OmniAI::Mistral

An Mistral implementation of the OmniAI APIs.

Installation

gem install omniai-mistral

Usage

Client

A client is setup as follows if ENV['MISTRAL_API_KEY'] exists:

client = OmniAI::Mistral::Client.new

A client may also be passed the following options:

• api_key (required - default is ENV['MISTRAL_API_KEY'])
• host (optional)

Configuration

Global configuration is supported for the following options:

OmniAI::Mistral.configure do |config|
  config.api_key = 'sk-...' # default: ENV['MISTRAL_API_KEY']
  config.host = '...' # default: 'https://api.mistral.ai'
end

Chat

A chat completion is generated by passing in prompts using any a variety of formats:

completion = client.chat('Tell me a joke!')
completion.text # 'Why did the chicken cross the road? To get to the other side.'

completion = client.chat do |prompt|
  prompt.system('You are a helpful assistant.')
  prompt.user('What is the capital of Canada?')
end
completion.text # 'The capital of Canada is Ottawa.'

Model

model takes an optional string (default is mistral-medium-latest):

completion = client.chat('Provide code for fibonacci', model: OmniAI::Mistral::Chat::Model::CODESTRAL)
completion.text # 'def fibonacci(n)...end'

Mistral API Reference model

Temperature

temperature takes an optional float between 0.0 and 1.0 (defaults is 0.7):

completion = client.chat('Pick a number between 1 and 5', temperature: 1.0)
completion.text # '3'

Mistral API Reference temperature

Stream

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.text) # 'Better', 'three', 'hours', ...
end
client.chat('Be poetic.', stream:)

Mistral API Reference stream

Format

format takes an optional symbol (:json) and that sets 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.text) # { "name": "Ringo" }

Mistral API Reference response_format

When using JSON mode you MUST also instruct the model to produce JSON yourself with a system or a user message.

Embed

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, ...]