id: string

Unique identifier for this Response.

created_at: number

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

formatunixtime
error: BetaResponseError { code, message, misalignment } | null

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

code: "server_error" | "rate_limit_exceeded" | "invalid_prompt" | 18 more

The error code for the response.

One of the following:
"server_error"
"rate_limit_exceeded"
"invalid_prompt"
"data_residency_mismatch"
"bio_policy"
"misalignment_policy_violation"
"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.

misalignment?: Misalignment { detailed_explanation, error_type, steer }
detailed_explanation?: string

The public explanation for this block.

error_type?: (string & {}) | "potentially_unintended_data_transfer" | "potentially_unintended_data_access" | "potentially_unintended_destructive_activity" | "other"

An optional classification; clients must accept additional values.

One of the following:
(string & {})
"potentially_unintended_data_transfer" | "potentially_unintended_data_access" | "potentially_unintended_destructive_activity" | "other"
"potentially_unintended_data_transfer"
"potentially_unintended_data_access"
"potentially_unintended_destructive_activity"
"other"
steer?: Steer { message }

An optional public continuation instruction.

message: string

The public continuation instruction.

incomplete_details: IncompleteDetails | null

Details about why the response is incomplete.

reason?: "max_output_tokens" | "max_messages" | "content_filter" | "steered"

The reason why the response is incomplete. steered means the response stopped at a safe output boundary after a WebSocket response.steer event. The server can then create a successor response automatically with the queued input.

One of the following:
"max_output_tokens"
"max_messages"
"content_filter"
"steered"
instructions: string | Array<BetaResponseInputItem> | null

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

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

One of the following:
string
BetaEasyInputMessage { 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 | BetaResponseInputMessageContentList { , , }

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

One of the following:
string
BetaResponseInputMessageContentList = Array<BetaResponseInputContent>

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

One of the following:
BetaResponseInputText { text, type, prompt_cache_breakpoint }

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.

prompt_cache_breakpoint?: PromptCacheBreakpoint { mode }

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: "explicit"

The breakpoint mode. Always explicit.

BetaResponseInputImage { detail, type, file_id, 2 more }

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

detail: BetaImageDetail

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

One of the following:
"low"
"high"
"auto"
"original"
type: "input_image"

The type of the input item. Always input_image.

file_id?: string | null

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

image_url?: string | null

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

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prompt_cache_breakpoint?: PromptCacheBreakpoint { mode }

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: "explicit"

The breakpoint mode. Always explicit.

BetaResponseInputFile { type, detail, file_data, 4 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

detail?: "auto" | "low" | "high"

The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.

One of the following:
"auto"
"low"
"high"
file_data?: string

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

file_id?: string | null

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

file_url?: string

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

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filename?: string

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

prompt_cache_breakpoint?: PromptCacheBreakpoint { mode }

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: "explicit"

The breakpoint mode. Always explicit.

role: "user" | "assistant" | "system" | "developer"

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

One of the following:
"user"
"assistant"
"system"
"developer"
phase?: "commentary" | "final_answer" | null

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

One of the following:
"commentary"
"final_answer"
type?: "message"

The type of the message input. Always message.

Message { content, role, agent, 2 more }

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

content: BetaResponseInputMessageContentList { , , }

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

One of the following:
BetaResponseInputText { text, type, prompt_cache_breakpoint }

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.

prompt_cache_breakpoint?: PromptCacheBreakpoint { mode }

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: "explicit"

The breakpoint mode. Always explicit.

BetaResponseInputImage { detail, type, file_id, 2 more }

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

detail: BetaImageDetail

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

One of the following:
"low"
"high"
"auto"
"original"
type: "input_image"

The type of the input item. Always input_image.

file_id?: string | null

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

image_url?: string | null

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

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prompt_cache_breakpoint?: PromptCacheBreakpoint { mode }

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: "explicit"

The breakpoint mode. Always explicit.

BetaResponseInputFile { type, detail, file_data, 4 more }

A file input to the model.

type: "input_file"

The type of the input item. Always input_file.

detail?: "auto" | "low" | "high"

The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.

One of the following:
"auto"
"low"
"high"
file_data?: string

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

file_id?: string | null

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

file_url?: string

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

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filename?: string

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

prompt_cache_breakpoint?: PromptCacheBreakpoint { mode }

Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request’s prompt_cache_options.ttl; the boundary is not rounded to a token block.

mode: "explicit"

The breakpoint mode. Always explicit.

role: "user" | "system" | "developer"

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

One of the following:
"user"
"system"
"developer"
agent?: Agent | null

The agent that produced this item.

agent_name: string

The canonical name of the agent that produced this item.

status?: "in_progress" | "completed" | "incomplete"

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

One of the following:
"in_progress"
"completed"
"incomplete"
type?: "message"

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

BetaResponseOutputMessage { id, content, role, 4 more }

An output message from the model.

id: string

The unique ID of the output message.

content: Array<BetaResponseOutputText { annotations, text, type, logprobs } | BetaResponseOutputRefusal { refusal, type } >

The content of the output message.

One of the following:
BetaResponseOutputText { annotations, text, type, logprobs }

A text output from the model.

annotations: Array<FileCitation { file_id, filename, index, type } | URLCitation { end_index, start_index, title, 2 more } | ContainerFileCitation { container_id, end_index, file_id, 3 more } | FilePath { file_id, index, type } >

The annotations of the text output.

One of the following:
FileCitation { file_id, filename, index, type }

A citation to a file.

file_id: string

The ID of the file.

filename: string

The filename of the file cited.

index: number

The index of the file in the list of files.

type: "file_citation"

The type of the file citation. Always file_citation.

URLCitation { 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.

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ContainerFileCitation { container_id, end_index, file_id, 3 more }

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

container_id: string

The ID of the container file.

end_index: number

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

file_id: string

The ID of the file.

filename: string

The filename of the container file cited.

start_index: number

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

type: "container_file_citation"

The type of the container file citation. Always container_file_citation.

FilePath { 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?: Array<Logprob>
token: string
bytes: Array<number>
logprob: number
top_logprobs: Array<TopLogprob>
token: string
bytes: Array<number>
logprob: number
BetaResponseOutputRefusal { 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" | "completed" | "incomplete"

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

One of the following:
"in_progress"
"completed"
"incomplete"
type: "message"

The type of the output message. Always message.

agent?: Agent | null

The agent that produced this item.

agent_name: string

The canonical name of the agent that produced this item.

phase?: "commentary" | "final_answer" | null

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

One of the following:
"commentary"
"final_answer"
BetaResponseFileSearchToolCall { id, queries, status, 3 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<string>

The queries used to search for files.

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

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

One of the following:
"in_progress"
"searching"
"completed"
"incomplete"
"failed"
type: "file_search_call"

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

agent?: Agent | null

The agent that produced this item.

agent_name: string

The canonical name of the agent that produced this item.

results?: Array<Result> | null

The results of the file search tool call.

attributes?: Record<string, string | number | boolean> | null

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

One of the following:
string
number
boolean
file_id?: string

The unique ID of the file.

filename?: string

The name of the file.

score?: number

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

formatfloat
text?: string

The text that was retrieved from the file.

BetaResponseComputerToolCall { id, call_id, pending_safety_checks, 5 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<PendingSafetyCheck>

The pending safety checks for the computer call.

id: string

The ID of the pending safety check.

code?: string | null

The type of the pending safety check.

message?: string | null

Details about the pending safety check.

status: "in_progress" | "completed" | "incomplete"

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

One of the following:
"in_progress"
"completed"
"incomplete"
type: "computer_call"

The type of the computer call. Always computer_call.

action?: BetaComputerAction

A click action.

One of the following:
Click { button, type, x, 2 more }

A click action.

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

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

One of the following:
"left"
"right"
"wheel"
"back"
"forward"
type: "click"

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

x: number

The x-coordinate where the click occurred.

y: number

The y-coordinate where the click occurred.

keys?: Array<string> | null

The keys being held while clicking.

DoubleClick { keys, type, x, y }

A double click action.

keys: Array<string> | null

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 { path, type, keys }

A drag action.

path: Array<Path>

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?: Array<string> | null

The keys being held while dragging the mouse.

Keypress { keys, type }

A collection of keypresses the model would like to perform.

Move { type, x, y, keys }

A mouse move action.

Screenshot { type }

A screenshot action.

Scroll { scroll_x, scroll_y, type, 3 more }

A scroll action.

Type { text, type }

An action to type in text.

Wait { type }

A wait action.

actions?: BetaComputerActionList { , , , 6 more }

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

agent?: Agent | null

The agent that produced this item.

ComputerCallOutput { call_id, output, type, 4 more }

The output of a computer tool call.

BetaResponseFunctionToolCall { arguments, call_id, name, 7 more }

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

FunctionCallOutput { output, type, id, 6 more }

The output of a function tool call.

AgentMessage { author, content, recipient, 3 more }

A message routed between agents.

MultiAgentCall { action, arguments, call_id, 3 more }
MultiAgentCallOutput { action, call_id, output, 3 more }
ToolSearchCall { arguments, type, id, 4 more }
BetaResponseToolSearchOutputItemParam { tools, type, id, 4 more }
AdditionalTools { role, tools, type, 2 more }
BetaResponseConfigurationUpdateItemParam { type, id, agent, reasoning }

An update to the conversation’s response configuration. The configuration remains in effect for subsequent responses until it is replaced by another configuration update.

BetaResponseReasoningItem { id, summary, type, 4 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.

BetaResponseCompactionItemParam { encrypted_content, type, id, agent }

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

ImageGenerationCall { id, result, status, 8 more }

An image generation request made by the model.

BetaResponseCodeInterpreterToolCall { id, code, container_id, 4 more }

A tool call to run code.

LocalShellCall { id, action, call_id, 3 more }

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

LocalShellCallOutput { id, output, type, 2 more }

The output of a local shell tool call.

ShellCall { action, call_id, type, 5 more }

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

ShellCallOutput { call_id, output, type, 5 more }

The streamed output items emitted by a shell tool call.

ApplyPatchCall { call_id, operation, status, 4 more }

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

ApplyPatchCallOutput { call_id, status, type, 4 more }

The streamed output emitted by an apply patch tool call.

McpListTools { id, server_label, tools, 3 more }

A list of tools available on an MCP server.

McpApprovalRequest { id, arguments, name, 3 more }

A request for human approval of a tool invocation.

McpApprovalResponse { approval_request_id, approve, type, 3 more }

A response to an MCP approval request.

McpCall { id, arguments, name, 7 more }

An invocation of a tool on an MCP server.

BetaResponseCustomToolCallOutput { call_id, output, type, 3 more }

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

BetaResponseCustomToolCall { call_id, input, name, 6 more }

A call to a custom tool created by the model.

CompactionTrigger { type, agent }

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

ItemReference { id, agent, type }

An internal identifier for an item to reference.

Program { id, call_id, code, 3 more }
ProgramOutput { id, call_id, result, 3 more }
metadata: Record<string, string> | null

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: "gpt-6-astra" | "gpt-5.6-sol" | "gpt-5.6-terra" | 100 more | (string & {})

Model ID used to generate the response, like gpt-6-astra. 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.

object: "response"

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

output: Array<BetaResponseOutputItem>

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.
parallel_tool_calls: boolean

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

temperature: number | null

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

minimum0
maximum2
tool_choice: BetaToolChoiceOptions | BetaToolChoiceAllowed { mode, tools, type } | BetaToolChoiceTypes { type } | 6 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.

tools: Array<BetaTool>

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_p: number | null

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

We generally recommend altering this or temperature but not both.

minimum0
maximum1
background?: boolean | null

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

completed_at?: number | null

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

formatunixtime
conversation?: Conversation | null

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

max_output_tokens?: number | null

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?: number | null

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?: Moderation | null

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

previous_response_id?: string | null

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?: BetaResponsePrompt { id, variables, version } | null

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

prompt_cache_diagnostics?: CacheMiss { cache_missed_tokens, reason, type, comparison_reusable_tokens } | CacheHit { type } | ComparisonResponseNotFound { type } | Unavailable { type }

Prompt cache diagnostics requested for this response.

prompt_cache_key?: string | null

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

prompt_cache_options?: PromptCacheOptions { mode, ttl, comparison_response_id }

The prompt-caching options that were applied to the response. Supported for gpt-5.6 and later models.

Deprecatedprompt_cache_retention?: "in_memory" | "24h" | null

Deprecated. Use prompt_cache_options.ttl instead.

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. This field expresses a maximum retention policy, while prompt_cache_options.ttl expresses a minimum cache lifetime. The two fields are independent and do not interact. 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?: Reasoning | null

Configuration options for reasoning models.

safety_identifier?: string | null

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

maxLength64
service_tier?: BetaServiceTier | null

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’, then the request will be processed with the Flex Processing service tier.
  • To opt-in to Fast mode at the request level, include the service_tier=fast or service_tier=priority parameter for Responses or Chat Completions. The response will show service_tier=priority regardless of if you specify service_tier=fast or priority in your request.
  • If set to ‘ultrafast’, then the request will be processed with the access-controlled Ultrafast Processing service tier. This tier is currently available for gpt-5.6-sol; a response served through it will show service_tier=ultrafast.
  • 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.

status?: BetaResponseStatus

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

text?: BetaResponseTextConfig { format, verbosity }

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

top_logprobs?: number | null

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.

minimum0
maximum20
truncation?: "auto" | "disabled" | null

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.
usage?: BetaResponseUsage { 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.

Deprecateduser?: 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.