id: str

Unique identifier for this Response.

access_programs: Optional[AccessPrograms]
cyber: Literal["standard", "daybreak_blue", "daybreak_red"]

The effective Cyber access program used for this response.

One of the following:
"standard"
"daybreak_blue"
"daybreak_red"
created_at: float

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

formatunixtime
error: Optional[BetaResponseError]

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

incomplete_details: Optional[IncompleteDetails]

Details about why the response is incomplete.

reason: Optional[Literal["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: Union[str, List[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:
str

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

List[BetaResponseInputItem]

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

One of the following:
class BetaEasyInputMessage: …

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

content: Union[str, BetaResponseInputMessageContentList]

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

One of the following:
str

A text input to the model.

List[BetaResponseInputContent]
One of the following:
class BetaResponseInputText: …

A text input to the model.

text: str

The text input to the model.

type: Literal["input_text"]

The type of the input item. Always input_text.

prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]

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

mode: Literal["explicit"]

The breakpoint mode. Always explicit.

class BetaResponseInputImage: …

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.

type: Literal["input_image"]

The type of the input item. Always input_image.

file_id: Optional[str]

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

image_url: Optional[str]

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

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prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]

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

mode: Literal["explicit"]

The breakpoint mode. Always explicit.

class BetaResponseInputFile: …

A file input to the model.

type: Literal["input_file"]

The type of the input item. Always input_file.

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

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

One of the following:
"auto"
"low"
"high"
file_data: Optional[str]

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

file_id: Optional[str]

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

file_url: Optional[str]

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

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filename: Optional[str]

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

prompt_cache_breakpoint: Optional[PromptCacheBreakpoint]

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

mode: Literal["explicit"]

The breakpoint mode. Always explicit.

role: Literal["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: Optional[Literal["commentary", "final_answer"]]

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

One of the following:
"commentary"
"final_answer"
type: Optional[Literal["message"]]

The type of the message input. Always message.

class Message: …

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

content: BetaResponseInputMessageContentList

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

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

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

One of the following:
"user"
"system"
"developer"
agent: Optional[MessageAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

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

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

One of the following:
"in_progress"
"completed"
"incomplete"
type: Optional[Literal["message"]]

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

class BetaResponseOutputMessage: …

An output message from the model.

id: str

The unique ID of the output message.

content: List[Content]

The content of the output message.

One of the following:
class BetaResponseOutputText: …

A text output from the model.

annotations: List[Annotation]

The annotations of the text output.

One of the following:
class AnnotationFileCitation: …

A citation to a file.

file_id: str

The ID of the file.

filename: str

The filename of the file cited.

index: int

The index in the output text at which to insert the file citation.

type: Literal["file_citation"]

The type of the file citation. Always file_citation.

class AnnotationURLCitation: …

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

end_index: int

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

start_index: int

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

title: str

The title of the web resource.

type: Literal["url_citation"]

The type of the URL citation. Always url_citation.

url: str

The URL of the web resource.

formaturi
class AnnotationContainerFileCitation: …

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

container_id: str

The ID of the container file.

end_index: int

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

file_id: str

The ID of the file.

filename: str

The filename of the container file cited.

start_index: int

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

type: Literal["container_file_citation"]

The type of the container file citation. Always container_file_citation.

class AnnotationFilePath: …

A path to a file.

file_id: str

The ID of the file.

index: int

The index of the file in the list of files.

type: Literal["file_path"]

The type of the file path. Always file_path.

text: str

The text output from the model.

type: Literal["output_text"]

The type of the output text. Always output_text.

logprobs: Optional[List[Logprob]]
token: str
bytes: List[int]
logprob: float
top_logprobs: List[LogprobTopLogprob]
token: str
bytes: List[int]
logprob: float
class BetaResponseOutputRefusal: …

A refusal from the model.

refusal: str

The refusal explanation from the model.

type: Literal["refusal"]

The type of the refusal. Always refusal.

role: Literal["assistant"]

The role of the output message. Always assistant.

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

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

One of the following:
"in_progress"
"completed"
"incomplete"
type: Literal["message"]

The type of the output message. Always message.

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

phase: Optional[Literal["commentary", "final_answer"]]

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

One of the following:
"commentary"
"final_answer"
class BetaResponseFileSearchToolCall: …

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

id: str

The unique ID of the file search tool call.

queries: List[str]

The queries used to search for files.

status: Literal["in_progress", "searching", "completed", 2 more]

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

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

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

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

results: Optional[List[Result]]

The results of the file search tool call.

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

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

One of the following:
str
float
bool
file_id: Optional[str]

The unique ID of the file.

filename: Optional[str]

The name of the file.

score: Optional[float]

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

formatfloat
text: Optional[str]

The text that was retrieved from the file.

class BetaResponseComputerToolCall: …

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

id: str

The unique ID of the computer call.

call_id: str

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

pending_safety_checks: List[PendingSafetyCheck]

The pending safety checks for the computer call.

id: str

The ID of the pending safety check.

code: Optional[str]

The type of the pending safety check.

message: Optional[str]

Details about the pending safety check.

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

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

One of the following:
"in_progress"
"completed"
"incomplete"
type: Literal["computer_call"]

The type of the computer call. Always computer_call.

action: Optional[BetaComputerAction]

A click action.

actions: Optional[BetaComputerActionList]

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

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

class ComputerCallOutput: …

The output of a computer tool call.

call_id: str

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

minLength1
maxLength64
output: BetaResponseComputerToolCallOutputScreenshot

A computer screenshot image used with the computer use tool.

type: Literal["computer_call_output"]

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

id: Optional[str]

The ID of the computer tool call output.

acknowledged_safety_checks: Optional[List[ComputerCallOutputAcknowledgedSafetyCheck]]

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

id: str

The ID of the pending safety check.

code: Optional[str]

The type of the pending safety check.

message: Optional[str]

Details about the pending safety check.

agent: Optional[ComputerCallOutputAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

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

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

One of the following:
"in_progress"
"completed"
"incomplete"
class BetaResponseFunctionWebSearch: …

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

id: str

The unique ID of the web search tool call.

action: Action

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

One of the following:
class ActionSearch: …

Action type “search” - Performs a web search query.

type: Literal["search"]

The action type.

queries: Optional[List[str]]

The search queries.

query: Optional[str]

Deprecated.

The search query.

sources: Optional[List[ActionSearchSource]]

The sources used in the search.

type: Literal["url"]

The type of source. Always url.

url: str

The URL of the source.

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class ActionOpenPage: …

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

type: Literal["open_page"]

The action type.

url: Optional[str]

The URL opened by the model.

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class ActionFindInPage: …

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

pattern: str

The pattern or text to search for within the page.

type: Literal["find_in_page"]

The action type.

url: str

The URL of the page searched for the pattern.

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status: Literal["in_progress", "searching", "completed", 2 more]

The status of the web search tool call.

One of the following:
"in_progress"
"searching"
"completed"
"failed"
"incomplete"
type: Literal["web_search_call"]

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

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

class BetaResponseFunctionToolCall: …

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

arguments: str

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

call_id: str

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

name: str

The name of the function to run.

type: Literal["function_call"]

The type of the function tool call. Always function_call.

id: Optional[str]

The unique ID of the function tool call.

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

async_: Optional[bool]

Whether the function tool call runs asynchronously.

caller: Optional[Caller]

The execution context that produced this tool call.

One of the following:
class CallerDirect: …
type: Literal["direct"]
class CallerProgram: …
caller_id: str

The call ID of the program item that produced this tool call.

type: Literal["program"]
namespace: Optional[str]

The namespace of the function to run.

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

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

One of the following:
"in_progress"
"completed"
"incomplete"
class FunctionCallOutput: …

The output of a function tool call.

output: Union[str, BetaResponseFunctionCallOutputItemList]

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

type: Literal["function_call_output"]

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

id: Optional[str]

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

agent: Optional[FunctionCallOutputAgent]

The agent that produced this item.

call_id: Optional[str]

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

minLength1
maxLength64
caller: Optional[FunctionCallOutputCaller]

The execution context that produced this tool call.

name: Optional[str]

The name of the tool that produced the output.

minLength1
maxLength128
namespace: Optional[str]

The namespace of the tool that produced the output.

minLength1
maxLength64
status: Optional[Literal["in_progress", "completed", "incomplete"]]

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

class AgentMessage: …

A message routed between agents.

class MultiAgentCall: …
class MultiAgentCallOutput: …
class ToolSearchCall: …
class BetaResponseToolSearchOutputItemParam: …
class AdditionalTools: …
class BetaResponseConfigurationUpdateItemParam: …

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

class BetaResponseReasoningItem: …

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

class BetaResponseCompactionItemParam: …

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

class ImageGenerationCall: …

An image generation request made by the model.

class BetaResponseCodeInterpreterToolCall: …

A tool call to run code.

class LocalShellCall: …

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

class LocalShellCallOutput: …

The output of a local shell tool call.

class ShellCall: …

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

class ShellCallOutput: …

The streamed output items emitted by a shell tool call.

class ApplyPatchCall: …

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

class ApplyPatchCallOutput: …

The streamed output emitted by an apply patch tool call.

class McpListTools: …

A list of tools available on an MCP server.

class McpApprovalRequest: …

A request for human approval of a tool invocation.

class McpApprovalResponse: …

A response to an MCP approval request.

class McpCall: …

An invocation of a tool on an MCP server.

class BetaResponseCustomToolCallOutput: …

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

class BetaResponseCustomToolCall: …

A call to a custom tool created by the model.

class CompactionTrigger: …

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

class ItemReference: …

An internal identifier for an item to reference.

class Program: …
class ProgramOutput: …
metadata: Optional[Dict[str, str]]

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: Union[Literal["gpt-6-astra", "gpt-6.1-sol", "gpt-6-sol", 106 more], str]

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: Literal["response"]

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

output: List[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: bool

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

temperature: Optional[float]

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

minimum0
maximum2
tool_choice: ToolChoice

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

tools: List[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: Optional[float]

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

We generally recommend altering this or temperature but not both.

minimum0
maximum1
background: Optional[bool]

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

completed_at: Optional[float]

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

formatunixtime
conversation: Optional[Conversation]

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

max_output_tokens: Optional[int]

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

max_tool_calls: Optional[int]

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

moderation: Optional[Moderation]

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

previous_response_id: Optional[str]

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

prompt: Optional[BetaResponsePrompt]

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

prompt_cache_diagnostics: Optional[PromptCacheDiagnostics]

Prompt cache diagnostics requested for this response.

prompt_cache_key: Optional[str]

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

prompt_cache_options: Optional[PromptCacheOptions]

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

prompt_cache_retention: Optional[Literal["in_memory", "24h"]]

Deprecated.

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: Optional[Reasoning]

Configuration options for reasoning models.

safety_identifier: Optional[str]

A stable identifier used to help detect users of your application that may be violating OpenAI’s usage policies. The IDs should be a string that uniquely identifies each user, with a maximum length of 128 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.

maxLength128
service_tier: Optional[BetaServiceTier]

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: Optional[BetaResponseStatus]

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

text: Optional[BetaResponseTextConfig]

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

top_logprobs: Optional[int]

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: Optional[Literal["auto", "disabled"]]

The truncation strategy to use for the model response.

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

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

user: Optional[str]

Deprecated.

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.