> ## Documentation Index > Fetch the complete documentation index at: https://openai-hd4n6.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Create completion > Creates a completion for the provided prompt and parameters. ## OpenAPI ````yaml api-definition.yaml post /completions openapi: 3.0.0 info: title: OpenAI API description: >- The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details. version: 2.3.0 termsOfService: https://openai.com/policies/terms-of-use contact: name: OpenAI Support url: https://help.openai.com/ license: name: MIT url: https://github.com/openai/openai-openapi/blob/master/LICENSE servers: - url: https://api.openai.com/v1 security: - ApiKeyAuth: [] tags: - name: Assistants description: Build Assistants that can call models and use tools. - name: Audio description: Turn audio into text or text into audio. - name: Chat description: >- Given a list of messages comprising a conversation, the model will return a response. - name: Completions description: >- Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position. - name: Embeddings description: >- Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. - name: Evals description: Manage and run evals in the OpenAI platform. - name: Fine-tuning description: Manage fine-tuning jobs to tailor a model to your specific training data. - name: Batch description: Create large batches of API requests to run asynchronously. - name: Files description: >- Files are used to upload documents that can be used with features like Assistants and Fine-tuning. - name: Uploads description: Use Uploads to upload large files in multiple parts. - name: Images description: Given a prompt and/or an input image, the model will generate a new image. - name: Models description: List and describe the various models available in the API. - name: Moderations description: >- Given text and/or image inputs, classifies if those inputs are potentially harmful. - name: Audit Logs description: List user actions and configuration changes within this organization. paths: /completions: post: tags: - Completions summary: Create completion description: Creates a completion for the provided prompt and parameters. operationId: createCompletion requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CreateCompletionRequest' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/CreateCompletionResponse' components: schemas: 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: $ref: '#/components/schemas/StopConfiguration' 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 CreateCompletionResponse: type: object description: > Represents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint). properties: id: type: string description: A unique identifier for the completion. choices: type: array description: >- The list of completion choices the model generated for the input prompt. items: type: object required: - finish_reason - index - logprobs - text properties: finish_reason: type: string description: > The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, `length` if the maximum number of tokens specified in the request was reached, or `content_filter` if content was omitted due to a flag from our content filters. enum: - stop - length - content_filter index: type: integer logprobs: type: object nullable: true properties: text_offset: type: array items: type: integer token_logprobs: type: array items: type: number tokens: type: array items: type: string top_logprobs: type: array items: type: object additionalProperties: type: number text: type: string created: type: integer description: The Unix timestamp (in seconds) of when the completion was created. model: type: string description: The model used for completion. system_fingerprint: type: string description: > This fingerprint represents the backend configuration that the model runs with. Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism. object: type: string description: The object type, which is always "text_completion" enum: - text_completion x-stainless-const: true usage: $ref: '#/components/schemas/CompletionUsage' required: - id - object - created - model - choices x-oaiMeta: name: The completion object legacy: true example: | { "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7", "object": "text_completion", "created": 1589478378, "model": "gpt-4-turbo", "choices": [ { "text": "\n\nThis is indeed a test", "index": 0, "logprobs": null, "finish_reason": "length" } ], "usage": { "prompt_tokens": 5, "completion_tokens": 7, "total_tokens": 12 } } StopConfiguration: 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"]' 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. **NOTE:** If the stream is interrupted, you may not receive the final usage chunk which contains the total token usage for the request. CompletionUsage: type: object description: Usage statistics for the completion request. properties: completion_tokens: type: integer default: 0 description: Number of tokens in the generated completion. prompt_tokens: type: integer default: 0 description: Number of tokens in the prompt. total_tokens: type: integer default: 0 description: Total number of tokens used in the request (prompt + completion). completion_tokens_details: type: object description: Breakdown of tokens used in a completion. properties: accepted_prediction_tokens: type: integer default: 0 description: | When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion. audio_tokens: type: integer default: 0 description: Audio input tokens generated by the model. reasoning_tokens: type: integer default: 0 description: Tokens generated by the model for reasoning. rejected_prediction_tokens: type: integer default: 0 description: > When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits. prompt_tokens_details: type: object description: Breakdown of tokens used in the prompt. properties: audio_tokens: type: integer default: 0 description: Audio input tokens present in the prompt. cached_tokens: type: integer default: 0 description: Cached tokens present in the prompt. required: - prompt_tokens - completion_tokens - total_tokens securitySchemes: ApiKeyAuth: type: http scheme: bearer ````