---
title: "Gets stored completion by the given stored completion id."
method: GET
path: "/chat/completions/{stored-completion-id}"
tags: ["StoredCompletion:"]
---

# Gets stored completion by the given stored completion id.

`GET /chat/completions/{stored-completion-id}`

## Path parameters

- `stored-completion-id` string, required

## Query parameters

- `api-version` string, required

## Response `200`

Success

- StoredCompletionResponse
  - `id` string — The identity of stored completion.
  - `model` string — ID of the model to use.
  - `created` integer — The Unix timestamp (in seconds) of when the chat completion was created.
  - `request_id` string — An unique identifier for the OpenAI API request. Please include this request ID when contacting support.
  - `tool_choice` string — Controls which (if any) tool is called by the model.
  - `usage` Usage
    - `total_tokens` integer — Total number of tokens used in the request (prompt + completion).
    - `completion_tokens` integer — Number of tokens in the generated completion.
    - `prompt_tokens` integer — Number of tokens in the prompt.
  - `seed` integer — 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.
  - `top_p` number, float — 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.
  - `temperature` number, float — 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.
  - `presence_penalty` number, float — 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.
  - `frequency_penalty` number, float — 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.
  - `system_fingerprint` 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.
  - `input_user` string — The input user for this request.
  - `service_tier` string — Specifies the latency tier to use for processing the request.
  - `tools` Tool[] — A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
    - `type` string — The type of tool call. This is always going to be `function` for this type of tool call.
    - `function` FunctionDefinition
      - `parameters` unknown
      - `description` string — A description of what the function does, used by the model to choose when and how to call the function.
      - `name` string — The name of the function to be called.
  - `metadata` object — Arbitrary key-value pairs for additional information.
  - `choices` Choice[] — A list of chat completion choices. Can be more than one if `n` is greater than 1.
    - `index` integer — The index of the choice in the list of choices.
    - `message` ChoiceMessage
      - `content` string — The contents of the message.
      - `role` string — The role of the entity that is creating the message.
      - `tool_calls` ToolCall[] — A list of the relevant tool calls.
        - `type` string — The type of tool call the output is required for. For now, this is always `function`.
        - `function` FunctionCallFunction
          - `name` string — The name of the function.
          - `arguments` string — The arguments that the model expects you to pass to the function.
        - `id` string — The ID of the tool call.
    - `finish_reason` string — The reason the model stopped generating tokens.
    - `logprobs` object — Log probability information for the choice.
  - `object` string — The type of this object.

## Other responses

- `default` — An error occurred.

---

[API](https://skmtc.net/azure/apis/cognitiveservices-azureopenai-authoring.md) · [All operations](https://skmtc.net/azure/apis/cognitiveservices-azureopenai-authoring/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/azure/cognitiveservices-azureopenai-authoring/revisions/b177dc430e39/schema)