# CreateCompletionRequest

## Properties

Name | Type | Description | Notes
------------ | ------------- | ------------- | -------------
**model** | **String** | 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** | Option<[**crate::models::CreateCompletionRequestPrompt**](CreateCompletionRequest_prompt.md)> |  | [optional]
**suffix** | Option<**String**> | The suffix that comes after a completion of inserted text. | [optional]
**max_tokens** | Option<**i32**> | 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).  | [optional][default to 16]
**temperature** | Option<**f32**> | 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.  | [optional][default to 1]
**top_p** | Option<**f32**> | 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.  | [optional][default to 1]
**n** | Option<**i32**> | 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`.  | [optional][default to 1]
**stream** | Option<**bool**> | 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.  | [optional][default to false]
**logprobs** | Option<**i32**> | 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.  | [optional]
**echo** | Option<**bool**> | Echo back the prompt in addition to the completion  | [optional][default to false]
**stop** | Option<[**crate::models::CreateCompletionRequestStop**](CreateCompletionRequest_stop.md)> |  | [optional]
**presence_penalty** | Option<**f32**> | 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)  | [optional][default to 0]
**frequency_penalty** | Option<**f32**> | 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)  | [optional][default to 0]
**best_of** | Option<**i32**> | 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`.  | [optional][default to 1]
**logit_bias** | Option<[**serde_json::Value**](.md)> | 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.  | [optional]
**user** | Option<**String**> | 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).  | [optional]

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