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Answers

Name: model
Type: string; Required
Description: ID of the model to use for completion. You can select one of `ada`, `babbage`, `curie`, or `davinci`.

Name: examples
Type: array[object]; Required
Description: List of (question, answer) pairs that will help steer the model towards the tone and answer format you'd like. We recommend adding 2 to 3 examples.

Name: examples_context
Type: string; Required
Description: A text snippet containing the contextual information used to generate the answers for the `examples` you provide.

Name: documents
Type: array[string]
Description: List of documents from which the answer for the input `question` should be derived. If this is an empty list, the question will be answered based on the question-answer examples. You should specify either `documents` or a `file`, but not both.

Name: file
Type: string
Description: The ID of an uploaded file that contains documents to search over. See [upload file](/docs/api-reference/files/upload) for how to upload a file of the desired format and purpose. You should specify either `documents` or a `file`, but not both.

Name: search_model
Type: string
Description: ID of the model to use for [Search](/docs/api-reference/searches/create). You can select one of `ada`, `babbage`, `curie`, or `davinci`.

Name: max_rerank
Type: integer
Description: The maximum number of documents to be ranked by [Search](/docs/api-reference/searches/create) when using `file`. Setting it to a higher value leads to improved accuracy but with increased latency and cost.

Name: temperature
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.

Name: logprobs
Type: integer
Description: 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. When `logprobs` is set, `completion` will be automatically added into `expand` to get the logprobs.

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

Name: logit_bias
Type: object
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) (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.

Name: return_metadata
Type: boolean
Description: A special boolean flag for showing metadata. If set to `true`, each document entry in the returned JSON will contain a "metadata" field. This flag only takes effect when `file` is set.

Name: return_prompt
Type: boolean
Description: If set to `true`, the returned JSON will include a "prompt" field containing the final prompt that was used to request a completion. This is mainly useful for debugging purposes.

Name: expand
Type: array[object]
Description: If an object name is in the list, we provide the full information of the object; otherwise, we only provide the object ID. Currently we support `completion` and `file` objects for expansion.

Name: 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).