v1
latestOpenAPI 3.1.02026-07-1730321418.0 KBRequest body
Whether to run the model response in the background. Learn more.
Specify additional output data to include in the model response. Currently supported values are:
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web_search_call.action.sources: Include the sources of the web search tool call.
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code_interpreter_call.outputs: Includes the outputs of python code execution in code interpreter tool call items.
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computer_call_output.output.image_url: Include image urls from the computer call output.
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file_search_call.results: Include the search results of the file search tool call.
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message.input_image.image_url: Include image urls from the input message.
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message.output_text.logprobs: Include logprobs with assistant messages.
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reasoning.encrypted_content: Includes an encrypted version of reasoning tokens in reasoning item outputs. This enables reasoning items to be used in multi-turn conversations when using the Responses API statelessly (like when the store parameter is set to false, or when an organization is enrolled in the zero data retention program).
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.
An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
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.
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 ID used to generate the response, like gpt-4o or o3. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.
Whether to allow the model to run tool calls in parallel.
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.
Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.
The retention policy for the prompt cache.
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. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.
Whether to store the generated model response for later retrieval via API.
If set to true, the model response data will be streamed to the client as it is generated using server-sent events. See the Streaming section below for more information.
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.
An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
Truncation strategies.
Response
Response generated successfully
Whether to run the model response in the background. Learn more.
Unix timestamp (in seconds) when this Response was created.
Unique identifier for this response.
An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
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 ID used to generate the response, like gpt-4o or o3. OpenAI offers a wide range of models with different capabilities, performance characteristics, and price points. Refer to the model guide to browse and compare available models.
The object type of this resource - always set to response.
SDK-only convenience property that contains the aggregated text output from all output_text items in the output array, if any are present. Supported in the Python and JavaScript SDKs. Whether to allow the model to run tool calls in parallel.
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.
Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.
The retention policy for the prompt cache.
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. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.
What sampling temperature was used, between 0 and 2. Higher values like 0.8 make outputs more random, lower values like 0.2 make output more focused and deterministic.
We generally recommend altering this or top_p but not both.
An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.
Truncation strategies.