Cloudflare is testing its Workers AI API. Hopefully this project makes it easier for ruby-first developers to consume Cloudflare's latest and greatest.

I'm really interested in applying retrieval-augmented generation to make legal services more accessible. Email me.

If you're looking for legal help, it's best to book a slot via https://www.krishnan.ca.

It's still early days, and here are my immediate priorities:

• Support for streamed responses
• CI pipeline
• Support for more AI model categories
  • Text Generation
  • Text Embeddings
  • Text Classification
  • Image Classification
  • Translation
  • Text-to-Image
  • Automatic Speech Recognition

• Installation
• Usage
• Logging
• Development

Install the gem and add to the application's Gemfile by executing:

bundle add cloudflare-ai

If bundler is not being used to manage dependencies, install the gem by executing:

gem install cloudflare-ai

require "cloudflare/ai"

Please visit the Cloudflare Workers AI website for more details. Thiis gem provides a client that wraps around Cloudflare's REST API.

client = Cloudflare::AI::Client.new(account_id: ENV["CLOUDFLARE_ACCOUNT_ID"], api_token: ENV["CLOUDFLARE_API_TOKEN"])

The model name is an optional parameter to every one of the client methods described below. For example, if an example is documented as

result = client.complete(prompt: "Hello my name is")

this is implicitly the same as

result = client.complete(prompt: "Hello my name is", model: "@cf/meta/llama-2-7b-chat-fp16")

The full list of supported models is available here: models.rb. More information is available in the cloudflare documentation. The default model used is the first enumerated model in the applicable set in models.rb.

messages = [
  Cloudflare::AI::Message.new(role: "system", content: "You are a big fan of Cloudflare and Ruby."),
  Cloudflare::AI::Message.new(role: "user", content: "What is your favourite tech stack?"),
  Cloudflare::AI::Message.new(role: "assistant", content: "I love building with Ruby on Rails and Cloudflare!"),
  Cloudflare::AI::Message.new(role: "user", content: "Really? You like Cloudflare even though there isn't great support for Ruby?"),
]
result = client.chat(messages: messages)
puts result.response # => "Yes, I love Cloudflare!"

Responses will be streamed back to the client using Server Side Events (SSE) if a block is passed to the chat or complete method.

result = client.complete(prompt: "Hi!") { |data| puts data}
# {"response":" "}
# {"response":" Hello"}
# {"response":" there"}
# {"response":"!"}
# {"response":""}
# [DONE]

All invocations of the prompt and chat methods return a Cloudflare::AI::Results::TextGeneration object. This object's serializable JSON output is based on the raw response from the Cloudflare API.

result = client.complete(prompt: "What is your name?")

# Successful
puts result.response # => "My name is John."
puts result.success? # => true
puts result.failure? # => false
puts result.to_json # => {"result":{"response":"My name is John"},"success":true,"errors":[],"messages":[]}

# Unsuccessful
puts result.response # => nil
puts result.success? # => false
puts result.failure? # => true
puts result.to_json # => {"result":null,"success":false,"errors":[{"code":7009,"message":"Upstream service unavailable"}],"messages":[]}

result = client.embed(text: "Hello")
p result.shape # => [1, 768] # (1 embedding, 768 dimensions per embedding)
p result.embedding # => [[-0.008496830239892006, 0.001376907923258841, -0.0323275662958622, ...]]

The input can be either a string (as above) or an array of strings:

result = client.embed(text: ["Hello", "World"])

All invocations of the embed methods return a Cloudflare::AI::Results::TextEmbedding.

result = client.classify(text: "You meanie!")
p result.result # => [{"label"=>"NEGATIVE", "score"=>0.6647962927818298}, {"label"=>"POSITIVE", "score"=>0.3352036774158478}]

All invocations of the classify methods return a Cloudflare::AI::Results::TextClassification.

This gem uses standard logging mechanisms and defaults to :warn level. Most messages are at info level, but we will add debug or warn statements as needed. To show all log messages:

Cloudflare::AI.logger.level = :debug

You can use this logger as you would the default ruby logger. For example:

Cloudflare::AI.logger = Logger.new($stdout)

1. git clone https://github.com/ajaynomics/cloudflare-ai.git
2. bundle exec rake to ensure that the tests pass and to run standardrb

Bug reports and pull requests are welcome on GitHub at https://github.com/ajaynomics/cloudflare-ai.

The gem is available as open source under the terms of the MIT License. A special thanks to the team at langchainrb – I learnt a lot reading your codebase as I muddled my way through the initial effort.