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CreateAnswerRequest

Hierarchy

  • CreateAnswerRequest

Properties

documents?: null | string[]

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.

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CreateAnswerRequest

examples: any[]

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.

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CreateAnswerRequest

examples-context: string

A text snippet containing the contextual information used to generate the answers for the examples you provide.

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CreateAnswerRequest

expand?: null | any[]

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.

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CreateAnswerRequest

file?: null | string

The ID of an uploaded file that contains documents to search over. See upload file for how to upload a file of the desired format and purpose. You should specify either documents or a file, but not both.

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CreateAnswerRequest

logit-bias?: null | object

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 (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.

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CreateAnswerRequest

logprobs?: null | number

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. When logprobs is set, completion will be automatically added into expand to get the logprobs.

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CreateAnswerRequest

max-rerank?: null | number

The maximum number of documents to be ranked by Search when using file. Setting it to a higher value leads to improved accuracy but with increased latency and cost.

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CreateAnswerRequest

max-tokens?: null | number

The maximum number of tokens allowed for the generated answer

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CreateAnswerRequest

model: string

ID of the model to use for completion. You can select one of ada, babbage, curie, or davinci.

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CreateAnswerRequest

n?: null | number

How many answers to generate for each question.

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CreateAnswerRequest

question: string

Question to get answered.

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CreateAnswerRequest

return-metadata?: null | boolean

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.

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CreateAnswerRequest

return-prompt?: null | boolean

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.

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CreateAnswerRequest

search-model?: null | string

ID of the model to use for Search. You can select one of ada, babbage, curie, or davinci.

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CreateAnswerRequest

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CreateAnswerRequest

temperature?: null | number

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.

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CreateAnswerRequest

user?: string

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.

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CreateAnswerRequest

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