--- title: "CreateCompletionRequest" url: "https://kongair.terwilligar.com/apis/openai-api-2-3-0/versions/ea92d048-c746-4ead-a6a8-da28d93137d1/schemas/CreateCompletionRequest" --- > Full API specification: https://kongair.terwilligar.com/apis/openai-api-2-3-0/versions/ea92d048-c746-4ead-a6a8-da28d93137d1.md # CreateCompletionRequest ## OpenAPI definition ```yaml openapi: 3.0.0 info: title: OpenAI API version: 2.3.0 servers: - url: https://api.openai.com/v1 components: schemas: ChatCompletionStreamOptions: description: > Options for streaming response. Only set this when you set `stream: true`. type: object nullable: true default: null properties: include_usage: type: boolean description: > If set, an additional chunk will be streamed before the `data: [DONE]` message. The `usage` field on this chunk shows the token usage statistics for the entire request, and the `choices` field will always be an empty array. All other chunks will also include a `usage` field, but with a null value. CreateCompletionRequest: type: object properties: model: description: > 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) for descriptions of them. anyOf: - type: string - type: string enum: - gpt-3.5-turbo-instruct - davinci-002 - babbage-002 x-oaiTypeLabel: string prompt: description: > 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. default: <|endoftext|> nullable: true oneOf: - type: string default: "" example: This is a test. - type: array items: type: string default: "" example: This is a test. - type: array minItems: 1 items: type: integer example: "[1212, 318, 257, 1332, 13]" - type: array minItems: 1 items: type: array minItems: 1 items: type: integer example: "[[1212, 318, 257, 1332, 13]]" best_of: type: integer default: 1 minimum: 0 maximum: 20 nullable: true description: > 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`. echo: type: boolean default: false nullable: true description: | Echo back the prompt in addition to the completion frequency_penalty: type: number default: 0 minimum: -2 maximum: 2 nullable: true description: > 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/guides/text-generation) logit_bias: type: object x-oaiTypeLabel: map default: null nullable: true additionalProperties: type: integer description: > 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) 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. logprobs: type: integer minimum: 0 maximum: 5 default: null nullable: true description: > Include the log probabilities on the `logprobs` most likely output 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. max_tokens: type: integer minimum: 0 default: 16 example: 16 nullable: true description: | The maximum number of [tokens](/tokenizer) that can be generated in the completion. The token count of your prompt plus `max_tokens` cannot exceed the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. n: type: integer minimum: 1 maximum: 128 default: 1 example: 1 nullable: true description: > 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`. presence_penalty: type: number default: 0 minimum: -2 maximum: 2 nullable: true description: > 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/guides/text-generation) seed: type: integer format: int64 nullable: true description: > 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. stop: description: > Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. default: null nullable: true oneOf: - type: string default: <|endoftext|> example: |+ nullable: true - type: array minItems: 1 maxItems: 4 items: type: string example: '["\n"]' stream: description: | 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. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions). type: boolean nullable: true default: false stream_options: $ref: "#/components/schemas/ChatCompletionStreamOptions" suffix: description: | The suffix that comes after a completion of inserted text. This parameter is only supported for `gpt-3.5-turbo-instruct`. default: null nullable: true type: string example: test. temperature: type: number minimum: 0 maximum: 2 default: 1 example: 1 nullable: true description: > 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. top_p: type: number minimum: 0 maximum: 1 default: 1 example: 1 nullable: true description: > 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. user: type: string example: user-1234 description: > 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). required: - model - prompt ```