API Reference

Beta

Responses

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Get a model response

BetaResponse beta().responses().retrieve(ResponseRetrieveParamsparams = ResponseRetrieveParams.none(), RequestOptionsrequestOptions = RequestOptions.none())

GET/responses/{response_id}

Retrieves a model response with the given ID.

ParametersExpand Collapse

ResponseRetrieveParams params

Optional<String> responseId

Optional<List<BetaResponseIncludable>> include

Additional fields to include in the response. See the include parameter for Response creation above for more information.

Optional<Boolean> includeObfuscation

When true, stream obfuscation will be enabled. Stream obfuscation adds random characters to an obfuscation field on streaming delta events to normalize payload sizes as a mitigation to certain side-channel attacks. These obfuscation fields are included by default, but add a small amount of overhead to the data stream. You can set include_obfuscation to false to optimize for bandwidth if you trust the network links between your application and the OpenAI API.

Optional<Long> startingAfter

The sequence number of the event after which to start streaming.

Optional<List<Beta>> betas

ReturnsExpand Collapse

class BetaResponse:

String id

Unique identifier for this Response.

double createdAt

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

formatunixtime

Optional<BetaResponseError> error

An error object returned when the model fails to generate a Response.

Optional<IncompleteDetails> incompleteDetails

Details about why the response is incomplete.

Optional<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.

Optional<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 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.

JsonValue; object_ "response"constant"response"constant

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

List<BetaResponseOutputItem> 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.

boolean parallelToolCalls

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

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.

minimum0

maximum2

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.

List<BetaTool> 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.

We support the following categories of tools:

• 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.
• MCP Tools: Integrations with third-party systems via custom MCP servers or predefined connectors such as Google Drive and SharePoint. Learn more about MCP 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.

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.

minimum0

maximum1

Optional<Boolean> background

Whether to run the model response in the background. Learn more.

Optional<Double> completedAt

Unix timestamp (in seconds) of when this Response was completed. Only present when the status is completed.

formatunixtime

Optional<Conversation> conversation

The conversation that this response belonged to. Input items and output items from this response were automatically added to this conversation.

Optional<Long> maxOutputTokens

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

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.

Optional<Moderation> moderation

Moderation results for the response input and output, if moderated completions were requested.

Optional<String> previousResponseId

The unique ID of the previous response to the model. Use this to create multi-turn conversations. Learn more about conversation state. Cannot be used in conjunction with conversation.

Optional<BetaResponsePrompt> prompt

Reference to a prompt template and its variables. Learn more.

Optional<String> promptCacheKey

Used by OpenAI to cache responses for similar requests to optimize your cache hit rates. Replaces the user field. Learn more.

Optional<PromptCacheOptions> promptCacheOptions

The prompt-caching options that were applied to the response. Supported for gpt-5.6 and later models.

DeprecatedOptional<PromptCacheRetention> promptCacheRetention

Deprecated. Use prompt_cache_options.ttl instead.

The retention policy for the prompt cache. Set to 24h to enable extended prompt caching, which keeps cached prefixes active for longer, up to a maximum of 24 hours. Learn more. This field expresses a maximum retention policy, while prompt_cache_options.ttl expresses a minimum cache lifetime. The two fields are independent and do not interact. For gpt-5.5, gpt-5.5-pro, and future models, only 24h is supported.

For older models that support both in_memory and 24h, the default depends on your organization’s data retention policy:

• Organizations without ZDR enabled default to 24h.
• Organizations with ZDR enabled default to in_memory when prompt_cache_retention is not specified.

Optional<Reasoning> reasoning

gpt-5 and o-series models only

Configuration options for reasoning models.

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, with a maximum length of 64 characters. We recommend hashing their username or email address, in order to avoid sending us any identifying information. Learn more.

maxLength64

Optional<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’, then the request will be processed with the Flex Processing service tier.
• To opt-in to Fast mode at the request level, include the service_tier=fast or service_tier=priority parameter for Responses or Chat Completions. The response will show service_tier=priority regardless of if you specify service_tier=fast or priority in your request.
• 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.

Optional<BetaResponseStatus> status

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

Optional<BetaResponseTextConfig> text

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

Optional<Long> topLogprobs

An integer between 0 and 20 specifying the maximum number of most likely tokens to return at each token position, each with an associated log probability. In some cases, the number of returned tokens may be fewer than requested.

minimum0

maximum20

Optional<Truncation> truncation

The truncation strategy to use for the model response.

• auto: If the input to this Response exceeds the model’s context window size, the model will truncate the response to fit the context window by dropping items from the beginning of the conversation.
• disabled (default): If the input size will exceed the context window size for a model, the request will fail with a 400 error.

Optional<BetaResponseUsage> usage

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

DeprecatedOptional<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.

Get a model response

Java

HTTP

Python

TypeScript

Go

Ruby

Java

CLI Tool

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.beta.responses.BetaResponse;
import com.openai.models.beta.responses.ResponseRetrieveParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        BetaResponse betaResponse = client.beta().responses().retrieve("resp_677efb5139a88190b512bc3fef8e535d");
    }
}

{
  "id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
  "object": "response",
  "created_at": 1741386163,
  "status": "completed",
  "completed_at": 1741386164,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-4o-2024-08-06",
  "output": [
    {
      "type": "message",
      "id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "Silent circuits hum,  \nThoughts emerge in data streams—  \nDigital dawn breaks.",
          "annotations": []
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 32,
    "input_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0
    },
    "output_tokens": 18,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 50
  },
  "user": null,
  "metadata": {}
}

Returns Examples

{
  "id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
  "object": "response",
  "created_at": 1741386163,
  "status": "completed",
  "completed_at": 1741386164,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "model": "gpt-4o-2024-08-06",
  "output": [
    {
      "type": "message",
      "id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "Silent circuits hum,  \nThoughts emerge in data streams—  \nDigital dawn breaks.",
          "annotations": []
        }
      ]
    }
  ],
  "parallel_tool_calls": true,
  "previous_response_id": null,
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "store": true,
  "temperature": 1.0,
  "text": {
    "format": {
      "type": "text"
    }
  },
  "tool_choice": "auto",
  "tools": [],
  "top_p": 1.0,
  "truncation": "disabled",
  "usage": {
    "input_tokens": 32,
    "input_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0
    },
    "output_tokens": 18,
    "output_tokens_details": {
      "reasoning_tokens": 0
    },
    "total_tokens": 50
  },
  "user": null,
  "metadata": {}
}