DEV: Add spec

Author: keegangeorge

spec/fabricators/llm_model_fabricator.rb

@@ -8,6 +8,9 @@
   api_key "123"
   url "https://api.openai.com/v1/chat/completions"
   max_prompt_tokens 131_072
+  input_cost 10
+  cached_input_cost 2.5
+  output_cost 40
 end
 
 Fabricator(:anthropic_model, from: :llm_model) do

spec/requests/admin/ai_usage_controller_spec.rb

@@ -5,6 +5,7 @@
 RSpec.describe DiscourseAi::Admin::AiUsageController do
   fab!(:admin)
   fab!(:user)
+  fab!(:llm_model)
   let(:usage_report_path) { "/admin/plugins/discourse-ai/ai-usage-report.json" }
 
   before { SiteSetting.discourse_ai_enabled = true }
@@ -35,6 +36,18 @@
         )
       end
 
+      fab!(:log3) do
+        AiApiAuditLog.create!(
+          provider_id: 1,
+          feature_name: "ai_helper",
+          language_model: llm_model.name,
+          request_tokens: 300,
+          response_tokens: 150,
+          cached_tokens: 50,
+          created_at: 3.days.ago,
+        )
+      end
+
       it "returns correct data structure" do
         get usage_report_path
 
@@ -55,7 +68,7 @@
             }
 
         json = response.parsed_body
-        expect(json["summary"]["total_tokens"]).to eq(450) # sum of all tokens
+        expect(json["summary"]["total_tokens"]).to eq(900) # sum of all tokens
       end
 
       it "filters by feature" do
@@ -79,6 +92,26 @@
         expect(models.first["total_tokens"]).to eq(300)
       end
 
+      it "shows an estimated cost" do
+        get usage_report_path, params: { model: llm_model.name }
+
+        json = response.parsed_body
+        summary = json["summary"]
+        feature = json["features"].find { |f| f["feature_name"] == "ai_helper" }
+
+        expected_input_spending = llm_model.input_cost * log3.request_tokens / 1_000_000.0
+        expected_cached_input_spending =
+          llm_model.cached_input_cost * log3.cached_tokens / 1_000_000.0
+        expected_output_spending = llm_model.output_cost * log3.response_tokens / 1_000_000.0
+        expected_total_spending =
+          expected_input_spending + expected_cached_input_spending + expected_output_spending
+
+        expect(feature["input_spending"]).to eq(expected_input_spending.to_s)
+        expect(feature["output_spending"]).to eq(expected_output_spending.to_s)
+        expect(feature["cached_input_spending"]).to eq(expected_cached_input_spending.to_s)
+        expect(summary["total_spending"]).to eq(expected_total_spending.round(2))
+      end
+
       it "handles different period groupings" do
         get usage_report_path, params: { period: "hour" }
         expect(response.status).to eq(200)