To get more details, visit https://platform.openai.com/docs/api-reference/completions/create
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()
)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)
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.
API endpoint parameter
string/NULL, the suffix that comes after a completion of inserted text.
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.
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.
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.
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`.
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.
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.
logical, echo back the prompt in addition to the completion
string or array, up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
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.
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.
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.
string, A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse
string, OpenAI API key (see https://platform.openai.com/account/api-keys)
if (FALSE) {
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)
}
}
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