Ruby

In this guide, we will show how to send users’ interactions with an OpenAI model to Nebuly’s platform.

Before getting started, you would need two API keys:

Your OpenAI key
Nebuly authentication key

require 'net/http'
require 'uri'
require 'json'
require 'date'

OPENAI_API_KEY = "<OPENAI_API_KEY>"
NEBULY_API_KEY = "<NEBULY_API_KEY>"

system_prompt = "You are a helpful assistant"
messages = [
    { role: "system", content: system_prompt },
    { role: "user", content: "Who is the president of the United States of America?" },
]
time_start = Time.now.utc.to_datetime.iso8601

uri = URI.parse("https://api.openai.com/v1/chat/completions")
request = Net::HTTP::Post.new(uri)
request.content_type = "application/json"
request["Authorization"] = "Bearer #{OPENAI_API_KEY}"
request.body = JSON.dump({
  "model" => "gpt-3.5-turbo",
  "messages" => messages
})

req_options = {
  use_ssl: uri.scheme == "https",
}

response = Net::HTTP.start(uri.hostname, uri.port, req_options) do |http|
  http.request(request)
end

completion = JSON.parse(response.body)
output = completion['choices'].first['message']['content']
model = completion['model']

time_end = Time.now.utc.to_datetime.iso8601

uri = URI.parse("https://backend.nebuly.com/event-ingestion/api/v2/events/interactions")
request = Net::HTTP::Post.new(uri)
request.content_type = "application/json"
request["Authorization"] = "Bearer #{NEBULY_API_KEY}"
request.body = JSON.dump({
  "interaction" => {
    "messages" => messages,
    "output" => output,
    "time_start" => time_start,
    "time_end" => time_end,
    "end_user" => "<YOUR_USER_ID>",
    "model" => model,
    "tags" => {
      "version" => "v1.0.0"
    }
  },
  "anonymize" => true,
})

req_options = {
  use_ssl: uri.scheme == "https",
}

response = Net::HTTP.start(uri.hostname, uri.port, req_options) do |http|
  http.request(request)
end

puts JSON.parse(response.body)

Below you can find a detailed explanation of the parameters:

messages

array

required

A list of messages from the conversation so far, following the same format used by OpenAI Chat Completion endpoints.

Each message has two required fields:

role: the role of who is sending the message. Possible values are: system, user, assistant, tool.
content: the content of the message.

The messages in the list should be ordered according to the conversation’s sequence, from the oldest message to the most recent.

Example:

messages = [
  {
    "role" => "system",
    "content" => "This is a system prompt"
  },
  {
    "role" => "user",
    "content" => "What's the weather like in Turin?"
  },
  {
    "role" => "assistant",
    "content" => "The weather is currently rainy in Turin."
  },
  {
    "role" => "user",
    "content" => "What's the weather like in Rome?"
  }
]

output

string

required

Output from the LLM model

time_start

string

required

When the end-user request process started

time_end

string

required

When the end-user request process ended

end_user

string

required

An id or username uniquely identifying the end-user. We recommend hashing their username or email address, in order to avoid sending us any identifying information.

model

string

required

The LLM model you are using. Please note that this is needed if you want to visualize the cost of your requests. Now we support costs only for OpenAI models, cost of other providers coming soon.

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