "none" or "auto" or "required"

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

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

      auto means the model can pick between generating a message or calling one or more tools.

      required means the model must call one or more tools.

      • "none"

      • "auto"

      • "required"

    • tool_choice_allowed: object { mode, tools, type }

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

      • mode: "auto" or "required"

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

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

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

        • "auto"

        • "required"

      • tools: array of map[unknown]

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

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

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

      • type: "allowed_tools"

        Allowed tool configuration type. Always allowed_tools.

    • tool_choice_types: object { type }

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

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

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

        Allowed values are:

        • file_search

        • web_search_preview

        • computer

        • computer_use_preview

        • computer_use

        • code_interpreter

        • image_generation

        • "file_search"

        • "web_search_preview"

        • "computer"

        • "computer_use_preview"

        • "computer_use"

        • "web_search_preview_2025_03_11"

        • "image_generation"

        • "code_interpreter"

    • tool_choice_function: object { name, type }

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

      • name: string

        The name of the function to call.

      • type: "function"

        For function calling, the type is always function.

    • tool_choice_mcp: object { server_label, type, name }

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

      • server_label: string

        The label of the MCP server to use.

      • type: "mcp"

        For MCP tools, the type is always mcp.

      • name: optional string

        The name of the tool to call on the server.

    • tool_choice_custom: object { name, type }

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

      • name: string

        The name of the custom tool to call.

      • type: "custom"

        For custom tool calling, the type is always custom.

    • tool_choice_apply_patch: object { type }

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

      • type: "apply_patch"

        The tool to call. Always apply_patch.

    • tool_choice_shell: object { type }

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

      • type: "shell"

        The tool to call. Always shell.

  • tools: array of Tool

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

    We support the following categories of tools:

    • Built-in tools: Tools that are provided by OpenAI that extend the model's capabilities, like web search or file search. Learn more about built-in tools.

    • MCP Tools: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about MCP Tools.

    • Function calls (custom tools): Functions that are defined by you, enabling the model to call your own code with strongly typed arguments and outputs. Learn more about function calling. You can also use custom tools to call your own code.

    • function_tool: object { name, parameters, strict, 3 more }

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

    • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

    • computer_tool: object { type }

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

    • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

    • web_search_tool: object { type, filters, search_context_size, user_location }

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

    • mcp: object { server_label, type, allowed_tools, 8 more }

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

    • code_interpreter: object { container, type }

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

    • image_generation: object { type, action, background, 9 more }

      A tool that generates images using the GPT image models.

    • local_shell: object { type }

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

    • function_shell_tool: object { type, environment }

      A tool that allows the model to execute shell commands.

    • custom_tool: object { name, type, defer_loading, 2 more }

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

    • namespace_tool: object { description, name, tools, type }

      Groups function/custom tools under a shared namespace.

    • tool_search_tool: object { type, description, execution, parameters }

      Hosted or BYOT tool search configuration for deferred tools.

    • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

    • apply_patch_tool: object { type }

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

  • top_p: number

    An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

    We generally recommend altering this or temperature but not both.

  • background: optional boolean

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

  • completed_at: optional number

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

  • conversation: optional object { id }

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

    • id: string

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

  • max_output_tokens: optional number

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

  • max_tool_calls: optional number

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

  • moderation: optional object { input, output }

    Moderation results for the response input and output, if moderated completions were requested.

    • input: object { categories, category_applied_input_types, category_scores, 3 more } or object { code, message, type }

      Moderation for the response input.

      • moderation_result: object { categories, category_applied_input_types, category_scores, 3 more }

        A moderation result produced for the response input or output.

        • categories: map[boolean]

          A dictionary of moderation categories to booleans, True if the input is flagged under this category.

        • category_applied_input_types: map[array of "text" or "image"]

          Which modalities of input are reflected by the score for each category.

          • "text"

          • "image"

        • category_scores: map[number]

          A dictionary of moderation categories to scores.

        • flagged: boolean

          A boolean indicating whether the content was flagged by any category.

        • model: string

          The moderation model that produced this result.

        • type: "moderation_result"

          The object type, which was always moderation_result for successful moderation results.

      • error: object { code, message, type }

        An error produced while attempting moderation for the response input or output.

        • code: string

          The error code.

        • message: string

          The error message.

        • type: "error"

          The object type, which was always error for moderation failures.

    • output: object { categories, category_applied_input_types, category_scores, 3 more } or object { code, message, type }

      Moderation for the response output.

      • moderation_result: object { categories, category_applied_input_types, category_scores, 3 more }

        A moderation result produced for the response input or output.

        • categories: map[boolean]

          A dictionary of moderation categories to booleans, True if the input is flagged under this category.

        • category_applied_input_types: map[array of "text" or "image"]

          Which modalities of input are reflected by the score for each category.

          • "text"

          • "image"

        • category_scores: map[number]

          A dictionary of moderation categories to scores.

        • flagged: boolean

          A boolean indicating whether the content was flagged by any category.

        • model: string

          The moderation model that produced this result.

        • type: "moderation_result"

          The object type, which was always moderation_result for successful moderation results.

      • error: object { code, message, type }

        An error produced while attempting moderation for the response input or output.

        • code: string

          The error code.

        • message: string

          The error message.

        • type: "error"

          The object type, which was always error for moderation failures.

  • previous_response_id: optional string

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

  • prompt: optional object { id, variables, version }

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

    • id: string

      The unique identifier of the prompt template to use.

    • variables: optional map[string or ResponseInputText or ResponseInputImage or ResponseInputFile]

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

      • union_member_0: string

      • response_input_text: object { text, type }

        A text input to the model.

      • response_input_image: object { detail, type, file_id, image_url }

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

      • response_input_file: object { type, detail, file_data, 3 more }

        A file input to the model.

    • version: optional string

      Optional version of the prompt template.

  • prompt_cache_key: optional string

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

  • prompt_cache_retention: optional "in_memory" or "24h"

    The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more. For gpt-5.5, gpt-5.5-pro, and future models, only 24h is supported.

    For older models that support both in_memory and 24h, the default depends on your organization's data retention policy:

    • Organizations without ZDR enabled default to 24h.

    • Organizations with ZDR enabled default to in_memory when prompt_cache_retention is not specified.

    • "in_memory"

    • "24h"

  • reasoning: optional object { context, effort, generate_summary, summary }

    gpt-5 and o-series models only

    Configuration options for reasoning models.

    • context: optional "auto" or "current_turn" or "all_turns"

      Controls which reasoning items are rendered back to the model on later turns. When returned on a response, this is the effective reasoning context mode used for the response.

      • "auto"

      • "current_turn"

      • "all_turns"

    • effort: optional "none" or "minimal" or "low" or 3 more

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

      • gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.

      • All models before gpt-5.1 default to medium reasoning effort, and do not support none.

      • The gpt-5-pro model defaults to (and only supports) high reasoning effort.

      • xhigh is supported for all models after gpt-5.1-codex-max.

      • "none"

      • "minimal"

      • "low"

      • "medium"

      • "high"

      • "xhigh"

    • generate_summary: optional "auto" or "concise" or "detailed"

      Deprecated: use summary instead.

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

      • "auto"

      • "concise"

      • "detailed"

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

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

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

      • "auto"

      • "concise"

      • "detailed"

  • safety_identifier: optional string

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

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

    Specifies the processing type used for serving the request.

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

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

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • status: optional "completed" or "failed" or "in_progress" or 3 more

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

    • "completed"

    • "failed"

    • "in_progress"

    • "cancelled"

    • "queued"

    • "incomplete"

  • text: optional object { format, verbosity }

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

    • Text inputs and outputs

    • Structured Outputs

    • format: optional ResponseFormatText or ResponseFormatTextJSONSchemaConfig or ResponseFormatJSONObject

      An object specifying the format that the model must output.

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

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

      Not recommended for gpt-4o and newer models:

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

      • response_format_text: object { type }

        Default response format. Used to generate text responses.

        • type: "text"

          The type of response format being defined. Always text.

      • response_format_text_json_schema_config: object { name, schema, type, 2 more }

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

        • name: string

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

        • schema: map[unknown]

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

        • type: "json_schema"

          The type of response format being defined. Always json_schema.

        • description: optional string

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

        • strict: optional boolean

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

      • response_format_json_object: object { type }

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

        • type: "json_object"

          The type of response format being defined. Always json_object.

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

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

      • "low"

      • "medium"

      • "high"

  • top_logprobs: optional number

    An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested.

  • truncation: optional "auto" or "disabled"

    The truncation strategy to use for the model response.

    • auto: If the input to this Response exceeds the model's context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation.

    • disabled (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error.

    • "auto"

    • "disabled"

  • usage: optional object { input_tokens, input_tokens_details, output_tokens, 2 more }

    Represents token usage details including input tokens, output tokens, a breakdown of output tokens, and the total tokens used.

    • input_tokens: number

      The number of input tokens.

    • input_tokens_details: object { cached_tokens }

      A detailed breakdown of the input tokens.

      • cached_tokens: number

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

    • output_tokens: number

      The number of output tokens.

    • output_tokens_details: object { reasoning_tokens }

      A detailed breakdown of the output tokens.

      • reasoning_tokens: number

        The number of reasoning tokens.

    • total_tokens: number

      The total number of tokens used.

  • user: optional string

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

Example

openai responses create \
  --api-key 'My API Key'

Response

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

Get a model response

$ openai responses retrieve

get /responses/{response_id}

Retrieves a model response with the given ID.

Parameters

• --response-id: string

  The ID of the response to retrieve.

• --include: optional array of ResponseIncludable

  Additional fields to include in the response. See the include parameter for Response creation above for more information.

• --include-obfuscation: optional boolean

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

• --starting-after: optional number

  The sequence number of the event after which to start streaming.

Returns

• response: object { id, created_at, error, 30 more }

  • id: string

    Unique identifier for this Response.

  • created_at: number

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

  • error: object { code, message }

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

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

      The error code for the response.

      • "server_error"

      • "rate_limit_exceeded"

      • "invalid_prompt"

      • "vector_store_timeout"

      • "invalid_image"

      • "invalid_image_format"

      • "invalid_base64_image"

      • "invalid_image_url"

      • "image_too_large"

      • "image_too_small"

      • "image_parse_error"

      • "image_content_policy_violation"

      • "invalid_image_mode"

      • "image_file_too_large"

      • "unsupported_image_media_type"

      • "empty_image_file"

      • "failed_to_download_image"

      • "image_file_not_found"

    • message: string

      A human-readable description of the error.

  • incomplete_details: object { reason }

    Details about why the response is incomplete.

    • reason: optional "max_output_tokens" or "content_filter"

      The reason why the response is incomplete.

      • "max_output_tokens"

      • "content_filter"

  • instructions: string or array of ResponseInputItem

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

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

    • union_member_0: string

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

    • Input item list: array of ResponseInputItem

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

      • easy_input_message: object { content, role, phase, type }

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

        • content: string or ResponseInputMessageContentList

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

          • Text input: string

            A text input to the model.

          • response_input_message_content_list: array of ResponseInputContent

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

            • response_input_text: object { text, type }

              A text input to the model.

              • text: string

                The text input to the model.

              • type: "input_text"

                The type of the input item. Always input_text.

            • response_input_image: object { detail, type, file_id, image_url }

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

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

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

                • "low"

                • "high"

                • "auto"

                • "original"

              • type: "input_image"

                The type of the input item. Always input_image.

              • file_id: optional string

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

              • image_url: optional string

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

            • response_input_file: object { type, detail, file_data, 3 more }

              A file input to the model.

              • type: "input_file"

                The type of the input item. Always input_file.

              • detail: optional "low" or "high"

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

                • "low"

                • "high"

              • file_data: optional string

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

              • file_id: optional string

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

              • file_url: optional string

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

              • filename: optional string

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

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

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

          • "user"

          • "assistant"

          • "system"

          • "developer"

        • phase: optional "commentary" or "final_answer"

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

          • "commentary"

          • "final_answer"

        • type: optional "message"

          The type of the message input. Always message.

          • "message"

      • message: object { content, role, status, type }

        A message input to the model with a role indicating instruction following hierarchy. Instructions given with the developer or system role take precedence over instructions given with the user role.

        • content: array of ResponseInputContent

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

          • response_input_text: object { text, type }

            A text input to the model.

          • response_input_image: object { detail, type, file_id, image_url }

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

          • response_input_file: object { type, detail, file_data, 3 more }

            A file input to the model.

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

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

          • "user"

          • "system"

          • "developer"

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: optional "message"

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

          • "message"

      • response_output_message: object { id, content, role, 3 more }

        An output message from the model.

        • id: string

          The unique ID of the output message.

        • content: array of ResponseOutputText or ResponseOutputRefusal

          The content of the output message.

          • response_output_text: object { annotations, text, type, logprobs }

            A text output from the model.

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

              The annotations of the text output.

              • file_citation: object { file_id, filename, index, type }

                A citation to a file.

                • file_id: string

                  The ID of the file.

                • filename: string

                  The filename of the file cited.

                • index: number

                  The index of the file in the list of files.

                • type: "file_citation"

                  The type of the file citation. Always file_citation.

              • url_citation: object { end_index, start_index, title, 2 more }

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

                • end_index: number

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

                • start_index: number

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

                • title: string

                  The title of the web resource.

                • type: "url_citation"

                  The type of the URL citation. Always url_citation.

                • url: string

                  The URL of the web resource.

              • container_file_citation: object { container_id, end_index, file_id, 3 more }

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

                • container_id: string

                  The ID of the container file.

                • end_index: number

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

                • file_id: string

                  The ID of the file.

                • filename: string

                  The filename of the container file cited.

                • start_index: number

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

                • type: "container_file_citation"

                  The type of the container file citation. Always container_file_citation.

              • file_path: object { file_id, index, type }

                A path to a file.

                • file_id: string

                  The ID of the file.

                • index: number

                  The index of the file in the list of files.

                • type: "file_path"

                  The type of the file path. Always file_path.

            • text: string

              The text output from the model.

            • type: "output_text"

              The type of the output text. Always output_text.

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

              • token: string

              • bytes: array of number

              • logprob: number

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

                • token: string

                • bytes: array of number

                • logprob: number

          • response_output_refusal: object { refusal, type }

            A refusal from the model.

            • refusal: string

              The refusal explanation from the model.

            • type: "refusal"

              The type of the refusal. Always refusal.

        • role: "assistant"

          The role of the output message. Always assistant.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: "message"

          The type of the output message. Always message.

        • phase: optional "commentary" or "final_answer"

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

          • "commentary"

          • "final_answer"

      • response_file_search_tool_call: object { id, queries, status, 2 more }

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

        • id: string

          The unique ID of the file search tool call.

        • queries: array of string

          The queries used to search for files.

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

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

          • "in_progress"

          • "searching"

          • "completed"

          • "incomplete"

          • "failed"

        • type: "file_search_call"

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

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

          The results of the file search tool call.

          • attributes: optional map[string or number or boolean]

            Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters, booleans, or numbers.

            • union_member_0: string

            • union_member_1: number

            • union_member_2: boolean

          • file_id: optional string

            The unique ID of the file.

          • filename: optional string

            The name of the file.

          • score: optional number

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

          • text: optional string

            The text that was retrieved from the file.

      • response_computer_tool_call: object { id, call_id, pending_safety_checks, 4 more }

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

        • id: string

          The unique ID of the computer call.

        • call_id: string

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

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

          The pending safety checks for the computer call.

          • id: string

            The ID of the pending safety check.

          • code: optional string

            The type of the pending safety check.

          • message: optional string

            Details about the pending safety check.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: "computer_call"

          The type of the computer call. Always computer_call.

          • "computer_call"

        • action: optional object { button, type, x, 2 more } or object { keys, type, x, y } or object { path, type, keys } or 6 more

          A click action.

          • click: object { button, type, x, 2 more }

            A click action.

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

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

              • "left"

              • "right"

              • "wheel"

              • "back"

              • "forward"

            • type: "click"

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

            • x: number

              The x-coordinate where the click occurred.

            • y: number

              The y-coordinate where the click occurred.

            • keys: optional array of string

              The keys being held while clicking.

          • double_click: object { keys, type, x, y }

            A double click action.

            • keys: array of string

              The keys being held while double-clicking.

            • type: "double_click"

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

            • x: number

              The x-coordinate where the double click occurred.

            • y: number

              The y-coordinate where the double click occurred.

          • drag: object { path, type, keys }

            A drag action.

            • path: array of object { x, y }

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

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

              • x: number

                The x-coordinate.

              • y: number

                The y-coordinate.

            • type: "drag"

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

            • keys: optional array of string

              The keys being held while dragging the mouse.

          • keypress: object { keys, type }

            A collection of keypresses the model would like to perform.

            • keys: array of string

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

            • type: "keypress"

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

          • move: object { type, x, y, keys }

            A mouse move action.

            • type: "move"

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

            • x: number

              The x-coordinate to move to.

            • y: number

              The y-coordinate to move to.

            • keys: optional array of string

              The keys being held while moving the mouse.

          • screenshot: object { type }

            A screenshot action.

          • scroll: object { scroll_x, scroll_y, type, 3 more }

            A scroll action.

            • scroll_x: number

              The horizontal scroll distance.

            • scroll_y: number

              The vertical scroll distance.

            • type: "scroll"

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

            • x: number

              The x-coordinate where the scroll occurred.

            • y: number

              The y-coordinate where the scroll occurred.

            • keys: optional array of string

              The keys being held while scrolling.

          • type: object { text, type }

            An action to type in text.

            • text: string

              The text to type.

            • type: "type"

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

          • wait: object { type }

            A wait action.

        • actions: optional array of ComputerAction

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

          • click: object { button, type, x, 2 more }

            A click action.

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

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

              • "left"

              • "right"

              • "wheel"

              • "back"

              • "forward"

            • type: "click"

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

            • x: number

              The x-coordinate where the click occurred.

            • y: number

              The y-coordinate where the click occurred.

            • keys: optional array of string

              The keys being held while clicking.

          • double_click: object { keys, type, x, y }

            A double click action.

            • keys: array of string

              The keys being held while double-clicking.

            • type: "double_click"

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

            • x: number

              The x-coordinate where the double click occurred.

            • y: number

              The y-coordinate where the double click occurred.

          • drag: object { path, type, keys }

            A drag action.

            • path: array of object { x, y }

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

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

              • x: number

                The x-coordinate.

              • y: number

                The y-coordinate.

            • type: "drag"

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

            • keys: optional array of string

              The keys being held while dragging the mouse.

          • keypress: object { keys, type }

            A collection of keypresses the model would like to perform.

            • keys: array of string

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

            • type: "keypress"

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

          • move: object { type, x, y, keys }

            A mouse move action.

            • type: "move"

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

            • x: number

              The x-coordinate to move to.

            • y: number

              The y-coordinate to move to.

            • keys: optional array of string

              The keys being held while moving the mouse.

          • screenshot: object { type }

            A screenshot action.

          • scroll: object { scroll_x, scroll_y, type, 3 more }

            A scroll action.

            • scroll_x: number

              The horizontal scroll distance.

            • scroll_y: number

              The vertical scroll distance.

            • type: "scroll"

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

            • x: number

              The x-coordinate where the scroll occurred.

            • y: number

              The y-coordinate where the scroll occurred.

            • keys: optional array of string

              The keys being held while scrolling.

          • type: object { text, type }

            An action to type in text.

            • text: string

              The text to type.

            • type: "type"

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

          • wait: object { type }

            A wait action.

      • computer_call_output: object { call_id, output, type, 3 more }

        The output of a computer tool call.

        • call_id: string

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

        • output: object { type, file_id, image_url }

          A computer screenshot image used with the computer use tool.

          • type: "computer_screenshot"

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

          • file_id: optional string

            The identifier of an uploaded file that contains the screenshot.

          • image_url: optional string

            The URL of the screenshot image.

        • type: "computer_call_output"

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

        • id: optional string

          The ID of the computer tool call output.

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

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

          • id: string

            The ID of the pending safety check.

          • code: optional string

            The type of the pending safety check.

          • message: optional string

            Details about the pending safety check.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • response_function_web_search: object { id, action, status, type }

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

        • id: string

          The unique ID of the web search tool call.

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

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

          • search: object { type, queries, query, sources }

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

            • type: "search"

              The action type.

            • queries: optional array of string

              The search queries.

            • query: optional string

              The search query.

            • sources: optional array of object { type, url }

              The sources used in the search.

              • type: "url"

                The type of source. Always url.

              • url: string

                The URL of the source.

          • open_page: object { type, url }

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

            • type: "open_page"

              The action type.

            • url: optional string

              The URL opened by the model.

          • find_in_page: object { pattern, type, url }

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

            • pattern: string

              The pattern or text to search for within the page.

            • type: "find_in_page"

              The action type.

            • url: string

              The URL of the page searched for the pattern.

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

          The status of the web search tool call.

          • "in_progress"

          • "searching"

          • "completed"

          • "failed"

        • type: "web_search_call"

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

      • response_function_tool_call: object { arguments, call_id, name, 4 more }

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

        • arguments: string

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

        • call_id: string

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

        • name: string

          The name of the function to run.

        • type: "function_call"

          The type of the function tool call. Always function_call.

        • id: optional string

          The unique ID of the function tool call.

        • namespace: optional string

          The namespace of the function to run.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • function_call_output: object { call_id, output, type, 2 more }

        The output of a function tool call.

        • call_id: string

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

        • output: string or ResponseFunctionCallOutputItemList

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

          • union_member_0: string

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

          • response_function_call_output_item_list: array of ResponseFunctionCallOutputItem

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

            • response_input_text_content: object { text, type }

              A text input to the model.

              • text: string

                The text input to the model.

              • type: "input_text"

                The type of the input item. Always input_text.

            • response_input_image_content: object { type, detail, file_id, image_url }

              An image input to the model. Learn about image inputs

              • type: "input_image"

                The type of the input item. Always input_image.

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

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

                • "low"

                • "high"

                • "auto"

                • "original"

              • file_id: optional string

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

              • image_url: optional string

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

            • response_input_file_content: object { type, detail, file_data, 3 more }

              A file input to the model.

              • type: "input_file"

                The type of the input item. Always input_file.

              • detail: optional "low" or "high"

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

                • "low"

                • "high"

              • file_data: optional string

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

              • file_id: optional string

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

              • file_url: optional string

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

              • filename: optional string

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

        • type: "function_call_output"

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

        • id: optional string

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

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • tool_search_call: object { arguments, type, id, 3 more }

        • arguments: unknown

          The arguments supplied to the tool search call.

        • type: "tool_search_call"

          The item type. Always tool_search_call.

        • id: optional string

          The unique ID of this tool search call.

        • call_id: optional string

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

        • execution: optional "server" or "client"

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

          • "server"

          • "client"

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

          The status of the tool search call.

          • "in_progress"

          • "completed"

          • "incomplete"

      • response_tool_search_output_item_param: object { tools, type, id, 3 more }

        • tools: array of Tool

          The loaded tool definitions returned by the tool search output.

          • function_tool: object { name, parameters, strict, 3 more }

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

            • name: string

              The name of the function to call.

            • parameters: map[unknown]

              A JSON schema object describing the parameters of the function.

            • strict: boolean

              Whether to enforce strict parameter validation. Default true.

            • type: "function"

              The type of the function tool. Always function.

            • defer_loading: optional boolean

              Whether this function is deferred and loaded via tool search.

            • description: optional string

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

          • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

            • type: "file_search"

              The type of the file search tool. Always file_search.

            • vector_store_ids: array of string

              The IDs of the vector stores to search.

            • filters: optional ComparisonFilter or CompoundFilter

              A filter to apply.

              • comparison_filter: object { key, type, value }

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

                • key: string

                  The key to compare against the value.

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

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

                  • eq: equals

                  • ne: not equal

                  • gt: greater than

                  • gte: greater than or equal

                  • lt: less than

                  • lte: less than or equal

                  • in: in

                  • nin: not in

                  • "eq"

                  • "ne"

                  • "gt"

                  • "gte"

                  • "lt"

                  • "lte"

                  • "in"

                  • "nin"

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

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

                  • union_member_0: string

                  • union_member_1: number

                  • union_member_2: boolean

                  • union_member_3: array of string or number

                    • union_member_0: string

                    • union_member_1: number

              • compound_filter: object { filters, type }

                Combine multiple filters using and or or.

                • filters: array of ComparisonFilter or unknown

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

                  • comparison_filter: object { key, type, value }

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

                  • union_member_1: unknown

                • type: "and" or "or"

                  Type of operation: and or or.

                  • "and"

                  • "or"

            • max_num_results: optional number

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

            • ranking_options: optional object { hybrid_search, ranker, score_threshold }

              Ranking options for search.

              • hybrid_search: optional object { embedding_weight, text_weight }

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

                • embedding_weight: number

                  The weight of the embedding in the reciprocal ranking fusion.

                • text_weight: number

                  The weight of the text in the reciprocal ranking fusion.

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

                The ranker to use for the file search.

                • "auto"

                • "default-2024-11-15"

              • score_threshold: optional number

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

          • computer_tool: object { type }

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

            • type: "computer"

              The type of the computer tool. Always computer.

          • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

            • display_height: number

              The height of the computer display.

            • display_width: number

              The width of the computer display.

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

              The type of computer environment to control.

              • "windows"

              • "mac"

              • "linux"

              • "ubuntu"

              • "browser"

            • type: "computer_use_preview"

              The type of the computer use tool. Always computer_use_preview.

          • web_search_tool: object { type, filters, search_context_size, user_location }

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

            • type: "web_search" or "web_search_2025_08_26"

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

              • "web_search"

              • "web_search_2025_08_26"

            • filters: optional object { allowed_domains }

              Filters for the search.

              • allowed_domains: optional array of string

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

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

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

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

              • "low"

              • "medium"

              • "high"

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

              The approximate location of the user.

              • city: optional string

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

              • country: optional string

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

              • region: optional string

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

              • timezone: optional string

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

              • type: optional "approximate"

                The type of location approximation. Always approximate.

                • "approximate"

          • mcp: object { server_label, type, allowed_tools, 8 more }

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

            • server_label: string

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

            • type: "mcp"

              The type of the MCP tool. Always mcp.

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

              List of allowed tool names or a filter object.

              • MCP allowed tools: array of string

                A string array of allowed tool names

              • MCP tool filter: object { read_only, tool_names }

                A filter object to specify which tools are allowed.

                • read_only: optional boolean

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

                • tool_names: optional array of string

                  List of allowed tool names.

            • authorization: optional string

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

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

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

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • "connector_dropbox"

              • "connector_gmail"

              • "connector_googlecalendar"

              • "connector_googledrive"

              • "connector_microsoftteams"

              • "connector_outlookcalendar"

              • "connector_outlookemail"

              • "connector_sharepoint"

            • defer_loading: optional boolean

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

            • headers: optional map[string]

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

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

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

              • MCP tool approval filter: object { always, never }

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

                • always: optional object { read_only, tool_names }

                  A filter object to specify which tools are allowed.

                  • read_only: optional boolean

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

                  • tool_names: optional array of string

                    List of allowed tool names.

                • never: optional object { read_only, tool_names }

                  A filter object to specify which tools are allowed.

                  • read_only: optional boolean

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

                  • tool_names: optional array of string

                    List of allowed tool names.

              • MCP tool approval setting: "always" or "never"

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

                • "always"

                • "never"

            • server_description: optional string

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

            • server_url: optional string

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

            • tunnel_id: optional string

              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.

          • code_interpreter: object { container, type }

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

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

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

              • union_member_0: string

                The container ID.

              • CodeInterpreterToolAuto: object { type, file_ids, memory_limit, network_policy }

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

                • type: "auto"

                  Always auto.

                • file_ids: optional array of string

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

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

                  The memory limit for the code interpreter container.

                  • "1g"

                  • "4g"

                  • "16g"

                  • "64g"

                • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

                  Network access policy for the container.

                  • container_network_policy_disabled: object { type }

                    • type: "disabled"

                      Disable outbound network access. Always disabled.

                  • container_network_policy_allowlist: object { allowed_domains, type, domain_secrets }

                    • allowed_domains: array of string

                      A list of allowed domains when type is allowlist.

                    • type: "allowlist"

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

                    • domain_secrets: optional array of ContainerNetworkPolicyDomainSecret

                      Optional domain-scoped secrets for allowlisted domains.

                      • domain: string

                        The domain associated with the secret.

                      • name: string

                        The name of the secret to inject for the domain.

                      • value: string

                        The secret value to inject for the domain.

            • type: "code_interpreter"

              The type of the code interpreter tool. Always code_interpreter.

          • image_generation: object { type, action, background, 9 more }

            A tool that generates images using the GPT image models.

            • type: "image_generation"

              The type of the image generation tool. Always image_generation.

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

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

              • "generate"

              • "edit"

              • "auto"

            • background: optional "transparent" or "opaque" or "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 "high" or "low"

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

              • "high"

              • "low"

            • input_image_mask: optional object { file_id, image_url }

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

              • file_id: optional string

                File ID for the mask image.

              • image_url: optional string

                Base64-encoded mask image.

            • model: optional string or "gpt-image-1" or "gpt-image-1-mini" or "gpt-image-2" or 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 "auto" or "low"

              Moderation level for the generated image. Default: auto.

              • "auto"

              • "low"

            • output_compression: optional number

              Compression level for the output image. Default: 100.

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

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

              • "png"

              • "webp"

              • "jpeg"

            • partial_images: optional number

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

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

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

              • "low"

              • "medium"

              • "high"

              • "auto"

            • size: optional string or "1024x1024" or "1024x1536" or "1536x1024" or "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"

          • local_shell: object { type }

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

          • function_shell_tool: object { type, environment }

            A tool that allows the model to execute shell commands.

            • type: "shell"

              The type of the shell tool. Always shell.

            • environment: optional ContainerAuto or LocalEnvironment or ContainerReference

              • container_auto: object { type, file_ids, memory_limit, 2 more }

                • type: "container_auto"

                  Automatically creates a container for this request

                • file_ids: optional array of string

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

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

                  The memory limit for the container.

                  • "1g"

                  • "4g"

                  • "16g"

                  • "64g"

                • network_policy: optional ContainerNetworkPolicyDisabled or ContainerNetworkPolicyAllowlist

                  Network access policy for the container.

                  • container_network_policy_disabled: object { type }

                  • container_network_policy_allowlist: object { allowed_domains, type, domain_secrets }

                • skills: optional array of SkillReference or InlineSkill

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

                  • skill_reference: object { skill_id, type, version }

                    • skill_id: string

                      The ID of the referenced skill.

                    • type: "skill_reference"

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

                    • version: optional string

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

                  • inline_skill: object { description, name, source, type }

                    • description: string

                      The description of the skill.

                    • name: string

                      The name of the skill.

                    • source: object { data, media_type, type }

                      Inline skill payload

                      • data: string

                        Base64-encoded skill zip bundle.

                      • media_type: "application/zip"

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

                      • type: "base64"

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

                    • type: "inline"

                      Defines an inline skill for this request.

              • local_environment: object { type, skills }

                • type: "local"

                  Use a local computer environment.

                • skills: optional array of LocalSkill

                  An optional list of skills.

                  • description: string

                    The description of the skill.

                  • name: string

                    The name of the skill.

                  • path: string

                    The path to the directory containing the skill.

              • container_reference: object { container_id, type }

                • container_id: string

                  The ID of the referenced container.

                • type: "container_reference"

                  References a container created with the /v1/containers endpoint

          • custom_tool: object { name, type, defer_loading, 2 more }

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

            • name: string

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

            • type: "custom"

              The type of the custom tool. Always custom.

            • defer_loading: optional boolean

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

            • description: optional string

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

            • format: optional object { type } or object { definition, syntax, type }

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

              • text: object { type }

                Unconstrained free-form text.

              • grammar: object { definition, syntax, type }

                A grammar defined by the user.

                • definition: string

                  The grammar definition.

                • syntax: "lark" or "regex"

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

                  • "lark"

                  • "regex"

                • type: "grammar"

                  Grammar format. Always grammar.

          • namespace_tool: object { description, name, tools, type }

            Groups function/custom tools under a shared namespace.

            • description: string

              A description of the namespace shown to the model.

            • name: string

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

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

              The function/custom tools available inside this namespace.

              • function: object { name, type, defer_loading, 3 more }

                • name: string

                • type: "function"

                • defer_loading: optional boolean

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

                • description: optional string

                • parameters: optional unknown

                • strict: optional boolean

              • custom_tool: object { name, type, defer_loading, 2 more }

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

                • name: string

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

                • type: "custom"

                  The type of the custom tool. Always custom.

                • defer_loading: optional boolean

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

                • description: optional string

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

                • format: optional object { type } or object { definition, syntax, type }

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

            • type: "namespace"

              The type of the tool. Always namespace.

          • tool_search_tool: object { type, description, execution, parameters }

            Hosted or BYOT tool search configuration for deferred tools.

            • type: "tool_search"

              The type of the tool. Always tool_search.

            • description: optional string

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

            • execution: optional "server" or "client"

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

              • "server"

              • "client"

            • parameters: optional unknown

              Parameter schema for a client-executed tool search tool.

          • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

            • type: "web_search_preview" or "web_search_preview_2025_03_11"

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

              • "web_search_preview"

              • "web_search_preview_2025_03_11"

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

              • "text"

              • "image"

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

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

              • "low"

              • "medium"

              • "high"

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

              The user's location.

              • type: "approximate"

                The type of location approximation. Always approximate.

              • city: optional string

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

              • country: optional string

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

              • region: optional string

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

              • timezone: optional string

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

          • apply_patch_tool: object { type }

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

            • type: "apply_patch"

              The type of the tool. Always apply_patch.

        • type: "tool_search_output"

          The item type. Always tool_search_output.

        • id: optional string

          The unique ID of this tool search output.

        • call_id: optional string

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

        • execution: optional "server" or "client"

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

          • "server"

          • "client"

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

          The status of the tool search output.

          • "in_progress"

          • "completed"

          • "incomplete"

      • additional_tools: object { role, tools, type, id }

        • role: "developer"

          The role that provided the additional tools. Only developer is supported.

        • tools: array of Tool

          A list of additional tools made available at this item.

          • function_tool: object { name, parameters, strict, 3 more }

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

          • file_search_tool: object { type, vector_store_ids, filters, 2 more }

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

          • computer_tool: object { type }

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

          • computer_use_preview_tool: object { display_height, display_width, environment, type }

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

          • web_search_tool: object { type, filters, search_context_size, user_location }

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

          • mcp: object { server_label, type, allowed_tools, 8 more }

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

          • code_interpreter: object { container, type }

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

          • image_generation: object { type, action, background, 9 more }

            A tool that generates images using the GPT image models.

          • local_shell: object { type }

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

          • function_shell_tool: object { type, environment }

            A tool that allows the model to execute shell commands.

          • custom_tool: object { name, type, defer_loading, 2 more }

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

          • namespace_tool: object { description, name, tools, type }

            Groups function/custom tools under a shared namespace.

          • tool_search_tool: object { type, description, execution, parameters }

            Hosted or BYOT tool search configuration for deferred tools.

          • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

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

          • apply_patch_tool: object { type }

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

        • type: "additional_tools"

          The item type. Always additional_tools.

        • id: optional string

          The unique ID of this additional tools item.

      • response_reasoning_item: object { id, summary, type, 3 more }

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

        • id: string

          The unique identifier of the reasoning content.

        • summary: array of object { text, type }

          Reasoning summary content.

          • text: string

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

          • type: "summary_text"

            The type of the object. Always summary_text.

        • type: "reasoning"

          The type of the object. Always reasoning.

        • content: optional array of object { text, type }

          Reasoning text content.

          • text: string

            The reasoning text from the model.

          • type: "reasoning_text"

            The type of the reasoning text. Always reasoning_text.

        • encrypted_content: optional string

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

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • response_compaction_item_param: object { encrypted_content, type, id }

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

        • encrypted_content: string

          The encrypted content of the compaction summary.

        • type: "compaction"

          The type of the item. Always compaction.

        • id: optional string

          The ID of the compaction item.

      • image_generation_call: object { id, result, status, type }

        An image generation request made by the model.

        • id: string

          The unique ID of the image generation call.

        • result: string

          The generated image encoded in base64.

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

          The status of the image generation call.

          • "in_progress"

          • "completed"

          • "generating"

          • "failed"

        • type: "image_generation_call"

          The type of the image generation call. Always image_generation_call.

      • response_code_interpreter_tool_call: object { id, code, container_id, 3 more }

        A tool call to run code.

        • id: string

          The unique ID of the code interpreter tool call.

        • code: string

          The code to run, or null if not available.

        • container_id: string

          The ID of the container used to run the code.

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

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

          • logs: object { logs, type }

            The logs output from the code interpreter.

            • logs: string

              The logs output from the code interpreter.

            • type: "logs"

              The type of the output. Always logs.

          • image: object { type, url }

            The image output from the code interpreter.

            • type: "image"

              The type of the output. Always image.

            • url: string

              The URL of the image output from the code interpreter.

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

          • "interpreting"

          • "failed"

        • type: "code_interpreter_call"

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

      • local_shell_call: object { id, action, call_id, 2 more }

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

        • id: string

          The unique ID of the local shell call.

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

          Execute a shell command on the server.

          • command: array of string

            The command to run.

          • env: map[string]

            Environment variables to set for the command.

          • type: "exec"

            The type of the local shell action. Always exec.

          • timeout_ms: optional number

            Optional timeout in milliseconds for the command.

          • user: optional string

            Optional user to run the command as.

          • working_directory: optional string

            Optional working directory to run the command in.

        • call_id: string

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

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

          The status of the local shell call.

          • "in_progress"

          • "completed"

          • "incomplete"

        • type: "local_shell_call"

          The type of the local shell call. Always local_shell_call.

      • local_shell_call_output: object { id, output, type, status }

        The output of a local shell tool call.

        • id: string

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

        • output: string

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

        • type: "local_shell_call_output"

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

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • shell_call: object { action, call_id, type, 3 more }

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

        • action: object { commands, max_output_length, timeout_ms }

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

          • commands: array of string

            Ordered shell commands for the execution environment to run.

          • max_output_length: optional number

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

          • timeout_ms: optional number

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

        • call_id: string

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

        • type: "shell_call"

          The type of the item. Always shell_call.

        • id: optional string

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

        • environment: optional LocalEnvironment or ContainerReference

          The environment to execute the shell commands in.

          • local_environment: object { type, skills }

          • container_reference: object { container_id, type }

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

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

          • "in_progress"

          • "completed"

          • "incomplete"

      • shell_call_output: object { call_id, output, type, 3 more }

        The streamed output items emitted by a shell tool call.

        • call_id: string

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

        • output: array of ResponseFunctionShellCallOutputContent

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

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

            The exit or timeout outcome associated with this shell call.

            • timeout: object { type }

              Indicates that the shell call exceeded its configured time limit.

            • exit: object { exit_code, type }

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

              • exit_code: number

                The exit code returned by the shell process.

              • type: "exit"

                The outcome type. Always exit.

          • stderr: string

            Captured stderr output for the shell call.

          • stdout: string

            Captured stdout output for the shell call.

        • type: "shell_call_output"

          The type of the item. Always shell_call_output.

        • id: optional string

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

        • max_output_length: optional number

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

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

          The status of the shell call output.

          • "in_progress"

          • "completed"

          • "incomplete"

      • apply_patch_call: object { call_id, operation, status, 2 more }

        A tool call representing a request to create, delete, or update files using diff patches.

        • call_id: string

          The unique ID of the apply patch tool call generated by the model.

        • operation: object { diff, path, type } or object { path, type } or object { diff, path, type }

          The specific create, delete, or update instruction for the apply_patch tool call.

          • create_file: object { diff, path, type }

            Instruction for creating a new file via the apply_patch tool.

            • diff: string

              Unified diff content to apply when creating the file.

            • path: string

              Path of the file to create relative to the workspace root.

            • type: "create_file"

              The operation type. Always create_file.

          • delete_file: object { path, type }

            Instruction for deleting an existing file via the apply_patch tool.

            • path: string

              Path of the file to delete relative to the workspace root.

            • type: "delete_file"

              The operation type. Always delete_file.

          • update_file: object { diff, path, type }

            Instruction for updating an existing file via the apply_patch tool.

            • diff: string

              Unified diff content to apply to the existing file.

            • path: string

              Path of the file to update relative to the workspace root.

            • type: "update_file"

              The operation type. Always update_file.

        • status: "in_progress" or "completed"

          The status of the apply patch tool call. One of in_progress or completed.

          • "in_progress"

          • "completed"

        • type: "apply_patch_call"

          The type of the item. Always apply_patch_call.

        • id: optional string

          The unique ID of the apply patch tool call. Populated when this item is returned via API.

      • apply_patch_call_output: object { call_id, status, type, 2 more }

        The streamed output emitted by an apply patch tool call.

        • call_id: string

          The unique ID of the apply patch tool call generated by the model.

        • status: "completed" or "failed"

          The status of the apply patch tool call output. One of completed or failed.

          • "completed"

          • "failed"

        • type: "apply_patch_call_output"

          The type of the item. Always apply_patch_call_output.

        • id: optional string

          The unique ID of the apply patch tool call output. Populated when this item is returned via API.

        • output: optional string

          Optional human-readable log text from the apply patch tool (e.g., patch results or errors).

      • mcp_list_tools: object { id, server_label, tools, 2 more }

        A list of tools available on an MCP server.

        • id: string

          The unique ID of the list.

        • server_label: string

          The label of the MCP server.

        • tools: array of object { input_schema, name, annotations, description }

          The tools available on the server.

          • input_schema: unknown

            The JSON schema describing the tool's input.

          • name: string

            The name of the tool.

          • annotations: optional unknown

            Additional annotations about the tool.

          • description: optional string

            The description of the tool.

        • type: "mcp_list_tools"

          The type of the item. Always mcp_list_tools.

        • error: optional string

          Error message if the server could not list tools.

      • mcp_approval_request: object { id, arguments, name, 2 more }

        A request for human approval of a tool invocation.

        • id: string

          The unique ID of the approval request.

        • arguments: string

          A JSON string of arguments for the tool.

        • name: string

          The name of the tool to run.

        • server_label: string

          The label of the MCP server making the request.

        • type: "mcp_approval_request"

          The type of the item. Always mcp_approval_request.

      • mcp_approval_response: object { approval_request_id, approve, type, 2 more }

        A response to an MCP approval request.

        • approval_request_id: string

          The ID of the approval request being answered.

        • approve: boolean

          Whether the request was approved.

        • type: "mcp_approval_response"

          The type of the item. Always mcp_approval_response.

        • id: optional string

          The unique ID of the approval response

        • reason: optional string

          Optional reason for the decision.

      • mcp_call: object { id, arguments, name, 6 more }

        An invocation of a tool on an MCP server.

        • id: string

          The unique ID of the tool call.

        • arguments: string

          A JSON string of the arguments passed to the tool.

        • name: string

          The name of the tool that was run.

        • server_label: string

          The label of the MCP server running the tool.

        • type: "mcp_call"

          The type of the item. Always mcp_call.

        • approval_request_id: optional string

          Unique identifier for the MCP tool call approval request. Include this value in a subsequent mcp_approval_response input to approve or reject the corresponding tool call.

        • error: optional string

          The error from the tool call, if any.

        • output: optional string

          The output from the tool call.

        • status: optional "in_progress" or "completed" or "incomplete" or 2 more

          The status of the tool call. One of in_progress, completed, incomplete, calling, or failed.

          • "in_progress"

          • "completed"

          • "incomplete"

          • "calling"

          • "failed"

      • response_custom_tool_call_output: object { call_id, output, type, id }

        The output of a custom tool call from your code, being sent back to the model.

        • call_id: string

          The call ID, used to map this custom tool call output to a custom tool call.

        • output: string or array of ResponseInputText or ResponseInputImage or ResponseInputFile

          The output from the custom tool call generated by your code. Can be a string or an list of output content.

          • string output: string

            A string of the output of the custom tool call.

          • output content list: array of ResponseInputText or ResponseInputImage or ResponseInputFile

            Text, image, or file output of the custom tool call.

            • response_input_text: object { text, type }

              A text input to the model.

              • text: string

                The text input to the model.

              • type: "input_text"

                The type of the input item. Always input_text.

            • response_input_image: object { detail, type, file_id, image_url }

              An image input to the model. Learn about image inputs.

              • detail: "low" or "high" or "auto" or "original"

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

              • type: "input_image"

                The type of the input item. Always input_image.

              • file_id: optional string

                The ID of the file to be sent to the model.

              • image_url: optional string

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • response_input_file: object { type, detail, file_data, 3 more }

              A file input to the model.

              • type: "input_file"

                The type of the input item. Always input_file.

              • detail: optional "low" or "high"

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

              • file_data: optional string

                The content of the file to be sent to the model.

              • file_id: optional string

                The ID of the file to be sent to the model.

              • file_url: optional string

                The URL of the file to be sent to the model.

              • filename: optional string

                The name of the file to be sent to the model.

        • type: "custom_tool_call_output"

          The type of the custom tool call output. Always custom_tool_call_output.

        • id: optional string

          The unique ID of the custom tool call output in the OpenAI platform.

      • response_custom_tool_call: object { call_id, input, name, 3 more }

        A call to a custom tool created by the model.

        • call_id: string

          An identifier used to map this custom tool call to a tool call output.

        • input: string

          The input for the custom tool call generated by the model.

        • name: string

          The name of the custom tool being called.

        • type: "custom_tool_call"

          The type of the custom tool call. Always custom_tool_call.

        • id: optional string

          The unique ID of the custom tool call in the OpenAI platform.

        • namespace: optional string

          The namespace of the custom tool being called.

      • compaction_trigger: object { type }

        Compacts the current context. Must be the final input item.

      • item_reference: object { id, type }

        An internal identifier for an item to reference.

        • id: string

          The ID of the item to reference.

        • type: optional "item_reference"

          The type of item to reference. Always item_reference.

          • "item_reference"

  • metadata: map[string]

    Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

    Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

  • model: string or ChatModel or "o1-pro" or "o1-pro-2025-03-19" or "o3-pro" or 11 more

    Model ID used to generate the response, like gpt-4o or o3. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.

    • union_member_0: string

    • chat_model: "gpt-5.4" or "gpt-5.4-mini" or "gpt-5.4-nano" or 75 more

      • "gpt-5.4"

      • "gpt-5.4-mini"

      • "gpt-5.4-nano"

      • "gpt-5.4-mini-2026-03-17"

      • "gpt-5.4-nano-2026-03-17"

      • "gpt-5.3-chat-latest"

      • "gpt-5.2"

      • "gpt-5.2-2025-12-11"

      • "gpt-5.2-chat-latest"

      • "gpt-5.2-pro"

      • "gpt-5.2-pro-2025-12-11"

      • "gpt-5.1"

      • "gpt-5.1-2025-11-13"

      • "gpt-5.1-codex"

      • "gpt-5.1-mini"

      • "gpt-5.1-chat-latest"

      • "gpt-5"

      • "gpt-5-mini"

      • "gpt-5-nano"

      • "gpt-5-2025-08-07"

      • "gpt-5-mini-2025-08-07"

      • "gpt-5-nano-2025-08-07"

      • "gpt-5-chat-latest"

      • "gpt-4.1"

      • "gpt-4.1-mini"

      • "gpt-4.1-nano"

      • "gpt-4.1-2025-04-14"

      • "gpt-4.1-mini-2025-04-14"

      • "gpt-4.1-nano-2025-04-14"

      • "o4-mini"

      • "o4-mini-2025-04-16"

      • "o3"

      • "o3-2025-04-16"

      • "o3-mini"

      • "o3-mini-2025-01-31"

      • "o1"

      • "o1-2024-12-17"

      • "o1-preview"

      • "o1-preview-2024-09-12"

      • "o1-mini"

      • "o1-mini-2024-09-12"

      • "gpt-4o"

      • "gpt-4o-2024-11-20"

      • "gpt-4o-2024-08-06"

      • "gpt-4o-2024-05-13"

      • "gpt-4o-audio-preview"

      • "gpt-4o-audio-preview-2024-10-01"

      • "gpt-4o-audio-preview-2024-12-17"

      • "gpt-4o-audio-preview-2025-06-03"

      • "gpt-4o-mini-audio-preview"

      • "gpt-4o-mini-audio-preview-2024-12-17"

      • "gpt-4o-search-preview"

      • "gpt-4o-mini-search-preview"

      • "gpt-4o-search-preview-2025-03-11"

      • "gpt-4o-mini-search-preview-2025-03-11"

      • "chatgpt-4o-latest"

      • "codex-mini-latest"

      • "gpt-4o-mini"

      • "gpt-4o-mini-2024-07-18"

      • "gpt-4-turbo"

      • "gpt-4-turbo-2024-04-09"

      • "gpt-4-0125-preview"

      • "gpt-4-turbo-preview"

      • "gpt-4-1106-preview"

      • "gpt-4-vision-preview"

      • "gpt-4"

      • "gpt-4-0314"

      • "gpt-4-0613"

      • "gpt-4-32k"

      • "gpt-4-32k-0314"

      • "gpt-4-32k-0613"

      • "gpt-3.5-turbo"

      • "gpt-3.5-turbo-16k"

      • "gpt-3.5-turbo-0301"

      • "gpt-3.5-turbo-0613"

      • "gpt-3.5-turbo-1106"

      • "gpt-3.5-turbo-0125"

      • "gpt-3.5-turbo-16k-0613"

    • ResponsesOnlyModel: "o1-pro" or "o1-pro-2025-03-19" or "o3-pro" or 11 more

      • "o1-pro"

      • "o1-pro-2025-03-19"

      • "o3-pro"

      • "o3-pro-2025-06-10"

      • "o3-deep-research"

      • "o3-deep-research-2025-06-26"

      • "o4-mini-deep-research"

      • "o4-mini-deep-research-2025-06-26"

      • "computer-use-preview"

      • "computer-use-preview-2025-03-11"

      • "gpt-5-codex"

      • "gpt-5-pro"

      • "gpt-5-pro-2025-10-06"

      • "gpt-5.1-codex-max"

  • object: "response"

    The object type of this resource - always set to response.

  • output: array of ResponseOutputItem

    An array of content items generated by the model.

    • The length and order of items in the output array is dependent on the model's response.

    • Rather than accessing the first item in the output array and assuming it's an assistant message with the content generated by the model, you might consider using the output_text property where supported in SDKs.

    • response_output_message: object { id, content, role, 3 more }

      An output message from the model.

      • id: string

        The unique ID of the output message.

      • content: array of ResponseOutputText or ResponseOutputRefusal

        The content of the output message.

      • role: "assistant"

        The role of the output message. Always assistant.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

      • type: "message"

        The type of the output message. Always message.

      • phase: optional "commentary" or "final_answer"

        Labels an assistant message as intermediate commentary (commentary) or the final answer (final_answer). For models like gpt-5.3-codex and beyond, when sending follow-up requests, preserve and resend phase on all assistant messages — dropping it can degrade performance. Not used for user messages.

    • response_file_search_tool_call: object { id, queries, status, 2 more }

      The results of a file search tool call. See the file search guide for more information.

      • id: string

        The unique ID of the file search tool call.

      • queries: array of string

        The queries used to search for files.

      • status: "in_progress" or "searching" or "completed" or 2 more

        The status of the file search tool call. One of in_progress, searching, incomplete or failed,

      • type: "file_search_call"

        The type of the file search tool call. Always file_search_call.

      • results: optional array of object { attributes, file_id, filename, 2 more }

        The results of the file search tool call.

    • response_function_tool_call: object { arguments, call_id, name, 4 more }

      A tool call to run a function. See the function calling guide for more information.

      • arguments: string

        A JSON string of the arguments to pass to the function.

      • call_id: string

        The unique ID of the function tool call generated by the model.

      • name: string

        The name of the function to run.

      • type: "function_call"

        The type of the function tool call. Always function_call.

      • id: optional string

        The unique ID of the function tool call.

      • namespace: optional string

        The namespace of the function to run.

      • status: optional "in_progress" or "completed" or "incomplete"

        The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

    • response_function_tool_call_output_item: object { id, call_id, output, 3 more }

      • id: string

        The unique ID of the function call tool output.

      • call_id: string

        The unique ID of the function tool call generated by the model.

      • output: string or array of ResponseInputText or ResponseInputImage or ResponseInputFile

        The output from the function call generated by your code. Can be a string or an list of output content.

        • string output: string

          A string of the output of the function call.

        • output content list: array of ResponseInputText or ResponseInputImage or ResponseInputFile

          Text, image, or file output of the function call.

          • response_input_text: object { text, type }

            A text input to the model.

          • response_input_image: object { detail, type, file_id, image_url }

            An image input to the model. Learn about image inputs.

          • response_input_file: object { type, detail, file_data, 3 more }

            A file input to the model.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "function_call_output"

        The type of the function tool call output. Always function_call_output.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_function_web_search: object { id, action, status, type }

      The results of a web search tool call. See the web search guide for more information.

      • id: string

        The unique ID of the web search tool call.

      • action: object { type, queries, query, sources } or object { type, url } or object { pattern, type, url }

        An object describing the specific action taken in this web search call. Includes details on how the model used the web (search, open_page, find_in_page).

      • status: "in_progress" or "searching" or "completed" or "failed"

        The status of the web search tool call.

      • type: "web_search_call"

        The type of the web search tool call. Always web_search_call.

    • response_computer_tool_call: object { id, call_id, pending_safety_checks, 4 more }

      A tool call to a computer use tool. See the computer use guide for more information.

      • id: string

        The unique ID of the computer call.

      • call_id: string

        An identifier used when responding to the tool call with output.

      • pending_safety_checks: array of object { id, code, message }

        The pending safety checks for the computer call.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

      • type: "computer_call"

        The type of the computer call. Always computer_call.

      • action: optional object { button, type, x, 2 more } or object { keys, type, x, y } or object { path, type, keys } or 6 more

        A click action.

      • actions: optional array of ComputerAction

        Flattened batched actions for computer_use. Each action includes an type discriminator and action-specific fields.

    • response_computer_tool_call_output_item: object { id, call_id, output, 4 more }

      • id: string

        The unique ID of the computer call tool output.

      • call_id: string

        The ID of the computer tool call that produced the output.

      • output: object { type, file_id, image_url }

        A computer screenshot image used with the computer use tool.

        • type: "computer_screenshot"

          Specifies the event type. For a computer screenshot, this property is always set to computer_screenshot.

        • file_id: optional string

          The identifier of an uploaded file that contains the screenshot.

        • image_url: optional string

          The URL of the screenshot image.

      • status: "completed" or "incomplete" or "failed" or "in_progress"

        The status of the message input. One of in_progress, completed, or incomplete. Populated when input items are returned via API.

        • "completed"

        • "incomplete"

        • "failed"

        • "in_progress"

      • type: "computer_call_output"

        The type of the computer tool call output. Always computer_call_output.

      • acknowledged_safety_checks: optional array of object { id, code, message }

        The safety checks reported by the API that have been acknowledged by the developer.

        • id: string

          The ID of the pending safety check.

        • code: optional string

          The type of the pending safety check.

        • message: optional string

          Details about the pending safety check.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_reasoning_item: object { id, summary, type, 3 more }

      A description of the chain of thought used by a reasoning model while generating a response. Be sure to include these items in your input to the Responses API for subsequent turns of a conversation if you are manually managing context.

      • id: string

        The unique identifier of the reasoning content.

      • summary: array of object { text, type }

        Reasoning summary content.

      • type: "reasoning"

        The type of the object. Always reasoning.

      • content: optional array of object { text, type }

        Reasoning text content.

      • encrypted_content: optional string

        The encrypted content of the reasoning item - populated when a response is generated with reasoning.encrypted_content in the include parameter.

      • status: optional "in_progress" or "completed" or "incomplete"

        The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

    • response_tool_search_call: object { id, arguments, call_id, 4 more }

      • id: string

        The unique ID of the tool search call item.

      • arguments: unknown

        Arguments used for the tool search call.

      • call_id: string

        The unique ID of the tool search call generated by the model.

      • execution: "server" or "client"

        Whether tool search was executed by the server or by the client.

        • "server"

        • "client"

      • status: "in_progress" or "completed" or "incomplete"

        The status of the tool search call item that was recorded.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "tool_search_call"

        The type of the item. Always tool_search_call.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_tool_search_output_item: object { id, call_id, execution, 4 more }

      • id: string

        The unique ID of the tool search output item.

      • call_id: string

        The unique ID of the tool search call generated by the model.

      • execution: "server" or "client"

        Whether tool search was executed by the server or by the client.

        • "server"

        • "client"

      • status: "in_progress" or "completed" or "incomplete"

        The status of the tool search output item that was recorded.

        • "in_progress"

        • "completed"

        • "incomplete"

      • tools: array of Tool

        The loaded tool definitions returned by tool search.

        • function_tool: object { name, parameters, strict, 3 more }

          Defines a function in your own code the model can choose to call. Learn more about function calling.

        • file_search_tool: object { type, vector_store_ids, filters, 2 more }

          A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

        • computer_tool: object { type }

          A tool that controls a virtual computer. Learn more about the computer tool.

        • computer_use_preview_tool: object { display_height, display_width, environment, type }

          A tool that controls a virtual computer. Learn more about the computer tool.

        • web_search_tool: object { type, filters, search_context_size, user_location }

          Search the Internet for sources related to the prompt. Learn more about the web search tool.

        • mcp: object { server_label, type, allowed_tools, 8 more }

          Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

        • code_interpreter: object { container, type }

          A tool that runs Python code to help generate a response to a prompt.

        • image_generation: object { type, action, background, 9 more }

          A tool that generates images using the GPT image models.

        • local_shell: object { type }

          A tool that allows the model to execute shell commands in a local environment.

        • function_shell_tool: object { type, environment }

          A tool that allows the model to execute shell commands.

        • custom_tool: object { name, type, defer_loading, 2 more }

          A custom tool that processes input using a specified format. Learn more about custom tools

        • namespace_tool: object { description, name, tools, type }

          Groups function/custom tools under a shared namespace.

        • tool_search_tool: object { type, description, execution, parameters }

          Hosted or BYOT tool search configuration for deferred tools.

        • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

          This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

        • apply_patch_tool: object { type }

          Allows the assistant to create, delete, or update files using unified diffs.

      • type: "tool_search_output"

        The type of the item. Always tool_search_output.

      • created_by: optional string

        The identifier of the actor that created the item.

    • additional_tools: object { id, role, tools, type }

      • id: string

        The unique ID of the additional tools item.

      • role: "unknown" or "user" or "assistant" or 5 more

        The role that provided the additional tools.

        • "unknown"

        • "user"

        • "assistant"

        • "system"

        • "critic"

        • "discriminator"

        • "developer"

        • "tool"

      • tools: array of Tool

        The additional tool definitions made available at this item.

        • function_tool: object { name, parameters, strict, 3 more }

          Defines a function in your own code the model can choose to call. Learn more about function calling.

        • file_search_tool: object { type, vector_store_ids, filters, 2 more }

          A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

        • computer_tool: object { type }

          A tool that controls a virtual computer. Learn more about the computer tool.

        • computer_use_preview_tool: object { display_height, display_width, environment, type }

          A tool that controls a virtual computer. Learn more about the computer tool.

        • web_search_tool: object { type, filters, search_context_size, user_location }

          Search the Internet for sources related to the prompt. Learn more about the web search tool.

        • mcp: object { server_label, type, allowed_tools, 8 more }

          Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

        • code_interpreter: object { container, type }

          A tool that runs Python code to help generate a response to a prompt.

        • image_generation: object { type, action, background, 9 more }

          A tool that generates images using the GPT image models.

        • local_shell: object { type }

          A tool that allows the model to execute shell commands in a local environment.

        • function_shell_tool: object { type, environment }

          A tool that allows the model to execute shell commands.

        • custom_tool: object { name, type, defer_loading, 2 more }

          A custom tool that processes input using a specified format. Learn more about custom tools

        • namespace_tool: object { description, name, tools, type }

          Groups function/custom tools under a shared namespace.

        • tool_search_tool: object { type, description, execution, parameters }

          Hosted or BYOT tool search configuration for deferred tools.

        • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

          This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

        • apply_patch_tool: object { type }

          Allows the assistant to create, delete, or update files using unified diffs.

      • type: "additional_tools"

        The type of the item. Always additional_tools.

    • response_compaction_item: object { id, encrypted_content, type, created_by }

      A compaction item generated by the v1/responses/compact API.

      • id: string

        The unique ID of the compaction item.

      • encrypted_content: string

        The encrypted content that was produced by compaction.

      • type: "compaction"

        The type of the item. Always compaction.

      • created_by: optional string

        The identifier of the actor that created the item.

    • image_generation_call: object { id, result, status, type }

      An image generation request made by the model.

      • id: string

        The unique ID of the image generation call.

      • result: string

        The generated image encoded in base64.

      • status: "in_progress" or "completed" or "generating" or "failed"

        The status of the image generation call.

        • "in_progress"

        • "completed"

        • "generating"

        • "failed"

      • type: "image_generation_call"

        The type of the image generation call. Always image_generation_call.

    • response_code_interpreter_tool_call: object { id, code, container_id, 3 more }

      A tool call to run code.

      • id: string

        The unique ID of the code interpreter tool call.

      • code: string

        The code to run, or null if not available.

      • container_id: string

        The ID of the container used to run the code.

      • outputs: array of object { logs, type } or object { type, url }

        The outputs generated by the code interpreter, such as logs or images. Can be null if no outputs are available.

      • status: "in_progress" or "completed" or "incomplete" or 2 more

        The status of the code interpreter tool call. Valid values are in_progress, completed, incomplete, interpreting, and failed.

      • type: "code_interpreter_call"

        The type of the code interpreter tool call. Always code_interpreter_call.

    • local_shell_call: object { id, action, call_id, 2 more }

      A tool call to run a command on the local shell.

      • id: string

        The unique ID of the local shell call.

      • action: object { command, env, type, 3 more }

        Execute a shell command on the server.

        • command: array of string

          The command to run.

        • env: map[string]

          Environment variables to set for the command.

        • type: "exec"

          The type of the local shell action. Always exec.

        • timeout_ms: optional number

          Optional timeout in milliseconds for the command.

        • user: optional string

          Optional user to run the command as.

        • working_directory: optional string

          Optional working directory to run the command in.

      • call_id: string

        The unique ID of the local shell tool call generated by the model.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the local shell call.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "local_shell_call"

        The type of the local shell call. Always local_shell_call.

    • local_shell_call_output: object { id, output, type, status }

      The output of a local shell tool call.

      • id: string

        The unique ID of the local shell tool call generated by the model.

      • output: string

        A JSON string of the output of the local shell tool call.

      • type: "local_shell_call_output"

        The type of the local shell tool call output. Always local_shell_call_output.

      • status: optional "in_progress" or "completed" or "incomplete"

        The status of the item. One of in_progress, completed, or incomplete.

        • "in_progress"

        • "completed"

        • "incomplete"

    • response_function_shell_tool_call: object { id, action, call_id, 4 more }

      A tool call that executes one or more shell commands in a managed environment.

      • id: string

        The unique ID of the shell tool call. Populated when this item is returned via API.

      • action: object { commands, max_output_length, timeout_ms }

        The shell commands and limits that describe how to run the tool call.

        • commands: array of string

        • max_output_length: number

          Optional maximum number of characters to return from each command.

        • timeout_ms: number

          Optional timeout in milliseconds for the commands.

      • call_id: string

        The unique ID of the shell tool call generated by the model.

      • environment: ResponseLocalEnvironment or ResponseContainerReference

        Represents the use of a local environment to perform shell actions.

        • response_local_environment: object { type }

          Represents the use of a local environment to perform shell actions.

          • type: "local"

            The environment type. Always local.

        • response_container_reference: object { container_id, type }

          Represents a container created with /v1/containers.

          • container_id: string

          • type: "container_reference"

            The environment type. Always container_reference.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the shell call. One of in_progress, completed, or incomplete.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "shell_call"

        The type of the item. Always shell_call.

      • created_by: optional string

        The ID of the entity that created this tool call.

    • response_function_shell_tool_call_output: object { id, call_id, max_output_length, 4 more }

      The output of a shell tool call that was emitted.

      • id: string

        The unique ID of the shell call output. Populated when this item is returned via API.

      • call_id: string

        The unique ID of the shell tool call generated by the model.

      • max_output_length: number

        The maximum length of the shell command output. This is generated by the model and should be passed back with the raw output.

      • output: array of object { outcome, stderr, stdout, created_by }

        An array of shell call output contents

        • outcome: object { type } or object { exit_code, type }

          Represents either an exit outcome (with an exit code) or a timeout outcome for a shell call output chunk.

          • timeout: object { type }

            Indicates that the shell call exceeded its configured time limit.

          • exit: object { exit_code, type }

            Indicates that the shell commands finished and returned an exit code.

            • exit_code: number

              Exit code from the shell process.

            • type: "exit"

              The outcome type. Always exit.

        • stderr: string

          The standard error output that was captured.

        • stdout: string

          The standard output that was captured.

        • created_by: optional string

          The identifier of the actor that created the item.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the shell call output. One of in_progress, completed, or incomplete.

        • "in_progress"

        • "completed"

        • "incomplete"

      • type: "shell_call_output"

        The type of the shell call output. Always shell_call_output.

      • created_by: optional string

        The identifier of the actor that created the item.

    • response_apply_patch_tool_call: object { id, call_id, operation, 3 more }

      A tool call that applies file diffs by creating, deleting, or updating files.

      • id: string

        The unique ID of the apply patch tool call. Populated when this item is returned via API.

      • call_id: string

        The unique ID of the apply patch tool call generated by the model.

      • operation: object { diff, path, type } or object { path, type } or object { diff, path, type }

        One of the create_file, delete_file, or update_file operations applied via apply_patch.

        • create_file: object { diff, path, type }

          Instruction describing how to create a file via the apply_patch tool.

          • diff: string

            Diff to apply.

          • path: string

            Path of the file to create.

          • type: "create_file"

            Create a new file with the provided diff.

        • delete_file: object { path, type }

          Instruction describing how to delete a file via the apply_patch tool.

          • path: string

            Path of the file to delete.

          • type: "delete_file"

            Delete the specified file.

        • update_file: object { diff, path, type }

          Instruction describing how to update a file via the apply_patch tool.

          • diff: string

            Diff to apply.

          • path: string

            Path of the file to update.

          • type: "update_file"

            Update an existing file with the provided diff.

      • status: "in_progress" or "completed"

        The status of the apply patch tool call. One of in_progress or completed.

        • "in_progress"

        • "completed"

      • type: "apply_patch_call"

        The type of the item. Always apply_patch_call.

      • created_by: optional string

        The ID of the entity that created this tool call.

    • response_apply_patch_tool_call_output: object { id, call_id, status, 3 more }

      The output emitted by an apply patch tool call.

      • id: string

        The unique ID of the apply patch tool call output. Populated when this item is returned via API.

      • call_id: string

        The unique ID of the apply patch tool call generated by the model.

      • status: "completed" or "failed"

        The status of the apply patch tool call output. One of completed or failed.

        • "completed"

        • "failed"

      • type: "apply_patch_call_output"

        The type of the item. Always apply_patch_call_output.

      • created_by: optional string

        The ID of the entity that created this tool call output.

      • output: optional string

        Optional textual output returned by the apply patch tool.

    • mcp_call: object { id, arguments, name, 6 more }

      An invocation of a tool on an MCP server.

      • id: string

        The unique ID of the tool call.

      • arguments: string

        A JSON string of the arguments passed to the tool.

      • name: string

        The name of the tool that was run.

      • server_label: string

        The label of the MCP server running the tool.

      • type: "mcp_call"

        The type of the item. Always mcp_call.

      • approval_request_id: optional string

        Unique identifier for the MCP tool call approval request. Include this value in a subsequent mcp_approval_response input to approve or reject the corresponding tool call.

      • error: optional string

        The error from the tool call, if any.

      • output: optional string

        The output from the tool call.

      • status: optional "in_progress" or "completed" or "incomplete" or 2 more

        The status of the tool call. One of in_progress, completed, incomplete, calling, or failed.

        • "in_progress"

        • "completed"

        • "incomplete"

        • "calling"

        • "failed"

    • mcp_list_tools: object { id, server_label, tools, 2 more }

      A list of tools available on an MCP server.

      • id: string

        The unique ID of the list.

      • server_label: string

        The label of the MCP server.

      • tools: array of object { input_schema, name, annotations, description }

        The tools available on the server.

        • input_schema: unknown

          The JSON schema describing the tool's input.

        • name: string

          The name of the tool.

        • annotations: optional unknown

          Additional annotations about the tool.

        • description: optional string

          The description of the tool.

      • type: "mcp_list_tools"

        The type of the item. Always mcp_list_tools.

      • error: optional string

        Error message if the server could not list tools.

    • mcp_approval_request: object { id, arguments, name, 2 more }

      A request for human approval of a tool invocation.

      • id: string

        The unique ID of the approval request.

      • arguments: string

        A JSON string of arguments for the tool.

      • name: string

        The name of the tool to run.

      • server_label: string

        The label of the MCP server making the request.

      • type: "mcp_approval_request"

        The type of the item. Always mcp_approval_request.

    • mcp_approval_response: object { id, approval_request_id, approve, 2 more }

      A response to an MCP approval request.

      • id: string

        The unique ID of the approval response

      • approval_request_id: string

        The ID of the approval request being answered.

      • approve: boolean

        Whether the request was approved.

      • type: "mcp_approval_response"

        The type of the item. Always mcp_approval_response.

      • reason: optional string

        Optional reason for the decision.

    • response_custom_tool_call: object { call_id, input, name, 3 more }

      A call to a custom tool created by the model.

      • call_id: string

        An identifier used to map this custom tool call to a tool call output.

      • input: string

        The input for the custom tool call generated by the model.

      • name: string

        The name of the custom tool being called.

      • type: "custom_tool_call"

        The type of the custom tool call. Always custom_tool_call.

      • id: optional string

        The unique ID of the custom tool call in the OpenAI platform.

      • namespace: optional string

        The namespace of the custom tool being called.

    • response_custom_tool_call_output_item: ResponseCustomToolCallOutput

      The output of a custom tool call from your code, being sent back to the model.

      • id: string

        The unique ID of the custom tool call output item.

      • status: "in_progress" or "completed" or "incomplete"

        The status of the item. One of in_progress, completed, or incomplete. Populated when items are returned via API.

        • "in_progress"

        • "completed"

        • "incomplete"

      • created_by: optional string

        The identifier of the actor that created the item.

  • parallel_tool_calls: boolean

    Whether to allow the model to run tool calls in parallel.

  • temperature: number

    What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.

  • tool_choice: ToolChoiceOptions or ToolChoiceAllowed or ToolChoiceTypes or 5 more

    How the model should select which tool (or tools) to use when generating a response. See the tools parameter to see how to specify which tools the model can call.

    • tool_choice_options: "none" or "auto" or "required"

      Controls which (if any) tool is called by the model.

      none means the model will not call any tool and instead generates a message.

      auto means the model can pick between generating a message or calling one or more tools.

      required means the model must call one or more tools.

      • "none"

      • "auto"

      • "required"

    • tool_choice_allowed: object { mode, tools, type }

      Constrains the tools available to the model to a pre-defined set.

      • mode: "auto" or "required"

        Constrains the tools available to the model to a pre-defined set.

        auto allows the model to pick from among the allowed tools and generate a message.

        required requires the model to call one or more of the allowed tools.

        • "auto"

        • "required"

      • tools: array of map[unknown]

        A list of tool definitions that the model should be allowed to call.

        For the Responses API, the list of tool definitions might look like:

        [
          { "type": "function", "name": "get_weather" },
          { "type": "mcp", "server_label": "deepwiki" },
          { "type": "image_generation" }
        ]
        

      • type: "allowed_tools"

        Allowed tool configuration type. Always allowed_tools.

    • tool_choice_types: object { type }

      Indicates that the model should use a built-in tool to generate a response. Learn more about built-in tools.

      • type: "file_search" or "web_search_preview" or "computer" or 5 more

        The type of hosted tool the model should to use. Learn more about built-in tools.

        Allowed values are:

        • file_search

        • web_search_preview

        • computer

        • computer_use_preview

        • computer_use

        • code_interpreter

        • image_generation

        • "file_search"

        • "web_search_preview"

        • "computer"

        • "computer_use_preview"

        • "computer_use"

        • "web_search_preview_2025_03_11"

        • "image_generation"

        • "code_interpreter"

    • tool_choice_function: object { name, type }

      Use this option to force the model to call a specific function.

      • name: string

        The name of the function to call.

      • type: "function"

        For function calling, the type is always function.

    • tool_choice_mcp: object { server_label, type, name }

      Use this option to force the model to call a specific tool on a remote MCP server.

      • server_label: string

        The label of the MCP server to use.

      • type: "mcp"

        For MCP tools, the type is always mcp.

      • name: optional string

        The name of the tool to call on the server.

    • tool_choice_custom: object { name, type }

      Use this option to force the model to call a specific custom tool.

      • name: string

        The name of the custom tool to call.

      • type: "custom"

        For custom tool calling, the type is always custom.

    • tool_choice_apply_patch: object { type }

      Forces the model to call the apply_patch tool when executing a tool call.

      • type: "apply_patch"

        The tool to call. Always apply_patch.

    • tool_choice_shell: object { type }

      Forces the model to call the shell tool when a tool call is required.

      • type: "shell"

        The tool to call. Always shell.

  • tools: array of Tool

    An array of tools the model may call while generating a response. You can specify which tool to use by setting the tool_choice parameter.

    We support the following categories of tools:

    • Built-in tools: Tools that are provided by OpenAI that extend the model's capabilities, like web search or file search. Learn more about built-in tools.

    • MCP Tools: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about MCP Tools.

    • Function calls (custom tools): Functions that are defined by you, enabling the model to call your own code with strongly typed arguments and outputs. Learn more about function calling. You can also use custom tools to call your own code.

    • function_tool: object { name, parameters, strict, 3 more }

      Defines a function in your own code the model can choose to call. Learn more about function calling.

    • file_search_tool: object { type, vector_store_ids, filters, 2 more }

      A tool that searches for relevant content from uploaded files. Learn more about the file search tool.

    • computer_tool: object { type }

      A tool that controls a virtual computer. Learn more about the computer tool.

    • computer_use_preview_tool: object { display_height, display_width, environment, type }

      A tool that controls a virtual computer. Learn more about the computer tool.

    • web_search_tool: object { type, filters, search_context_size, user_location }

      Search the Internet for sources related to the prompt. Learn more about the web search tool.

    • mcp: object { server_label, type, allowed_tools, 8 more }

      Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

    • code_interpreter: object { container, type }

      A tool that runs Python code to help generate a response to a prompt.

    • image_generation: object { type, action, background, 9 more }

      A tool that generates images using the GPT image models.

    • local_shell: object { type }

      A tool that allows the model to execute shell commands in a local environment.

    • function_shell_tool: object { type, environment }

      A tool that allows the model to execute shell commands.

    • custom_tool: object { name, type, defer_loading, 2 more }

      A custom tool that processes input using a specified format. Learn more about custom tools

    • namespace_tool: object { description, name, tools, type }

      Groups function/custom tools under a shared namespace.

    • tool_search_tool: object { type, description, execution, parameters }

      Hosted or BYOT tool search configuration for deferred tools.

    • web_search_preview_tool: object { type, search_content_types, search_context_size, user_location }

      This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

    • apply_patch_tool: object { type }

      Allows the assistant to create, delete, or update files using unified diffs.

  • top_p: number

    An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

    We generally recommend altering this or temperature but not both.

  • background: optional boolean

    Whether to run the model response in the background. Learn more.

  • completed_at: optional number

    Unix timestamp (in seconds) of when this Response was completed. Only present when the status is completed.

  • conversation: optional object { id }

    The conversation that this response belonged to. Input items and output items from this response were automatically added to this conversation.

    • id: string

      The unique ID of the conversation that this response was associated with.

  • max_output_tokens: optional number

    An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.

  • max_tool_calls: optional number

    The maximum number of total calls to built-in tools that can be processed in a response. This maximum number applies across all built-in tool calls, not per individual tool. Any further attempts to call a tool by the model will be ignored.

  • moderation: optional object { input, output }

    Moderation results for the response input and output, if moderated completions were requested.

    • input: object { categories, category_applied_input_types, category_scores, 3 more } or object { code, message, type }

      Moderation for the response input.

      • moderation_result: object { categories, category_applied_input_types, category_scores, 3 more }

        A moderation result produced for the response input or output.

        • categories: map[boolean]

          A dictionary of moderation categories to booleans, True if the input is flagged under this category.

        • category_applied_input_types: map[array of "text" or "image"]

          Which modalities of input are reflected by the score for each category.

          • "text"

          • "image"

        • category_scores: map[number]

          A dictionary of moderation categories to scores.

        • flagged: boolean

          A boolean indicating whether the content was flagged by any category.

        • model: string

          The moderation model that produced this result.

        • type: "moderation_result"

          The object type, which was always moderation_result for successful moderation results.

      • error: object { code, message, type }

        An error produced while attempting moderation for the response input or output.

        • code: string

          The error code.

        • message: string

          The error message.

        • type: "error"

          The object type, which was always error for moderation failures.

    • output: object { categories, category_applied_input_types, category_scores, 3 more } or object { code, message, type }

      Moderation for the response output.

      • moderation_result: object { categories, category_applied_input_types, category_scores, 3 more }

        A moderation result produced for the response input or output.

        • categories: map[boolean]

          A dictionary of moderation categories to booleans, True if the input is flagged under this category.

        • category_applied_input_types: map[array of "text" or "image"]

          Which modalities of input are reflected by the score for each category.

          • "text"

          • "image"

        • category_scores: map[number]

          A dictionary of moderation categories to scores.

        • flagged: boolean

          A boolean indicating whether the content was flagged by any category.

        • model: string

          The moderation model that produced this result.

        • type: "moderation_result"

          The object type, which was always moderation_result for successful moderation results.

      • error: object { code, message, type }

        An error produced while attempting moderation for the response input or output.

        • code: string

          The error code.

        • message: string

          The error message.

        • type: "error"

          The object type, which was always error for moderation failures.

  • previous_response_id: optional string

    The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state. Cannot be used in conjunction with conversation.

  • prompt: optional object { id, variables, version }

    Reference to a prompt template and its variables. Learn more.

    • id: string

      The unique identifier of the prompt template to use.

    • variables: optional map[string or ResponseInputText or ResponseInputImage or ResponseInputFile]

      Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

      • union_member_0: string

      • response_input_text: object { text, type }

        A text input to the model.

      • response_input_image: object { detail, type, file_id, image_url }

        An image input to the model. Learn about image inputs.

      • response_input_file: object { type, detail, file_data, 3 more }

        A file input to the model.

    • version: optional string

      Optional version of the prompt template.

  • prompt_cache_key: optional string

    Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.

  • prompt_cache_retention: optional "in_memory" or "24h"

    The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more. For gpt-5.5, gpt-5.5-pro, and future models, only 24h is supported.

    For older models that support both in_memory and 24h, the default depends on your organization's data retention policy:

    • Organizations without ZDR enabled default to 24h.

    • Organizations with ZDR enabled default to in_memory when prompt_cache_retention is not specified.

    • "in_memory"

    • "24h"

  • reasoning: optional object { context, effort, generate_summary, summary }

    gpt-5 and o-series models only

    Configuration options for reasoning models.

    • context: optional "auto" or "current_turn" or "all_turns"

      Controls which reasoning items are rendered back to the model on later turns. When returned on a response, this is the effective reasoning context mode used for the response.

      • "auto"

      • "current_turn"

      • "all_turns"

    • effort: optional "none" or "minimal" or "low" or 3 more

      Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

      • gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.

      • All models before gpt-5.1 default to medium reasoning effort, and do not support none.

      • The gpt-5-pro model defaults to (and only supports) high reasoning effort.

      • xhigh is supported for all models after gpt-5.1-codex-max.

      • "none"

      • "minimal"

      • "low"

      • "medium"

      • "high"

      • "xhigh"

    • generate_summary: optional "auto" or "concise" or "detailed"

      Deprecated: use summary instead.

      A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

      • "auto"

      • "concise"

      • "detailed"

    • summary: optional "auto" or "concise" or "detailed"

      A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

      concise is supported for computer-use-preview models and all reasoning models after gpt-5.

      • "auto"

      • "concise"

      • "detailed"

  • safety_identifier: optional string

    A stable identifier used to help detect users of your application that may be violating OpenAI's usage policies. The IDs should be a string that uniquely identifies each user, with a maximum length of 64 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.

  • service_tier: optional "auto" or "default" or "flex" or 2 more

    Specifies the processing type used for serving the request.

    • If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.
    • If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.
    • If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier.
    • When not set, the default behavior is 'auto'.

    When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • status: optional "completed" or "failed" or "in_progress" or 3 more

    The status of the response generation. One of completed, failed, in_progress, cancelled, queued, or incomplete.

    • "completed"

    • "failed"

    • "in_progress"

    • "cancelled"

    • "queued"

    • "incomplete"

  • text: optional object { format, verbosity }

    Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more:

    • Text inputs and outputs

    • Structured Outputs

    • format: optional ResponseFormatText or ResponseFormatTextJSONSchemaConfig or ResponseFormatJSONObject

      An object specifying the format that the model must output.

      Configuring { "type": "json_schema" } enables Structured Outputs, which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

      The default format is { "type": "text" } with no additional options.

      Not recommended for gpt-4o and newer models:

      Setting to { "type": "json_object" } enables the older JSON mode, which ensures the message the model generates is valid JSON. Using json_schema is preferred for models that support it.

      • response_format_text: object { type }

        Default response format. Used to generate text responses.

        • type: "text"

          The type of response format being defined. Always text.

      • response_format_text_json_schema_config: object { name, schema, type, 2 more }

        JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

        • name: string

          The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

        • schema: map[unknown]

          The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

        • type: "json_schema"

          The type of response format being defined. Always json_schema.

        • description: optional string

          A description of what the response format is for, used by the model to determine how to respond in the format.

        • strict: optional boolean

          Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the schema field. Only a subset of JSON Schema is supported when strict is true. To learn more, read the Structured Outputs guide.

      • response_format_json_object: object { type }

        JSON object response format. An older method of generating JSON responses. Using json_schema is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.

        • type: "json_object"

          The type of response format being defined. Always json_object.

    • verbosity: optional "low" or "medium" or "high"

      Constrains the verbosity of the model's response. Lower values will result in more concise responses, while higher values will result in more verbose responses. Currently supported values are low, medium, and high.

      • "low"

      • "medium"

      • "high"

  • top_logprobs: optional number

    An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested.

  • truncation: optional "auto" or "disabled"

    The truncation strategy to use for the model response.

    • auto: If the input to this Response exceeds the model's context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation.

    • disabled (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error.

    • "auto"

    • "disabled"

  • usage: optional object { input_tokens, input_tokens_details, output_tokens, 2 more }

    Represents token usage details including input tokens, output tokens, a breakdown of output tokens, and the total tokens used.

    • input_tokens: number

      The number of input tokens.

    • input_tokens_details: object { cached_tokens }

      A detailed breakdown of the input tokens.

      • cached_tokens: number

        The number of tokens that were retrieved from the cache. More on prompt caching.

    • output_tokens: number

      The number of output tokens.

    • output_tokens_details: object { reasoning_tokens }

      A detailed breakdown of the output tokens.

      • reasoning_tokens: number

        The number of reasoning tokens.

    • total_tokens: number

      The total number of tokens used.

  • user: optional string

    This field is being replaced by safety_identifier and prompt_cache_key. Use prompt_cache_key instead to maintain caching optimizations. A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. Learn more.