Class: CompletionKit::Run

Inherits:
ApplicationRecord show all
Includes:
Turbo::Broadcastable
Defined in:
app/models/completion_kit/run.rb

Constant Summary collapse

STATUSES = 
%w[pending generating judging completed failed].freeze

Constants inherited from ApplicationRecord

ApplicationRecord::TenantScopedUniquenessValidator

Instance Method Summary collapse

Instance Method Details

#as_json(options = {}) ⇒ Object 



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# File 'app/models/completion_kit/run.rb', line 163

def as_json(options = {})
  {
    id: id, name: name, status: status, prompt_id: prompt_id,
    dataset_id: dataset_id, judge_model: judge_model, temperature: temperature,
    created_at: created_at, updated_at: updated_at,
    responses_count: responses.count, avg_score: avg_score,
    progress_current: progress_current, progress_total: progress_total,
    error_message: error_message, metric_ids: metric_ids
  }
end

#avg_score ⇒ Object 



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# File 'app/models/completion_kit/run.rb', line 32

def avg_score
  all_reviews = responses.flat_map(&:reviews)
  scores = all_reviews.map(&:ai_score).compact.map(&:to_f)
  return nil if scores.empty?

  (scores.sum / scores.length).round(2)
end

#generate_responses! ⇒ Object 



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# File 'app/models/completion_kit/run.rb', line 48

def generate_responses!
  rows = if dataset
           CsvProcessor.process_self(self)
         else
           [{}]
         end

  if rows.empty?
    errors.add(:base, "Dataset has no rows")
    return false
  end

  client = LlmClient.for_model(prompt.llm_model, ApiConfig.for_model(prompt.llm_model))

  unless client.configured?
    msg = "LLM API not configured: #{client.configuration_errors.join(', ')}"
    errors.add(:base, msg)
    update_columns(status: "failed", error_message: msg) if persisted?
    return false
  end

  update!(status: "generating", progress_current: 0, progress_total: rows.length, error_message: nil)
  responses.destroy_all
  broadcast_ui
  broadcast_clear_responses

  rows.each_with_index do |row, index|
    input = row.empty? ? nil : row.to_json
    rendered = CsvProcessor.apply_variables(prompt, row)
    response_text = client.generate_completion(rendered, model: prompt.llm_model, temperature: temperature)

    resp = responses.create!(
      input_data: input,
      response_text: response_text,
      expected_output: row["expected_output"]
    )

    update_columns(progress_current: index + 1)
    broadcast_progress
    broadcast_response(resp)
  end

  if judge_configured?
    judge_responses!
  else
    update!(status: "completed")
    broadcast_ui
  end

  true
rescue Faraday::Error => e
  update_columns(status: "failed", error_message: e.message)
  errors.add(:base, e.message)
  broadcast_ui
  false
rescue StandardError => e
  update_columns(status: "failed", error_message: e.message) if persisted?
  errors.add(:base, e.message)
  broadcast_ui if persisted?
  false
end

#judge_configured? ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'app/models/completion_kit/run.rb', line 20

def judge_configured?
  judge_model.present? && metrics.any? && ApiConfig.valid_for_model?(judge_model)
end

#judge_responses! ⇒ Object 



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# File 'app/models/completion_kit/run.rb', line 110

def judge_responses!
  total_evaluations = responses.count * metrics.count
  update!(status: "judging", progress_current: 0, progress_total: total_evaluations, error_message: nil)
  broadcast_ui

  judge = JudgeService.new(ApiConfig.for_model(judge_model).merge(judge_model: judge_model))
  evaluation_count = 0

  responses.find_each do |response|
    metrics.each do |metric|
      evaluation = judge.evaluate(
        response.response_text,
        response.expected_output,
        prompt.template,
        criteria: metric.instruction.to_s,
        rubric_text: metric.display_rubric_text,
        input_data: response.input_data
      )

      response.reviews.find_or_initialize_by(metric_id: metric.id).tap do |review|
        review.assign_attributes(
          metric_name: metric.name,
          instruction: metric.instruction.to_s,
          status: "evaluated",
          ai_score: evaluation[:score],
          ai_feedback: evaluation[:feedback]
        )
        review.save!
      end

      evaluation_count += 1
      update_columns(progress_current: evaluation_count)
      broadcast_progress
    end

    broadcast_response_update(response)
  end

  update!(status: "completed")
  broadcast_ui
  true
rescue Faraday::Error => e
  update_columns(status: "failed", error_message: e.message)
  errors.add(:base, e.message)
  broadcast_ui
  false
rescue StandardError => e
  update_columns(status: "failed", error_message: e.message) if persisted?
  errors.add(:base, e.message)
  broadcast_ui if persisted?
  false
end

#metric_averages ⇒ Object 



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# File 'app/models/completion_kit/run.rb', line 40

def metric_averages
  all_reviews = responses.flat_map(&:reviews).select { |r| r.ai_score.present? }
  all_reviews.group_by(&:metric_name).map do |name, reviews|
    scores = reviews.map { |r| r.ai_score.to_f }
    { name: name, avg: (scores.sum / scores.length).round(1) }
  end
end

#replace_metrics!(metric_ids) ⇒ Object 



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# File 'app/models/completion_kit/run.rb', line 24

def replace_metrics!(metric_ids)
  return unless metric_ids
  run_metrics.delete_all
  Array(metric_ids).reject(&:blank?).each_with_index do |metric_id, index|
    run_metrics.create!(metric_id: metric_id, position: index + 1)
  end
end