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Elixir SDK for OpenAI APIs

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ExOpenAI is an (unofficial) Elixir SDK for interacting with the OpenAI APIs

This SDK is fully auto-generated using metaprogramming and should always reflect the latest state of the OpenAI API.

Note: Due to the nature of auto-generating something, you may encounter stuff that isn't working yet. Make sure to report if you notice anything acting up.

Features

  • Up-to-date and complete thanks to metaprogramming and code-generation
  • Implements everything the OpenAI has to offer
  • Strictly follows the official OpenAI APIs for argument/function naming
  • Handling of required arguments as function parameters and optional arguments as Keyword list in true Elixir-fashion
  • Auto-generated embedded function documentation
  • Auto-generated @spec definitions for dialyzer, for strict parameter typing
  • Support for streaming responses with SSE

Installation

Add :ex_openai as a dependency in your mix.exs file.

def deps do
  [
    {:ex_openai, "~> 1.7"}
  ]
end

Supported endpoints (basically everything)

  • "/assistants/{assistant_id}"
  • "/assistants/{assistant_id}/files/{file_id}"
  • "/assistants"
  • "/assistants/{assistant_id}/files"
  • "/audio/speech"
  • "/audio/transcriptions"
  • "/audio/translations"
  • "/chat/completions"
  • "/completions"
  • "/edits"
  • "/embeddings"
  • "/files/{file_id}"
  • "/files/{file_id}/content"
  • "/files"
  • "/fine-tunes/{fine_tune_id}"
  • "/fine-tunes/{fine_tune_id}/events"
  • "/fine-tunes/{fine_tune_id}/cancel"
  • "/fine-tunes"
  • "/fine_tuning/jobs"
  • "/fine_tuning/jobs/{fine_tuning_job_id}"
  • "/fine_tuning/jobs/{fine_tuning_job_id}/events"
  • "/fine_tuning/jobs/{fine_tuning_job_id}/cancel"
  • "/images/edits"
  • "/images/generations"
  • "/images/variations"
  • "/models/{model}"
  • "/models"
  • "/moderations"
  • "/threads/{thread_id}/messages/{message_id}/files"
  • "/threads/{thread_id}"
  • "/threads"
  • "/threads/{thread_id}/runs/{run_id}/steps"
  • "/threads/{thread_id}/messages/{message_id}/files/{file_id}"
  • "/threads/{thread_id}/runs/{run_id}/submit_tool_outputs"
  • "/threads/{thread_id}/runs/{run_id}/steps/{step_id}"
  • "/threads/{thread_id}/messages"
  • "/threads/runs"
  • "/threads/{thread_id}/messages/{message_id}"
  • "/threads/{thread_id}/runs/{run_id}/cancel"
  • "/threads/{thread_id}/runs"
  • "/threads/{thread_id}/runs/{run_id}"

Editor features: Autocomplete, specs, docs

Autocompletion/type-hinting through LSP / ElixirSense

Typechecking and diagnostics through strict @spec definitions

Inline docs and signatures thanks to @spec and @doc

To Do's / What's not working yet

  • Streams don't have complete typespecs yet

Configuration

import Config

config :ex_openai,
  # find it at https://platform.openai.com/account/api-keys
  api_key: System.get_env("OPENAI_API_KEY"),
  # find it at https://platform.openai.com/account/api-keys
  organization_key: System.get_env("OPENAI_ORGANIZATION_KEY"),
	# optional, other clients allow overriding via the OPENAI_API_URL/OPENAI_API_BASE environment variable,
	# if unset the the default is https://api.openai.com/v1
  base_url: System.get_env("OPENAI_API_URL"),
  # optional, passed to [HTTPoison.Request](https://hexdocs.pm/httpoison/HTTPoison.Request.html) options
  http_options: [recv_timeout: 50_000],
  # optional, default request headers. The following header is required for Assistant endpoints, which are in beta as of December 2023.
  http_headers: [
    {"OpenAI-Beta", "assistants=v2"}
  ],
  # optional http client, useful for testing purposes on dependent projects
  # if unset the default client is ExOpenAI.Client
  http_client: ExOpenAI.Client

You can also pass base_url, api_key and organization_key directly by passing them into the opts argument when calling the openai apis:

ExOpenAI.Models.list_models(openai_api_key: "abc", openai_organization_key: "def", base_url: "https://cheapai.local")

Usage

Make sure to checkout the docs: https://hexdocs.pm/ex_openai

ExOpenAI.Models.list_models
{:ok,
 %{
   data: [
     %{
       "created": 1649358449,
       "id": "babbage",
       "object": "model",
       "owned_by": "openai",
       "parent": nil,
       "permission": [
         %{
           "allow_create_engine": false,
           "allow_fine_tuning": false,
           "allow_logprobs": true,
           "allow_sampling": true,
           "allow_search_indices": false,
           "allow_view": true,
           "created": 1669085501,
           "group": nil,
           "id": "modelperm-49FUp5v084tBB49tC4z8LPH5",
           "is_blocking": false,
           "object": "model_permission",
           "organization": "*"
         }
       ],
       "root": "babbage"
     },
  ...

Required parameters are converted into function arguments, optional parameters into the opts keyword list:

ExOpenAI.Completions.create_completion "text-davinci-003", "The sky is"
{:ok,
 %{
   choices: [
     %{
       "finish_reason": "length",
       "index": 0,
       "logprobs": nil,
       "text": " blue\n\nThe sky is a light blue hue that may have a few white"
     }
   ],
   created: 1677929239,
   id: "cmpl-6qKKllDPsQRtyJ5oHTbkQVS9w7iKM",
   model: "text-davinci-003",
   object: "text_completion",
   usage: %{
     "completion_tokens": 16,
     "prompt_tokens": 3,
     "total_tokens": 19
   }
 }}

Using ChatGPT APIs

msgs = [
  %ExOpenAI.Components.ChatCompletionRequestUserMessage{role: :user, content: "Hello!"},
  %ExOpenAI.Components.ChatCompletionRequestAssistantMessage{role: :assistant, content: "What's up?"},
  %ExOpenAI.Components.ChatCompletionRequestUserMessage{role: :user, content: "What ist the color of the sky?"}
]

{:ok, res} =
  ExOpenAI.Chat.create_chat_completion(msgs, "gpt-3.5-turbo",
    logit_bias: %{
      "8043" => -100
    }
  )

Using Assistant APIs

{:ok, assistant} =
	ExOpenAI.Assistants.create_assistant(:"gpt-4o",
		name: "Math Teacher",
		instruction:
			"You are a personal math tutor. Write and run code to answer math questions.",
		tools: [%{type: "code_interpreter"}]
	)

{:ok, thread} = ExOpenAI.Threads.create_thread()

{:ok, _msg} =
	ExOpenAI.Threads.create_message(
		thread.id,
		"I need to solve the equation `3x + 11 = 14`. Can you help me?",
		"user"
	)

{:ok, _run} =
	ExOpenAI.Threads.create_run(
		thread.id,
		assistant.id
	)

# sleep for 5 seconds
# :timer.sleep(5000)

{:ok, messages} = ExOpenAI.Threads.list_messages(thread.id)

Usage of endpoints that require files to upload

Load your file into memory, then pass it into the file parameter

duck = File.read!("#{__DIR__}/testdata/duck.png")

{:ok, res} = ExOpenAI.Images.create_image_variation(duck)

IO.inspect(res.data)

File endpoints that require filename information (Audio transcription)

Some endpoints (like audio transcription) require the original filename so the API knows what the encoding of something is. You can pass a {filename, bitstring} tuple into anything that requires a file:

audio = File.read!("/Users/david/Downloads/output.wav")
output = ExOpenAI.Audio.create_transcription {"foobar.wav", audio}, "whisper-1"

IO.inspect(output)

{:ok,
 %ExOpenAI.Components.CreateTranscriptionResponse{
   text: "Hello, hello, hello, just a test."
 }}

Usage of Audio related

Streaming data

streaming

You have 2 options to stream data, either by specifying a callback function or by specifying a separate PID

Streaming with a callback function

Pass a callback function to stream_to when invoking a call and set stream: to true:

callback = fn
	:finish -> IO.puts "Done"
	{:data, data} -> IO.puts "Data: #{inspect(data)}"
	{:error, err} -> IO.puts "Error: #{inspect(err)}"
end

ExOpenAI.Completions.create_completion "text-davinci-003", "hello world", stream: true, stream_to: callback

Streaming with a separate process

Create a new client for receiving the streamed data with use ExOpenAI.StreamingClient. You'll have to implement the @behaviour ExOpenAI.StreamingClient which defines 3 callback functions:

defmodule MyStreamingClient do
  use ExOpenAI.StreamingClient

  @impl true
  # callback on data
  def handle_data(data, state) do
    IO.puts("got data: #{inspect(data)}")
    {:noreply, state}
  end

  @impl true
  # callback on error
  def handle_error(e, state) do
    IO.puts("got error: #{inspect(e)}")
    {:noreply, state}
  end

  @impl true
  # callback on finish
  def handle_finish(state) do
    IO.puts("finished!!")
    {:noreply, state}
  end
end

Then use it in requests that support streaming by setting stream: true and specifying stream_to: pid:

{:ok, pid} = MyStreamingClient.start_link nil
ExOpenAI.Completions.create_completion "text-davinci-003", "hello world", stream: true, stream_to: pid

Your client will now receive the streamed chunks

Caveats

  • Type information for streamed data is not correct yet. For Completions.create_completion it's fine, however Chat.create_chat_completion requests use a different struct with a delta field
  • Return types for when setting stream: true is incorrect, dialyzer may complain

How to update once OpenAI changes something?

Run mix update_openai_docs and commit the new docs.yaml file

Some stuff built using this SDK (add yours with a PR!)

How auto-generation works / how can I extend this?

The code got a little complicated but here is the basic gist of it: codegen.ex is responsible for parsing the docs.yml file into Elixir types. This is then used in ex_openai.ex to generate modules.

The endpoint path is used to generate the group name, for example "/completions" turns into ExOpenAI.Completions.*.

  1. "parse_component_schema" parses the entire docs.yml file and spits out a bunch of "property" structs that look like this:
ChatCompletionRequestMessage:
  type: object
  properties:
    role:
      type: string
      enum: ["system", "user", "assistant", "function"]
      description: The role of the messages author. One of `system`, `user`, `assistant`, or `function`.
    content:
      type: string
      nullable: true
      description: The contents of the message. `content` is required for all messages, and may be null for assistant messages with function calls.
    name:
      type: string
      description: The name of the author of this message. `name` is required if role is `function`, and it should be the name of the function whose response is in the `content`. May contain a-z, A-Z, 0-9, and underscores, with a maximum length of 64 characters.
  required:
    - role
    - content

... turns into:

%{
  description: "",
	kind: :component, # can be 'oneOf' or 'component'
  required_props: [
    %{
      name: "content",
      type: "string",
      description: "The contents of the message. `content` is required for all messages, and may be null for assistant messages with function calls.",
      example: ""
    },
    %{
      name: "role",
      type: {:enum, [:system, :user, :assistant, :function]},
      description: "The role of the messages author. One of `system`, `user`, `assistant`, or `function`.",
      example: ""
    }
  ],
  optional_props: [
    %{
      name: "name",
      type: "string",
      description: "The name of the author of this message. `name` is required if role is `function`, and it should be the name of the function whose response is in the `content`. May contain a-z, A-Z, 0-9, and underscores, with a maximum length of 64 characters.",
      example: ""
    }
  ]
}

Important point here: "type" is parsed into an elixir representation that we can work with later. For example string -> string, or enum: ["system", "user", "assistant", "function"] -> {:enum, [:system, :user, :assistant, :function]}

  1. Type gets constructed by calling parse_type from the property parsing. This is a Elixir function with different pattern matching, for example, enum looks like this:
  def parse_type(%{"type" => "string", "enum" => enum_entries}),
    do: {:enum, Enum.map(enum_entries, &String.to_atom/1)}
  1. The final type is converted into a Elixir typespec by calling type_to_spec:
  def type_to_spec({:enum, l}) when is_list(l) do
    Enum.reduce(l, &{:|, [], [&1, &2]})
  end

  def type_to_spec("number"), do: quote(do: float())
  def type_to_spec("integer"), do: quote(do: integer())
  def type_to_spec("boolean"), do: quote(do: boolean())
  1. All of this is put together in ex_openai.ex to generate the actual modules, the spec is then used to generate documentation.

License

The package is available as open source under the terms of the MIT License.

Attribution