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6.  def createCompletion(model: String, prompt: Optional[Prompt] = Optional.Absent, suffix: Optional[String] = Optional.Absent, maxTokens: Optional[MaxTokens] = Optional.Absent, temperature: Optional[Temperature] = Optional.Absent, topP: Optional[TopP] = Optional.Absent, n: Optional[N] = Optional.Absent, stream: Optional[Boolean] = Optional.Absent, logprobs: Optional[Logprobs] = Optional.Absent, echo: Optional[Boolean] = Optional.Absent, stop: Optional[Stop] = Optional.Absent, presencePenalty: Optional[PresencePenalty] = Optional.Absent, frequencyPenalty: Optional[FrequencyPenalty] = Optional.Absent, bestOf: Optional[BestOf] = Optional.Absent, logitBias: Optional[LogitBias] = Optional.Absent, user: Optional[String] = Optional.Absent): ZIO[Completions, OpenAIFailure, CreateCompletionResponse]

   Creates a completion for the provided prompt and parameters

   Creates a completion for the provided prompt and parameters

   model

   ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.

   prompt

   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.

   suffix

   The suffix that comes after a completion of inserted text.

   maxTokens

   The maximum number of [tokens](/tokenizer) to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096).

   temperature

   What [sampling temperature](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277) to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. We generally recommend altering this or top_p but not both.

   topP

   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.

   n

   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

   Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a data: [DONE] message.

   logprobs

   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. The maximum value for logprobs is 5. If you need more than this, please contact us through our [Help center](https://help.openai.com) and describe your use case.

   echo

   Echo back the prompt in addition to the completion

   stop

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

   presencePenalty

   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. [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)

   frequencyPenalty

   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. [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)

   bestOf

   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. **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.

   logitBias

   Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) (which works for both GPT-2 and GPT-3) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. As an example, you can pass {"50256": -100} to prevent the <|endoftext|> token from being generated.

   user

   A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).

7.  def createCompletion(body: CreateCompletionRequest): ZIO[Completions, OpenAIFailure, CreateCompletionResponse]

   Creates a completion for the provided prompt and parameters

8.  def default: ZLayer[Any, Throwable, Completions]
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