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openai-openapi/openai-openapi.yaml

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---
openapi: 3.0.3
info:
title: OpenAI
description: "OpenAI API\n\nThis OpenAPI document was written based on the api documentation available [here](https://beta.openai.com/docs/api-reference/introduction).\n\nIt is currently maintained by [Showcase](https://getshowcase.io/).\n\nThe source code for this document can be found [here](https://github.com/showcasejobs/open-api).\n\n**NOTE** The naming can appear confusing, as they are _very_ similar. `OpenAI` (no `P`) is the \"GPT-3 as a service\" AI platform. `OpenAPI` (with a `P`) is a structured and machine-friendly way of defining RESTful API services.\n"
version: 1.0.0
contact: {}
servers:
- url: "https://api.openai.com/v1"
paths:
/answers:
post:
tags:
- Answers
summary: Create answer
description: "Answers the specified question using the provided documents and examples.\n\nThe endpoint first [searches](https://beta.openai.com/docs/api-reference/searches) over provided documents or files to find relevant context.\nThe relevant context is combined with the provided examples and question to create the prompt for [completion](https://beta.openai.com/docs/api-reference/completions).\n\n[See More](https://beta.openai.com/docs/api-reference/classifications/create)\n"
operationId: createAnswer
requestBody:
content:
application/json:
schema:
type: object
properties:
documents:
type: array
items:
type: string
example: Puppy A is happy.
example:
- Puppy A is happy.
- Puppy B is sad.
examples:
type: array
items:
type: array
items:
type: string
example: What is human life expectancy in the United States?
example:
- What is human life expectancy in the United States?
- 78 years.
example:
- - What is human life expectancy in the United States?
- 78 years.
examples_context:
type: string
example: "In 2017, U.S. life expectancy was 78.6 years."
max_tokens:
type: number
example: 5
model:
type: string
example: curie
question:
type: string
example: which puppy is happy?
search_model:
type: string
example: ada
stop:
type: array
items:
type: string
example: "\n"
example:
- "\n"
- "<|endoftext|>"
example:
documents:
- Puppy A is happy.
- Puppy B is sad.
examples:
- - What is human life expectancy in the United States?
- 78 years.
examples_context: "In 2017, U.S. life expectancy was 78.6 years."
max_tokens: 5
model: curie
question: which puppy is happy?
search_model: ada
stop:
- "\n"
- "<|endoftext|>"
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
answers:
type: array
items:
type: string
example: puppy A.
example:
- puppy A.
completion:
type: string
example: cmpl-2euVa1kmKUuLpSX600M41125Mo9NI
model:
type: string
example: "curie:2020-05-03"
object:
type: string
example: answer
search_model:
type: string
example: ada
selected_documents:
type: array
items:
type: object
properties:
document:
type: number
example: 0
text:
type: string
example: "Puppy A is happy. "
example:
- document: 0
text: "Puppy A is happy. "
- document: 1
text: "Puppy B is sad. "
examples:
Ok:
value:
answers:
- puppy A.
completion: cmpl-2euVa1kmKUuLpSX600M41125Mo9NI
model: "curie:2020-05-03"
object: answer
search_model: ada
selected_documents:
- document: 0
text: "Puppy A is happy. "
- document: 1
text: "Puppy B is sad. "
/classifications:
post:
tags:
- Classifications
summary: Create classification
description: "Classifies the specified query using provided examples.\n\nThe endpoint first [searches](https://beta.openai.com/docs/api-reference/searches) over the labeled examples to select the ones most relevant for the particular query.\nThen, the relevant examples are combined with the query to construct a prompt to produce the final label via the [completions](https://beta.openai.com/docs/api-reference/completions) endpoint.\n\nLabeled examples can be provided via an uploaded file, or explicitly listed in the request using the examples parameter for quick tests and small scale use cases.\n\n[See More](https://beta.openai.com/docs/api-reference/classifications/create)\n"
operationId: createClassification
requestBody:
content:
application/json:
schema:
type: object
properties:
examples:
type: array
items:
type: array
items:
type: string
example: A happy moment
example:
- A happy moment
- Positive
example:
- - A happy moment
- Positive
- - I am sad.
- Negative
- - I am feeling awesome
- Positive
labels:
type: array
items:
type: string
example: Positive
example:
- Positive
- Negative
- Neutral
model:
type: string
example: curie
query:
type: string
example: "It is a raining day :("
search_model:
type: string
example: ada
example:
examples:
- - A happy moment
- Positive
- - I am sad.
- Negative
- - I am feeling awesome
- Positive
labels:
- Positive
- Negative
- Neutral
model: curie
query: "It is a raining day :("
search_model: ada
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
completion:
type: string
example: cmpl-2euN7lUVZ0d4RKbQqRV79IiiE6M1f
label:
type: string
example: Negative
model:
type: string
example: "curie:2020-05-03"
object:
type: string
example: classification
search_model:
type: string
example: ada
selected_examples:
type: array
items:
type: object
properties:
document:
type: number
example: 1
label:
type: string
example: Negative
text:
type: string
example: I am sad.
example:
- document: 1
label: Negative
text: I am sad.
- document: 0
label: Positive
text: A happy moment
- document: 2
label: Positive
text: I am feeling awesome
examples:
Ok:
value:
completion: cmpl-2euN7lUVZ0d4RKbQqRV79IiiE6M1f
label: Negative
model: "curie:2020-05-03"
object: classification
search_model: ada
selected_examples:
- document: 1
label: Negative
text: I am sad.
- document: 0
label: Positive
text: A happy moment
- document: 2
label: Positive
text: I am feeling awesome
/engines:
get:
tags:
- Engines
summary: List engines
description: "Lists the currently available engines, and provides basic information about each one such as the owner and availability.\n\n[See More](https://beta.openai.com/docs/api-reference/engines/list)\n"
operationId: listEngines
responses:
"200":
description: Ok
content:
application/json:
schema:
type: array
items:
type: object
properties:
created:
type: number
example: 1624492800
id:
type: string
example: davinci
max_replicas:
type: number
example: 66225769
object:
type: string
example: engine
owner:
type: string
example: openai
ready:
type: boolean
example: true
ready_replicas:
type: boolean
example: true
example:
- created: 1624492800
id: davinci
max_replicas: 66225769
object: engine
owner: openai
ready: true
ready_replicas: true
- created: 1624492800
id: davinci
max_replicas: -92918205
object: engine
owner: openai
ready: false
ready_replicas: true
examples:
Ok:
value:
- created: 1624492800
id: davinci
max_replicas: 66225769
object: engine
owner: openai
ready: true
ready_replicas: true
- created: 1624492800
id: davinci
max_replicas: -92918205
object: engine
owner: openai
ready: false
ready_replicas: true
"/engines/{engineId}":
get:
tags:
- Engines
summary: Retrieve engine
description: "Retrieves an engine instance, providing basic information about the engine such as the owner and availability.\n\n[See More](https://beta.openai.com/docs/api-reference/engines/retrieve)\n"
operationId: retrieveEngine
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
created:
type: number
example: 1624492800
id:
type: string
example: davinci
max_replicas:
type: number
example: 75121544
object:
type: string
example: engine
owner:
type: string
example: openai
ready:
type: boolean
example: false
ready_replicas:
type: boolean
example: false
examples:
Ok:
value:
created: 1624492800
id: davinci
max_replicas: 75121544
object: engine
owner: openai
ready: false
ready_replicas: false
parameters:
- name: engineId
in: path
required: true
schema:
type: string
example: davinci
description: "(Required) The ID of the engine to use for this request.\n"
"/engines/{engineId}/completions":
post:
tags:
- Completions
summary: Create completion
description: "**Important**: This experimental endpoint is intended for use in browsers. Please **do not** expose your secret key in your client code.\n\nStream generated text from the model via `GET` request. This method is provided because the browser-native EventSource method can only send `GET` requests. It supports a more limited set of configuration options than the `POST` variant.\n\nIf you'd like to stream results from the POST variant in your browser, consider using the [SSE library](https://github.com/mpetazzoni/sse.js)."
operationId: createCompletion
parameters:
- name: prompt
in: query
required: false
schema:
type: string
description: "(Optional) The prompt to complete from. If you would like to provide multiple prompts, use the POST variant of this method.\n\nNote 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."
- name: max_tokens
in: query
required: false
schema:
type: integer
description: (Optional) The maximum number of tokens to generate. Requests can use up to 2048 tokens shared between prompt and completion. (One token is roughly 4 characters for normal English text)
- name: temperature
in: query
required: false
schema:
type: number
description: "(Optional) What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.\n\nWe generally recommend altering this or top_p but not both."
- name: top_p
in: query
required: false
schema:
type: number
description: "(Optional) An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both."
- name: n
in: query
required: false
schema:
type: number
description: "(Optional) How many completions to generate for each prompt.\n\nNote: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop."
- name: logprobs
in: query
required: false
schema:
type: integer
description: "(Optional) Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 10, the API will return a list of the 10 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."
- name: stop
in: query
required: false
schema:
type: array
description: (Optional) Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
- name: echo
in: query
required: false
schema:
type: boolean
description: (Optional) Echo back the prompt in addition to the completion
- name: presence_penalty
in: query
required: false
schema:
type: number
description: "(Optional) Number between 0 and 1 that penalizes new tokens based on whether they appear in the text so far. Increases the model's likelihood to talk about new topics."
- name: frequency_penalty
in: query
required: false
schema:
type: number
description: "(Optional) Number between 0 and 1 that penalizes new tokens based on their existing frequency in the text so far. Decreases the model's likelihood to repeat the same line verbatim."
- name: best_of
in: query
required: false
schema:
type: integer
description: "(Optional) Generates best_of completions server-side and returns the \"best\" (the one with the lowest log probability per token). Results cannot be streamed.\n\nWhen used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n.\n\nNote: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop."
- name: logit_bias
in: query
required: false
schema:
type: object
description: "(Optional) Modify the likelihood of specified tokens appearing in the completion.\n\nAccepts 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.\n\nAs an example, you can pass {\"50256\": -100} to prevent the <|endoftext|> token from being generated."
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
choices:
type: array
items:
type: object
properties:
finish_reason:
type: string
example: length
index:
type: number
example: 0
logprobs:
nullable: true
example: ~
text:
type: string
example: " there was a girl who"
example:
- finish_reason: length
index: 0
logprobs: ~
text: " there was a girl who"
created:
type: number
example: 1589478378
id:
type: string
example: cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7
model:
type: string
example: "davinci:2020-05-03"
object:
type: string
example: text_completion
examples:
Ok:
value:
choices:
- finish_reason: length
index: 0
logprobs: ~
text: " there was a girl who"
created: 1589478378
id: cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7
model: "davinci:2020-05-03"
object: text_completion
parameters:
- name: engineId
in: path
required: true
schema:
type: string
example: davinci
description: "(Required) The ID of the engine to use for this request.\n"
"/engines/{engineId}/completions/browser_stream":
get:
tags:
- Completions
summary: Create completion via GET
description: "**Important**: This experimental endpoint is intended for use in browsers. Please **do not** expose your secret key in your client code.\n\nStream generated text from the model via `GET` request. This method is provided because the browser-native EventSource method can only send `GET` requests. It supports a more limited set of configuration options than the `POST` variant.\n\nIf you'd like to stream results from the POST variant in your browser, consider using the [SSE library](https://github.com/mpetazzoni/sse.js)."
operationId: createCompletionViaGet
parameters:
- name: prompt
in: query
required: false
schema:
type: string
description: "(Optional) The prompt to complete from. If you would like to provide multiple prompts, use the POST variant of this method.\n\nNote 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."
- name: max_tokens
in: query
required: false
schema:
type: integer
description: (Optional) The maximum number of tokens to generate. Requests can use up to 2048 tokens shared between prompt and completion. (One token is roughly 4 characters for normal English text)
- name: temperature
in: query
required: false
schema:
type: number
description: "(Optional) What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.\n\nWe generally recommend altering this or top_p but not both."
- name: top_p
in: query
required: false
schema:
type: number
description: "(Optional) An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\nWe generally recommend altering this or temperature but not both."
- name: n
in: query
required: false
schema:
type: number
description: "(Optional) How many completions to generate for each prompt.\n\nNote: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop."
- name: logprobs
in: query
required: false
schema:
type: integer
description: "(Optional) Include the log probabilities on the logprobs most likely tokens, as well the chosen tokens. For example, if logprobs is 10, the API will return a list of the 10 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."
- name: stop
in: query
required: false
schema:
type: array
description: (Optional) Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
- name: echo
in: query
required: false
schema:
type: boolean
description: (Optional) Echo back the prompt in addition to the completion
- name: presence_penalty
in: query
required: false
schema:
type: number
description: "(Optional) Number between 0 and 1 that penalizes new tokens based on whether they appear in the text so far. Increases the model's likelihood to talk about new topics."
- name: frequency_penalty
in: query
required: false
schema:
type: number
description: "(Optional) Number between 0 and 1 that penalizes new tokens based on their existing frequency in the text so far. Decreases the model's likelihood to repeat the same line verbatim."
- name: best_of
in: query
required: false
schema:
type: integer
description: "(Optional) Generates best_of completions server-side and returns the \"best\" (the one with the lowest log probability per token). Results cannot be streamed.\n\nWhen used with n, best_of controls the number of candidate completions and n specifies how many to return – best_of must be greater than n.\n\nNote: Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for max_tokens and stop."
- name: logit_bias
in: query
required: false
schema:
type: object
description: "(Optional) Modify the likelihood of specified tokens appearing in the completion.\n\nAccepts 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.\n\nAs an example, you can pass {\"50256\": -100} to prevent the <|endoftext|> token from being generated."
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
choices:
type: array
items:
type: object
properties:
finish_reason:
nullable: true
example: ~
index:
type: number
example: 0
logprobs:
nullable: true
example: ~
text:
type: string
example: ","
example:
- finish_reason: ~
index: 0
logprobs: ~
text: ","
created:
type: number
example: 1592103423
id:
type: string
example: cmpl-GxetY7rxbQDVuGoMhX19c8Qy
model:
type: string
example: "davinci:2020-05-03"
object:
type: string
example: text_completion
examples:
Ok:
value:
choices:
- finish_reason: ~
index: 0
logprobs: ~
text: ","
created: 1592103423
id: cmpl-GxetY7rxbQDVuGoMhX19c8Qy
model: "davinci:2020-05-03"
object: text_completion
parameters:
- name: engineId
in: path
required: true
schema:
type: string
example: davinci
description: "(Required) The ID of the engine to use for this request.\n"
"/engines/{engineId}/search":
post:
tags:
- Searches
summary: Create search
description: "The search endpoint computes similarity scores between provided query and documents.\nDocuments can be passed directly to the API if there are no more than 200 of them.\n\nTo go beyond the 200 document limit, documents can be processed offline and then used for efficient retrieval at query time.\nWhen `file` is set, the search endpoint searches over all the documents in the given file and returns up to the `max_rerank` number of documents.\nThese documents will be returned along with their search scores.\n\nThe similarity score is a positive score that usually ranges from 0 to 300 (but can sometimes go higher), where a score above 200 usually means the document is semantically similar to the query.\n\n[See More](https://beta.openai.com/docs/api-reference/searches/create)\n"
operationId: createSearch
requestBody:
content:
application/json:
schema:
type: object
properties:
documents:
type: array
items:
type: string
example: White House
example:
- White House
- hospital
- school
query:
type: string
example: the president
example:
documents:
- White House
- hospital
- school
query: the president
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
data:
type: array
items:
type: object
properties:
document:
type: number
example: 0
object:
type: string
example: search_result
score:
type: number
example: 215.412
example:
- document: 0
object: search_result
score: 215.412
- document: 1
object: search_result
score: 40.316
- document: 2
object: search_result
score: 55.226
object:
type: string
example: list
examples:
Ok:
value:
data:
- document: 0
object: search_result
score: 215.412
- document: 1
object: search_result
score: 40.316
- document: 2
object: search_result
score: 55.226
object: list
parameters:
- name: engineId
in: path
required: true
schema:
type: string
example: davinci
description: "(Required) The ID of the engine to use for this request.\n"
/files:
get:
tags:
- Files
summary: List files
description: "Returns a list of files that belong to the user's organization.\n\n[See More](https://beta.openai.com/docs/api-reference/files/list)\n"
operationId: listFiles
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
data:
type: array
items:
type: object
properties:
bytes:
type: number
example: 175
created_at:
type: number
example: 1613677385
filename:
type: string
example: train.jsonl
id:
type: string
example: file-ccdDZrC3iZVNiQVeEA6Z66wf
object:
type: string
example: file
purpose:
type: string
example: search
example:
- bytes: 175
created_at: 1613677385
filename: train.jsonl
id: file-ccdDZrC3iZVNiQVeEA6Z66wf
object: file
purpose: search
- bytes: 140
created_at: 1613779121
filename: puppy.jsonl
id: file-XjGxS3KTG0uNmNOK362iJua3
object: file
purpose: search
object:
type: string
example: list
examples:
Ok:
value:
data:
- bytes: 175
created_at: 1613677385
filename: train.jsonl
id: file-ccdDZrC3iZVNiQVeEA6Z66wf
object: file
purpose: search
- bytes: 140
created_at: 1613779121
filename: puppy.jsonl
id: file-XjGxS3KTG0uNmNOK362iJua3
object: file
purpose: search
object: list
post:
tags:
- Files
summary: Upload file
description: "Upload a file that contains document(s) to be used across various endpoints/features.\nCurrently, the size of all the files uploaded by one organization can be up to 1 GB.\nPlease contact us if you need to increase the storage limit.\n\n[See More](https://beta.openai.com/docs/api-reference/files/upload)\n"
operationId: uploadFile
requestBody:
content:
application/octet-stream: {}
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
bytes:
type: number
example: 140
created_at:
type: number
example: 1613779121
filename:
type: string
example: puppy.jsonl
id:
type: string
example: file-XjGxS3KTG0uNmNOK362iJua3
object:
type: string
example: file
purpose:
type: string
example: answers
examples:
Ok:
value:
bytes: 140
created_at: 1613779121
filename: puppy.jsonl
id: file-XjGxS3KTG0uNmNOK362iJua3
object: file
purpose: answers
"/files/{file_id}":
get:
tags:
- Files
summary: Retrieve file
description: "Returns information about a specific file.\n\n[See More](https://beta.openai.com/docs/api-reference/files/retrieve)\n"
operationId: retrieveFile
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
bytes:
type: number
example: 140
created_at:
type: number
example: 1613779657
filename:
type: string
example: puppy.jsonl
id:
type: string
example: file-XjGxS3KTG0uNmNOK362iJua3
object:
type: string
example: file
purpose:
type: string
example: answers
examples:
Ok:
value:
bytes: 140
created_at: 1613779657
filename: puppy.jsonl
id: file-XjGxS3KTG0uNmNOK362iJua3
object: file
purpose: answers
delete:
tags:
- Files
summary: Delete file
description: "Delete a file.\n\n[See More](https://beta.openai.com/docs/api-reference/files/delete)\n"
operationId: deleteFile
responses:
"204":
description: Removed
content:
text/plain:
examples:
Removed:
value: ""
parameters:
- name: file_id
in: path
required: true
schema:
type: string
/fine-tunes:
get:
tags:
- Fine-tunes
summary: List fine-tunes
description: "List your organization's fine-tuning jobs"
operationId: listFineTunes
responses:
"200":
description: Ok
content:
text/plain:
examples:
Ok:
value: "{\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"ftjob-AF1WoRqd3aJAHsqc9NY7iL8F\",\n \"object\": \"fine-tune\",\n \"model\": \"curie\",\n \"created_at\": 1614807352,\n \"events\": [ { ... } ],\n \"fine_tuned_model\": null,\n \"hyperparams\": { ... },\n \"organization_id\": \"org-hgpU6lQMdxgqSY8fmklyOcwP\",\n \"result_files\": [],\n \"status\": \"pending\",\n \"validation_files\": [],\n \"training_files\": [ { ... } ],\n \"updated_at\": 1614807352,\n \"user_id\": \"user-YEu26bFANWmICJuWuidWA31c\"\n },\n { ... },\n { ... }\n ]\n}\n"
post:
tags:
- Fine-tunes
summary: Create fine-tune
description: "Creates a job that fine-tunes a specified model from a given dataset.\r\n\r\nResponse includes details of the enqueued job including job status and the name of the fine-tuned models once complete.\r\n\r\n[Learn more about Fine-tuning](https://beta.openai.com/docs/guides/fine-tuning)"
operationId: createFineTune
requestBody:
content:
application/json:
schema:
type: object
properties:
training_file:
type: string
example: file-XGinujblHPwGLSztz8cPS8XY
example:
training_file: file-XGinujblHPwGLSztz8cPS8XY
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
created_at:
type: number
example: 1614807352
events:
type: array
items:
type: object
properties:
created_at:
type: number
example: 1614807352
level:
type: string
example: info
message:
type: string
example: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object:
type: string
example: fine-tune-event
example:
- created_at: 1614807352
level: info
message: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object: fine-tune-event
fine_tuned_model:
nullable: true
example: ~
hyperparams:
type: object
properties:
batch_size:
type: number
example: 4
learning_rate_multiplier:
type: number
example: 0.1
n_epochs:
type: number
example: 4
prompt_loss_weight:
type: number
example: 0.1
use_packing:
type: boolean
example: true
id:
type: string
example: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
model:
type: string
example: curie
object:
type: string
example: fine-tune
organization_id:
type: string
example: org-hgpU6lQMdxgqSY8fmklyOcwP
result_files:
type: array
items: {}
example: []
status:
type: string
example: pending
training_files:
type: array
items:
type: object
properties:
bytes:
type: number
example: 1547276
created_at:
type: number
example: 1610062281
filename:
type: string
example: my-data-train.jsonl
id:
type: string
example: file-XGinujblHPwGLSztz8cPS8XY
object:
type: string
example: file
purpose:
type: string
example: fine-tune-train
example:
- bytes: 1547276
created_at: 1610062281
filename: my-data-train.jsonl
id: file-XGinujblHPwGLSztz8cPS8XY
object: file
purpose: fine-tune-train
updated_at:
type: number
example: 1614807352
user_id:
type: string
example: user-YEu26bFANWmICJuWuidWA31c
validation_files:
type: array
items: {}
example: []
examples:
Ok:
value:
created_at: 1614807352
events:
- created_at: 1614807352
level: info
message: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object: fine-tune-event
fine_tuned_model: ~
hyperparams:
batch_size: 4
learning_rate_multiplier: 0.1
n_epochs: 4
prompt_loss_weight: 0.1
use_packing: true
id: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
model: curie
object: fine-tune
organization_id: org-hgpU6lQMdxgqSY8fmklyOcwP
result_files: []
status: pending
training_files:
- bytes: 1547276
created_at: 1610062281
filename: my-data-train.jsonl
id: file-XGinujblHPwGLSztz8cPS8XY
object: file
purpose: fine-tune-train
updated_at: 1614807352
user_id: user-YEu26bFANWmICJuWuidWA31c
validation_files: []
"/fine-tunes/{fine_tune_id}":
get:
tags:
- Fine-tunes
summary: Retrieve fine-tune
description: "List your organization's fine-tuning jobs"
operationId: retrieveFineTune
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
created_at:
type: number
example: 1614807352
events:
type: array
items:
type: object
properties:
created_at:
type: number
example: 1614807352
level:
type: string
example: info
message:
type: string
example: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object:
type: string
example: fine-tune-event
example:
- created_at: 1614807352
level: info
message: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object: fine-tune-event
- created_at: 1614807356
level: info
message: Job started.
object: fine-tune-event
- created_at: 1614807861
level: info
message: "Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20."
object: fine-tune-event
- created_at: 1614807864
level: info
message: "Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT."
object: fine-tune-event
- created_at: 1614807864
level: info
message: Job succeeded.
object: fine-tune-event
fine_tuned_model:
type: string
example: "curie:ft-acmeco-2021-03-03-21-44-20"
hyperparams:
type: object
properties:
batch_size:
type: number
example: 4
learning_rate_multiplier:
type: number
example: 0.1
n_epochs:
type: number
example: 4
prompt_loss_weight:
type: number
example: 0.1
use_packing:
type: boolean
example: true
id:
type: string
example: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
model:
type: string
example: curie
object:
type: string
example: fine-tune
organization_id:
type: string
example: org-hgpU6lQMdxgqSY8fmklyOcwP
result_files:
type: array
items:
type: object
properties:
bytes:
type: number
example: 81509
created_at:
type: number
example: 1614807863
filename:
type: string
example: compiled_results.csv
id:
type: string
example: file-QQm6ZpqdNwAaVC3aSz5sWwLT
object:
type: string
example: file
purpose:
type: string
example: fine-tune-results
example:
- bytes: 81509
created_at: 1614807863
filename: compiled_results.csv
id: file-QQm6ZpqdNwAaVC3aSz5sWwLT
object: file
purpose: fine-tune-results
status:
type: string
example: succeeded
training_files:
type: array
items:
type: object
properties:
bytes:
type: number
example: 1547276
created_at:
type: number
example: 1610062281
filename:
type: string
example: my-data-train.jsonl
id:
type: string
example: file-XGinujblHPwGLSztz8cPS8XY
object:
type: string
example: file
purpose:
type: string
example: fine-tune-train
example:
- bytes: 1547276
created_at: 1610062281
filename: my-data-train.jsonl
id: file-XGinujblHPwGLSztz8cPS8XY
object: file
purpose: fine-tune-train
updated_at:
type: number
example: 1614807865
user_id:
type: string
example: user-YEu26bFANWmICJuWuidWA31c
validation_files:
type: array
items: {}
example: []
examples:
Ok:
value:
created_at: 1614807352
events:
- created_at: 1614807352
level: info
message: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object: fine-tune-event
- created_at: 1614807356
level: info
message: Job started.
object: fine-tune-event
- created_at: 1614807861
level: info
message: "Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20."
object: fine-tune-event
- created_at: 1614807864
level: info
message: "Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT."
object: fine-tune-event
- created_at: 1614807864
level: info
message: Job succeeded.
object: fine-tune-event
fine_tuned_model: "curie:ft-acmeco-2021-03-03-21-44-20"
hyperparams:
batch_size: 4
learning_rate_multiplier: 0.1
n_epochs: 4
prompt_loss_weight: 0.1
use_packing: true
id: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
model: curie
object: fine-tune
organization_id: org-hgpU6lQMdxgqSY8fmklyOcwP
result_files:
- bytes: 81509
created_at: 1614807863
filename: compiled_results.csv
id: file-QQm6ZpqdNwAaVC3aSz5sWwLT
object: file
purpose: fine-tune-results
status: succeeded
training_files:
- bytes: 1547276
created_at: 1610062281
filename: my-data-train.jsonl
id: file-XGinujblHPwGLSztz8cPS8XY
object: file
purpose: fine-tune-train
updated_at: 1614807865
user_id: user-YEu26bFANWmICJuWuidWA31c
validation_files: []
parameters:
- name: fine_tune_id
in: path
required: true
schema:
type: string
example: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
description: "(Required) The ID of the fine-tune job to cancel\n\n"
"/fine-tunes/{fine_tune_id}/cancel":
post:
tags:
- Fine-tunes
summary: Cancel fine-tune
description: "Creates a job that fine-tunes a specified model from a given dataset.\r\n\r\nResponse includes details of the enqueued job including job status and the name of the fine-tuned models once complete.\r\n\r\n[Learn more about Fine-tuning](https://beta.openai.com/docs/guides/fine-tuning)"
operationId: cancelFineTune
requestBody:
content:
application/json:
schema:
type: object
properties:
training_file:
type: string
example: file-XGinujblHPwGLSztz8cPS8XY
example:
training_file: file-XGinujblHPwGLSztz8cPS8XY
responses:
"200":
description: ""
parameters:
- name: fine_tune_id
in: path
required: true
schema:
type: string
example: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
description: "(Required) The ID of the fine-tune job to cancel\n"
"/fine-tunes/{fine_tune_id}/events":
get:
tags:
- Fine-tunes
summary: List fine-tune events
description: "List your organization's fine-tuning jobs"
operationId: listFineTuneEvents
responses:
"200":
description: Ok
content:
application/json:
schema:
type: object
properties:
data:
type: array
items:
type: object
properties:
created_at:
type: number
example: 1614807352
level:
type: string
example: info
message:
type: string
example: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object:
type: string
example: fine-tune-event
example:
- created_at: 1614807352
level: info
message: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object: fine-tune-event
- created_at: 1614807356
level: info
message: Job started.
object: fine-tune-event
- created_at: 1614807861
level: info
message: "Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20."
object: fine-tune-event
- created_at: 1614807864
level: info
message: "Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT."
object: fine-tune-event
- created_at: 1614807864
level: info
message: Job succeeded.
object: fine-tune-event
object:
type: string
example: list
examples:
Ok:
value:
data:
- created_at: 1614807352
level: info
message: "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
object: fine-tune-event
- created_at: 1614807356
level: info
message: Job started.
object: fine-tune-event
- created_at: 1614807861
level: info
message: "Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20."
object: fine-tune-event
- created_at: 1614807864
level: info
message: "Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT."
object: fine-tune-event
- created_at: 1614807864
level: info
message: Job succeeded.
object: fine-tune-event
object: list
parameters:
- name: fine_tune_id
in: path
required: true
schema:
type: string
example: ftjob-AF1WoRqd3aJAHsqc9NY7iL8F
description: "(Required) The ID of the fine-tune job to cancel\n\n"
tags:
- name: Engines
- name: Completions
- name: Searches
- name: Classifications
- name: Answers
- name: Files
- name: Fine-tunes