Generate legacy text completion from prompt

client.completions.create(, ?): Completion { id, choices, created, 4 more } | Stream<Completion { id, choices, created, 4 more } >

POST/v5/completions

Generates a legacy text completion from a raw prompt (a string or list of strings).

Use this endpoint for non-chat, prompt-in/text-out inference using the OpenAI text-completion contract; use /v5/chat/completions when you have a structured messages array, /v5/responses for the OpenAI Responses API, and /v5/inference for payloads that follow no OpenAI schema. The model is selected from model given as vendor/name and routed to the matching per-vendor gateway. When stream is set the response is delivered as server-sent events; otherwise a single text_completion object is returned. Token usage is recorded for the account, read from the final chunk on streaming responses.

ParametersExpand Collapse

CompletionCreateParams = CompletionCreateParamsNonStreaming { stream } | CompletionCreateParamsStreaming { stream }

CompletionCreateParamsBase { model, prompt, best_of, 15 more }

model: string

model specified as model_vendor/model, for example openai/gpt-4o

prompt: string | Array<string>

The prompt to generate completions for, encoded as a string

One of the following:

string

Array<string>

best_of?: number

Generates best_of completions server-side and returns the best one. Must be greater than n when used together.

echo?: boolean

Echo back the prompt in addition to the completion

frequency_penalty?: number

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text.

logit_bias?: Record<string, number>

Modify the likelihood of specified tokens appearing in the completion. Maps tokens to bias values from -100 to 100.

logprobs?: number

Include log probabilities of the most likely tokens. Maximum value is 5.

max_tokens?: number

The maximum number of tokens that can be generated in the completion.

n?: number

How many completions to generate for each prompt.

presence_penalty?: number

Number between -2.0 and 2.0. Positive values penalize new tokens based on their presence in the text so far.

seed?: number

If specified, attempts to generate deterministic samples. Determinism is not guaranteed.

stop?: string | Array<string>

Up to 4 sequences where the API will stop generating further tokens.

One of the following:

string

Array<string>

stream?: false

Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events.

stream_options?: Record<string, unknown>

Options for streaming response. Only set this when stream is True.

suffix?: string

The suffix that comes after a completion of inserted text. Only supported for gpt-3.5-turbo-instruct.

temperature?: number

Sampling temperature between 0 and 2. Higher values make output more random, lower more focused.

top_p?: number

Alternative to temperature. Consider only tokens with top_p probability mass. Range 0-1.

user?: string

A unique identifier representing your end-user, which can help OpenAI monitor and detect abuse.

CompletionCreateParamsNonStreaming extends CompletionCreateParamsBase { model, prompt, best_of, 15 more } { stream }

stream?: false

Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events.

CompletionCreateParamsStreaming extends CompletionCreateParamsBase { model, prompt, best_of, 15 more } { stream }

stream: true

Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events.

ReturnsExpand Collapse

Completion { id, choices, created, 4 more }

id: string

choices: Array<Choice>

finish_reason: "stop" | "length" | "content_filter"

One of the following:

"stop"

"length"

"content_filter"

index: number

text: string

logprobs?: Logprobs { text_offset, token_logprobs, tokens, top_logprobs }

text_offset?: Array<number>

token_logprobs?: Array<number>

tokens?: Array<string>

top_logprobs?: Array<Record<string, number>>

created: number

model: string

object?: "text_completion"

system_fingerprint?: string

usage?: CompletionUsage { completion_tokens, prompt_tokens, total_tokens, 2 more }

Usage statistics for the completion request.

completion_tokens: number

prompt_tokens: number

total_tokens: number

completion_tokens_details?: CompletionTokensDetails { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

Breakdown of tokens used in a completion.

accepted_prediction_tokens?: number

audio_tokens?: number

reasoning_tokens?: number

rejected_prediction_tokens?: number

prompt_tokens_details?: PromptTokensDetails { audio_tokens, cached_tokens }

Breakdown of tokens used in the prompt.

audio_tokens?: number

cached_tokens?: number

Completion { id, choices, created, 4 more }

id: string

choices: Array<Choice>

finish_reason: "stop" | "length" | "content_filter"

One of the following:

"stop"

"length"

"content_filter"

index: number

text: string

logprobs?: Logprobs { text_offset, token_logprobs, tokens, top_logprobs }

text_offset?: Array<number>

token_logprobs?: Array<number>

tokens?: Array<string>

top_logprobs?: Array<Record<string, number>>

created: number

model: string

object?: "text_completion"

system_fingerprint?: string

usage?: CompletionUsage { completion_tokens, prompt_tokens, total_tokens, 2 more }

Usage statistics for the completion request.

completion_tokens: number

prompt_tokens: number

total_tokens: number

completion_tokens_details?: CompletionTokensDetails { accepted_prediction_tokens, audio_tokens, reasoning_tokens, rejected_prediction_tokens }

Breakdown of tokens used in a completion.

accepted_prediction_tokens?: number

audio_tokens?: number

reasoning_tokens?: number

rejected_prediction_tokens?: number

prompt_tokens_details?: PromptTokensDetails { audio_tokens, cached_tokens }

Breakdown of tokens used in the prompt.

audio_tokens?: number

cached_tokens?: number

Generate legacy text completion from prompt

import SGPClient from 'scale-gp';

const client = new SGPClient({
  accountID: 'My Account ID',
  apiKey: process.env['SGP_API_KEY'], // This is the default and can be omitted
});

const completion = await client.completions.create({ model: 'model', prompt: 'string' });

console.log(completion.id);

{
  "id": "id",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "text": "text",
      "logprobs": {
        "text_offset": [
          0
        ],
        "token_logprobs": [
          0
        ],
        "tokens": [
          "string"
        ],
        "top_logprobs": [
          {
            "foo": 0
          }
        ]
      }
    }
  ],
  "created": 0,
  "model": "model",
  "object": "text_completion",
  "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
    }
  }
}

Returns Examples

{
  "id": "id",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "text": "text",
      "logprobs": {
        "text_offset": [
          0
        ],
        "token_logprobs": [
          0
        ],
        "tokens": [
          "string"
        ],
        "top_logprobs": [
          {
            "foo": 0
          }
        ]
      }
    }
  ],
  "created": 0,
  "model": "model",
  "object": "text_completion",
  "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
    }
  }
}