openai | openpm

Classifications

Name: model
Type: string; Required
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.

Name: examples
Type: array[object]
Description: A list of examples with labels, in the following format: `[["The movie is so interesting.", "Positive"], ["It is quite boring.", "Negative"], ...]` All the label strings will be normalized to be capitalized. You should specify either `examples` or `file`, but not both.

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

Name: labels
Type: array[string]
Description: The set of categories being classified. If not specified, candidate labels will be automatically collected from the examples you provide. All the label strings will be normalized to be capitalized.

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: 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: max_examples
Type: integer
Description: The maximum number of examples 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: 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_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: 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: 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).