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# frozen_string_literal: true
module LangchainrbRails
module Generators
#
# PineconeGenerator does the following:
# 1. Creates the `langchainrb_rails.rb` initializer file
# 2. Adds necessary code to the ActiveRecord model to enable vectorsearch
# 3. Adds `qdrant-ruby` gem to the Gemfile
#
# Usage:
# rails generate langchainrb_rails:qdrant --model=Product --llm=openai
#
class QdrantGenerator < LangchainrbRails::Generators::BaseGenerator
desc "This generator adds Qdrant vectorsearch integration to your ActiveRecord model"
source_root File.join(__dir__, "templates")
# Creates the `langchainrb_rails.rb` initializer file
def create_initializer_file
template "qdrant_initializer.rb", "config/initializers/langchainrb_rails.rb"
end
# Adds `vectorsearch` class method to the model and `after_save` callback that calls `upsert_to_vectorsearch()`
def add_to_model
inject_into_class "app/models/#{model_name.downcase}.rb", model_name do
" vectorsearch\n\n after_save :upsert_to_vectorsearch\n\n"
end
end
# Adds `qdrant-ruby` gem to the Gemfile
# TODO: Can we automatically run `bundle install`?
def add_to_gemfile
gem "qdrant-ruby"
end
private
# @return [String] Name of the model
def model_name
options["model"]
end
# @return [String] LLM provider to use
def llm
options["llm"]
end
# @return [Langchain::LLM::*] LLM class
def llm_class
Langchain::LLM.const_get(LLMS[llm])
end
end
end
end
Version data entries
6 entries across 6 versions & 1 rubygems