Class Response

  • All Implemented Interfaces:

    
    public final class Response
    
                        
    • Constructor Detail

    • Method Detail

      • id

         final String id()

        Unique identifier for this Response.

      • createdAt

         final Double createdAt()

        Unix timestamp (in seconds) of when this Response was created.

      • instructions

         final Optional<Response.Instructions> instructions()

        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.

      • metadata

         final Optional<Response.Metadata> metadata()

        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

         final ResponsesModel model()

        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.

      • _object_

         final JsonValue _object_()

        The object type of this resource - always set to response.

        Expected to always return the following:

        JsonValue.from("response")

        However, this method can be useful for debugging and logging (e.g. if the server responded with an unexpected value).

      • output

         final List<ResponseOutputItem> output()

        An array of content items generated by the model.

        • The length and order of items in the output array is dependent on the model's response.

        • Rather than accessing the first item in the output array and assuming it's an assistant message with the content generated by the model, you might consider using the output_text property where supported in SDKs.

      • temperature

         final Optional<Double> temperature()

        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.

      • toolChoice

         final Response.ToolChoice toolChoice()

        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.

      • tools

         final List<Tool> tools()

        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 with strongly typed arguments and outputs. Learn more about function calling. You can also use custom tools to call your own code.

      • topP

         final Optional<Double> topP()

        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.

      • maxToolCalls

         final Optional<Long> maxToolCalls()

        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.

      • safetyIdentifier

         final Optional<String> safetyIdentifier()

        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.

      • serviceTier

         final Optional<Response.ServiceTier> serviceTier()

        Specifies the processing type used for serving the request.

        • If set to 'auto', then the request will be processed with the service tier configured in the Project settings. Unless otherwise configured, the Project will use 'default'.

        • If set to 'default', then the request will be processed with the standard pricing and performance for the selected model.

        • If set to 'flex' or 'priority', then the request will be processed with the corresponding service tier. Contact sales to learn more about Priority processing.

        • When not set, the default behavior is 'auto'.

        When the service_tier parameter is set, the response body will include the service_tier value based on the processing mode actually used to serve the request. This response value may be different from the value set in the parameter.

      • status

         final Optional<ResponseStatus> status()

        The status of the response generation. One of completed, failed, in_progress, cancelled, queued, or incomplete.

      • topLogprobs

         final Optional<Long> topLogprobs()

        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.

      • truncation

         final Optional<Response.Truncation> truncation()

        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.

      • usage

         final Optional<ResponseUsage> usage()

        Represents token usage details including input tokens, output tokens, a breakdown of output tokens, and the total tokens used.

      • user

        @Deprecated(message = "deprecated") final Optional<String> user()

        This field is being replaced by safety_identifier and prompt_cache_key. Use prompt_cache_key instead to maintain caching optimizations. A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. Learn more.

      • _id

         final JsonField<String> _id()

        Returns the raw JSON value of id.

        Unlike id, this method doesn't throw if the JSON field has an unexpected type.

      • _topP

         final JsonField<Double> _topP()

        Returns the raw JSON value of topP.

        Unlike topP, this method doesn't throw if the JSON field has an unexpected type.

      • _user

        @Deprecated(message = "deprecated") final JsonField<String> _user()

        Returns the raw JSON value of user.

        Unlike user, this method doesn't throw if the JSON field has an unexpected type.

      • builder

         final static Response.Builder builder()

        Returns a mutable builder for constructing an instance of Response.

        The following fields are required:

        .id()
        .createdAt()
        .error()
        .incompleteDetails()
        .instructions()
        .metadata()
        .model()
        .output()
        .parallelToolCalls()
        .temperature()
        .toolChoice()
        .tools()
        .topP()