Chat completion API — chat_completion

oai_create_chat_completion(): Create a chat completion.`

oai_get_chat_completion(): Get a stored chat completion.

oai_get_chat_messages(): Get the messages in a stored chat completion.

oai_list_chat_completions(): List stored chat completions.

oai_update_chat_completion(): Update a stored chat completion.

oai_delete_chat_completion(): Delete a stored chat completion. Only chat completions that have been created with the store parameter set to true can be deleted.

Usage

oai_create_chat_completion(
  messages,
  model = getOption("openaiapi.model"),
  frequency_penalty = NULL,
  logit_bias = NULL,
  logprobs = NULL,
  top_logprobs = NULL,
  max_tokens = NULL,
  n = NULL,
  presence_penalty = NULL,
  response_format = NULL,
  seed = NULL,
  service_tier = NULL,
  stop = NULL,
  stream = NULL,
  stream_options = NULL,
  temperature = NULL,
  top_p = NULL,
  tools = NULL,
  tools_choice = NULL,
  parallel_tool_calls = NULL,
  user = NULL,
  web_search_options = NULL,
  .classify_response = TRUE,
  .async = FALSE
)

oai_get_chat_completion(
  completion_id,
  .classify_response = TRUE,
  .async = FALSE
)

oai_get_chat_messages(
  completion_id,
  after = NULL,
  limit = NULL,
  order = NULL,
  .async = FALSE
)

oai_list_chat_completions(
  model = NULL,
  metadata = NULL,
  after = NULL,
  limit = NULL,
  order = NULL
)

oai_update_chat_completion(
  completion_id,
  metadata,
  .classify_response = TRUE,
  .async = FALSE
)

oai_delete_chat_completion(completion_id, .async = FALSE)

Arguments

messages: A list of messages comprising the conversation so far. You can also pass a oai_message object or a character vector.
model: The model used to generate the chat completions.
frequency_penalty: Numeric. 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.
logit_bias: List. Modify the likelihood of specified tokens appearing in the completion.
logprobs: Logical. Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.
top_logprobs: Integer. An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.
max_tokens: Integer. The maximum number of tokens that can be generated in the chat completion.
n: Integer. How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.
presence_penalty: Numeric. 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.
response_format: List. An object specifying the format that the model must output. Compatible with GPT-4o, GPT-4o mini, GPT-4 Turbo and all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106.
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.
service_tier: Character. Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service.
stop: Character. Up to 4 sequences where the API will stop generating further tokens.
stream: Logical. If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data.
stream_options: List. Options for streaming response. Only set this when you set stream = TRUE.
temperature: Numeric. 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: Numeric. 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.
tools: List. 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.
tools_choice: Character. Controls which (if any) tool is called by the model. "none" means the model will not call any tool and instead generates a message. "auto" means the model can pick between generating a message or calling one or more tools. "required" means the model must call one or more tools. Specifying a particular tool via list(type = "function", function = list(name = "my_function")) forces the model to call that tool. "none" is the default when no tools are present. "auto" is the default if tools are present.
parallel_tool_calls: Logical. Whether to enable parallel function calling during tool use.
user: Character. A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
web_search_options: List. This tool searches the web for relevant results to use in a response.
.classify_response: Logical. If TRUE (default), the response is classified as an R6 object. If FALSE, the response is returned as a list.
.async: Logical. If TRUE, the request is performed asynchronously.
completion_id: The ID of the chat completion to delete.
after: Identifier for the last chat completion from the previous pagination request.
limit: Number of chat completions to retrieve.
order: Sort order for chat completions by timestamp. Use asc for ascending order or desc for descending order. Defaults to asc.
metadata: List. Optional. A named list of at most 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Value

A ChatCompletion R6 object.

oai_get_chat_messages() returns a list of messages in the chat completion.

oai_list_chat_completions() returns a list of ChatCompletion objects.

oai_delete_chat_completion() returns a deletion confirmation object.

Details

Only chat completions that have been created with the store parameter set to true will be returned.