pub struct DecisionRequest {
pub model: String,
pub input: DecisionInput,
pub questions: Vec<QuestionParam>,
pub safety_identifier: Option<String>,
pub prompt_cache_key: Option<String>,
pub prompt_cache_options: Option<DecisionRequestPromptCacheOptions>,
}decision-types only.Fields§
§model: StringThe model to use. Only gpt-6-luna is supported.
input: DecisionInput§questions: Vec<QuestionParam>Ask 1–400 questions about the input. Each question can be a predicate, choice, or score. Answers come back in the same order.
safety_identifier: Option<String>Opaque caller-provided end-user identifier, scoped by the verified org. Match Responses’ limit; this is never the authenticated user identity.
prompt_cache_key: Option<String>Partition prompt cache reuse by caller-provided key.
prompt_cache_options: Option<DecisionRequestPromptCacheOptions>Options for prompt caching. Supported for gpt-5.6 and later models. By default, OpenAI automatically chooses one implicit cache breakpoint. You can add explicit breakpoints to content blocks with prompt_cache_breakpoint. Each request can write up to four breakpoints. For cache matching, OpenAI considers up to the latest 80 breakpoints in the conversation, without a content-block lookback limit. Set mode to explicit to disable the implicit breakpoint. The ttl defaults to 30m, which is currently the only supported value. See the prompt caching guide for current details.