POST /responses

Default value: "application/json"

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.

Default value: false

Text, image, or file inputs to the model, used to generate a response.

Learn more:

• Text inputs and outputs
• Image inputs
• File inputs
• Conversation state
• Function calling

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.

Default value: 1

The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state.

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.

The two categories of tools you can provide the model are:

• 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.
• Function calls (custom tools): Functions that are defined by you, enabling the model to call your own code. Learn more about function calling.

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.

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

Default value: true

o-series models only

Configuration options for reasoning models.

Deprecated: use summary instead.

A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

Possible values:

• "concise"
• "auto"
• "detailed"

o-series models only

Constrains effort on reasoning for reasoning models. Currently supported values are low, medium, and high. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

Possible values:

• "medium"
• "low"
• "high"

Default value: "medium"

A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process. One of auto, concise, or detailed.

Possible values:

• "concise"
• "auto"
• "detailed"

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.

Possible values:

• "auto"
• "disabled"

Default value: "disabled"

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.

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.

Default value: 1

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

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

• Text inputs and outputs
• Structured Outputs

An object specifying the format that the model must output.

Configuring { "type": "json_schema" } enables Structured Outputs, which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

The default format is { "type": "text" } with no additional options.

Not recommended for gpt-4o and newer models:

Setting to { "type": "json_object" } enables the older JSON mode, which ensures the message the model generates is valid JSON. Using json_schema is preferred for models that support it.

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.

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.

Possible values:

• "auto"
• "flex"
• "default"

Default value: "auto"

Whether to store the generated model response for later retrieval via API.

Default value: true

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.