pub struct ResponseProperties {
pub previous_response_id: Option<String>,
pub model: Option<ModelIdsResponses>,
pub reasoning: Option<Reasoning>,
pub background: Option<bool>,
pub max_output_tokens: Option<u64>,
pub instructions: Option<String>,
pub text: Option<ResponsePropertiesText>,
pub tools: Option<Vec<Tool>>,
pub tool_choice: Option<ResponsePropertiesToolChoice>,
pub truncation: Option<ResponsePropertiesTruncation>,
}
Fields§
§previous_response_id: Option<String>
The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state.
model: Option<ModelIdsResponses>
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.
reasoning: Option<Reasoning>
§background: Option<bool>
Whether to run the model response in the background. Learn more.
max_output_tokens: Option<u64>
An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
instructions: Option<String>
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.
text: Option<ResponsePropertiesText>
Configuration options for a text response from the model. Can be plain text or structured JSON data. Learn more:
tools: Option<Vec<Tool>>
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.
tool_choice: Option<ResponsePropertiesToolChoice>
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.
truncation: Option<ResponsePropertiesTruncation>
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.
Implementations§
Source§impl ResponseProperties
impl ResponseProperties
Sourcepub fn builder() -> ResponsePropertiesBuilder<((), (), (), (), (), (), (), (), (), ())>
pub fn builder() -> ResponsePropertiesBuilder<((), (), (), (), (), (), (), (), (), ())>
Create a builder for building ResponseProperties
.
On the builder, call .previous_response_id(...)
(optional), .model(...)
(optional), .reasoning(...)
(optional), .background(...)
(optional), .max_output_tokens(...)
(optional), .instructions(...)
(optional), .text(...)
(optional), .tools(...)
(optional), .tool_choice(...)
(optional), .truncation(...)
(optional) to set the values of the fields.
Finally, call .build()
to create the instance of ResponseProperties
.
Trait Implementations§
Source§impl Clone for ResponseProperties
impl Clone for ResponseProperties
Source§fn clone(&self) -> ResponseProperties
fn clone(&self) -> ResponseProperties
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read more