One of the following:
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.

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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 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 BetaResponseFunctionToolCallOutputItem: …
id: str

The unique ID of the function call tool output.

output: Union[str, List[OutputOutputContentList]]

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

One of the following:
str

A string of the output of the function call.

List[OutputOutputContentList]

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

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.

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["function_call_output"]

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

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

call_id: Optional[str]

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

caller: Optional[Caller]

The execution context that produced this tool call.

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

The caller type. Always direct.

class CallerProgram: …
caller_id: str

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

minLength1
maxLength64
type: Literal["program"]

The caller type. Always program.

created_by: Optional[str]

The identifier of the actor that created the item.

name: Optional[str]

The name of the tool that produced the output.

namespace: Optional[str]

The namespace of the tool that produced the output.

class AgentMessage: …
id: str

The unique ID of the agent message.

author: str

The sending agent identity.

content: List[AgentMessageContent]

Encrypted content sent between agents.

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 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.

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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 AgentMessageContentText: …

A text content.

text: str
type: Literal["text"]
class AgentMessageContentSummaryText: …

A summary text from the model.

text: str

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

type: Literal["summary_text"]

The type of the object. Always summary_text.

class AgentMessageContentReasoningText: …

Reasoning text from the model.

text: str

The reasoning text from the model.

type: Literal["reasoning_text"]

The type of the reasoning text. Always reasoning_text.

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.

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 AgentMessageContentComputerScreenshot: …

A screenshot of a computer.

detail: BetaImageDetail

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

file_id: Optional[str]

The identifier of an uploaded file that contains the screenshot.

image_url: Optional[str]

The URL of the screenshot image.

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type: Literal["computer_screenshot"]

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

prompt_cache_breakpoint: Optional[AgentMessageContentComputerScreenshotPromptCacheBreakpoint]

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

mode: Literal["explicit"]

The breakpoint mode. Always explicit.

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.

class AgentMessageContentEncryptedContent: …

Opaque encrypted content that Responses API decrypts inside trusted model execution.

encrypted_content: str

Opaque encrypted content.

type: Literal["encrypted_content"]

The type of the input item. Always encrypted_content.

recipient: str

The destination agent identity.

type: Literal["agent_message"]

The type of the item. Always agent_message.

agent: Optional[AgentMessageAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

class MultiAgentCall: …
id: str

The unique ID of the multi-agent call item.

action: Literal["spawn_agent", "interrupt_agent", "list_agents", 3 more]

The multi-agent action to execute.

One of the following:
"spawn_agent"
"interrupt_agent"
"list_agents"
"send_message"
"followup_task"
"wait_agent"
arguments: str

The JSON string of arguments generated for the action.

call_id: str

The unique ID linking this call to its output.

type: Literal["multi_agent_call"]

The type of the multi-agent call. Always multi_agent_call.

agent: Optional[MultiAgentCallAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

class MultiAgentCallOutput: …
id: str

The unique ID of the multi-agent call output item.

action: Literal["spawn_agent", "interrupt_agent", "list_agents", 3 more]

The multi-agent action that produced this result.

One of the following:
"spawn_agent"
"interrupt_agent"
"list_agents"
"send_message"
"followup_task"
"wait_agent"
call_id: str

The unique ID of the multi-agent call.

output: List[BetaResponseOutputText]

Text output returned by the multi-agent action.

annotations: List[Annotation]

The annotations of the text output.

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.

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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
type: Literal["multi_agent_call_output"]

The type of the multi-agent result. Always multi_agent_call_output.

agent: Optional[MultiAgentCallOutputAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

One of the following:
One of the following:
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 BetaResponseComputerToolCallOutputItem: …
id: str

The ID of the computer tool call output.

call_id: str

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

output: BetaResponseComputerToolCallOutputScreenshot

A computer screenshot image used with the computer use tool.

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

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

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

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

acknowledged_safety_checks: Optional[List[AcknowledgedSafetyCheck]]

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

id: str

The ID of the pending safety check.

code: Optional[str]

The type of the pending safety check.

message: Optional[str]

Details about the pending safety check.

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

created_by: Optional[str]

The identifier of the actor that created the item.

class BetaResponseReasoningItem: …

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

id: str

The unique identifier of the reasoning content.

summary: List[Summary]

Reasoning summary content.

text: str

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

type: Literal["summary_text"]

The type of the object. Always summary_text.

type: Literal["reasoning"]

The type of the object. Always reasoning.

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

content: Optional[List[Content]]

Reasoning text content.

text: str

The reasoning text from the model.

type: Literal["reasoning_text"]

The type of the reasoning text. Always reasoning_text.

encrypted_content: Optional[str]

The encrypted content of the reasoning item. This is populated by default for reasoning items returned by POST /v1/responses and WebSocket response.create requests.

When streaming, use the completed reasoning item and its encrypted_content from the response.output_item.done event in subsequent requests. The encrypted_content in response.output_item.added may be incomplete. This is especially important when store is false or when using Zero Data Retention.

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 Program: …
id: str

The unique ID of the program item.

call_id: str

The stable call ID of the program item.

code: str

The JavaScript source executed by programmatic tool calling.

fingerprint: str

Opaque program replay fingerprint that must be round-tripped.

type: Literal["program"]

The type of the item. Always program.

agent: Optional[ProgramAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

class ProgramOutput: …
id: str

The unique ID of the program output item.

call_id: str

The call ID of the program item.

result: str

The result produced by the program item.

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

The terminal status of the program output item.

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

The type of the item. Always program_output.

agent: Optional[ProgramOutputAgent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

class BetaResponseToolSearchCall: …
id: str

The unique ID of the tool search call item.

arguments: object

Arguments used for the tool search call.

call_id: Optional[str]

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

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

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

One of the following:
"server"
"client"
status: Literal["in_progress", "completed", "incomplete"]

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

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

The type of the item. Always tool_search_call.

agent: Optional[Agent]

The agent that produced this item.

agent_name: str

The canonical name of the agent that produced this item.

created_by: Optional[str]

The identifier of the actor that created the item.

class BetaResponseToolSearchOutputItem: …
id: str

The unique ID of the tool search output item.

call_id: Optional[str]

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

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

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

One of the following:
"server"
"client"
status: Literal["in_progress", "completed", "incomplete"]

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

One of the following:
"in_progress"
"completed"
"incomplete"
tools: List[BetaTool]

The loaded tool definitions returned by tool search.

One of the following:
class BetaFunctionTool: …

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

name: str

The name of the function to call.

parameters: Optional[Dict[str, object]]

A JSON schema object describing the parameters of the function.

strict: Optional[bool]

Whether strict parameter validation is enforced for this function tool.

type: Literal["function"]

The type of the function tool. Always function.

allowed_callers: Optional[List[Literal["direct", "programmatic"]]]

The tool invocation context(s).

One of the following:
"direct"
"programmatic"
async_: Optional[bool]
defer_loading: Optional[bool]

Whether this function is deferred and loaded via tool search.

description: Optional[str]

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

output_schema: Optional[Dict[str, object]]

A JSON schema object describing the JSON value encoded in string outputs for this function.

class BetaFileSearchTool: …

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

type: Literal["file_search"]

The type of the file search tool. Always file_search.

vector_store_ids: List[str]

The IDs of the vector stores to search.

filters: Optional[Filters]

A filter to apply.

One of the following:
class FiltersComparisonFilter: …

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

key: str

The key to compare against the value.

type: Literal["eq", "ne", "gt", 5 more]

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

  • eq: equals
  • ne: not equal
  • gt: greater than
  • gte: greater than or equal
  • lt: less than
  • lte: less than or equal
  • in: in
  • nin: not in
One of the following:
"eq"
"ne"
"gt"
"gte"
"lt"
"lte"
"in"
"nin"
value: Union[str, float, bool, List[Union[str, float]]]

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

One of the following:
str
float
bool
List[Union[str, float]]
One of the following:
str
float
class FiltersCompoundFilter: …

Combine multiple filters using and or or.

filters: List[FiltersCompoundFilterFilter]

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

One of the following:
class FiltersCompoundFilterFilterComparisonFilter: …

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

key: str

The key to compare against the value.

type: Literal["eq", "ne", "gt", 5 more]

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

  • eq: equals
  • ne: not equal
  • gt: greater than
  • gte: greater than or equal
  • lt: less than
  • lte: less than or equal
  • in: in
  • nin: not in
One of the following:
"eq"
"ne"
"gt"
"gte"
"lt"
"lte"
"in"
"nin"
value: Union[str, float, bool, List[Union[str, float]]]

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

One of the following:
str
float
bool
List[Union[str, float]]
One of the following:
str
float
object
type: Literal["and", "or"]

Type of operation: and or or.

One of the following:
"and"
"or"
max_num_results: Optional[int]

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

ranking_options: Optional[RankingOptions]

Ranking options for search.

class BetaComputerTool: …

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

class BetaComputerUsePreviewTool: …

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

class BetaWebSearchTool: …

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

class Mcp: …

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

class CodeInterpreter: …

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

class ProgrammaticToolCalling: …
class ImageGeneration: …

A tool that generates images using the GPT image models.

class LocalShell: …

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

class BetaFunctionShellTool: …

A tool that allows the model to execute shell commands.

class BetaCustomTool: …

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

class BetaNamespaceTool: …

Groups function/custom tools under a shared namespace.

class BetaToolSearchTool: …

Hosted or BYOT tool search configuration for deferred tools.

class BetaWebSearchPreviewTool: …

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

class BetaApplyPatchTool: …

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

type: Literal["tool_search_output"]

The type of the item. Always tool_search_output.

agent: Optional[Agent]

The agent that produced this item.

created_by: Optional[str]

The identifier of the actor that created the item.

class AdditionalTools: …
class BetaResponseCompactionItem: …

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 BetaResponseFunctionShellToolCall: …

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

class BetaResponseFunctionShellToolCallOutput: …

The output of a shell tool call that was emitted.

class BetaResponseApplyPatchToolCall: …

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

class BetaResponseApplyPatchToolCallOutput: …

The output emitted by an apply patch tool call.

class McpCall: …

An invocation of a tool on an MCP server.

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 BetaResponseCustomToolCall: …

A call to a custom tool created by the model.

class BetaResponseCustomToolCallOutputItem: …

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