The endpoint first searches over provided documents or files to find relevant context. The relevant context is combined with the provided examples and question to create the prompt for completion.

Example request

OpenAI.answers(
  model: "curie",
  documents: ["Puppy A is happy.", "Puppy B is sad."],
  question: "which puppy is happy?",
  search_model: "ada",
  examples_context: "In 2017, U.S. life expectancy was 78.6 years.",
  examples: [["What is human life expectancy in the United States?", "78 years."]],
  max_tokens: 5
)

Example response

{:ok,
  %{
  answers: ["puppy A."],
  completion: "cmpl-2kdRgXcoUfaAXxlPjmZXBT8AlKWfB",
  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. "}
  ]
  }
}

See: https://beta.openai.com/docs/api-reference/answers

Creates a completion for the chat message

Example request

OpenAI.chat_completion(
  model: "gpt-3.5-turbo",
  messages: [
        %{role: "system", content: "You are a helpful assistant."},
        %{role: "user", content: "Who won the world series in 2020?"},
        %{role: "assistant", content: "The Los Angeles Dodgers won the World Series in 2020."},
        %{role: "user", content: "Where was it played?"}
    ]
)

Example response

{:ok,
  %{
  choices: [
    %{
      "finish_reason" => "stop",
      "index" => 0,
      "message" => %{
        "content" => "The 2020 World Series was played at Globe Life Field in Arlington, Texas due to the COVID-19 pandemic.",
        "role" => "assistant"
      }
    }
  ],
  created: 1677773799,
  id: "chatcmpl-6pftfA4NO9pOQIdxao6Z4McDlx90l",
  model: "gpt-3.5-turbo-0301",
  object: "chat.completion",
  usage: %{
    "completion_tokens" => 26,
    "prompt_tokens" => 56,
    "total_tokens" => 82
  }
  }
}

Known issue: the stream param is not working properly in the current implementation

See: https://platform.openai.com/docs/api-reference/chat/create for the complete list of parameters you can pass to the completions function

@deprecated: "DEPRECATED by OpenAI"

It returns the most likely label for the query passed to the function. The function accepts as arguments a set of parameters that will be passed to the Classifications OpenAI api

Given a query and a set of labeled examples, the model will predict the most likely label for the query. Useful as a drop-in replacement for any ML classification or text-to-label task.

Example request

OpenAI.classifications(
  examples: [
    ["A happy moment", "Positive"],
    ["I am sad.", "Negative"],
    ["I am feeling awesome", "Positive"]
  ],
  labels: ["Positive", "Negative", "Neutral"],
  query: "It is a raining day :(",
  search_model: "ada",
  model: "curie"
)

Example response

{:ok,
  %{
    completion: "cmpl-2jIXZYg7Buyg1DDRYtozkre50TSMb",
    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"}
    ]
  }
}

See: https://beta.openai.com/docs/api-reference/classifications for the complete list of parameters you can pass to the classifications function

It returns one or more predicted completions given a prompt. The function accepts as arguments the "engine_id" and the set of parameters used by the Completions OpenAI api

Example request

OpenAI.completions(
  model: "finetuned-model",
  prompt: "once upon a time",
  max_tokens: 5,
  temperature: 1,
  ...
)

Example response

{:ok, %{
  choices: [
    %{
      "finish_reason" => "length",
      "index" => 0,
      "logprobs" => nil,
      "text" => "" thing we are given"
    }
  ],
  created: 1617147958,
  id: "...",
  model: "...",
  object: "text_completion"
  }
}

See: https://platform.openai.com/docs/api-reference/completions/create

It returns one or more predicted completions given a prompt. The function accepts as arguments the "engine_id" and the set of parameters used by the Completions OpenAI api

Example request

OpenAI.completions(
  "davinci", # engine_id
  prompt: "once upon a time",
  max_tokens: 5,
  temperature: 1,
  ...
)

Example response

{:ok, %{
  choices: [
    %{
      "finish_reason" => "length",
      "index" => 0,
      "logprobs" => nil,
      "text" => "" thing we are given"
    }
  ],
  created: 1617147958,
  id: "...",
  model: "...",
  object: "text_completion"
  }
}

See: https://beta.openai.com/docs/api-reference/completions/create for the complete list of parameters you can pass to the completions function

Creates a new edit for the provided input, instruction, and parameters

Example request

OpenAI.edits( model: "text-davinci-edit-001", input: "What day of the wek is it?", instruction: "Fix the spelling mistakes" )

Example response

{:ok, %{ choices: [%{"index" => 0, "text" => "What day of the week is it? "}], created: 1675443483, object: "edit", usage: %{ "completion_tokens" => 28, "prompt_tokens" => 25, "total_tokens" => 53 } }}

See: https://platform.openai.com/docs/api-reference/edits/create

Creates an embedding vector representing the input text.

Example request

OpenAI.embeddings( model: "text-embedding-ada-002", input: "The food was delicious and the waiter..." )

Example response

{:ok, %{ data: [ %{

 "embedding" => [0.0022523515000000003, -0.009276069000000001,
  0.015758524000000003, -0.007790373999999999, -0.004714223999999999,
  0.014806155000000001, -0.009803046499999999, -0.038323310000000006,
  -0.006844355, -0.028672641, 0.025345700000000002, 0.018145794000000003,
  -0.0035904291999999997, -0.025498080000000003, 5.142790000000001e-4,
  -0.016317246, 0.028444072, 0.0053713582, 0.009631619999999999,
  -0.016469626, -0.015390275, 0.004301531, 0.006984035499999999,
  -0.007079272499999999, -0.003926933, 0.018602932000000003, 0.008666554,
  -0.022717162999999995, 0.011460166999999997, 0.023860006,
  0.015568050999999998, -0.003587254600000001, -0.034843990000000005,
  -0.0041555012999999995, -0.026107594000000005, -0.02151083,
  -0.0057618289999999996, 0.011714132499999998, 0.008355445999999999,
  0.004098358999999999, 0.019199749999999998, -0.014336321, 0.008952264,
  0.0063395994, -0.04576447999999999, ...],
 "index" => 0,
 "object" => "embedding"

} ], model: "text-embedding-ada-002-v2", object: "list", usage: %{"prompt_tokens" => 8, "total_tokens" => 8} }}

See: https://platform.openai.com/docs/api-reference/embeddings/create

@deprecated: "use models instead" Get the list of available engines

Example request

OpenAI.engines()

Example response

{:ok, %{
  "data" => [
    %{"id" => "davinci", "object" => "engine", "max_replicas": ...},
    ...,
    ...
  ]
}

See: https://beta.openai.com/docs/api-reference/engines/list

Retrieve specific engine info

Example request

OpenAI.engines("davinci")

Example response

{:ok, %{
  "id" => "davinci",
  "object" => "engine",
  "max_replicas": ...
}
}

See: https://beta.openai.com/docs/api-reference/engines/retrieve

Returns a list of files that belong to the user's organization.

Example request

OpenAI.files()

Example response

{:ok,
  %{
  data: [
    %{
      "bytes" => 123,
      "created_at" => 213,
      "filename" => "file.jsonl",
      "id" => "file-123321",
      "object" => "file",
      "purpose" => "fine-tune",
      "status" => "processed",
      "status_details" => nil
    }
  ],
  object: "list"
  }
}

See: https://platform.openai.com/docs/api-reference/files

Returns a file that belong to the user's organization, given a file id

Example Request

OpenAI.files("file-123321")

Example Response

{:ok,
  %{
    bytes: 923,
    created_at: 1675370979,
    filename: "file.jsonl",
    id: "file-123321",
    object: "file",
    purpose: "fine-tune",
    status: "processed",
    status_details: nil
  }
}

See: https://platform.openai.com/docs/api-reference/files/retrieve

delete a file

Example Request

OpenAI.files_delete("file-123")

Example Response

{:ok, %{deleted: true, id: "file-123", object: "file"}}

See: https://platform.openai.com/docs/api-reference/files/delete

Upload a file that contains document(s) to be used across various endpoints/features. Currently, the size of all the files uploaded by one organization can be up to 1 GB. Please contact OpenAI if you need to increase the storage limit.

Example request

OpenAI.files_upload("./file.jsonl", purpose: "fine-tune")

Example response

{:ok,
  %{
    bytes: 923,
    created_at: 1675373519,
    filename: "file.jsonl",
    id: "file-123",
    object: "file",
    purpose: "fine-tune",
    status: "uploaded",
    status_details: nil
  }
}

See: https://platform.openai.com/docs/api-reference/files/upload

List your organization's fine-tuning jobs

Example request

OpenAI.finetunes()

Example response

{:ok, %{
  "data" => [
    %{"created_at" => 1614807352, "fine_tuned_model" => "curie:ft-acmeco-2021-03-03-21-44-20", "model": ...},
    ...,
    ...
  ]
}

See: https://beta.openai.com/docs/api-reference/fine-tunes/list

Gets info about the fine-tune job.

Example request

OpenAI.finetunes("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

Example response

{:ok, %{
  created_at: 1614807352,
  events: [
    %{
      "created_at" => 1614807352,
      "level" => "info",
      "message" => "Created fine-tune: ft-AF1WoRqd3aJAHsqc9NY7iL8F",
      "object" => "fine-tune-event"
    },
    %{
      "created_at" => 1614807360,
      "level" => "info",
      "message" => "Fine-tune costs $0.02",
      "object" => "fine-tune-event"
    },
    ...,
    ...
}

See: https://beta.openai.com/docs/api-reference/fine-tunes/retrieve

Immediately cancel a fine-tune job.

Example request

OpenAI.finetunes_cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

Example response

{:ok, %{ created_at: 1675527767, events: [ ... %{

 "created_at" => 1675528080,
 "level" => "info",
 "message" => "Fine-tune cancelled",
 "object" => "fine-tune-event"

} ], fine_tuned_model: nil, hyperparams: %{ "batch_size" => 1, "learning_rate_multiplier" => 0.1, "n_epochs" => 4, "prompt_loss_weight" => 0.01 }, id: "ft-IaBYfSSAK47UUCbebY5tBIEj", model: "curie", object: "fine-tune", organization_id: "org-1iPTOIak4b5fpuIB697AYMmO", result_files: [], status: "cancelled", training_files: [ %{

 "bytes" => 923,
 "created_at" => 1675373519,
 "filename" => "file123.jsonl",
 "id" => "file-123",
 "object" => "file",
 "purpose" => "fine-tune",
 "status" => "processed",
 "status_details" => nil

} ], updated_at: 1675528080, validation_files: [] }}

See: https://platform.openai.com/docs/api-reference/fine-tunes/cancel

Creates a job that fine-tunes a specified model from a given dataset.

Example request

OpenAI.finetunes_create(training_file: "file-123", model: "curie", validation_file: "file-456")

Example response

See: https://platform.openai.com/docs/api-reference/fine-tunes/create

Delete a fine-tuned model. You must have the Owner role in your organization.

Example request

OpenAI.finetunes_delete_model("model-id")

Example response

{:ok, %{ id: "model-id", object: "model", deleted: true }}

See: https://platform.openai.com/docs/api-reference/fine-tunes/delete-model

Get fine-grained status updates for a fine-tune job.

Example request

OpenAI.finetunes_list_events("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

Example response

{:ok, %{ data: [ %{

 "created_at" => 1675376995,
 "level" => "info",
 "message" => "Created fine-tune: ft-123",
 "object" => "fine-tune-event"

}, %{

 "created_at" => 1675377104,
 "level" => "info",
 "message" => "Fine-tune costs $0.00",
 "object" => "fine-tune-event"

}, %{

 "created_at" => 1675377105,
 "level" => "info",
 "message" => "Fine-tune enqueued. Queue number: 18",
 "object" => "fine-tune-event"

}, ..., ] } }

See: https://platform.openai.com/docs/api-reference/fine-tunes/events

alias of images_edits(file_path, params, request_options) - will be deprecated in future releases

alias of images_generations(params, request_options) - will be deprecated in future releases

alias of images_variations(file_path, params, request_options) - will be deprecated in future releases

This edits an image based on the given prompt.

Example Request

OpenAI.images_edits(
  "/home/developer/myImg.png",
  [prompt: "A developer writing a test", "size": "256x256"],
  [recv_timeout: 10 * 60 * 1000]
)

Example Response

{:ok,
%{
 created: 1670341737,
 data: [
   %{
     "url" => ...Returned url
   }
 ]
}}

See: https://beta.openai.com/docs/api-reference/images/create-edit for the complete list of parameters you can pass to the image creation function

This generates an image based on the given prompt. If needed, you can pass a second argument to the function to add specific http options to this specific call (i.e. increasing the timeout)

Example Request

OpenAI.images_generations(
  [prompt: "A developer writing a test", size: "256x256"],
  [recv_timeout: 10 * 60 * 1000]
)

Example Response

{:ok,

%{
created: 1670341737,
data: [
  %{
   "url" => ...Returned url
 }
]

}} See: https://beta.openai.com/docs/api-reference/images/create for the complete list of parameters you can pass to the image creation function

Creates a variation of a given image. If needed, you can pass a second argument to the function to add specific http options to this specific call (i.e. increasing the timeout)

Example Request

OpenAI.images_variations(
   "/home/developer/myImg.png",
   [n: "5"],
   [recv_timeout: 10 * 60 * 1000]
)

Example Response

{:ok,
%{
 created: 1670341737,
 data: [
   %{
     "url" => ...Returned url
   }
 ]
}}

See: https://beta.openai.com/docs/api-reference/images/create-variation for the complete list of parameters you can pass to the image creation function

Retrieve the list of available models

Example request

OpenAI.models()

Example response

 %{
 "created" => 1651172505,
 "id" => "davinci-search-query",
 "object" => "model",
 "owned_by" => "openai-dev",
 "parent" => nil,
 "permission" => [
   %{
     "allow_create_engine" => false,
     "allow_fine_tuning" => false,
     "allow_logprobs" => true,
     ...
   }
 ],
 "root" => "davinci-search-query"

} See: https://platform.openai.com/docs/api-reference/models/retrieve

Retrieve specific model info

Example request

OpenAI.models("davinci-search-query")

Example response

 {:ok, %{

data: [%{ "created" => 1651172505, "id" => "davinci-search-query", "object" => "model", "owned_by" => "openai-dev", "parent" => nil, "permission" => [

%{
  "allow_create_engine" => false,
  "allow_fine_tuning" => false,
  "allow_logprobs" => true,
  ...
}

], "root" => "davinci-search-query" }, ....], object: "list" }} See: https://platform.openai.com/docs/api-reference/models/retrieve

Classifies if text violates OpenAI's Content Policy

Example request

OpenAI.moderations(input: "I want to kill everyone!")

Example response

{:ok, %{ id: "modr-6gEWXyuaU8dqiHpbAHIsdru0zuC88", model: "text-moderation-004", results: [ %{

 "categories" => %{
   "hate" => false,
   "hate/threatening" => false,
   "self-harm" => false,
   "sexual" => false,
   "sexual/minors" => false,
   "violence" => true,
   "violence/graphic" => false
 },
 "category_scores" => %{
   "hate" => 0.05119025334715844,
   "hate/threatening" => 0.00321022979915142,
   "self-harm" => 7.337320857914165e-5,
   "sexual" => 1.1111642379546538e-6,
   "sexual/minors" => 3.588798147546868e-10,
   "violence" => 0.9190407395362855,
   "violence/graphic" => 1.2791929293598514e-7
 },
 "flagged" => true

} ] }}

See: https://platform.openai.com/docs/api-reference/moderations/create

@deprecated: "DEPRECATED by OpenAI"

It returns a rank of each document passed to the function, based on its semantic similarity to the passed query. The function accepts as arguments the engine_id and theset of parameters used by the Search OpenAI api

Example request

OpenAI.search(
  "babbage", #engine_id
  documents: ["White House", "hospital", "school"],
  query: "the president"
)

Example response

{:ok,
  %{
    data: [
      %{"document" => 0, "object" => "search_result", "score" => 218.676},
      %{"document" => 1, "object" => "search_result", "score" => 17.797},
      %{"document" => 2, "object" => "search_result", "score" => 29.65}
    ],
    model: "...",
    object: "list"
  }}

See: https://beta.openai.com/docs/api-reference/searches for the complete list of parameters you can pass to the search function

Callback implementation for Application.start/2.