Chat Completions API

POST

https://api.gptnb.me/v1/completions

Given a prompt, the model will return one or more predicted completions along with the probabilities of alternative tokens at each position. Most developer should use our Chat Completions API to leverage our best and newest models.

Request

Header Params

Authorization

string

optional

Example:

Bearer {{YOUR_API_KEY}}

Body Params application/json

model

string

required

ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.

prompt

string

optional

The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays. Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.

max_tokens

integer

optional

The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. Example Python code for counting tokens.

temperature

integer

optional

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.

top_p

integer

optional

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.

integer

optional

How many completions to generate for each prompt. Note: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop.

stream

boolean

optional

Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Example Python code.

logprobs

null

optional

Include the log probabilities on the logprobs most likely output tokens, as well the chosen tokens. For example, if logprobs is 5, the API will return a list of the 5 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response. The maximum value for logprobs is 5.

stop

string

optional

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

Example

{
  "model": "gpt-3.5-turbo-instruct",
  "prompt": "Say this is a test",
  "max_tokens": 7,
  "temperature": 0,
  "top_p": 1,
  "n": 1,
  "stream": false,
  "logprobs": null,
  "stop": "\n"
}

Request samples

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location --request POST 'https://api.gptnb.me/v1/completions' \
--header 'Authorization: Bearer ' \
--header 'Content-Type: application/json' \
--data-raw '{
  "model": "gpt-3.5-turbo-instruct",
  "prompt": "Say this is a test",
  "max_tokens": 7,
  "temperature": 0,
  "top_p": 1,
  "n": 1,
  "stream": false,
  "logprobs": null,
  "stop": "\n"
}'

Responses

🟢200Ok

application/json

Body

string

required

object

string

required

created

integer

required

model

string

required

choices

array [object {4}]

required

text

string

optional

index

integer

optional

logprobs

null

optional

finish_reason

string

optional

usage

object

required

prompt_tokens

integer

required

completion_tokens

integer

required

total_tokens

integer

required

Example

{
    "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
    "object": "text_completion",
    "created": 1589478378,
    "model": "text-davinci-003",
    "choices": [
        {
            "text": "\n\nThis is indeed a test",
            "index": 0,
            "logprobs": null,
            "finish_reason": "length"
        }
    ],
    "usage": {
        "prompt_tokens": 5,
        "completion_tokens": 7,
        "total_tokens": 12
    }
}

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