An OpenAI implementation of the OmniAI interface supporting ChatGPT, Whisper, Text-to-Voice, Voice-to-Text, and more. This library is community maintained.
gem install omniai-openai
A client is setup as follows if ENV['OPENAI_API_KEY'] exists:
client = OmniAI::OpenAI::Client.new
A client may also be passed the following options:
api_key (required - default is ENV['OPENAI_API_KEY'])api_prefix (optional) - used with a host when necessaryorganization (optional)project (optional)host (optional) useful for usage with Ollama, LocalAI or other OpenAI API compatible servicesGlobal configuration is supported for the following options:
OmniAI::OpenAI.configure do |config|
config.api_key = 'sk-...' # default: ENV['OPENAI_API_KEY']
config.organization = '...' # default: ENV['OPENAI_ORGANIZATION']
config.project = '...' # default: ENV['OPENAI_PROJECT']
config.host = '...' # default: 'https://api.openai.com' - override for usage with LocalAI / Ollama
end
LocalAI offers built in compatability with the OpenAI specification. To initialize a client that points to a Ollama change the host accordingly:
client = OmniAI::OpenAI::Client.new(host: 'http://localhost:8080', api_key: nil)
For details on installation or running LocalAI see the getting started tutorial.
Ollama offers built in compatability with the OpenAI specification. To initialize a client that points to a Ollama change the host accordingly:
client = OmniAI::OpenAI::Client.new(host: 'http://localhost:11434', api_key: nil)
For details on installation or running Ollama checkout the project README.
Other fee-based systems/services have adopted all or some of the OpenAI API. For example open_router.ai is a web-services that provides access to many models and providers using their own as well as an OpenAI API.
client = OmniAI::OpenAI::Client.new(
host: 'https://open_router.ai',
api_key: ENV['OPENROUTER_API_KEY'],
api_prefix: '/api')
A chat completion is generated by passing in a simple text prompt:
completion = client.chat('Tell me a joke!')
completion.content # 'Why did the chicken cross the road? To get to the other side.'
A chat completion may also be generated by using a prompt builder:
completion = client.chat do |prompt|
prompt.system('Your are an expert in geography.')
prompt.user('What is the capital of Canada?')
end
completion.content # 'The capital of Canada is Ottawa.'
model takes an optional string (default is gtp-4o):
completion = client.chat('How fast is a cheetah?', model: OmniAI::OpenAI::Chat::Model::GPT_3_5_TURBO)
completion.content # 'A cheetah can reach speeds over 100 km/h.'
temperature takes an optional float between 0.0 and 2.0 (defaults is 0.7):
completion = client.chat('Pick a number between 1 and 5', temperature: 2.0)
completion.content # '3'
OpenAI API Reference temperature
stream takes an optional a proc to stream responses in real-time chunks instead of waiting for a complete response:
stream = proc do |chunk|
print(chunk.content) # 'Better', 'three', 'hours', ...
end
client.chat('Be poetic.', stream:)
format takes an optional symbol (:json) and that setes the response_format to json_object:
completion = client.chat(format: :json) do |prompt|
prompt.system(OmniAI::Chat::JSON_PROMPT)
prompt.user('What is the name of the drummer for the Beatles?')
end
JSON.parse(completion.content) # { "name": "Ringo" }
OpenAI API Reference response_format
When using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message.
A transcription is generated by passing in a path to a file:
transcription = client.transcribe(file.path)
transcription.text # '...'
prompt is optional and can provide additional context for transcribing:
transcription = client.transcribe(file.path, prompt: '')
transcription.text # '...'
format is optional and supports json, text, srt or vtt:
transcription = client.transcribe(file.path, format: OmniAI::Transcribe::Format::TEXT)
transcription.text # '...'
OpenAI API Reference response_format
language is optional and may improve accuracy and latency:
transcription = client.transcribe(file.path, language: OmniAI::Transcribe::Language::SPANISH)
transcription.text
temperature is optional and must be between 0.0 (more deterministic) and 1.0 (less deterministic):
transcription = client.transcribe(file.path, temperature: 0.2)
transcription.text
OpenAI API Reference temperature
Speech can be generated by passing text with a block:
File.open('example.ogg', 'wb') do |file|
client.speak('How can a clam cram in a clean cream can?') do |chunk|
file << chunk
end
end
If a block is not provided then a tempfile is returned:
tempfile = client.speak('Can you can a can as a canner can can a can?')
tempfile.close
tempfile.unlink
voice is optional and must be one of the supported voices:
client.speak('She sells seashells by the seashore.', voice: OmniAI::OpenAI::Speak::Voice::SHIMMER)
model is optional and must be either tts-1 or tts-1-hd (default):
client.speak('I saw a kitten eating chicken in the kitchen.', format: OmniAI::OpenAI::Speak::Model::TTS_1)
speed is optional and must be between 0.25 and 0.40:
client.speak('How much wood would a woodchuck chuck if a woodchuck could chuck wood?', speed: 4.0)
format is optional and supports MP3 (default), OPUS, AAC, FLAC, WAV or PCM:
client.speak('A pessemistic pest exists amidst us.', format: OmniAI::OpenAI::Speak::Format::FLAC)
client.files.find(id: 'file_...')
client.files.all
file = client.files.build(io: File.open('demo.pdf', 'wb'))
file.save!
file = client.files.build(io: 'demo.pdf'))
file.save!
file = client.files.find(id: 'file_...')
File.open('...', 'wb') do |file|
file.content do |chunk|
file << chunk
end
end
client.files.destroy!('file_...')
client.assistants.find(id: 'asst_...')
client.assistants.all
assistant = client.assistants.build
assistant.name = 'Ringo'
assistant.model = OmniAI::OpenAI::Chat::Model::GPT_4
assistant.description = 'The drummer for the Beatles.'
assistant.save!
assistant = client.assistants.find(id: 'asst_...')
assistant.name = 'George'
assistant.model = OmniAI::OpenAI::Chat::Model::GPT_4
assistant.description = 'A guitarist for the Beatles.'
assistant.save!
client.assistants.destroy!('asst_...')
client.threads.find(id: 'thread_...')
thread = client.threads.build
thread.metadata = { user: 'Ringo' }
thread.save!
thread = client.threads.find(id: 'thread_...')
thread.metadata = { user: 'Ringo' }
thread.save!
client.threads.destroy!('thread_...')
thread = client.threads.find(id: 'thread_...')
message = thread.messages.find(id: 'msg_...')
message.save!
thread = client.threads.find(id: 'thread_...')
thread.messages.all
thread = client.threads.find(id: 'thread_...')
message = thread.messages.build(role: 'user', content: 'Hello?')
message.save!
thread = client.threads.find(id: 'thread_...')
message = thread.messages.build(role: 'user', content: 'Hello?')
message.save!
thread = client.threads.find(id: 'thread_...')
run = thread.runs.find(id: 'run_...')
run.save!
thread = client.threads.find(id: 'thread_...')
thread.runs.all
run = client.runs.find(id: 'thread_...')
run = thread.runs.build
run.metadata = { user: 'Ringo' }
run.save!
thread = client.threads.find(id: 'thread_...')
run = thread.messages.find(id: 'run_...')
run.metadata = { user: 'Ringo' }
run.save!
run.terminated? # false
run.poll!
run.terminated? # true
run.status # 'cancelled' / 'failed' / 'completed' / 'expired'
thread = client.threads.find(id: 'thread_...')
run = thread.runs.cancel!(id: 'run_...')
Text can be converted into a vector embedding for similarity comparison usage via:
response = client.embed('The quick brown fox jumps over a lazy dog.')
response.embedding # [0.0, ...]
FAQs
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We found that omniai-openai demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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