Token Calculator

studies/202512_GenesysCX/ctm-token-calculator/tests/test_meters.py

@@ -10,10 +10,26 @@ from tokencalc.meters import Confidence, MeterType, TokenMeter, TokenPricing
 
 def test_all_spec_meters_present():
     expected = {
-        "Voice Bot", "Virtual Agent (legacy)", "Agentic Virtual Agent",
-        "AI Summary & Insights", "Direct Messaging", "Social Listening",
-        "Social Responses", "Speech & Text Analytics", "Agent Copilot",
-        "Email AI (Auto-Suggest)", "Email AI (Auto-Respond)", "AI Translate",
+        # Voice / Bot
+        "Voice Bot", "Digital Bot",
+        # Virtual Agent
+        "Virtual Agent (legacy)", "Agentic Virtual Agent",
+        # Agent Copilot (named + concurrent)
+        "Agent Copilot [named]", "Agent Copilot [concurrent]",
+        # AI Quality / Analytics
+        "AI Scoring", "AI Summary & Insights",
+        # Speech & Text Analytics (named + concurrent)
+        "Speech & Text Analytics [named]", "Speech & Text Analytics [concurrent]",
+        # Routing
+        "Predictive Routing",
+        # Messaging
+        "Direct Messaging", "Social Listening", "Social Responses",
+        # Language
+        "AI Translate",
+        # Genesys Cloud Copilot
+        "Genesys Cloud Copilot",
+        # Email AI (rates TBD)
+        "Email AI (Auto-Suggest)", "Email AI (Auto-Respond)",
     }
     assert expected == set(DEFAULT_METERS)
 
@@ -22,17 +38,29 @@ def test_confirmed_rates():
     m = DEFAULT_METERS
     assert m["Voice Bot"].units_per_token == 17
     assert m["Voice Bot"].tokens_per_unit == pytest.approx(0.0588, abs=1e-3)
+    assert m["Digital Bot"].units_per_token == 51
     assert m["Agentic Virtual Agent"].tokens_per_unit == 1.2
     assert m["AI Summary & Insights"].tokens_per_unit == 0.02
     assert m["Direct Messaging"].units_per_token == 400
-    assert m["Speech & Text Analytics"].tokens_per_unit == 30
-    assert m["Agent Copilot"].tokens_per_unit == 40
+    # Named variants
+    assert m["Speech & Text Analytics [named]"].tokens_per_unit == 30
+    assert m["Speech & Text Analytics [concurrent]"].tokens_per_unit == 45
+    assert m["Agent Copilot [named]"].tokens_per_unit == 40
+    assert m["Agent Copilot [concurrent]"].tokens_per_unit == 60
+    # AI Translate is now a confirmed consumption meter
+    assert m["AI Translate"].tokens_per_unit == 0.5
+    assert m["AI Translate"].units_per_token == 2
+    assert m["AI Translate"].confidence is Confidence.CONFIRMED
+    # New meters
+    assert m["AI Scoring"].units_per_token == 20
+    assert m["Predictive Routing"].units_per_token == 17
+    assert m["Genesys Cloud Copilot"].units_per_token == 20
 
 
 def test_unknown_meters_flagged():
     unknown = {f for f, m in DEFAULT_METERS.items() if m.confidence is Confidence.UNKNOWN}
     assert unknown == {
-        "Email AI (Auto-Suggest)", "Email AI (Auto-Respond)", "AI Translate"
+        "Email AI (Auto-Suggest)", "Email AI (Auto-Respond)",
     }
     assert Confidence.UNKNOWN.icon == "🔴"
     assert Confidence.CONFIRMED.icon == "🟢"