A Ruby gem for interacting with Mistral AI's large language models.
This Gem is designed to provide low-level access to Mistral, enabling people to build abstractions on top of it. If you are interested in more high-level abstractions or more user-friendly tools, you may want to consider Nano Bots ๐ ๐ค.
gem 'mistral-ai', '~> 1.2.0'
require 'mistral-ai'
client = Mistral.new(
credentials: { api_key: ENV['MISTRAL_API_KEY'] },
options: { server_sent_events: true }
)
result = client.chat_completions(
{ model: 'mistral-medium',
messages: [{ role: 'user', content: 'hi!' }] }
)
Result:
{ 'id' => 'cmpl-74fb544d49d04195a4182342936af43b',
'object' => 'chat.completion',
'created' => 1_703_792_737,
'model' => 'mistral-medium',
'choices' =>
[{ 'index' => 0,
'message' =>
{ 'role' => 'assistant',
'content' =>
"Hello! How can I assist you today? If you have any questions or need help with something, feel free to ask. I'm here to help.\n" \
"\n" \
"If you're not sure where to start, you can ask me about a specific topic, such as a programming language, a scientific concept, or a current event. You can also ask me to tell you a joke, generate a random number, or provide a fun fact.\n" \
"\n" \
"I'm a large language model trained by Mistral AI, so I can understand and generate human-like text on a wide range of topics. I can also perform tasks such as summarizing text, translating between languages, and answering questions about a given text. I look forward to helping you!" },
'finish_reason' => 'stop' }],
'usage' => { 'prompt_tokens' => 10, 'total_tokens' => 166, 'completion_tokens' => 156 } }
- TL;DR and Quick Start
- Index
- Setup
- Usage
- Development
- Resources and References
- Disclaimer
gem install mistral-ai -v 1.2.0
gem 'mistral-ai', '~> 1.2.0'
You can obtain your API key from the Mistral AI Platform.
Ensure that you have an API Key for authentication.
Create a new client:
require 'mistral-ai'
client = Mistral.new(
credentials: { api_key: ENV['MISTRAL_API_KEY'] },
options: { server_sent_events: true }
)
You can use a custom address:
require 'mistral-ai'
client = Mistral.new(
credentials: {
address: 'https://api.mistral.ai',
api_key: ENV['MISTRAL_API_KEY']
},
options: { server_sent_events: true }
)
result = client.chat_completions(
{ model: 'mistral-medium',
messages: [{ role: 'user', content: 'hi!' }] }
)
Result:
{ 'id' => 'cmpl-74fb544d49d04195a4182342936af43b',
'object' => 'chat.completion',
'created' => 1_703_792_737,
'model' => 'mistral-medium',
'choices' =>
[{ 'index' => 0,
'message' =>
{ 'role' => 'assistant',
'content' =>
"Hello! How can I assist you today? If you have any questions or need help with something, feel free to ask. I'm here to help.\n" \
"\n" \
"If you're not sure where to start, you can ask me about a specific topic, such as a programming language, a scientific concept, or a current event. You can also ask me to tell you a joke, generate a random number, or provide a fun fact.\n" \
"\n" \
"I'm a large language model trained by Mistral AI, so I can understand and generate human-like text on a wide range of topics. I can also perform tasks such as summarizing text, translating between languages, and answering questions about a given text. I look forward to helping you!" },
'finish_reason' => 'stop' }],
'usage' => { 'prompt_tokens' => 10, 'total_tokens' => 166, 'completion_tokens' => 156 } }
Ensure that you have enabled Server-Sent Events before using blocks for streaming. You also need to add stream: true
in your payload:
client.chat_completions(
{ model: 'mistral-medium',
stream: true,
messages: [{ role: 'user', content: 'hi!' }] }
) do |event, parsed, raw|
puts event
end
Event:
{ 'id' => 'cmpl-011e6223d8414df4840293b98e0b18ca',
'object' => 'chat.completion.chunk',
'created' => 1_703_796_464,
'model' => 'mistral-medium',
'choices' => [
{ 'index' => 0, 'delta' => { 'role' => nil, 'content' => 'Hello' },
'finish_reason' => nil }
] }
You can get all the receive events at once as an array:
result = client.chat_completions(
{ model: 'mistral-medium',
stream: true,
messages: [{ role: 'user', content: 'hi!' }] }
)
Result:
[{ 'id' => 'cmpl-20bc384332d749958251e11427aeeb42',
'model' => 'mistral-medium',
'choices' => [{ 'index' => 0, 'delta' => { 'role' => 'assistant' }, 'finish_reason' => nil }] },
{ 'id' => 'cmpl-20bc384332d749958251e11427aeeb42',
'object' => 'chat.completion.chunk',
'created' => 1_703_796_630,
'model' => 'mistral-medium',
'choices' => [{ 'index' => 0, 'delta' => { 'role' => nil, 'content' => 'Hello! How can I' },
'finish_reason' => nil }] },
{ 'id' => 'cmpl-20bc384332d749958251e11427aeeb42',
'object' => 'chat.completion.chunk',
'created' => 1_703_796_630,
'model' => 'mistral-medium',
'choices' => [{ 'index' => 0, 'delta' => { 'role' => nil, 'content' => ' assist you today?' },
'finish_reason' => nil }] },
# ...
{ 'id' => 'cmpl-20bc384332d749958251e11427aeeb42',
'object' => 'chat.completion.chunk',
'created' => 1_703_796_630,
'model' => 'mistral-medium',
'choices' => [{ 'index' => 0, 'delta' => { 'role' => nil, 'content' => '' },
'finish_reason' => 'stop' }] }]
You can mix both as well:
result = client.chat_completions(
{ model: 'mistral-medium',
stream: true,
messages: [{ role: 'user', content: 'hi!' }] }
) do |event, parsed, raw|
puts event
end
result = client.embeddings(
{ model: 'mistral-embed',
input: [
'Embed this sentence.',
'As well as this one.'
] }
)
Result:
{ 'id' => 'embd-03f43eaec35744a3bab6f2ca83418555',
'object' => 'list',
'data' =>
[{ 'object' => 'embedding',
'embedding' =>
[-0.0165863037109375,
0.07012939453125,
# ...
0.00428009033203125,
-0.036895751953125],
'index' => 0 },
{ 'object' => 'embedding',
'embedding' =>
[-0.0234222412109375,
0.039337158203125,
# ...
0.00044846534729003906,
-0.01065826416015625],
'index' => 1 }],
'model' => 'mistral-embed',
'usage' => { 'prompt_tokens' => 15, 'total_tokens' => 15, 'completion_tokens' => 0 } }
result = client.models
Result:
{ 'object' => 'list',
'data' =>
[{ 'id' => 'mistral-medium',
'object' => 'model',
'created' => 1_703_855_983,
'owned_by' => 'mistralai',
'root' => nil,
'parent' => nil,
'permission' =>
[{ 'id' => 'modelperm-30...',
'object' => 'model_permission',
'created' => 1_703_855_983,
'allow_create_engine' => false,
'allow_sampling' => true,
'allow_logprobs' => false,
'allow_search_indices' => false,
'allow_view' => true,
'allow_fine_tuning' => false,
'organization' => '*',
'group' => nil,
'is_blocking' => false }] },
{ 'id' => 'mistral-small',
'object' => 'model',
'created' => 1_703_855_983,
'owned_by' => 'mistralai',
# ...
},
# ...
] }
Server-Sent Events (SSE) is a technology that allows certain endpoints to offer streaming capabilities, such as creating the impression that "the model is typing along with you," rather than delivering the entire answer all at once.
You can set up the client to use Server-Sent Events (SSE) for all supported endpoints:
client = Mistral.new(
credentials: { api_key: ENV['MISTRAL_API_KEY'] },
options: { server_sent_events: true }
)
Or, you can decide on a request basis:
client.chat_completions(
{ model: 'mistral-medium',
stream: true,
messages: [{ role: 'user', content: 'hi!' }] },
server_sent_events: true
) do |event, parsed, raw|
puts event
end
With Server-Sent Events (SSE) enabled, you can use a block to receive partial results via events. This feature is particularly useful for methods that offer streaming capabilities, such as chat_completions
: Receiving Stream Events
Method calls will hang until the server-sent events finish, so even without providing a block, you can obtain the final results of the received events: Receiving Stream Events
System messages influence how the model answers:
result = client.chat_completions(
{ model: 'mistral-medium',
messages: [
{ role: 'system', content: 'Only answer strictly using JSON.' },
{ role: 'user', content: 'Calculate 1 + 1.' }
] }
)
Result:
{ 'id' => 'cmpl-0c6fee44022841728e435ac91416d211',
'object' => 'chat.completion',
'created' => 1_703_794_201,
'model' => 'mistral-medium',
'choices' => [{
'index' => 0,
'message' => { 'role' => 'assistant', 'content' => '{"result": 2}' },
'finish_reason' => 'stop'
}],
'usage' => { 'prompt_tokens' => 24, 'total_tokens' => 30, 'completion_tokens' => 6 } }
To maintain a back-and-forth conversation, you need to append the received responses and build a history for your requests:
result = client.chat_completions(
{ model: 'mistral-medium',
messages: [
{ role: 'user',
content: 'Hi! My name is Purple.' },
{ role: 'assistant',
content: "Hello Purple! It's nice to meet you. How can I help you today?" },
{ role: 'user', content: "What's my name?" }
] }
)
Result:
{ 'id' => 'cmpl-cbc4a8db84b347738840e34e46388f1f',
'object' => 'chat.completion',
'created' => 1_703_793_492,
'model' => 'mistral-medium',
'choices' =>
[{ 'index' => 0,
'message' => {
'role' => 'assistant',
'content' => 'Your name is Purple, as you introduced yourself earlier. Is there anything else I can help you with?'
},
'finish_reason' => 'stop' }],
'usage' => { 'prompt_tokens' => 49, 'total_tokens' => 71, 'completion_tokens' => 22 } }
Mistral may launch a new endpoint that we haven't covered in the Gem yet. If that's the case, you may still be able to use it through the request
method. For example, chat_completions
is just a wrapper for v1/chat/completions
, which you can call directly like this:
result = client.request(
'v1/chat/completions',
{ model: 'mistral-medium',
messages: [{ role: 'user', content: 'hi!' }] },
request_method: 'POST', server_sent_events: true
)
The gem uses Faraday with the Typhoeus adapter by default.
You can use a different adapter if you want:
require 'faraday/net_http'
client = Mistral.new(
credentials: { api_key: ENV['MISTRAL_API_KEY'] },
options: { connection: { adapter: :net_http } }
)
You can set the maximum number of seconds to wait for the request to complete with the timeout
option:
client = Mistral.new(
credentials: { api_key: ENV['MISTRAL_API_KEY'] },
options: { connection: { request: { timeout: 5 } } }
)
You can also have more fine-grained control over Faraday's Request Options if you prefer:
client = Mistral.new(
credentials: { api_key: ENV['MISTRAL_API_KEY'] },
options: {
connection: {
request: {
timeout: 5,
open_timeout: 5,
read_timeout: 5,
write_timeout: 5
}
}
}
)
require 'mistral-ai'
begin
client.chat_completions(
{ model: 'mistral-medium',
messages: [{ role: 'user', content: 'hi!' }] }
)
rescue Mistral::Errors::MistralError => error
puts error.class # Mistral::Errors::RequestError
puts error.message # 'the server responded with status 500'
puts error.payload
# { model: 'mistral-medium',
# messages: [{ role: 'user', content: 'hi!' }] },
# ...
# }
puts error.request
# #<Faraday::ServerError response={:status=>500, :headers...
end
require 'mistral-ai/errors'
begin
client.chat_completions(
{ model: 'mistral-medium',
messages: [{ role: 'user', content: 'hi!' }] }
)
rescue MistralError => error
puts error.class # Mistral::Errors::RequestError
end
MistralError
MissingAPIKeyError
BlockWithoutServerSentEventsError
RequestError
bundle
rubocop -A
bundle exec ruby spec/tasks/run-client.rb
This Gem is designed to provide low-level access to Mistral, enabling people to build abstractions on top of it. If you are interested in more high-level abstractions or more user-friendly tools, you may want to consider Nano Bots ๐ ๐ค.
gem build mistral-ai.gemspec
gem signin
gem push mistral-ai-1.2.0.gem
Install Babashka:
curl -s https://github.com/raw/babashka/babashka/master/install | sudo bash
Update the template.md
file and then:
bb tasks/generate-readme.clj
Trick for automatically updating the README.md
when template.md
changes:
sudo pacman -S inotify-tools # Arch / Manjaro
sudo apt-get install inotify-tools # Debian / Ubuntu / Raspberry Pi OS
sudo dnf install inotify-tools # Fedora / CentOS / RHEL
while inotifywait -e modify template.md; do bb tasks/generate-readme.clj; done
Trick for Markdown Live Preview:
pip install -U markdown_live_preview
mlp README.md -p 8076
These resources and references may be useful throughout your learning process.
This is not an official Mistral project, nor is it affiliated with Mistral in any way.
This software is distributed under the MIT License. This license includes a disclaimer of warranty. Moreover, the authors assume no responsibility for any damage or costs that may result from using this project. Use the Mistral AI Ruby Gem at your own risk.