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chore: Add chatbot examples for OpenAI and AWS Bedrock (#2)
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‎examples/chatbot/README.md

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# LaunchDarkly sample Ruby AI application
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We've built a simple console application that demonstrates how LaunchDarkly's Ruby AI SDK works.
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Below, you'll find the build procedure. For more comprehensive instructions, you can visit your [Quickstart page](https://docs.launchdarkly.com/home/ai-configs/quickstart) or the [Ruby reference guide](https://docs.launchdarkly.com/sdk/ai/ruby).
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This demo requires Ruby 3.0 or higher.
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## Build Instructions
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This repository includes examples for `OpenAI` and `Bedrock`. Depending on your preferred provider, you may have to take some additional steps.
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### General setup
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1. Install the required dependencies with `bundle install` in the appropriate example directory.
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1. Set the environment variable `LAUNCHDARKLY_SDK_KEY` to your LaunchDarkly SDK key. If there is an existing an AI Config in your LaunchDarkly project that you want to evaluate, set `LAUNCHDARKLY_AI_CONFIG_KEY` to the flag key; otherwise, an AI Config of `sample-ai-config` will be assumed.
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```bash
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export LAUNCHDARKLY_SDK_KEY="1234567890abcdef"
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export LAUNCHDARKLY_AI_CONFIG_KEY="sample-ai-config"
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```
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1. Replace `my-default-model` with your preferred model if the application cannot connect to LaunchDarkly Services.
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### OpenAI setup
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1. Set the environment variable `OPENAI_API_KEY` to your OpenAI key.
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```bash
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export OPENAI_API_KEY="0987654321fedcba"
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```
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1. Run the program `bundle exec ruby hello_openai.rb`
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### Bedrock setup
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1. Ensure the required AWS credentials can be [auto-detected by the AWS client][aws-configuration]. In the provided example we use the following environment variables.
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```bash
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export AWS_ACCESS_KEY_ID="0987654321fedcba"
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export AWS_SECRET_ACCESS_KEY="0987654321fedcba"
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```
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1. Run the program `bundle exec ruby hello_bedrock.rb`
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[aws-configuration]: https://docs.aws.amazon.com/sdk-for-ruby/v3/developer-guide/configuring.html#precedence-settings

‎examples/chatbot/aws-bedrock/Gemfile

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# frozen_string_literal: true
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source 'https://rubygems.org'
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ruby '>= 3.0.0'
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gem 'aws-sdk-bedrockruntime', '~> 1.0'
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gem 'launchdarkly-server-sdk-ai', path: '../../..'

‎examples/chatbot/aws-bedrock/hello_bedrock.rb

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# frozen_string_literal: true
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require 'aws-sdk-bedrockruntime'
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require 'launchdarkly-server-sdk'
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require 'launchdarkly-server-sdk-ai'
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# Set sdk_key to your LaunchDarkly SDK key.
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sdk_key = ENV['LAUNCHDARKLY_SDK_KEY']
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# Set config_key to the AI Config key you want to evaluate.
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ai_config_key = ENV['LAUNCHDARKLY_AI_CONFIG_KEY'] || 'sample-ai-config'
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# Set aws_access_key_id and aws_secret_access_key for AWS credentials.
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aws_access_key_id = ENV['AWS_ACCESS_KEY_ID']
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aws_secret_access_key = ENV['AWS_SECRET_ACCESS_KEY']
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region = ENV['AWS_REGION'] || 'us-east-1'
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if sdk_key.nil? || sdk_key.empty?
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puts '*** Please set the LAUNCHDARKLY_SDK_KEY env first'
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exit 1
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end
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if aws_access_key_id.nil? || aws_access_key_id.empty?
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puts '*** Please set the AWS_ACCESS_KEY_ID env variable first'
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exit 1
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end
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if aws_secret_access_key.nil? || aws_secret_access_key.empty?
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puts '*** Please set the AWS_SECRET_ACCESS_KEY env variable first'
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exit 1
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end
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#
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# Chatbot class that interacts with LaunchDarkly AI and AWS Bedrock
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#
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class BedrockChatbot
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attr_reader :aiclient, :ai_config_key, :bedrock_client
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DEFAULT_VALUE = LaunchDarkly::Server::AI::AIConfig.new(
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enabled: true,
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model: LaunchDarkly::Server::AI::ModelConfig.new(name: 'my-default-model'),
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messages: [
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LaunchDarkly::Server::AI::Message.new('system',
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'You are a default unhelpful assistant with the persona of HAL 9000 talking with {{ldctx.name}}'),
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LaunchDarkly::Server::AI::Message.new('user', '{{user_question}}'),
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]
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)
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def initialize(aiclient, ai_config_key, bedrock_client, context)
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@aiclient = aiclient
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@ai_config_key = ai_config_key
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@bedrock_client = bedrock_client
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@context = context
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end
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def ask_agent(question)
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ai_config = aiclient.config(
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@ai_config_key,
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@context,
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DEFAULT_VALUE,
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{ user_question: question }
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)
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begin
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response = ai_config.tracker.track_bedrock_converse_metrics do
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@bedrock_client.converse(
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map_converse_arguments(
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ai_config.model.name,
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ai_config.messages
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)
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)
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end
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[response.output.message.content[0].text, ai_config.tracker]
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rescue StandardError => e
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["An error occured: #{e.message}", nil]
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end
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end
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def agent_was_helpful(tracker, helpful)
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kind = helpful ? :positive : :negative
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tracker.track_feedback(kind: kind)
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end
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def map_converse_arguments(model_id, messages)
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args = {
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model_id: model_id,
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}
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mapped_messages = []
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user_messages = messages.select { |msg| msg.role == 'user' }
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mapped_messages << { role: 'user', content: user_messages.map { |msg| { text: msg.content } } } unless user_messages.empty?
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assistant_messages = messages.select { |msg| msg.role == 'assistant' }
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mapped_messages << { role: 'assistant', content: assistant_messages.map { |msg| { text: msg.content } } } unless assistant_messages.empty?
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args[:messages] = mapped_messages unless mapped_messages.empty?
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system_messages = messages.select { |msg| msg.role == 'system' }
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args[:system] = system_messages.map { |msg| { text: msg.content } } unless system_messages.empty?
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args
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end
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end
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# Initialize the LaunchDarkly client
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ld_client = LaunchDarkly::LDClient.new(sdk_key)
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ai_client = LaunchDarkly::Server::AI::Client.new(ld_client)
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unless ld_client.initialized?
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puts '*** SDK failed to initialize!'
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exit 1
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end
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# Create the LDContext
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context = LaunchDarkly::LDContext.create({
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key: 'user-key',
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kind: 'user',
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name: 'Lucy',
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})
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bedrock_client = Aws::BedrockRuntime::Client.new(
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aws_access_key_id: aws_access_key_id,
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aws_secret_access_key: aws_secret_access_key,
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region: region
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)
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chatbot = BedrockChatbot.new(ai_client, ai_config_key, bedrock_client, context)
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loop do
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print "Ask a question: (or type 'exit'): "
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question = gets&.chomp
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break if question.nil? || question.strip.downcase == 'exit'
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response, tracker = chatbot.ask_agent(question)
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puts "AI Response: #{response}"
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next if tracker.nil? # If tracker is nil, skip feedback collection
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print "Was the response helpful? [yes/no] (or type 'exit'): "
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feedback = gets&.chomp
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break if feedback.nil? || feedback.strip.downcase == 'exit'
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chatbot.agent_was_helpful(tracker, feedback == 'yes')
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end
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ld_client.close

‎examples/hello-bedrock/Gemfile renamed to ‎examples/chatbot/openai/Gemfile

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source 'https://rubygems.org'
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gem 'aws-sdk-bedrockruntime'
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ruby '>= 3.0.0'
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gem 'launchdarkly-server-sdk-ai', path: '../../..'
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gem 'openai', '~> 0.7.0'

‎examples/chatbot/openai/hello_openai.rb

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# frozen_string_literal: true
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require 'launchdarkly-server-sdk'
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require 'launchdarkly-server-sdk-ai'
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require 'openai'
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# Set sdk_key to your LaunchDarkly SDK key.
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sdk_key = ENV['LAUNCHDARKLY_SDK_KEY']
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# Set config_key to the AI Config key you want to evaluate.
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ai_config_key = ENV['LAUNCHDARKLY_AI_CONFIG_KEY'] || 'sample-ai-config'
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# Set openai_api_key to your OpenAI API key.
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openai_api_key = ENV['OPENAI_API_KEY']
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if sdk_key.nil? || sdk_key.empty?
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puts '*** Please set the LAUNCHDARKLY_SDK_KEY env first'
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exit 1
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end
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if openai_api_key.nil? || openai_api_key.empty?
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puts '*** Please set the OPENAI_API_KEY env first'
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exit 1
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end
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#
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# Chatbot class that interacts with LaunchDarkly AI and OpenAI
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#
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class Chatbot
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attr_reader :aiclient, :ai_config_key, :openai_client, :context
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DEFAULT_VALUE = LaunchDarkly::Server::AI::AIConfig.new(
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enabled: true,
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model: LaunchDarkly::Server::AI::ModelConfig.new(name: 'my-default-model'),
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messages: [
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LaunchDarkly::Server::AI::Message.new('system',
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'You are a default unhelpful assistant with the persona of HAL 9000 talking with {{ldctx.name}}'),
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LaunchDarkly::Server::AI::Message.new('user', '{{user_question}}'),
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]
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)
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def initialize(aiclient, ai_config_key, openai_client, context)
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@aiclient = aiclient
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@ai_config_key = ai_config_key
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@openai_client = openai_client
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@context = context
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end
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def ask_agent(question)
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ai_config = aiclient.config(
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@ai_config_key,
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@context,
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DEFAULT_VALUE,
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{ user_question: question }
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)
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begin
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completion = ai_config.tracker.track_openai_metrics do
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@openai_client.chat.completions.create(
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model: ai_config.model.name,
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messages: ai_config.messages.map(&:to_h)
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)
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end
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[completion[:choices][0][:message][:content], ai_config.tracker]
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rescue StandardError => e
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["An error occurred: #{e.message}", nil]
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end
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end
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def agent_was_helpful(tracker, helpful)
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kind = helpful ? :positive : :negative
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tracker.track_feedback(kind: kind)
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end
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end
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ld_client = LaunchDarkly::LDClient.new(sdk_key)
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ai_client = LaunchDarkly::Server::AI::Client.new(ld_client)
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unless ld_client.initialized?
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puts '*** SDK failed to initialize!'
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exit 1
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end
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puts '*** SDK successfully initialized'
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# Create the LDContext
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context = LaunchDarkly::LDContext.create({
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key: 'user-key',
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kind: 'user',
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name: 'Lucy',
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})
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chatbot = Chatbot.new(ai_client, ai_config_key, OpenAI::Client.new(api_key: openai_api_key), context)
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loop do
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print "Ask a question (or type 'exit'): "
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input = gets&.chomp
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break if input.nil? || input.strip.downcase == 'exit'
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response, tracker = chatbot.ask_agent(input)
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puts "AI Response: #{response}"
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next if tracker.nil? # If tracker is nil, skip feedback collection
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print "Was the response helpful? [yes/no] (or type 'exit'): "
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feedback = gets&.chomp
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break if feedback.nil? || feedback.strip.downcase == 'exit'
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helpful = feedback.strip.downcase == 'yes'
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chatbot.agent_was_helpful(tracker, helpful)
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end
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ld_client.close

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