Create Completion

Options

Body

Request body which must comply to the following JSON Schema:

{
  "required" : [ "model", "prompt" ],
  "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/overview) for descriptions of them.\n",
      "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.\n\nNote 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.\n",
      "nullable" : true,
      "oneOf" : [ {
        "type" : "string",
        "example" : "This is a test.",
        "default" : ""
      }, {
        "type" : "array",
        "items" : {
          "type" : "string",
          "example" : "This is a test.",
          "default" : ""
        }
      }, {
        "minItems" : 1,
        "type" : "array",
        "example" : "[1212, 318, 257, 1332, 13]",
        "items" : {
          "type" : "integer"
        }
      }, {
        "minItems" : 1,
        "type" : "array",
        "example" : "[[1212, 318, 257, 1332, 13]]",
        "items" : {
          "minItems" : 1,
          "type" : "array",
          "items" : {
            "type" : "integer"
          }
        }
      } ],
      "default" : "<|endoftext|>"
    },
    "best_of" : {
      "maximum" : 20,
      "minimum" : 0,
      "type" : "integer",
      "description" : "Generates `best_of` completions server-side and returns the \"best\" (the one with the highest log probability per token). Results cannot be streamed.\n\nWhen 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`.\n\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`.\n",
      "nullable" : true,
      "default" : 1
    },
    "echo" : {
      "type" : "boolean",
      "description" : "Echo back the prompt in addition to the completion\n",
      "nullable" : true,
      "default" : false
    },
    "frequency_penalty" : {
      "maximum" : 2,
      "minimum" : -2,
      "type" : "number",
      "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.\n\n[See more information about frequency and presence penalties.](/docs/guides/text-generation/parameter-details)\n",
      "nullable" : true,
      "default" : 0
    },
    "logit_bias" : {
      "type" : "object",
      "additionalProperties" : {
        "type" : "integer"
      },
      "description" : "Modify the likelihood of specified tokens appearing in the completion.\n\nAccepts 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.\n\nAs an example, you can pass `{\"50256\": -100}` to prevent the <|endoftext|> token from being generated.\n",
      "nullable" : true,
      "x-oaiTypeLabel" : "map"
    },
    "logprobs" : {
      "maximum" : 5,
      "minimum" : 0,
      "type" : "integer",
      "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.\n\nThe maximum value for `logprobs` is 5.\n",
      "nullable" : true
    },
    "max_tokens" : {
      "minimum" : 0,
      "type" : "integer",
      "description" : "The maximum number of [tokens](/tokenizer) that can be generated in the completion.\n\nThe 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",
      "nullable" : true,
      "example" : 16,
      "default" : 16
    },
    "n" : {
      "maximum" : 128,
      "minimum" : 1,
      "type" : "integer",
      "description" : "How many completions to generate for each prompt.\n\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`.\n",
      "nullable" : true,
      "example" : 1,
      "default" : 1
    },
    "presence_penalty" : {
      "maximum" : 2,
      "minimum" : -2,
      "type" : "number",
      "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.\n\n[See more information about frequency and presence penalties.](/docs/guides/text-generation/parameter-details)\n",
      "nullable" : true,
      "default" : 0
    },
    "seed" : {
      "maximum" : 9223372036854775807,
      "minimum" : -9223372036854775808,
      "type" : "integer",
      "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.\n\nDeterminism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.\n",
      "nullable" : true
    },
    "stop" : {
      "description" : "Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.\n",
      "nullable" : true,
      "oneOf" : [ {
        "type" : "string",
        "nullable" : true,
        "example" : "\n",
        "default" : "<|endoftext|>"
      }, {
        "maxItems" : 4,
        "minItems" : 1,
        "type" : "array",
        "items" : {
          "type" : "string",
          "example" : "[\"\\n\"]"
        }
      } ]
    },
    "stream" : {
      "type" : "boolean",
      "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).\n",
      "nullable" : true,
      "default" : false
    },
    "stream_options" : {
      "type" : "object",
      "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.\n"
        }
      },
      "description" : "Options for streaming response. Only set this when you set `stream: true`.\n",
      "nullable" : true
    },
    "suffix" : {
      "type" : "string",
      "description" : "The suffix that comes after a completion of inserted text.\n\nThis parameter is only supported for `gpt-3.5-turbo-instruct`.\n",
      "nullable" : true,
      "example" : "test."
    },
    "temperature" : {
      "maximum" : 2,
      "minimum" : 0,
      "type" : "number",
      "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.\n\nWe generally recommend altering this or `top_p` but not both.\n",
      "nullable" : true,
      "example" : 1,
      "default" : 1
    },
    "top_p" : {
      "maximum" : 1,
      "minimum" : 0,
      "type" : "number",
      "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.\n\nWe generally recommend altering this or `temperature` but not both.\n",
      "nullable" : true,
      "example" : 1,
      "default" : 1
    },
    "user" : {
      "type" : "string",
      "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).\n",
      "example" : "user-1234"
    }
  }
}

Result Format

Specify how the response should be mapped to the table output. The following formats are available:

Raw Response: Returns the raw response in a single row with the following columns:

• body: Response body
• status: HTTP status code

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