CreateCompletionResponse
objectRepresents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint).
A unique identifier for the completion.
The list of completion choices the model generated for the input prompt.
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The Unix timestamp (in seconds) of when the completion was created.
The model used for completion.
This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.
The object type, which is always “text_completion”
Allowed values:text_completion
Usage statistics for the completion request.
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CreateEmbeddingRequest
objectOne OfInput text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for text-embedding-ada-002), cannot be an empty string, and any array must be 2048 dimensions or less. Example Python code for counting tokens. Some models may also impose a limit on total number of tokens summed across inputs.
Example:The quick brown fox jumped over the lazy dog
The string that will be turned into an embedding.
Default:
Example:This is a test.
Any OfID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
Example:text-embedding-3-small
The format to return the embeddings in. Can be either float or base64.
Allowed values:floatbase64
Default:float
Example:float
The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.
>= 1
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
Example:user-1234
CreateEmbeddingResponse
objectRepresents an embedding vector returned by embedding endpoint.
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The name of the model used to generate the embedding.
The object type, which is always “list”.
Allowed values:list
The usage information for the request.
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CreateFileRequest
objectThe File object (not file name) to be uploaded.
The intended purpose of the uploaded file.
Use “assistants” for Assistants and Message files, “vision” for Assistants image file inputs, “batch” for Batch API, and “fine-tune” for Fine-tuning.
Allowed values:assistantsbatchfine-tunevision
CreateFineTuningJobRequest
objectAny OfThe name of the model to fine-tune. You can select one of the
supported models.
Example:gpt-4o-mini
The ID of an uploaded file that contains training data.
See upload file for how to upload a file.
Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose fine-tune.
The contents of the file should differ depending on if the model uses the chat, completions format, or if the fine-tuning method uses the preference format.
See the fine-tuning guide for more details.
Example:file-abc123
The hyperparameters used for the fine-tuning job.
This value is now deprecated in favor of method, and should be passed in under the method parameter.
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A string of up to 64 characters that will be added to your fine-tuned model name.
For example, a suffix of “custom-model-name” would produce a model name like ft:gpt-4o-mini:openai:custom-model-name:7p4lURel.
Default:null
>= 1 characters<= 64 characters
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.
The same data should not be present in both train and validation files.
Your dataset must be formatted as a JSONL file. You must upload your file with the purpose fine-tune.
See the fine-tuning guide for more details.
Example:file-abc123
A list of integrations to enable for your fine-tuning job.
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The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases.
If a seed is not specified, one will be generated for you.
>= 0<= 2147483647
Example:42
The method used for fine-tuning.