OmniAI

OmniAI is a flexible AI library that standardizes the APIs of many different AIs:

• OmniAI::Anthropic
• OmniAI::Google
• OmniAI::Mistral
• OmniAI::OpenAI

All libraries are community maintained.

Installation

gem install omniai

gem install omniai-anthropic
gem install omniai-mistral
gem install omniai-google
gem install omniai-openai

Usage

OmniAI implements APIs for a number of popular clients by default. A client can be initialized using the specific gem (e.g. omniai-openai for OmniAI::OpenAI). Vendor specific docs can be found within each repo.

Client

OmniAI::Anthropic

require 'omniai/anthropic'

client = OmniAI::Anthropic::Client.new

OmniAI::Google

require 'omniai/google'

client = OmniAI::Google::Client.new

OmniAI::Mistral

require 'omniai/mistral'

client = OmniAI::Mistral::Client.new

OmniAI::OpenAI

require 'omniai/openai'

client = OmniAI::OpenAI::Client.new

Usage with LocalAI

LocalAI support is offered through OmniAI::OpenAI:

Usage with LocalAI

Usage with Ollama

Ollama support is offered through OmniAI::OpenAI:

Usage with Ollama

Logging

Logging the request / response is configurable by passing a logger into any client:

require 'omniai/openai'
require 'logger'

logger = Logger.new(STDOUT)
client = OmniAI::Example::Client.new(logger:)

[INFO]: POST https://...
[INFO]: 200 OK
...

Timeouts

Timeouts are configurable by passing a timeout an integer duration for the request / response of any APIs using:

require 'omniai/openai'
require 'logger'

logger = Logger.new(STDOUT)
client = OmniAI::OpenAI::Client.new(timeout: 8) # i.e. 8 seconds

Timeouts are also be configurable by passing a timeout hash with timeout / read / write / `keys using:

require 'omniai/openai'
require 'logger'

logger = Logger.new(STDOUT)
client = OmniAI::OpenAI::Client.new(timeout: {
  read: 2, # i.e. 2 seconds
  write: 3, # i.e. 3 seconds
  connect: 4, # i.e. 4 seconds
})

Chat

Clients that support chat (e.g. Anthropic w/ "Claude", Google w/ "Gemini", Mistral w/ "LeChat", OpenAI w/ "ChatGPT", etc) generate completions using the following calls:

Completions using a Simple Prompt

Generating a completion is as simple as sending in the text:

completion = client.chat('Tell me a joke.')
completion.text # 'Why don't scientists trust atoms? They make up everything!'

Completions using a Complex Prompt

More complex completions are generated using a block w/ various system / user messages:

completion = client.chat do |prompt|
  prompt.system 'You are a helpful assistant with an expertise in animals.'
  prompt.user do |message|
    message.text 'What animals are in the attached photos?'
    message.url('https://.../cat.jpeg', "image/jpeg")
    message.url('https://.../dog.jpeg', "image/jpeg")
    message.file('./hamster.jpeg', "image/jpeg")
  end
end
completion.text  # 'They are photos of a cat, a cat, and a hamster.'

Completions using Streaming via Proc

A real-time stream of messages can be generated by passing in a proc:

stream = proc do |chunk|
  print(chunk.text) # '...'
end
client.chat('Tell me a joke.', stream:)

Completion using Streaming via IO

The above code can also be supplied any IO (e.g. File, $stdout, $stdin, etc):

client.chat('Tell me a story', stream: $stdout)

Completion with Tools

A chat can also be initialized with tools:

tool = OmniAI::Tool.new(
  proc { |location:, unit: 'celsius'| "#{rand(20..50)}° #{unit} in #{location}" },
  name: 'Weather',
  description: 'Lookup the weather in a location',
  parameters: OmniAI::Tool::Parameters.new(
    properties: {
      location: OmniAI::Tool::Property.string(description: 'e.g. Toronto'),
      unit: OmniAI::Tool::Property.string(enum: %w[celcius fahrenheit]),
    },
    required: %i[location]
  )
)
client.chat('What is the weather in "London" in celcius and "Paris" in fahrenheit?', tools: [tool])

Transcribe

Clients that support transcribe (e.g. OpenAI w/ "Whisper") convert recordings to text via the following calls:

Transcriptions with Path

transcription = client.transcribe("example.ogg")
transcription.text # '...'

Transcriptions with Files

File.open("example.ogg", "rb") do |file|
  transcription = client.transcribe(file)
  transcription.text # '...'
end

Speak

Clients that support speak (e.g. OpenAI w/ "Whisper") convert text to recordings via the following calls:

Speech with Stream

File.open('example.ogg', 'wb') do |file|
  client.speak('The quick brown fox jumps over a lazy dog.', voice: 'HAL') do |chunk|
    file << chunk
  end
end

Speech with File

tempfile = client.speak('The quick brown fox jumps over a lazy dog.', voice: 'HAL')
tempfile.close
tempfile.unlink

Embeddings

Clients that support generating embeddings (e.g. OpenAI, Mistral, etc.) convert text to embeddings via the following:

response = client.embed('The quick brown fox jumps over a lazy dog')
response.usage # <OmniAI::Embed::Usage prompt_tokens=5 total_tokens=5>
response.embedding # [0.1, 0.2, ...] >

Batches of text can also be converted to embeddings via the following:

response = client.embed([
  '',
  '',
])
response.usage # <OmniAI::Embed::Usage prompt_tokens=5 total_tokens=5>
response.embeddings.each do |embedding|
  embedding # [0.1, 0.2, ...]
end

CLI

OmniAI packages a basic command line interface (CLI) to allow for exploration of various APIs. A detailed CLI documentation can be found via help:

omniai --help

Chat

w/ a Prompt

omniai chat "What is the coldest place on earth?"

The coldest place on earth is Antarctica.

w/o a Prompt

omniai chat --provider="openai" --model="gpt-4" --temperature="0.5"

Type 'exit' or 'quit' to abort.
# What is the warmet place on earth?

The warmest place on earth is Africa.

Embed

w/ input

omniai embed "The quick brown fox jumps over a lazy dog."

0.0
...

w/o input

omniai embed --provider="openai" --model="text-embedding-ada-002"

Type 'exit' or 'quit' to abort.
# Whe quick brown fox jumps over a lazy dog.

0.0
...