completions_request {oaii}

API completions: create request

Description

To get more details, visit https://platform.openai.com/docs/api-reference/completions/create

Usage

completions_request(
  model,
  prompt,
  suffix = NULL,
  max_tokens = NULL,
  temperature = NULL,
  top_p = NULL,
  n = NULL,
  stream = NULL,
  logprobs = NULL,
  echo = NULL,
  stop = NULL,
  presence_penalty = NULL,
  frequency_penalty = NULL,
  best_of = NULL,
  user = NULL,
  api_key = api_get_key()
)

Arguments

model

string, ID of the model to use. You can use the list models (https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our model overview (https://platform.openai.com/docs/models/overview) for descriptions of them.

prompt

API endpoint parameter

suffix

string/NULL, the suffix that comes after a completion of inserted text.

max_tokens

integer, the maximum number of tokens (https://platform.openai.com/tokenizer) to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length.

temperature

double, 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.

top_p

double, 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.

n

integer, 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

flag, 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.

logprobs

integer, Include the log probabilities on the logprobs most likely 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.

echo

logical, echo back the prompt in addition to the completion

stop

string or array, up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

presence_penalty

double, 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

double, 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.

best_of

integer, Generates best_of completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed. When used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n.

user

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

api_key

string, OpenAI API key (see https://platform.openai.com/account/api-keys)

Value

content of the httr response object or SimpleError (conditions) enhanced with two additional fields: 'status_code' (response$status_code) and 'message_long' (built on response content)

Examples

## Not run: 
  prompt <- "x=1, y=2, z=x*y, z=?"
  res_content <- completions_request(
    model = "text-davinci-003",
    prompt = prompt
  )
  if (!is_error(res_content)) {
    answer <- completions_fetch_text(res_content)
    print(answer)
  }

## End(Not run)