Extract run persistance logic into a concern

This commit introduces the AnalysisResultsRecordable concern to encapsulate
the logic for persisting analysis results into runs. This can be reused
by future aggregate models.

Author: davidgisbey

app/models/answer_analysis/answer_relevancy_aggregate.rb

@@ -1,22 +1,8 @@
 module AnswerAnalysis
   class AnswerRelevancyAggregate < ApplicationRecord
+    include AnalysisResultsRecordable
+
     belongs_to :answer
     has_many :runs, class_name: "AnswerAnalysis::AnswerRelevancyRun"
-
-    def create_run_from_result(result)
-      run = runs.build(
-        score: result.score,
-        reason: result.reason,
-      )
-
-      result.llm_responses.stringify_keys.each do |name, llm_response|
-        run.assign_llm_response(name, llm_response)
-      end
-      result.metrics.stringify_keys.each do |name, metrics|
-        run.assign_metrics(name, metrics)
-      end
-
-      run.save!
-    end
   end
 end

app/models/concerns/analysis_results_recordable.rb

@@ -0,0 +1,21 @@
+module AnalysisResultsRecordable
+  extend ActiveSupport::Concern
+
+  included do
+    def create_run_from_result(result)
+      run = runs.build(
+        score: result.score,
+        reason: result.reason,
+      )
+
+      result.llm_responses.stringify_keys.each do |name, llm_response|
+        run.assign_llm_response(name, llm_response)
+      end
+      result.metrics.stringify_keys.each do |name, metrics|
+        run.assign_metrics(name, metrics)
+      end
+
+      run.save!
+    end
+  end
+end

spec/models/answer_analysis/answer_relevancy_aggregate_spec.rb

@@ -1,40 +1,5 @@
 RSpec.describe AnswerAnalysis::AnswerRelevancyAggregate do
-  describe "#create_run_from_result" do
+  include_examples "analysis results recordable" do
     let(:aggregate) { create(:answer_relevancy_aggregate) }
-    let(:result) do
-      AutoEvaluation::AnswerRelevancy::Result.new(
-        score: 0.85,
-        reason: "The answer is relevant to the question.",
-        success: true,
-        llm_responses: {
-          "response_1" => { "content" => "LLM response content 1" },
-          "response_2" => { "content" => "LLM response content 2" },
-        },
-        metrics: {
-          "metric_1" => { "detail" => "Metric detail 1" },
-          "metric_2" => { "detail" => "Metric detail 2" },
-        },
-      )
-    end
-
-    it "creates a run with correct attributes and associations" do
-      expect {
-        aggregate.create_run_from_result(result)
-      }.to change { aggregate.runs.count }.by(1)
-
-      run = aggregate.runs.strict_loading(false).last
-      expect(run).to have_attributes(
-        score: 0.85,
-        reason: "The answer is relevant to the question.",
-        llm_responses: {
-          "response_1" => { "content" => "LLM response content 1" },
-          "response_2" => { "content" => "LLM response content 2" },
-        },
-        metrics: {
-          "metric_1" => { "detail" => "Metric detail 1" },
-          "metric_2" => { "detail" => "Metric detail 2" },
-        },
-      )
-    end
   end
 end

spec/support/analysis_results_recordable_examples.rb

@@ -0,0 +1,39 @@
+shared_examples "analysis results recordable" do
+  describe "#create_run_from_result" do
+    let(:result) do
+      AutoEvaluation::AnswerRelevancy::Result.new(
+        score: 0.85,
+        reason: "The answer is relevant to the question.",
+        success: true,
+        llm_responses: {
+          "response_1" => { "content" => "LLM response content 1" },
+          "response_2" => { "content" => "LLM response content 2" },
+        },
+        metrics: {
+          "metric_1" => { "detail" => "Metric detail 1" },
+          "metric_2" => { "detail" => "Metric detail 2" },
+        },
+      )
+    end
+
+    it "creates a run with correct attributes and associations" do
+      expect {
+        aggregate.create_run_from_result(result)
+      }.to change { aggregate.runs.count }.by(1)
+
+      run = aggregate.runs.strict_loading(false).last
+      expect(run).to have_attributes(
+        score: 0.85,
+        reason: "The answer is relevant to the question.",
+        llm_responses: {
+          "response_1" => { "content" => "LLM response content 1" },
+          "response_2" => { "content" => "LLM response content 2" },
+        },
+        metrics: {
+          "metric_1" => { "detail" => "Metric detail 1" },
+          "metric_2" => { "detail" => "Metric detail 2" },
+        },
+      )
+    end
+  end
+end