sure/app/models/vector_store/registry.rb

class VectorStore::Registry
  ADAPTERS = {
    openai: "VectorStore::Openai",
    pgvector: "VectorStore::Pgvector",
    qdrant: "VectorStore::Qdrant"
  }.freeze

  class << self
    # Returns the configured adapter instance.
    # Reads from VECTOR_STORE_PROVIDER env var, falling back to :openai
    # when OpenAI credentials are present.
    def adapter
      name = adapter_name
      return nil unless name

      build_adapter(name)
    end

    def configured?
      adapter.present?
    end

    def adapter_name
      explicit = ENV["VECTOR_STORE_PROVIDER"].presence
      return explicit.to_sym if explicit && ADAPTERS.key?(explicit.to_sym)

      # Default routing:
      #   - When the configured LLM provider is Anthropic (which has no hosted
      #     vector store), fall back to the local pgvector adapter. The
      #     Embeddable concern still pulls embeddings from EMBEDDING_URI_BASE /
      #     OPENAI_ACCESS_TOKEN — Anthropic users typically point this at
      #     Voyage AI, a local Ollama instance, or OpenAI embeddings.
      #   - Otherwise, use OpenAI when credentials are available.
      return :pgvector if Setting.llm_provider == "anthropic"
      :openai if openai_access_token.present?
    end

    private

      def build_adapter(name)
        klass = ADAPTERS[name]&.safe_constantize
        raise VectorStore::ConfigurationError, "Unknown vector store adapter: #{name}" unless klass

        case name
        when :openai   then build_openai
        when :pgvector then build_pgvector
        when :qdrant   then build_qdrant
        else raise VectorStore::ConfigurationError, "No builder defined for adapter: #{name}"
        end
      end

      def build_openai
        token = openai_access_token
        return nil unless token.present?

        VectorStore::Openai.new(
          access_token: token,
          uri_base: ENV["OPENAI_URI_BASE"].presence || Setting.openai_uri_base
        )
      end

      def build_pgvector
        VectorStore::Pgvector.new
      end

      def build_qdrant
        url  = ENV.fetch("QDRANT_URL", "http://localhost:6333")
        api_key = ENV["QDRANT_API_KEY"].presence

        VectorStore::Qdrant.new(url: url, api_key: api_key)
      end

      def openai_access_token
        ENV["OPENAI_ACCESS_TOKEN"].presence || Setting.openai_access_token
      end
  end
end