OpenAIServiceWrapper

The ID of the fine-tune job to cancel

fine tune info or None if not found

The audio file to transcribe, in one of these formats: mp3, mp4, mpeg, mpga, m4a, wav, or webm.

An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.

transcription text

The audio file to translate, in one of these formats: mp3, mp4, mpeg, mpga, m4a, wav, or webm.

An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.

translation text

The messages to generate chat completions.

chat completion response

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.

text completion response

The input text to use as a starting point for the edit.

The instruction that tells the model how to edit the prompt.

text edit response

Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs in a single request, pass an array of strings or array of token arrays. Each input must not exceed 8192 tokens in length.

list of embeddings inside an envelope

The ID of an uploaded file that contains training data. See uploadFile for how to upload a file. Your dataset must be formatted as a JSONL file, where each training example is a JSON object with the keys "prompt" and "completion". Additionally, you must upload your file with the purpose fine-tune.

The ID of an uploaded file that contains validation data. If you provide this file, the data is used to generate validation metrics periodically during fine-tuning. These metrics can be viewed in the fine-tuning results file. Your train and validation data should be mutually exclusive. Your dataset must be formatted as a JSONL file, where each validation example is a JSON object with the keys "prompt" and "completion". Additionally, you must upload your file with the purpose fine-tune.

fine tune response

A text description of the desired image(s). The maximum length is 1000 characters.

image response (might contain multiple data items - one per image)

The image to edit. Must be a valid PNG file, less than 4MB, and square. If mask is not provided, image must have transparency, which will be used as the mask.

An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where image should be edited. Must be a valid PNG file, less than 4MB, and have the same dimensions as image.

A text description of the desired image(s). The maximum length is 1000 characters.

image response (might contain multiple data items - one per image)

The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square.

image response (might contain multiple data items - one per image)

The input text to classify

moderation results

The ID of the file to use for this request

enum indicating whether the file was deleted

The ID of the file to use for this request

enum indicating whether the model was deleted

file infos

The ID of the fine-tune job to get events for.

fine tune events or None if not found

fine tunes

models

The ID of the file to use for this request

file info or None if not found

The ID of the file to use for this request

file content or None if not found

The ID of the fine-tune job

fine tune info

The ID of the model to use for this request

model or None if not found

(Explicit) display file name; if not specified a full path is used instead.

Name of the JSON Lines file to be uploaded. If the purpose is set to "fine-tune", each line is a JSON record with "prompt" and "completion" fields representing your training examples.

file info