Chat

Completions

Create chat completion

$ openai chat:completions create

post /chat/completions

Starting a new project? We recommend trying Responses to take advantage of the latest OpenAI platform features. Compare Chat Completions with Responses.

Creates a model response for the given chat conversation. Learn more in the text generation, vision, and audio guides.

Parameter support can differ depending on the model used to generate the response, particularly for newer reasoning models. Parameters that are only supported for reasoning models are noted below. For the current state of unsupported parameters in reasoning models, refer to the reasoning guide.

Returns a chat completion object, or a streamed sequence of chat completion chunk objects if the request is streamed.

Parameters

• --message: array of ChatCompletionMessageParam

  A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio.

• --model: string or ChatModel

  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.

• --audio: optional object { format, voice }

  Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.

• --frequency-penalty: optional number

  Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

• --function-call: optional "none" or "auto" or ChatCompletionFunctionCallOption

  Deprecated in favor of tool_choice.

  Controls which (if any) function is called by the model.

  none means the model will not call a function and instead generates a message.

  auto means the model can pick between generating a message or calling a function.

  Specifying a particular function via {"name": "my_function"} forces the model to call that function.

  none is the default when no functions are present. auto is the default if functions are present.

• --function: optional array of object { name, description, parameters }

  Deprecated in favor of tools.

  A list of functions the model may generate JSON inputs for.

• --logit-bias: optional map[number]

  Modify the likelihood of specified tokens appearing in the completion.

  Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

• --logprobs: optional boolean

  Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

• --max-completion-tokens: optional number

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

• --max-tokens: optional number

  The maximum number of tokens that can be generated in the chat completion. This value can be used to control costs for text generated via API.

  This value is now deprecated in favor of max_completion_tokens, and is not compatible with o-series models.

• --metadata: optional map[string]

  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.

• --modality: optional array of "text" or "audio"

  Output types that you would like the model to generate. Most models are capable of generating text, which is the default:

  ["text"]

  The gpt-4o-audio-preview model can also be used to generate audio. To request that this model generate both text and audio responses, you can use:

  ["text", "audio"]

• --n: optional number

  How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.

• --parallel-tool-calls: optional boolean

  Whether to enable parallel function calling during tool use.

• --prediction: optional object { content, type }

  Static predicted output content, such as the content of a text file that is being regenerated.

• --presence-penalty: optional number

  Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

• --prompt-cache-key: optional string

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

• --prompt-cache-retention: optional "in_memory" or "24h"

  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.

• --reasoning-effort: optional "none" or "minimal" or "low" or 3 more

  Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

  • gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.
  • All models before gpt-5.1 default to medium reasoning effort, and do not support none.
  • The gpt-5-pro model defaults to (and only supports) high reasoning effort.
  • xhigh is supported for all models after gpt-5.1-codex-max.

• --response-format: optional ResponseFormatText or ResponseFormatJSONSchema or ResponseFormatJSONObject

  An object specifying the format that the model must output.

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

  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.

• --safety-identifier: optional string

  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.

• --seed: optional number

  This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

• --service-tier: optional "auto" or "default" or "flex" or 2 more

  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.
  • 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.

• --stop: optional string or array of string

  Not supported with latest reasoning models o3 and o4-mini.

  Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

• --store: optional boolean

  Whether or not to store the output of this chat completion request for use in our model distillation or evals products.

  Supports text and image inputs. Note: image inputs over 8MB will be dropped.

• --stream-options: optional object { include_obfuscation, include_usage }

  Options for streaming response. Only set this when you set stream: true.

• --temperature: optional number

  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.

• --tool-choice: optional "none" or "auto" or "required" or ChatCompletionAllowedToolChoice or ChatCompletionNamedToolChoice or ChatCompletionNamedToolChoiceCustom

  Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.

  none is the default when no tools are present. auto is the default if tools are present.

• --tool: optional array of ChatCompletionTool

  A list of tools the model may call. You can provide either custom tools or function tools.

• --top-logprobs: optional number

  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. logprobs must be set to true if this parameter is used.

• --top-p: optional number

  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.

• --user: optional string

  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.

• --verbosity: optional "low" or "medium" or "high"

  Constrains the verbosity of the model's response. Lower values will result in more concise responses, while higher values will result in more verbose responses. Currently supported values are low, medium, and high.

• --web-search-options: optional object { search_context_size, user_location }

  This tool searches the web for relevant results to use in a response. Learn more about the web search tool.

Returns

• chat_completion: object { id, choices, created, 5 more }

  Represents a chat completion response returned by model, based on the provided input.

  • id: string

    A unique identifier for the chat completion.

  • choices: array of object { finish_reason, index, logprobs, message }

    A list of chat completion choices. Can be more than one if n is greater than 1.

    • finish_reason: "stop" or "length" or "tool_calls" or 2 more

      The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

      • "stop"

      • "length"

      • "tool_calls"

      • "content_filter"

      • "function_call"

    • index: number

      The index of the choice in the list of choices.

    • logprobs: object { content, refusal }

      Log probability information for the choice.

      • content: array of ChatCompletionTokenLogprob

        A list of message content tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

      • refusal: array of ChatCompletionTokenLogprob

        A list of message refusal tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

    • message: object { content, refusal, role, 4 more }

      A chat completion message generated by the model.

      • content: string

        The contents of the message.

      • refusal: string

        The refusal message generated by the model.

      • role: "assistant"

        The role of the author of this message.

      • annotations: optional array of object { type, url_citation }

        Annotations for the message, when applicable, as when using the web search tool.

        • type: "url_citation"

          The type of the URL citation. Always url_citation.

        • url_citation: object { end_index, start_index, title, url }

          A URL citation when using web search.

          • end_index: number

            The index of the last character of the URL citation in the message.

          • start_index: number

            The index of the first character of the URL citation in the message.

          • title: string

            The title of the web resource.

          • url: string

            The URL of the web resource.

      • audio: optional object { id, data, expires_at, transcript }

        If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

        • id: string

          Unique identifier for this audio response.

        • data: string

          Base64 encoded audio bytes generated by the model, in the format specified in the request.

        • expires_at: number

          The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

        • transcript: string

          Transcript of the audio generated by the model.

      • function_call: optional object { arguments, name }

        Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

        • arguments: string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: string

          The name of the function to call.

      • tool_calls: optional array of ChatCompletionMessageToolCall

        The tool calls generated by the model, such as function calls.

        • chat_completion_message_function_tool_call: object { id, function, type }

          A call to a function tool created by the model.

          • id: string

            The ID of the tool call.

          • function: object { arguments, name }

            The function that the model called.

            • arguments: string

              The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

            • name: string

              The name of the function to call.

          • type: "function"

            The type of the tool. Currently, only function is supported.

        • chat_completion_message_custom_tool_call: object { id, custom, type }

          A call to a custom tool created by the model.

          • id: string

            The ID of the tool call.

          • custom: object { input, name }

            The custom tool that the model called.

            • input: string

              The input for the custom tool call generated by the model.

            • name: string

              The name of the custom tool to call.

          • type: "custom"

            The type of the tool. Always custom.

  • created: number

    The Unix timestamp (in seconds) of when the chat completion was created.

  • model: string

    The model used for the chat completion.

  • object: "chat.completion"

    The object type, which is always chat.completion.

  • service_tier: optional "auto" or "default" or "flex" or 2 more

    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.
    • 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.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • system_fingerprint: optional string

    This fingerprint represents the backend configuration that the model runs with.

    Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

  • usage: optional object { completion_tokens, prompt_tokens, total_tokens, 2 more }

    Usage statistics for the completion request.

    • completion_tokens: number

      Number of tokens in the generated completion.

    • prompt_tokens: number

      Number of tokens in the prompt.

    • total_tokens: number

      Total number of tokens used in the request (prompt + completion).

    • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

      Breakdown of tokens used in a completion.

      • accepted_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

      • audio_tokens: optional number

        Audio input tokens generated by the model.

      • reasoning_tokens: optional number

        Tokens generated by the model for reasoning.

      • rejected_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

    • prompt_tokens_details: optional object { audio_tokens, cached_tokens }

      Breakdown of tokens used in the prompt.

      • audio_tokens: optional number

        Audio input tokens present in the prompt.

      • cached_tokens: optional number

        Cached tokens present in the prompt.

Example

openai chat:completions create \
  --api-key 'My API Key' \
  --message '{content: string, role: developer}' \
  --model gpt-5.4

Response

{
  "id": "id",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": {
        "content": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ],
        "refusal": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ]
      },
      "message": {
        "content": "content",
        "refusal": "refusal",
        "role": "assistant",
        "annotations": [
          {
            "type": "url_citation",
            "url_citation": {
              "end_index": 0,
              "start_index": 0,
              "title": "title",
              "url": "https://example.com"
            }
          }
        ],
        "audio": {
          "id": "id",
          "data": "data",
          "expires_at": 0,
          "transcript": "transcript"
        },
        "function_call": {
          "arguments": "arguments",
          "name": "name"
        },
        "tool_calls": [
          {
            "id": "id",
            "function": {
              "arguments": "arguments",
              "name": "name"
            },
            "type": "function"
          }
        ]
      }
    }
  ],
  "created": 0,
  "model": "model",
  "object": "chat.completion",
  "service_tier": "auto",
  "system_fingerprint": "system_fingerprint",
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    }
  }
}

List Chat Completions

$ openai chat:completions list

get /chat/completions

List stored Chat Completions. Only Chat Completions that have been stored with the store parameter set to true will be returned.

Parameters

• --after: optional string

  Identifier for the last chat completion from the previous pagination request.

• --limit: optional number

  Number of Chat Completions to retrieve.

• --metadata: optional map[string]

  A list of metadata keys to filter the Chat Completions by. Example:

  metadata[key1]=value1&metadata[key2]=value2

• --model: optional string

  The model used to generate the Chat Completions.

• --order: optional "asc" or "desc"

  Sort order for Chat Completions by timestamp. Use asc for ascending order or desc for descending order. Defaults to asc.

Returns

• ChatCompletionList: object { data, first_id, has_more, 2 more }

  An object representing a list of Chat Completions.

  • data: array of ChatCompletion

    An array of chat completion objects.

    • id: string

      A unique identifier for the chat completion.

    • choices: array of object { finish_reason, index, logprobs, message }

      A list of chat completion choices. Can be more than one if n is greater than 1.

      • finish_reason: "stop" or "length" or "tool_calls" or 2 more

        The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

        • "stop"

        • "length"

        • "tool_calls"

        • "content_filter"

        • "function_call"

      • index: number

        The index of the choice in the list of choices.

      • logprobs: object { content, refusal }

        Log probability information for the choice.

        • content: array of ChatCompletionTokenLogprob

          A list of message content tokens with log probability information.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

          • top_logprobs: array of object { token, bytes, logprob }

            List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

            • token: string

              The token.

            • bytes: array of number

              A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

            • logprob: number

              The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • refusal: array of ChatCompletionTokenLogprob

          A list of message refusal tokens with log probability information.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

          • top_logprobs: array of object { token, bytes, logprob }

            List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

      • message: object { content, refusal, role, 4 more }

        A chat completion message generated by the model.

        • content: string

          The contents of the message.

        • refusal: string

          The refusal message generated by the model.

        • role: "assistant"

          The role of the author of this message.

        • annotations: optional array of object { type, url_citation }

          Annotations for the message, when applicable, as when using the web search tool.

          • type: "url_citation"

            The type of the URL citation. Always url_citation.

          • url_citation: object { end_index, start_index, title, url }

            A URL citation when using web search.

            • end_index: number

              The index of the last character of the URL citation in the message.

            • start_index: number

              The index of the first character of the URL citation in the message.

            • title: string

              The title of the web resource.

            • url: string

              The URL of the web resource.

        • audio: optional object { id, data, expires_at, transcript }

          If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

          • id: string

            Unique identifier for this audio response.

          • data: string

            Base64 encoded audio bytes generated by the model, in the format specified in the request.

          • expires_at: number

            The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

          • transcript: string

            Transcript of the audio generated by the model.

        • function_call: optional object { arguments, name }

          Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

          • arguments: string

            The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

          • name: string

            The name of the function to call.

        • tool_calls: optional array of ChatCompletionMessageToolCall

          The tool calls generated by the model, such as function calls.

          • chat_completion_message_function_tool_call: object { id, function, type }

            A call to a function tool created by the model.

            • id: string

              The ID of the tool call.

            • function: object { arguments, name }

              The function that the model called.

              • arguments: string

                The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

              • name: string

                The name of the function to call.

            • type: "function"

              The type of the tool. Currently, only function is supported.

          • chat_completion_message_custom_tool_call: object { id, custom, type }

            A call to a custom tool created by the model.

            • id: string

              The ID of the tool call.

            • custom: object { input, name }

              The custom tool that the model called.

              • input: string

                The input for the custom tool call generated by the model.

              • name: string

                The name of the custom tool to call.

            • type: "custom"

              The type of the tool. Always custom.

    • created: number

      The Unix timestamp (in seconds) of when the chat completion was created.

    • model: string

      The model used for the chat completion.

    • object: "chat.completion"

      The object type, which is always chat.completion.

    • service_tier: optional "auto" or "default" or "flex" or 2 more

      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.
      • 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.

      • "auto"

      • "default"

      • "flex"

      • "scale"

      • "priority"

    • system_fingerprint: optional string

      This fingerprint represents the backend configuration that the model runs with.

      Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

    • usage: optional object { completion_tokens, prompt_tokens, total_tokens, 2 more }

      Usage statistics for the completion request.

      • completion_tokens: number

        Number of tokens in the generated completion.

      • prompt_tokens: number

        Number of tokens in the prompt.

      • total_tokens: number

        Total number of tokens used in the request (prompt + completion).

      • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

        Breakdown of tokens used in a completion.

        • accepted_prediction_tokens: optional number

          When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

        • audio_tokens: optional number

          Audio input tokens generated by the model.

        • reasoning_tokens: optional number

          Tokens generated by the model for reasoning.

        • rejected_prediction_tokens: optional number

          When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

      • prompt_tokens_details: optional object { audio_tokens, cached_tokens }

        Breakdown of tokens used in the prompt.

        • audio_tokens: optional number

          Audio input tokens present in the prompt.

        • cached_tokens: optional number

          Cached tokens present in the prompt.

  • first_id: string

    The identifier of the first chat completion in the data array.

  • has_more: boolean

    Indicates whether there are more Chat Completions available.

  • last_id: string

    The identifier of the last chat completion in the data array.

  • object: "list"

    The type of this object. It is always set to "list".

Example

openai chat:completions list \
  --api-key 'My API Key'

Response

{
  "data": [
    {
      "id": "id",
      "choices": [
        {
          "finish_reason": "stop",
          "index": 0,
          "logprobs": {
            "content": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0,
                "top_logprobs": [
                  {
                    "token": "token",
                    "bytes": [
                      0
                    ],
                    "logprob": 0
                  }
                ]
              }
            ],
            "refusal": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0,
                "top_logprobs": [
                  {
                    "token": "token",
                    "bytes": [
                      0
                    ],
                    "logprob": 0
                  }
                ]
              }
            ]
          },
          "message": {
            "content": "content",
            "refusal": "refusal",
            "role": "assistant",
            "annotations": [
              {
                "type": "url_citation",
                "url_citation": {
                  "end_index": 0,
                  "start_index": 0,
                  "title": "title",
                  "url": "https://example.com"
                }
              }
            ],
            "audio": {
              "id": "id",
              "data": "data",
              "expires_at": 0,
              "transcript": "transcript"
            },
            "function_call": {
              "arguments": "arguments",
              "name": "name"
            },
            "tool_calls": [
              {
                "id": "id",
                "function": {
                  "arguments": "arguments",
                  "name": "name"
                },
                "type": "function"
              }
            ]
          }
        }
      ],
      "created": 0,
      "model": "model",
      "object": "chat.completion",
      "service_tier": "auto",
      "system_fingerprint": "system_fingerprint",
      "usage": {
        "completion_tokens": 0,
        "prompt_tokens": 0,
        "total_tokens": 0,
        "completion_tokens_details": {
          "accepted_prediction_tokens": 0,
          "audio_tokens": 0,
          "reasoning_tokens": 0,
          "rejected_prediction_tokens": 0
        },
        "prompt_tokens_details": {
          "audio_tokens": 0,
          "cached_tokens": 0
        }
      }
    }
  ],
  "first_id": "first_id",
  "has_more": true,
  "last_id": "last_id",
  "object": "list"
}

Get chat completion

$ openai chat:completions retrieve

get /chat/completions/{completion_id}

Get a stored chat completion. Only Chat Completions that have been created with the store parameter set to true will be returned.

Parameters

• --completion-id: string

  The ID of the chat completion to retrieve.

Returns

• chat_completion: object { id, choices, created, 5 more }

  Represents a chat completion response returned by model, based on the provided input.

  • id: string

    A unique identifier for the chat completion.

  • choices: array of object { finish_reason, index, logprobs, message }

    A list of chat completion choices. Can be more than one if n is greater than 1.

    • finish_reason: "stop" or "length" or "tool_calls" or 2 more

      The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

      • "stop"

      • "length"

      • "tool_calls"

      • "content_filter"

      • "function_call"

    • index: number

      The index of the choice in the list of choices.

    • logprobs: object { content, refusal }

      Log probability information for the choice.

      • content: array of ChatCompletionTokenLogprob

        A list of message content tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

      • refusal: array of ChatCompletionTokenLogprob

        A list of message refusal tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

    • message: object { content, refusal, role, 4 more }

      A chat completion message generated by the model.

      • content: string

        The contents of the message.

      • refusal: string

        The refusal message generated by the model.

      • role: "assistant"

        The role of the author of this message.

      • annotations: optional array of object { type, url_citation }

        Annotations for the message, when applicable, as when using the web search tool.

        • type: "url_citation"

          The type of the URL citation. Always url_citation.

        • url_citation: object { end_index, start_index, title, url }

          A URL citation when using web search.

          • end_index: number

            The index of the last character of the URL citation in the message.

          • start_index: number

            The index of the first character of the URL citation in the message.

          • title: string

            The title of the web resource.

          • url: string

            The URL of the web resource.

      • audio: optional object { id, data, expires_at, transcript }

        If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

        • id: string

          Unique identifier for this audio response.

        • data: string

          Base64 encoded audio bytes generated by the model, in the format specified in the request.

        • expires_at: number

          The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

        • transcript: string

          Transcript of the audio generated by the model.

      • function_call: optional object { arguments, name }

        Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

        • arguments: string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: string

          The name of the function to call.

      • tool_calls: optional array of ChatCompletionMessageToolCall

        The tool calls generated by the model, such as function calls.

        • chat_completion_message_function_tool_call: object { id, function, type }

          A call to a function tool created by the model.

          • id: string

            The ID of the tool call.

          • function: object { arguments, name }

            The function that the model called.

            • arguments: string

              The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

            • name: string

              The name of the function to call.

          • type: "function"

            The type of the tool. Currently, only function is supported.

        • chat_completion_message_custom_tool_call: object { id, custom, type }

          A call to a custom tool created by the model.

          • id: string

            The ID of the tool call.

          • custom: object { input, name }

            The custom tool that the model called.

            • input: string

              The input for the custom tool call generated by the model.

            • name: string

              The name of the custom tool to call.

          • type: "custom"

            The type of the tool. Always custom.

  • created: number

    The Unix timestamp (in seconds) of when the chat completion was created.

  • model: string

    The model used for the chat completion.

  • object: "chat.completion"

    The object type, which is always chat.completion.

  • service_tier: optional "auto" or "default" or "flex" or 2 more

    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.
    • 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.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • system_fingerprint: optional string

    This fingerprint represents the backend configuration that the model runs with.

    Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

  • usage: optional object { completion_tokens, prompt_tokens, total_tokens, 2 more }

    Usage statistics for the completion request.

    • completion_tokens: number

      Number of tokens in the generated completion.

    • prompt_tokens: number

      Number of tokens in the prompt.

    • total_tokens: number

      Total number of tokens used in the request (prompt + completion).

    • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

      Breakdown of tokens used in a completion.

      • accepted_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

      • audio_tokens: optional number

        Audio input tokens generated by the model.

      • reasoning_tokens: optional number

        Tokens generated by the model for reasoning.

      • rejected_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

    • prompt_tokens_details: optional object { audio_tokens, cached_tokens }

      Breakdown of tokens used in the prompt.

      • audio_tokens: optional number

        Audio input tokens present in the prompt.

      • cached_tokens: optional number

        Cached tokens present in the prompt.

Example

openai chat:completions retrieve \
  --api-key 'My API Key' \
  --completion-id completion_id

Response

{
  "id": "id",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": {
        "content": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ],
        "refusal": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ]
      },
      "message": {
        "content": "content",
        "refusal": "refusal",
        "role": "assistant",
        "annotations": [
          {
            "type": "url_citation",
            "url_citation": {
              "end_index": 0,
              "start_index": 0,
              "title": "title",
              "url": "https://example.com"
            }
          }
        ],
        "audio": {
          "id": "id",
          "data": "data",
          "expires_at": 0,
          "transcript": "transcript"
        },
        "function_call": {
          "arguments": "arguments",
          "name": "name"
        },
        "tool_calls": [
          {
            "id": "id",
            "function": {
              "arguments": "arguments",
              "name": "name"
            },
            "type": "function"
          }
        ]
      }
    }
  ],
  "created": 0,
  "model": "model",
  "object": "chat.completion",
  "service_tier": "auto",
  "system_fingerprint": "system_fingerprint",
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    }
  }
}

Update chat completion

$ openai chat:completions update

post /chat/completions/{completion_id}

Modify a stored chat completion. Only Chat Completions that have been created with the store parameter set to true can be modified. Currently, the only supported modification is to update the metadata field.

Parameters

• --completion-id: string

  The ID of the chat completion to update.

• --metadata: map[string]

  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.

Returns

• chat_completion: object { id, choices, created, 5 more }

  Represents a chat completion response returned by model, based on the provided input.

  • id: string

    A unique identifier for the chat completion.

  • choices: array of object { finish_reason, index, logprobs, message }

    A list of chat completion choices. Can be more than one if n is greater than 1.

    • finish_reason: "stop" or "length" or "tool_calls" or 2 more

      The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

      • "stop"

      • "length"

      • "tool_calls"

      • "content_filter"

      • "function_call"

    • index: number

      The index of the choice in the list of choices.

    • logprobs: object { content, refusal }

      Log probability information for the choice.

      • content: array of ChatCompletionTokenLogprob

        A list of message content tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

      • refusal: array of ChatCompletionTokenLogprob

        A list of message refusal tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

    • message: object { content, refusal, role, 4 more }

      A chat completion message generated by the model.

      • content: string

        The contents of the message.

      • refusal: string

        The refusal message generated by the model.

      • role: "assistant"

        The role of the author of this message.

      • annotations: optional array of object { type, url_citation }

        Annotations for the message, when applicable, as when using the web search tool.

        • type: "url_citation"

          The type of the URL citation. Always url_citation.

        • url_citation: object { end_index, start_index, title, url }

          A URL citation when using web search.

          • end_index: number

            The index of the last character of the URL citation in the message.

          • start_index: number

            The index of the first character of the URL citation in the message.

          • title: string

            The title of the web resource.

          • url: string

            The URL of the web resource.

      • audio: optional object { id, data, expires_at, transcript }

        If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

        • id: string

          Unique identifier for this audio response.

        • data: string

          Base64 encoded audio bytes generated by the model, in the format specified in the request.

        • expires_at: number

          The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

        • transcript: string

          Transcript of the audio generated by the model.

      • function_call: optional object { arguments, name }

        Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

        • arguments: string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: string

          The name of the function to call.

      • tool_calls: optional array of ChatCompletionMessageToolCall

        The tool calls generated by the model, such as function calls.

        • chat_completion_message_function_tool_call: object { id, function, type }

          A call to a function tool created by the model.

          • id: string

            The ID of the tool call.

          • function: object { arguments, name }

            The function that the model called.

            • arguments: string

              The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

            • name: string

              The name of the function to call.

          • type: "function"

            The type of the tool. Currently, only function is supported.

        • chat_completion_message_custom_tool_call: object { id, custom, type }

          A call to a custom tool created by the model.

          • id: string

            The ID of the tool call.

          • custom: object { input, name }

            The custom tool that the model called.

            • input: string

              The input for the custom tool call generated by the model.

            • name: string

              The name of the custom tool to call.

          • type: "custom"

            The type of the tool. Always custom.

  • created: number

    The Unix timestamp (in seconds) of when the chat completion was created.

  • model: string

    The model used for the chat completion.

  • object: "chat.completion"

    The object type, which is always chat.completion.

  • service_tier: optional "auto" or "default" or "flex" or 2 more

    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.
    • 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.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • system_fingerprint: optional string

    This fingerprint represents the backend configuration that the model runs with.

    Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

  • usage: optional object { completion_tokens, prompt_tokens, total_tokens, 2 more }

    Usage statistics for the completion request.

    • completion_tokens: number

      Number of tokens in the generated completion.

    • prompt_tokens: number

      Number of tokens in the prompt.

    • total_tokens: number

      Total number of tokens used in the request (prompt + completion).

    • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

      Breakdown of tokens used in a completion.

      • accepted_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

      • audio_tokens: optional number

        Audio input tokens generated by the model.

      • reasoning_tokens: optional number

        Tokens generated by the model for reasoning.

      • rejected_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

    • prompt_tokens_details: optional object { audio_tokens, cached_tokens }

      Breakdown of tokens used in the prompt.

      • audio_tokens: optional number

        Audio input tokens present in the prompt.

      • cached_tokens: optional number

        Cached tokens present in the prompt.

Example

openai chat:completions update \
  --api-key 'My API Key' \
  --completion-id completion_id \
  --metadata '{foo: string}'

Response

{
  "id": "id",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": {
        "content": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ],
        "refusal": [
          {
            "token": "token",
            "bytes": [
              0
            ],
            "logprob": 0,
            "top_logprobs": [
              {
                "token": "token",
                "bytes": [
                  0
                ],
                "logprob": 0
              }
            ]
          }
        ]
      },
      "message": {
        "content": "content",
        "refusal": "refusal",
        "role": "assistant",
        "annotations": [
          {
            "type": "url_citation",
            "url_citation": {
              "end_index": 0,
              "start_index": 0,
              "title": "title",
              "url": "https://example.com"
            }
          }
        ],
        "audio": {
          "id": "id",
          "data": "data",
          "expires_at": 0,
          "transcript": "transcript"
        },
        "function_call": {
          "arguments": "arguments",
          "name": "name"
        },
        "tool_calls": [
          {
            "id": "id",
            "function": {
              "arguments": "arguments",
              "name": "name"
            },
            "type": "function"
          }
        ]
      }
    }
  ],
  "created": 0,
  "model": "model",
  "object": "chat.completion",
  "service_tier": "auto",
  "system_fingerprint": "system_fingerprint",
  "usage": {
    "completion_tokens": 0,
    "prompt_tokens": 0,
    "total_tokens": 0,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    }
  }
}

Delete chat completion

$ openai chat:completions delete

delete /chat/completions/{completion_id}

Delete a stored chat completion. Only Chat Completions that have been created with the store parameter set to true can be deleted.

Parameters

• --completion-id: string

  The ID of the chat completion to delete.

Returns

• chat_completion_deleted: object { id, deleted, object }

  • id: string

    The ID of the chat completion that was deleted.

  • deleted: boolean

    Whether the chat completion was deleted.

  • object: "chat.completion.deleted"

    The type of object being deleted.

Example

openai chat:completions delete \
  --api-key 'My API Key' \
  --completion-id completion_id

Response

{
  "id": "id",
  "deleted": true,
  "object": "chat.completion.deleted"
}

Domain Types

Chat Completion

• chat_completion: object { id, choices, created, 5 more }

  Represents a chat completion response returned by model, based on the provided input.

  • id: string

    A unique identifier for the chat completion.

  • choices: array of object { finish_reason, index, logprobs, message }

    A list of chat completion choices. Can be more than one if n is greater than 1.

    • finish_reason: "stop" or "length" or "tool_calls" or 2 more

      The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

      • "stop"

      • "length"

      • "tool_calls"

      • "content_filter"

      • "function_call"

    • index: number

      The index of the choice in the list of choices.

    • logprobs: object { content, refusal }

      Log probability information for the choice.

      • content: array of ChatCompletionTokenLogprob

        A list of message content tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

      • refusal: array of ChatCompletionTokenLogprob

        A list of message refusal tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

    • message: object { content, refusal, role, 4 more }

      A chat completion message generated by the model.

      • content: string

        The contents of the message.

      • refusal: string

        The refusal message generated by the model.

      • role: "assistant"

        The role of the author of this message.

      • annotations: optional array of object { type, url_citation }

        Annotations for the message, when applicable, as when using the web search tool.

        • type: "url_citation"

          The type of the URL citation. Always url_citation.

        • url_citation: object { end_index, start_index, title, url }

          A URL citation when using web search.

          • end_index: number

            The index of the last character of the URL citation in the message.

          • start_index: number

            The index of the first character of the URL citation in the message.

          • title: string

            The title of the web resource.

          • url: string

            The URL of the web resource.

      • audio: optional object { id, data, expires_at, transcript }

        If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

        • id: string

          Unique identifier for this audio response.

        • data: string

          Base64 encoded audio bytes generated by the model, in the format specified in the request.

        • expires_at: number

          The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

        • transcript: string

          Transcript of the audio generated by the model.

      • function_call: optional object { arguments, name }

        Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

        • arguments: string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: string

          The name of the function to call.

      • tool_calls: optional array of ChatCompletionMessageToolCall

        The tool calls generated by the model, such as function calls.

        • chat_completion_message_function_tool_call: object { id, function, type }

          A call to a function tool created by the model.

          • id: string

            The ID of the tool call.

          • function: object { arguments, name }

            The function that the model called.

            • arguments: string

              The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

            • name: string

              The name of the function to call.

          • type: "function"

            The type of the tool. Currently, only function is supported.

        • chat_completion_message_custom_tool_call: object { id, custom, type }

          A call to a custom tool created by the model.

          • id: string

            The ID of the tool call.

          • custom: object { input, name }

            The custom tool that the model called.

            • input: string

              The input for the custom tool call generated by the model.

            • name: string

              The name of the custom tool to call.

          • type: "custom"

            The type of the tool. Always custom.

  • created: number

    The Unix timestamp (in seconds) of when the chat completion was created.

  • model: string

    The model used for the chat completion.

  • object: "chat.completion"

    The object type, which is always chat.completion.

  • service_tier: optional "auto" or "default" or "flex" or 2 more

    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.
    • 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.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • system_fingerprint: optional string

    This fingerprint represents the backend configuration that the model runs with.

    Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

  • usage: optional object { completion_tokens, prompt_tokens, total_tokens, 2 more }

    Usage statistics for the completion request.

    • completion_tokens: number

      Number of tokens in the generated completion.

    • prompt_tokens: number

      Number of tokens in the prompt.

    • total_tokens: number

      Total number of tokens used in the request (prompt + completion).

    • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

      Breakdown of tokens used in a completion.

      • accepted_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

      • audio_tokens: optional number

        Audio input tokens generated by the model.

      • reasoning_tokens: optional number

        Tokens generated by the model for reasoning.

      • rejected_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

    • prompt_tokens_details: optional object { audio_tokens, cached_tokens }

      Breakdown of tokens used in the prompt.

      • audio_tokens: optional number

        Audio input tokens present in the prompt.

      • cached_tokens: optional number

        Cached tokens present in the prompt.

Chat Completion Allowed Tool Choice

• chat_completion_allowed_tool_choice: object { allowed_tools, type }

  Constrains the tools available to the model to a pre-defined set.

  • allowed_tools: object { mode, tools }

    Constrains the tools available to the model to a pre-defined set.

    • mode: "auto" or "required"

      Constrains the tools available to the model to a pre-defined set.

      auto allows the model to pick from among the allowed tools and generate a message.

      required requires the model to call one or more of the allowed tools.

      • "auto"

      • "required"

    • tools: array of map[unknown]

      A list of tool definitions that the model should be allowed to call.

      For the Chat Completions API, the list of tool definitions might look like:

      [
        { "type": "function", "function": { "name": "get_weather" } },
        { "type": "function", "function": { "name": "get_time" } }
      ]
      

  • type: "allowed_tools"

    Allowed tool configuration type. Always allowed_tools.

Chat Completion Assistant Message Param

• chat_completion_assistant_message_param: object { role, audio, content, 4 more }

  Messages sent by the model in response to user messages.

  • role: "assistant"

    The role of the messages author, in this case assistant.

  • audio: optional object { id }

    Data about a previous audio response from the model. Learn more.

    • id: string

      Unique identifier for a previous audio response from the model.

  • content: optional string or array of ChatCompletionContentPartText or ChatCompletionContentPartRefusal

    The contents of the assistant message. Required unless tool_calls or function_call is specified.

    • Text content: string

      The contents of the assistant message.

    • Array of content parts: array of ChatCompletionContentPartText or ChatCompletionContentPartRefusal

      An array of content parts with a defined type. Can be one or more of type text, or exactly one of type refusal.

      • chat_completion_content_part_text: object { text, type }

        Learn about text inputs.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

      • chat_completion_content_part_refusal: object { refusal, type }

        • refusal: string

          The refusal message generated by the model.

        • type: "refusal"

          The type of the content part.

  • function_call: optional object { arguments, name }

    Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

    • arguments: string

      The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

    • name: string

      The name of the function to call.

  • name: optional string

    An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • refusal: optional string

    The refusal message by the assistant.

  • tool_calls: optional array of ChatCompletionMessageToolCall

    The tool calls generated by the model, such as function calls.

    • chat_completion_message_function_tool_call: object { id, function, type }

      A call to a function tool created by the model.

      • id: string

        The ID of the tool call.

      • function: object { arguments, name }

        The function that the model called.

        • arguments: string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: string

          The name of the function to call.

      • type: "function"

        The type of the tool. Currently, only function is supported.

    • chat_completion_message_custom_tool_call: object { id, custom, type }

      A call to a custom tool created by the model.

      • id: string

        The ID of the tool call.

      • custom: object { input, name }

        The custom tool that the model called.

        • input: string

          The input for the custom tool call generated by the model.

        • name: string

          The name of the custom tool to call.

      • type: "custom"

        The type of the tool. Always custom.

Chat Completion Audio

• chat_completion_audio: object { id, data, expires_at, transcript }

  If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

  • id: string

    Unique identifier for this audio response.

  • data: string

    Base64 encoded audio bytes generated by the model, in the format specified in the request.

  • expires_at: number

    The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

  • transcript: string

    Transcript of the audio generated by the model.

Chat Completion Audio Param

• chat_completion_audio_param: object { format, voice }

  Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.

  • format: "wav" or "aac" or "mp3" or 3 more

    Specifies the output audio format. Must be one of wav, mp3, flac, opus, or pcm16.

    • "wav"

    • "aac"

    • "mp3"

    • "flac"

    • "opus"

    • "pcm16"

  • voice: string or "alloy" or "ash" or "ballad" or 7 more or object { id }

    The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }.

    • union_member_0: string

    • union_member_1: "alloy" or "ash" or "ballad" or 7 more

      • "alloy"

      • "ash"

      • "ballad"

      • "coral"

      • "echo"

      • "sage"

      • "shimmer"

      • "verse"

      • "marin"

      • "cedar"

    • id: object { id }

      Custom voice reference.

      • id: string

        The custom voice ID, e.g. voice_1234.

Chat Completion Chunk

• chat_completion_chunk: object { id, choices, created, 5 more }

  Represents a streamed chunk of a chat completion response returned by the model, based on the provided input. Learn more.

  • id: string

    A unique identifier for the chat completion. Each chunk has the same ID.

  • choices: array of object { delta, finish_reason, index, logprobs }

    A list of chat completion choices. Can contain more than one elements if n is greater than 1. Can also be empty for the last chunk if you set stream_options: {"include_usage": true}.

    • delta: object { content, function_call, refusal, 2 more }

      A chat completion delta generated by streamed model responses.

      • content: optional string

        The contents of the chunk message.

      • function_call: optional object { arguments, name }

        Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

        • arguments: optional string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: optional string

          The name of the function to call.

      • refusal: optional string

        The refusal message generated by the model.

      • role: optional "developer" or "system" or "user" or 2 more

        The role of the author of this message.

        • "developer"

        • "system"

        • "user"

        • "assistant"

        • "tool"

      • tool_calls: optional array of object { index, id, function, type }

        • index: number

        • id: optional string

          The ID of the tool call.

        • function: optional object { arguments, name }

          • arguments: optional string

            The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

          • name: optional string

            The name of the function to call.

        • type: optional "function"

          The type of the tool. Currently, only function is supported.

          • "function"

    • finish_reason: "stop" or "length" or "tool_calls" or 2 more

      The reason the model stopped generating tokens. This will be stop if the model hit a natural stop point or a provided stop sequence, length if the maximum number of tokens specified in the request was reached, content_filter if content was omitted due to a flag from our content filters, tool_calls if the model called a tool, or function_call (deprecated) if the model called a function.

      • "stop"

      • "length"

      • "tool_calls"

      • "content_filter"

      • "function_call"

    • index: number

      The index of the choice in the list of choices.

    • logprobs: optional object { content, refusal }

      Log probability information for the choice.

      • content: array of ChatCompletionTokenLogprob

        A list of message content tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

          • token: string

            The token.

          • bytes: array of number

            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

          • logprob: number

            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

      • refusal: array of ChatCompletionTokenLogprob

        A list of message refusal tokens with log probability information.

        • token: string

          The token.

        • bytes: array of number

          A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

        • logprob: number

          The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

        • top_logprobs: array of object { token, bytes, logprob }

          List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

  • created: number

    The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp.

  • model: string

    The model to generate the completion.

  • object: "chat.completion.chunk"

    The object type, which is always chat.completion.chunk.

  • service_tier: optional "auto" or "default" or "flex" or 2 more

    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.
    • 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.

    • "auto"

    • "default"

    • "flex"

    • "scale"

    • "priority"

  • system_fingerprint: optional string

    This fingerprint represents the backend configuration that the model runs with. Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

  • usage: optional object { completion_tokens, prompt_tokens, total_tokens, 2 more }

    An optional field that will only be present when you set stream_options: {"include_usage": true} in your request. When present, it contains a null value except for the last chunk which contains the token usage statistics for the entire request.

    NOTE: If the stream is interrupted or cancelled, you may not receive the final usage chunk which contains the total token usage for the request.

    • completion_tokens: number

      Number of tokens in the generated completion.

    • prompt_tokens: number

      Number of tokens in the prompt.

    • total_tokens: number

      Total number of tokens used in the request (prompt + completion).

    • completion_tokens_details: optional object { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

      Breakdown of tokens used in a completion.

      • accepted_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.

      • audio_tokens: optional number

        Audio input tokens generated by the model.

      • reasoning_tokens: optional number

        Tokens generated by the model for reasoning.

      • rejected_prediction_tokens: optional number

        When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits.

    • prompt_tokens_details: optional object { audio_tokens, cached_tokens }

      Breakdown of tokens used in the prompt.

      • audio_tokens: optional number

        Audio input tokens present in the prompt.

      • cached_tokens: optional number

        Cached tokens present in the prompt.

Chat Completion Content Part

• chat_completion_content_part: ChatCompletionContentPartText or ChatCompletionContentPartImage or ChatCompletionContentPartInputAudio or object { file, type }

  Learn about text inputs.

  • chat_completion_content_part_text: object { text, type }

    Learn about text inputs.

    • text: string

      The text content.

    • type: "text"

      The type of the content part.

  • chat_completion_content_part_image: object { image_url, type }

    Learn about image inputs.

    • image_url: object { url, detail }

      • url: string

        Either a URL of the image or the base64 encoded image data.

      • detail: optional "auto" or "low" or "high"

        Specifies the detail level of the image. Learn more in the Vision guide.

        • "auto"

        • "low"

        • "high"

    • type: "image_url"

      The type of the content part.

  • chat_completion_content_part_input_audio: object { input_audio, type }

    Learn about audio inputs.

    • input_audio: object { data, format }

      • data: string

        Base64 encoded audio data.

      • format: "wav" or "mp3"

        The format of the encoded audio data. Currently supports "wav" and "mp3".

        • "wav"

        • "mp3"

    • type: "input_audio"

      The type of the content part. Always input_audio.

  • file: object { file, type }

    Learn about file inputs for text generation.

    • file: object { file_data, file_id, filename }

      • file_data: optional string

        The base64 encoded file data, used when passing the file to the model as a string.

      • file_id: optional string

        The ID of an uploaded file to use as input.

      • filename: optional string

        The name of the file, used when passing the file to the model as a string.

    • type: "file"

      The type of the content part. Always file.

Chat Completion Content Part Image

• chat_completion_content_part_image: object { image_url, type }

  Learn about image inputs.

  • image_url: object { url, detail }

    • url: string

      Either a URL of the image or the base64 encoded image data.

    • detail: optional "auto" or "low" or "high"

      Specifies the detail level of the image. Learn more in the Vision guide.

      • "auto"

      • "low"

      • "high"

  • type: "image_url"

    The type of the content part.

Chat Completion Content Part Input Audio

• chat_completion_content_part_input_audio: object { input_audio, type }

  Learn about audio inputs.

  • input_audio: object { data, format }

    • data: string

      Base64 encoded audio data.

    • format: "wav" or "mp3"

      The format of the encoded audio data. Currently supports "wav" and "mp3".

      • "wav"

      • "mp3"

  • type: "input_audio"

    The type of the content part. Always input_audio.

Chat Completion Content Part Refusal

• chat_completion_content_part_refusal: object { refusal, type }

  • refusal: string

    The refusal message generated by the model.

  • type: "refusal"

    The type of the content part.

Chat Completion Content Part Text

• chat_completion_content_part_text: object { text, type }

  Learn about text inputs.

  • text: string

    The text content.

  • type: "text"

    The type of the content part.

Chat Completion Custom Tool

• chat_completion_custom_tool: object { custom, type }

  A custom tool that processes input using a specified format.

  • custom: object { name, description, format }

    Properties of the custom tool.

    • name: string

      The name of the custom tool, used to identify it in tool calls.

    • description: optional string

      Optional description of the custom tool, used to provide more context.

    • format: optional object { type } or object { grammar, type }

      The input format for the custom tool. Default is unconstrained text.

      • text: object { type }

        Unconstrained free-form text.

      • grammar: object { grammar, type }

        A grammar defined by the user.

        • grammar: object { definition, syntax }

          Your chosen grammar.

          • definition: string

            The grammar definition.

          • syntax: "lark" or "regex"

            The syntax of the grammar definition. One of lark or regex.

            • "lark"

            • "regex"

        • type: "grammar"

          Grammar format. Always grammar.

  • type: "custom"

    The type of the custom tool. Always custom.

Chat Completion Deleted

• chat_completion_deleted: object { id, deleted, object }

  • id: string

    The ID of the chat completion that was deleted.

  • deleted: boolean

    Whether the chat completion was deleted.

  • object: "chat.completion.deleted"

    The type of object being deleted.

Chat Completion Developer Message Param

• chat_completion_developer_message_param: object { content, role, name }

  Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

  • content: string or array of ChatCompletionContentPartText

    The contents of the developer message.

    • Text content: string

      The contents of the developer message.

    • Array of content parts: array of ChatCompletionContentPartText

      An array of content parts with a defined type. For developer messages, only type text is supported.

      • text: string

        The text content.

      • type: "text"

        The type of the content part.

  • role: "developer"

    The role of the messages author, in this case developer.

  • name: optional string

    An optional name for the participant. Provides the model information to differentiate between participants of the same role.

Chat Completion Function Call Option

• chat_completion_function_call_option: object { name }

  Specifying a particular function via {"name": "my_function"} forces the model to call that function.

  • name: string

    The name of the function to call.

Chat Completion Function Message Param

• chat_completion_function_message_param: object { content, name, role }

  • content: string

    The contents of the function message.

  • name: string

    The name of the function to call.

  • role: "function"

    The role of the messages author, in this case function.

Chat Completion Function Tool

• chat_completion_function_tool: object { function, type }

  A function tool that can be used to generate a response.

  • function: object { name, description, parameters, strict }

    • name: string

      The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

    • description: optional string

      A description of what the function does, used by the model to choose when and how to call the function.

    • parameters: optional map[unknown]

      The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

      Omitting parameters defines a function with an empty parameter list.

    • strict: optional boolean

      Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the parameters field. Only a subset of JSON Schema is supported when strict is true. Learn more about Structured Outputs in the function calling guide.

  • type: "function"

    The type of the tool. Currently, only function is supported.

Chat Completion Message

• chat_completion_message: object { content, refusal, role, 4 more }

  A chat completion message generated by the model.

  • content: string

    The contents of the message.

  • refusal: string

    The refusal message generated by the model.

  • role: "assistant"

    The role of the author of this message.

  • annotations: optional array of object { type, url_citation }

    Annotations for the message, when applicable, as when using the web search tool.

    • type: "url_citation"

      The type of the URL citation. Always url_citation.

    • url_citation: object { end_index, start_index, title, url }

      A URL citation when using web search.

      • end_index: number

        The index of the last character of the URL citation in the message.

      • start_index: number

        The index of the first character of the URL citation in the message.

      • title: string

        The title of the web resource.

      • url: string

        The URL of the web resource.

  • audio: optional object { id, data, expires_at, transcript }

    If the audio output modality is requested, this object contains data about the audio response from the model. Learn more.

    • id: string

      Unique identifier for this audio response.

    • data: string

      Base64 encoded audio bytes generated by the model, in the format specified in the request.

    • expires_at: number

      The Unix timestamp (in seconds) for when this audio response will no longer be accessible on the server for use in multi-turn conversations.

    • transcript: string

      Transcript of the audio generated by the model.

  • function_call: optional object { arguments, name }

    Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

    • arguments: string

      The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

    • name: string

      The name of the function to call.

  • tool_calls: optional array of ChatCompletionMessageToolCall

    The tool calls generated by the model, such as function calls.

    • chat_completion_message_function_tool_call: object { id, function, type }

      A call to a function tool created by the model.

      • id: string

        The ID of the tool call.

      • function: object { arguments, name }

        The function that the model called.

        • arguments: string

          The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

        • name: string

          The name of the function to call.

      • type: "function"

        The type of the tool. Currently, only function is supported.

    • chat_completion_message_custom_tool_call: object { id, custom, type }

      A call to a custom tool created by the model.

      • id: string

        The ID of the tool call.

      • custom: object { input, name }

        The custom tool that the model called.

        • input: string

          The input for the custom tool call generated by the model.

        • name: string

          The name of the custom tool to call.

      • type: "custom"

        The type of the tool. Always custom.

Chat Completion Message Custom Tool Call

• chat_completion_message_custom_tool_call: object { id, custom, type }

  A call to a custom tool created by the model.

  • id: string

    The ID of the tool call.

  • custom: object { input, name }

    The custom tool that the model called.

    • input: string

      The input for the custom tool call generated by the model.

    • name: string

      The name of the custom tool to call.

  • type: "custom"

    The type of the tool. Always custom.

Chat Completion Message Function Tool Call

• chat_completion_message_function_tool_call: object { id, function, type }

  A call to a function tool created by the model.

  • id: string

    The ID of the tool call.

  • function: object { arguments, name }

    The function that the model called.

    • arguments: string

      The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

    • name: string

      The name of the function to call.

  • type: "function"

    The type of the tool. Currently, only function is supported.

Chat Completion Message Param

• chat_completion_message_param: ChatCompletionDeveloperMessageParam or ChatCompletionSystemMessageParam or ChatCompletionUserMessageParam or 3 more

  Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

  • chat_completion_developer_message_param: object { content, role, name }

    Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, developer messages replace the previous system messages.

    • content: string or array of ChatCompletionContentPartText

      The contents of the developer message.

      • Text content: string

        The contents of the developer message.

      • Array of content parts: array of ChatCompletionContentPartText

        An array of content parts with a defined type. For developer messages, only type text is supported.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

    • role: "developer"

      The role of the messages author, in this case developer.

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • chat_completion_system_message_param: object { content, role, name }

    Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, use developer messages for this purpose instead.

    • content: string or array of ChatCompletionContentPartText

      The contents of the system message.

      • Text content: string

        The contents of the system message.

      • Array of content parts: array of ChatCompletionContentPartText

        An array of content parts with a defined type. For system messages, only type text is supported.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

    • role: "system"

      The role of the messages author, in this case system.

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • chat_completion_user_message_param: object { content, role, name }

    Messages sent by an end user, containing prompts or additional context information.

    • content: string or array of ChatCompletionContentPart

      The contents of the user message.

      • Text content: string

        The text contents of the message.

      • Array of content parts: array of ChatCompletionContentPart

        An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text, image, or audio inputs.

        • chat_completion_content_part_text: object { text, type }

          Learn about text inputs.

          • text: string

            The text content.

          • type: "text"

            The type of the content part.

        • chat_completion_content_part_image: object { image_url, type }

          Learn about image inputs.

          • image_url: object { url, detail }

            • url: string

              Either a URL of the image or the base64 encoded image data.

            • detail: optional "auto" or "low" or "high"

              Specifies the detail level of the image. Learn more in the Vision guide.

              • "auto"

              • "low"

              • "high"

          • type: "image_url"

            The type of the content part.

        • chat_completion_content_part_input_audio: object { input_audio, type }

          Learn about audio inputs.

          • input_audio: object { data, format }

            • data: string

              Base64 encoded audio data.

            • format: "wav" or "mp3"

              The format of the encoded audio data. Currently supports "wav" and "mp3".

              • "wav"

              • "mp3"

          • type: "input_audio"

            The type of the content part. Always input_audio.

        • file: object { file, type }

          Learn about file inputs for text generation.

          • file: object { file_data, file_id, filename }

            • file_data: optional string

              The base64 encoded file data, used when passing the file to the model as a string.

            • file_id: optional string

              The ID of an uploaded file to use as input.

            • filename: optional string

              The name of the file, used when passing the file to the model as a string.

          • type: "file"

            The type of the content part. Always file.

    • role: "user"

      The role of the messages author, in this case user.

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

  • chat_completion_assistant_message_param: object { role, audio, content, 4 more }

    Messages sent by the model in response to user messages.

    • role: "assistant"

      The role of the messages author, in this case assistant.

    • audio: optional object { id }

      Data about a previous audio response from the model. Learn more.

      • id: string

        Unique identifier for a previous audio response from the model.

    • content: optional string or array of ChatCompletionContentPartText or ChatCompletionContentPartRefusal

      The contents of the assistant message. Required unless tool_calls or function_call is specified.

      • Text content: string

        The contents of the assistant message.

      • Array of content parts: array of ChatCompletionContentPartText or ChatCompletionContentPartRefusal

        An array of content parts with a defined type. Can be one or more of type text, or exactly one of type refusal.

        • chat_completion_content_part_text: object { text, type }

          Learn about text inputs.

          • text: string

            The text content.

          • type: "text"

            The type of the content part.

        • chat_completion_content_part_refusal: object { refusal, type }

          • refusal: string

            The refusal message generated by the model.

          • type: "refusal"

            The type of the content part.

    • function_call: optional object { arguments, name }

      Deprecated and replaced by tool_calls. The name and arguments of a function that should be called, as generated by the model.

      • arguments: string

        The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

      • name: string

        The name of the function to call.

    • name: optional string

      An optional name for the participant. Provides the model information to differentiate between participants of the same role.

    • refusal: optional string

      The refusal message by the assistant.

    • tool_calls: optional array of ChatCompletionMessageToolCall

      The tool calls generated by the model, such as function calls.

      • chat_completion_message_function_tool_call: object { id, function, type }

        A call to a function tool created by the model.

        • id: string

          The ID of the tool call.

        • function: object { arguments, name }

          The function that the model called.

          • arguments: string

            The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

          • name: string

            The name of the function to call.

        • type: "function"

          The type of the tool. Currently, only function is supported.

      • chat_completion_message_custom_tool_call: object { id, custom, type }

        A call to a custom tool created by the model.

        • id: string

          The ID of the tool call.

        • custom: object { input, name }

          The custom tool that the model called.

          • input: string

            The input for the custom tool call generated by the model.

          • name: string

            The name of the custom tool to call.

        • type: "custom"

          The type of the tool. Always custom.

  • chat_completion_tool_message_param: object { content, role, tool_call_id }

    • content: string or array of ChatCompletionContentPartText

      The contents of the tool message.

      • Text content: string

        The contents of the tool message.

      • Array of content parts: array of ChatCompletionContentPartText

        An array of content parts with a defined type. For tool messages, only type text is supported.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

    • role: "tool"

      The role of the messages author, in this case tool.

    • tool_call_id: string

      Tool call that this message is responding to.

  • chat_completion_function_message_param: object { content, name, role }

    • content: string

      The contents of the function message.

    • name: string

      The name of the function to call.

    • role: "function"

      The role of the messages author, in this case function.

Chat Completion Message Tool Call

• chat_completion_message_tool_call: ChatCompletionMessageFunctionToolCall or ChatCompletionMessageCustomToolCall

  A call to a function tool created by the model.

  • chat_completion_message_function_tool_call: object { id, function, type }

    A call to a function tool created by the model.

    • id: string

      The ID of the tool call.

    • function: object { arguments, name }

      The function that the model called.

      • arguments: string

        The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.

      • name: string

        The name of the function to call.

    • type: "function"

      The type of the tool. Currently, only function is supported.

  • chat_completion_message_custom_tool_call: object { id, custom, type }

    A call to a custom tool created by the model.

    • id: string

      The ID of the tool call.

    • custom: object { input, name }

      The custom tool that the model called.

      • input: string

        The input for the custom tool call generated by the model.

      • name: string

        The name of the custom tool to call.

    • type: "custom"

      The type of the tool. Always custom.

Chat Completion Modality

• chat_completion_modality: "text" or "audio"

  • "text"

  • "audio"

Chat Completion Named Tool Choice

• chat_completion_named_tool_choice: object { function, type }

  Specifies a tool the model should use. Use to force the model to call a specific function.

  • function: object { name }

    • name: string

      The name of the function to call.

  • type: "function"

    For function calling, the type is always function.

Chat Completion Named Tool Choice Custom

• chat_completion_named_tool_choice_custom: object { custom, type }

  Specifies a tool the model should use. Use to force the model to call a specific custom tool.

  • custom: object { name }

    • name: string

      The name of the custom tool to call.

  • type: "custom"

    For custom tool calling, the type is always custom.

Chat Completion Prediction Content

• chat_completion_prediction_content: object { content, type }

  Static predicted output content, such as the content of a text file that is being regenerated.

  • content: string or array of ChatCompletionContentPartText

    The content that should be matched when generating a model response. If generated tokens would match this content, the entire model response can be returned much more quickly.

    • Text content: string

      The content used for a Predicted Output. This is often the text of a file you are regenerating with minor changes.

    • Array of content parts: array of ChatCompletionContentPartText

      An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text inputs.

      • text: string

        The text content.

      • type: "text"

        The type of the content part.

  • type: "content"

    The type of the predicted content you want to provide. This type is currently always content.

Chat Completion Role

• chat_completion_role: "developer" or "system" or "user" or 3 more

  The role of the author of a message

  • "developer"

  • "system"

  • "user"

  • "assistant"

  • "tool"

  • "function"

Chat Completion Store Message

• chat_completion_store_message: ChatCompletionMessage

  A chat completion message generated by the model.

  • id: string

    The identifier of the chat message.

  • content_parts: optional array of ChatCompletionContentPartText or ChatCompletionContentPartImage

    If a content parts array was provided, this is an array of text and image_url parts. Otherwise, null.

    • chat_completion_content_part_text: object { text, type }

      Learn about text inputs.

      • text: string

        The text content.

      • type: "text"

        The type of the content part.

    • chat_completion_content_part_image: object { image_url, type }

      Learn about image inputs.

      • image_url: object { url, detail }

        • url: string

          Either a URL of the image or the base64 encoded image data.

        • detail: optional "auto" or "low" or "high"

          Specifies the detail level of the image. Learn more in the Vision guide.

          • "auto"

          • "low"

          • "high"

      • type: "image_url"

        The type of the content part.

Chat Completion Stream Options

• chat_completion_stream_options: object { include_obfuscation, include_usage }

  Options for streaming response. Only set this when you set stream: true.

  • include_obfuscation: optional boolean

    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.

  • include_usage: optional boolean

    If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array.

    All other chunks will also include a usage field, but with a null value. NOTE: If the stream is interrupted, you may not receive the final usage chunk which contains the total token usage for the request.

Chat Completion System Message Param

• chat_completion_system_message_param: object { content, role, name }

  Developer-provided instructions that the model should follow, regardless of messages sent by the user. With o1 models and newer, use developer messages for this purpose instead.

  • content: string or array of ChatCompletionContentPartText

    The contents of the system message.

    • Text content: string

      The contents of the system message.

    • Array of content parts: array of ChatCompletionContentPartText

      An array of content parts with a defined type. For system messages, only type text is supported.

      • text: string

        The text content.

      • type: "text"

        The type of the content part.

  • role: "system"

    The role of the messages author, in this case system.

  • name: optional string

    An optional name for the participant. Provides the model information to differentiate between participants of the same role.

Chat Completion Token Logprob

• chat_completion_token_logprob: object { token, bytes, logprob, top_logprobs }

  • token: string

    The token.

  • bytes: array of number

    A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

  • logprob: number

    The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

  • top_logprobs: array of object { token, bytes, logprob }

    List of the most likely tokens and their log probability, at this token position. The number of entries may be fewer than the requested top_logprobs.

    • token: string

      The token.

    • bytes: array of number

      A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be null if there is no bytes representation for the token.

    • logprob: number

      The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value -9999.0 is used to signify that the token is very unlikely.

Chat Completion Tool

• chat_completion_tool: ChatCompletionFunctionTool or ChatCompletionCustomTool

  A function tool that can be used to generate a response.

  • chat_completion_function_tool: object { function, type }

    A function tool that can be used to generate a response.

    • function: object { name, description, parameters, strict }

      • name: string

        The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

      • description: optional string

        A description of what the function does, used by the model to choose when and how to call the function.

      • parameters: optional map[unknown]

        The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.

        Omitting parameters defines a function with an empty parameter list.

      • strict: optional boolean

        Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the parameters field. Only a subset of JSON Schema is supported when strict is true. Learn more about Structured Outputs in the function calling guide.

    • type: "function"

      The type of the tool. Currently, only function is supported.

  • chat_completion_custom_tool: object { custom, type }

    A custom tool that processes input using a specified format.

    • custom: object { name, description, format }

      Properties of the custom tool.

      • name: string

        The name of the custom tool, used to identify it in tool calls.

      • description: optional string

        Optional description of the custom tool, used to provide more context.

      • format: optional object { type } or object { grammar, type }

        The input format for the custom tool. Default is unconstrained text.

        • text: object { type }

          Unconstrained free-form text.

        • grammar: object { grammar, type }

          A grammar defined by the user.

          • grammar: object { definition, syntax }

            Your chosen grammar.

            • definition: string

              The grammar definition.

            • syntax: "lark" or "regex"

              The syntax of the grammar definition. One of lark or regex.

              • "lark"

              • "regex"

          • type: "grammar"

            Grammar format. Always grammar.

    • type: "custom"

      The type of the custom tool. Always custom.

Chat Completion Tool Choice Option

• chat_completion_tool_choice_option: "none" or "auto" or "required" or ChatCompletionAllowedToolChoice or ChatCompletionNamedToolChoice or ChatCompletionNamedToolChoiceCustom

  Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.

  none is the default when no tools are present. auto is the default if tools are present.

  • Auto: "none" or "auto" or "required"

    none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools.

    • "none"

    • "auto"

    • "required"

  • chat_completion_allowed_tool_choice: object { allowed_tools, type }

    Constrains the tools available to the model to a pre-defined set.

    • allowed_tools: object { mode, tools }

      Constrains the tools available to the model to a pre-defined set.

      • mode: "auto" or "required"

        Constrains the tools available to the model to a pre-defined set.

        auto allows the model to pick from among the allowed tools and generate a message.

        required requires the model to call one or more of the allowed tools.

        • "auto"

        • "required"

      • tools: array of map[unknown]

        A list of tool definitions that the model should be allowed to call.

        For the Chat Completions API, the list of tool definitions might look like:

        [
          { "type": "function", "function": { "name": "get_weather" } },
          { "type": "function", "function": { "name": "get_time" } }
        ]
        

    • type: "allowed_tools"

      Allowed tool configuration type. Always allowed_tools.

  • chat_completion_named_tool_choice: object { function, type }

    Specifies a tool the model should use. Use to force the model to call a specific function.

    • function: object { name }

      • name: string

        The name of the function to call.

    • type: "function"

      For function calling, the type is always function.

  • chat_completion_named_tool_choice_custom: object { custom, type }

    Specifies a tool the model should use. Use to force the model to call a specific custom tool.

    • custom: object { name }

      • name: string

        The name of the custom tool to call.

    • type: "custom"

      For custom tool calling, the type is always custom.

Chat Completion Tool Message Param

• chat_completion_tool_message_param: object { content, role, tool_call_id }

  • content: string or array of ChatCompletionContentPartText

    The contents of the tool message.

    • Text content: string

      The contents of the tool message.

    • Array of content parts: array of ChatCompletionContentPartText

      An array of content parts with a defined type. For tool messages, only type text is supported.

      • text: string

        The text content.

      • type: "text"

        The type of the content part.

  • role: "tool"

    The role of the messages author, in this case tool.

  • tool_call_id: string

    Tool call that this message is responding to.

Chat Completion User Message Param

• chat_completion_user_message_param: object { content, role, name }

  Messages sent by an end user, containing prompts or additional context information.

  • content: string or array of ChatCompletionContentPart

    The contents of the user message.

    • Text content: string

      The text contents of the message.

    • Array of content parts: array of ChatCompletionContentPart

      An array of content parts with a defined type. Supported options differ based on the model being used to generate the response. Can contain text, image, or audio inputs.

      • chat_completion_content_part_text: object { text, type }

        Learn about text inputs.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

      • chat_completion_content_part_image: object { image_url, type }

        Learn about image inputs.

        • image_url: object { url, detail }

          • url: string

            Either a URL of the image or the base64 encoded image data.

          • detail: optional "auto" or "low" or "high"

            Specifies the detail level of the image. Learn more in the Vision guide.

            • "auto"

            • "low"

            • "high"

        • type: "image_url"

          The type of the content part.

      • chat_completion_content_part_input_audio: object { input_audio, type }

        Learn about audio inputs.

        • input_audio: object { data, format }

          • data: string

            Base64 encoded audio data.

          • format: "wav" or "mp3"

            The format of the encoded audio data. Currently supports "wav" and "mp3".

            • "wav"

            • "mp3"

        • type: "input_audio"

          The type of the content part. Always input_audio.

      • file: object { file, type }

        Learn about file inputs for text generation.

        • file: object { file_data, file_id, filename }

          • file_data: optional string

            The base64 encoded file data, used when passing the file to the model as a string.

          • file_id: optional string

            The ID of an uploaded file to use as input.

          • filename: optional string

            The name of the file, used when passing the file to the model as a string.

        • type: "file"

          The type of the content part. Always file.

  • role: "user"

    The role of the messages author, in this case user.

  • name: optional string

    An optional name for the participant. Provides the model information to differentiate between participants of the same role.

Chat Completion Allowed Tools

• ChatCompletionAllowedTools: object { mode, tools }

  Constrains the tools available to the model to a pre-defined set.

  • mode: "auto" or "required"

    Constrains the tools available to the model to a pre-defined set.

    auto allows the model to pick from among the allowed tools and generate a message.

    required requires the model to call one or more of the allowed tools.

    • "auto"

    • "required"

  • tools: array of map[unknown]

    A list of tool definitions that the model should be allowed to call.

    For the Chat Completions API, the list of tool definitions might look like:

    [
      { "type": "function", "function": { "name": "get_weather" } },
      { "type": "function", "function": { "name": "get_time" } }
    ]
    

Messages

Get chat messages

$ openai chat:completions:messages list

get /chat/completions/{completion_id}/messages

Get the messages in a stored chat completion. Only Chat Completions that have been created with the store parameter set to true will be returned.

Parameters

• --completion-id: string

  The ID of the chat completion to retrieve messages from.

• --after: optional string

  Identifier for the last message from the previous pagination request.

• --limit: optional number

  Number of messages to retrieve.

• --order: optional "asc" or "desc"

  Sort order for messages by timestamp. Use asc for ascending order or desc for descending order. Defaults to asc.

Returns

• ChatCompletionMessageList: object { data, first_id, has_more, 2 more }

  An object representing a list of chat completion messages.

  • data: array of ChatCompletionStoreMessage

    An array of chat completion message objects.

    • id: string

      The identifier of the chat message.

    • content_parts: optional array of ChatCompletionContentPartText or ChatCompletionContentPartImage

      If a content parts array was provided, this is an array of text and image_url parts. Otherwise, null.

      • chat_completion_content_part_text: object { text, type }

        Learn about text inputs.

        • text: string

          The text content.

        • type: "text"

          The type of the content part.

      • chat_completion_content_part_image: object { image_url, type }

        Learn about image inputs.

        • image_url: object { url, detail }

          • url: string

            Either a URL of the image or the base64 encoded image data.

          • detail: optional "auto" or "low" or "high"

            Specifies the detail level of the image. Learn more in the Vision guide.

            • "auto"

            • "low"

            • "high"

        • type: "image_url"

          The type of the content part.

  • first_id: string

    The identifier of the first chat message in the data array.

  • has_more: boolean

    Indicates whether there are more chat messages available.

  • last_id: string

    The identifier of the last chat message in the data array.

  • object: "list"

    The type of this object. It is always set to "list".

Example

openai chat:completions:messages list \
  --api-key 'My API Key' \
  --completion-id completion_id

Response

{
  "data": [
    {
      "content": "content",
      "refusal": "refusal",
      "role": "assistant",
      "annotations": [
        {
          "type": "url_citation",
          "url_citation": {
            "end_index": 0,
            "start_index": 0,
            "title": "title",
            "url": "https://example.com"
          }
        }
      ],
      "audio": {
        "id": "id",
        "data": "data",
        "expires_at": 0,
        "transcript": "transcript"
      },
      "function_call": {
        "arguments": "arguments",
        "name": "name"
      },
      "tool_calls": [
        {
          "id": "id",
          "function": {
            "arguments": "arguments",
            "name": "name"
          },
          "type": "function"
        }
      ],
      "id": "id",
      "content_parts": [
        {
          "text": "text",
          "type": "text"
        }
      ]
    }
  ],
  "first_id": "first_id",
  "has_more": true,
  "last_id": "last_id",
  "object": "list"
}