A Ruby gem for interacting with MariTalk from Maritaca AI.
This Gem is designed to provide low-level access to MariTalk, 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 💎 🤖.
gem 'maritaca-ai', '~> 1.2.0'require 'maritaca-ai'
client = Maritaca.new(
credentials: { api_key: ENV['MARITACA_API_KEY'] },
options: { server_sent_events: true }
)
result = client.chat_inference(
{ model: 'sabia-2-medium',
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
)Result:
{ 'answer' => ' Oi! Como posso ajudar você hoje?',
'usage' => {
'completion_tokens' => 15,
'prompt_tokens' => 3,
'total_tokens' => 18
},
'model' => 'sabia-2-medium' }- TL;DR and Quick Start
- Index
- Setup
- Usage
- Development
- Resources and References
- Disclaimer
gem install maritaca-ai -v 1.2.0gem 'maritaca-ai', '~> 1.2.0'You can obtain your API key at MariTalk.
Enclose credentials in single quotes when using environment variables to prevent issues with the $ character in the API key:
MARITACA_API_KEY='123...$a12...'Ensure that you have an API Key for authentication.
Create a new client:
require 'maritaca-ai'
client = Maritaca.new(
credentials: { api_key: ENV['MARITACA_API_KEY'] },
options: { server_sent_events: true }
)You can use a custom address:
require 'maritaca-ai'
client = Maritaca.new(
credentials: {
address: 'https://chat.maritaca.ai',
api_key: ENV['MARITACA_API_KEY']
}
)result = client.chat_inference(
{ model: 'sabia-2-medium',
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
)Result:
{ 'answer' => ' Oi! Como posso ajudar você hoje?',
'usage' => {
'completion_tokens' => 15,
'prompt_tokens' => 3,
'total_tokens' => 18
},
'model' => 'sabia-2-medium' }To maintain a back-and-forth conversation, you need to append the received responses and build a history for your requests:
result = client.chat_inference(
{ model: 'sabia-2-medium',
chat_mode: true,
messages: [
{ role: 'user', content: 'Oi, meu nome é Tamanduá.' },
{ role: 'assistant', content: 'Oi Tamanduá, como posso ajudá-lo hoje?' },
{ role: 'user', content: 'Qual é o meu nome?' }
] }
)Result:
{ 'answer' => ' Seu nome é Tamanduá. É um prazer conhecê-lo! Como posso ajudá-lo hoje?',
'usage' => {
'completion_tokens' => 35,
'prompt_tokens' => 39,
'total_tokens' => 74
},
'model' => 'sabia-2-medium' }You can prompt the model without using chat mode:
result = client.chat_inference(
{ model: 'sabia-2-medium',
chat_mode: false,
messages: "Minha terra tem palmeiras,\nOnde canta o Sabiá;\n",
stopping_tokens: ['.'] }
)Result:
{ 'answer' =>
"As aves, que aqui gorjeiam,\n" \
'Não gorjeiam como lá.',
'usage' => {
'completion_tokens' => 21,
'prompt_tokens' => 21,
'total_tokens' => 42
},
'model' => 'sabia-2-medium' }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_inference(
{ model: 'sabia-2-medium',
stream: true,
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
) do |event, parsed, raw|
puts event
endEvent:
{ 'text' => ' Oi! Com' }You can get all the receive events at once as an array:
result = client.chat_inference(
{ model: 'sabia-2-medium',
stream: true,
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
)Result:
[{ 'text' => ' Oi! Com' },
{ 'text' => 'o posso a' },
{ 'text' => 'judar você' },
{ 'text' => ' hoje?' },
{ 'completion_tokens' => 15,
'prompt_tokens' => 74,
'total_tokens' => 89,
'model' => 'sabia-2-medium' }]You can mix both as well:
result = client.chat_inference(
{ model: 'sabia-2-medium',
stream: true,
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
) do |event, parsed, raw|
puts event
endServer-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 = Maritaca.new(
credentials: { api_key: ENV['MARITACA_API_KEY'] },
options: { server_sent_events: true }
)Or, you can decide on a request basis:
client.chat_inference(
{ model: 'sabia-2-medium',
stream: true,
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] },
server_sent_events: true
) do |event, parsed, raw|
puts event
endWith 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_inference: 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
Maritaca 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_inference is just a wrapper for api/chat/inference, which you can call directly like this:
result = client.request(
'api/chat/inference',
{ model: 'sabia-2-medium',
chat_mode: true,
messages: [{ role: 'user', content: 'Oi!' }] },
request_method: 'POST'
)The gem uses Faraday with the Typhoeus adapter by default.
You can use a different adapter if you want:
require 'faraday/net_http'
client = Maritaca.new(
credentials: { api_key: ENV['MARITACA_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 = Maritaca.new(
credentials: { api_key: ENV['MARITACA_API_KEY'] },
options: { connection: { request: { timeout: 5 } } }
)You can also have more fine-grained control over Faraday's Request Options if you prefer:
client = Maritaca.new(
credentials: { api_key: ENV['MARITACA_API_KEY'] },
options: {
connection: {
request: {
timeout: 5,
open_timeout: 5,
read_timeout: 5,
write_timeout: 5
}
}
}
)require 'maritaca-ai'
begin
client.chat_inference(
{ model: 'sabia-2-medium',
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
)
rescue Maritaca::Errors::MaritacaError => error
puts error.class # Maritaca::Errors::RequestError
puts error.message # 'the server responded with status 500'
puts error.payload
# { model: 'sabia-2-medium',
# chat_mode: true,
# ...
# }
puts error.request
# #<Faraday::ServerError response={:status=>500, :headers...
endrequire 'maritaca-ai/errors'
begin
client.chat_inference(
{ model: 'sabia-2-medium',
chat_mode: true,
messages: [ { role: 'user', content: 'Oi!' } ] }
)
rescue MaritacaError => error
puts error.class # Maritaca::Errors::RequestError
endMaritacaError
MissingAPIKeyError
RequestErrorbundle
rubocop -A
bundle exec ruby spec/tasks/run-client.rbThis Gem is designed to provide low-level access to MariTalk, 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 💎 🤖.
gem build maritaca-ai.gemspec
gem signin
gem push maritaca-ai-1.2.0.gemInstall Babashka:
curl -s https://raw.githubusercontent.com/babashka/babashka/master/install | sudo bashUpdate the template.md file and then:
bb tasks/generate-readme.cljTrick 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; doneTrick for Markdown Live Preview:
pip install -U markdown_live_preview
mlp README.md -p 8076These resources and references may be useful throughout your learning process.
This is not an official Maritaca AI project, nor is it affiliated with Maritaca AI 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 Maritaca AI Ruby Gem at your own risk.