Creates a model response. Provide [text](/docs/guides/text) or [image](/docs/guides/images) inputs to generate [text](/docs/guides/text) or [JSON](/docs/guides/structured-outputs) outputs. Have the model call your own [custom code](/docs/guides/function-calling) or use built-in [tools](/docs/guides/tools) like [web search](/docs/guides/tools-web-search) or [file search](/docs/guides/tools-file-search) to use your own data as input for the model's response.
Request body
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.
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 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.
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:
- If set to 'auto', and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.
- If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'flex', the request will be processed with the Flex Processing service tier. Learn more.
- When not set, the default behavior is 'auto'.
When this parameter is set, the response body will include the service_tier utilized.
The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state.
An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
Inserts a system (or developer) message as the first item in 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.
The truncation strategy to use for the model response.
- auto: If the context of this response and previous ones exceeds the model's context window size, the model will truncate the response to fit the context window by dropping input items in the middle of the conversation.
- disabled (default): If a model response will exceed the context window size for a model, the request will fail with a 400 error.
Specify additional output data to include in the model response. Currently supported values are:
- file_search_call.results: Include the search results of the file search tool call.
- message.input_image.image_url: Include image urls from the input message.
- computer_call_output.output.image_url: Include image urls from the computer call output.
Whether to allow the model to run tool calls in parallel.
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.
Response
OK
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.
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 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.
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:
- If set to 'auto', and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.
- If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'flex', the request will be processed with the Flex Processing service tier. Learn more.
- When not set, the default behavior is 'auto'.
When this parameter is set, the response body will include the service_tier utilized.
The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state.
An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
Inserts a system (or developer) message as the first item in 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.
The truncation strategy to use for the model response.
- auto: If the context of this response and previous ones exceeds the model's context window size, the model will truncate the response to fit the context window by dropping input items in the middle of the conversation.
- disabled (default): If a model response will exceed the context window size for a model, the request will fail with a 400 error.
Unique identifier for this Response.
The object type of this resource - always set to response.
The status of the response generation. One of completed, failed, in_progress, or incomplete.
Unix timestamp (in seconds) of when this Response was created.
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.