Module: LangsmithrbRails::Wrappers::OpenAI

Defined in:
lib/langsmithrb_rails/wrappers/openai.rb

Overview

Wrapper for OpenAI client

Class Method Summary collapse

Class Method Details

.wrap(client, project_name: nil, tags: []) ⇒ Object

Wrap an OpenAI client with LangSmith tracing

Parameters:

  • client (Object) —

    The OpenAI client to wrap

  • project_name (String) (defaults to: nil) —

    Optional project name for traces

  • tags (Array<String>) (defaults to: []) —

    Optional tags for traces

Returns:

  • (Object) —

    The wrapped client



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# File 'lib/langsmithrb_rails/wrappers/openai.rb', line 14

def self.wrap(client, project_name: nil, tags: [])
  # Create a wrapper class that inherits from the client's class
  wrapper_class = Class.new(client.class) do
    attr_reader :original_client, :project_name, :tags

    def initialize(original_client, project_name, tags)
      @original_client = original_client
      @project_name = project_name
      @tags = tags
    end

    # Wrap chat completions
    def chat(messages:, model: nil, temperature: nil, max_tokens: nil, **params)
      # Prepare inputs for tracing
      inputs = {
        messages: messages,
        model: model,
        temperature: temperature,
        max_tokens: max_tokens
      }.merge(params).compact

      # Create a run
      run_id = nil
      begin
        run = LangsmithrbRails::Wrappers::Base.create_run(
          "openai.chat",
          inputs,
          run_type: "llm",
          project_name: project_name,
          tags: tags
        )
        run_id = run&.dig("id")
      rescue => e
        LangsmithrbRails.logger.error("Failed to create LangSmith run: #{e.message}")
      end

      # Call the original method
      begin
        result = original_client.chat(
          messages: messages,
          model: model,
          temperature: temperature,
          max_tokens: max_tokens,
          **params
        )

        # Update the run with the result
        if run_id
          outputs = { response: result }
          LangsmithrbRails::Wrappers::Base.update_run(run_id, outputs)
        end

        result
      rescue => e
        # Update the run with the error
        if run_id
          LangsmithrbRails::Wrappers::Base.update_run(run_id, {}, error: e.message)
        end
        raise e
      end
    end

    # Wrap completions
    def completions(prompt:, model: nil, temperature: nil, max_tokens: nil, **params)
      # Prepare inputs for tracing
      inputs = {
        prompt: prompt,
        model: model,
        temperature: temperature,
        max_tokens: max_tokens
      }.merge(params).compact

      # Create a run
      run_id = nil
      begin
        run = LangsmithrbRails::Wrappers::Base.create_run(
          "openai.completions",
          inputs,
          run_type: "llm",
          project_name: project_name,
          tags: tags
        )
        run_id = run&.dig("id")
      rescue => e
        LangsmithrbRails.logger.error("Failed to create LangSmith run: #{e.message}")
      end

      # Call the original method
      begin
        result = original_client.completions(
          prompt: prompt,
          model: model,
          temperature: temperature,
          max_tokens: max_tokens,
          **params
        )

        # Update the run with the result
        if run_id
          outputs = { response: result }
          LangsmithrbRails::Wrappers::Base.update_run(run_id, outputs)
        end

        result
      rescue => e
        # Update the run with the error
        if run_id
          LangsmithrbRails::Wrappers::Base.update_run(run_id, {}, error: e.message)
        end
        raise e
      end
    end

    # Wrap embeddings
    def embeddings(input:, model: nil, **params)
      # Prepare inputs for tracing
      inputs = {
        input: input,
        model: model
      }.merge(params).compact

      # Create a run
      run_id = nil
      begin
        run = LangsmithrbRails::Wrappers::Base.create_run(
          "openai.embeddings",
          inputs,
          run_type: "embedding",
          project_name: project_name,
          tags: tags
        )
        run_id = run&.dig("id")
      rescue => e
        LangsmithrbRails.logger.error("Failed to create LangSmith run: #{e.message}")
      end

      # Call the original method
      begin
        result = original_client.embeddings(
          input: input,
          model: model,
          **params
        )

        # Update the run with the result
        if run_id
          outputs = { response: result }
          LangsmithrbRails::Wrappers::Base.update_run(run_id, outputs)
        end

        result
      rescue => e
        # Update the run with the error
        if run_id
          LangsmithrbRails::Wrappers::Base.update_run(run_id, {}, error: e.message)
        end
        raise e
      end
    end

    # Forward other methods to the original client
    def method_missing(method_name, *args, **kwargs, &block)
      if original_client.respond_to?(method_name)
        original_client.send(method_name, *args, **kwargs, &block)
      else
        super
      end
    end

    def respond_to_missing?(method_name, include_private = false)
      original_client.respond_to?(method_name, include_private) || super
    end
  end

  # Create and return an instance of the wrapper class
  wrapper_class.new(client, project_name, tags)
end