Robert Helewka
64fb83257d
- Add 202512_GenesysCX TEI study (config, seed data, notebooks, README) with NPV $10.8M / ROI 266% including AI-token cost line - Add explicit `key` parameter to all chart wrappers in app/components to prevent StreamlitDuplicateElementId errors when the same figure type renders across Summary/Benefits/Costs tabs - Render benefits bar and cost pie charts on their respective tabs - Add benefits_vs_costs_by_year chart wrapper
67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
"""Meter catalogue integrity."""
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from __future__ import annotations
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import pytest
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from tokencalc.defaults import DEFAULT_METERS, DEFAULT_PRICING
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from tokencalc.meters import Confidence, MeterType, TokenMeter, TokenPricing
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def test_all_spec_meters_present():
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expected = {
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"Voice Bot", "Virtual Agent (legacy)", "Agentic Virtual Agent",
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"AI Summary & Insights", "Direct Messaging", "Social Listening",
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"Social Responses", "Speech & Text Analytics", "Agent Copilot",
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"Email AI (Auto-Suggest)", "Email AI (Auto-Respond)", "AI Translate",
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}
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assert expected == set(DEFAULT_METERS)
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def test_confirmed_rates():
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m = DEFAULT_METERS
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assert m["Voice Bot"].units_per_token == 17
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assert m["Voice Bot"].tokens_per_unit == pytest.approx(0.0588, abs=1e-3)
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assert m["Agentic Virtual Agent"].tokens_per_unit == 1.2
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assert m["AI Summary & Insights"].tokens_per_unit == 0.02
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assert m["Direct Messaging"].units_per_token == 400
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assert m["Speech & Text Analytics"].tokens_per_unit == 30
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assert m["Agent Copilot"].tokens_per_unit == 40
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def test_unknown_meters_flagged():
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unknown = {f for f, m in DEFAULT_METERS.items() if m.confidence is Confidence.UNKNOWN}
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assert unknown == {
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"Email AI (Auto-Suggest)", "Email AI (Auto-Respond)", "AI Translate"
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}
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assert Confidence.UNKNOWN.icon == "🔴"
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assert Confidence.CONFIRMED.icon == "🟢"
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def test_inverse_consistency_validated():
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with pytest.raises(ValueError, match="not inverses"):
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TokenMeter(
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feature="Bad", meter_type=MeterType.PER_MINUTE,
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units_per_token=10, tokens_per_unit=0.5,
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confidence=Confidence.ESTIMATED, notes="",
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)
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def test_every_confirmed_meter_has_source_url():
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for m in DEFAULT_METERS.values():
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if m.confidence is Confidence.CONFIRMED:
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assert m.source_url, f"{m.feature} missing source URL"
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def test_pricing_effective_rate():
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p = TokenPricing(region="US", list_rate_per_token=1.0,
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contracted_rate_per_token=0.85)
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assert p.effective_rate(use_contracted=False) == 1.0
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assert p.effective_rate(use_contracted=True) == 0.85
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# no contracted rate → falls back to list
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assert DEFAULT_PRICING["US"].effective_rate(use_contracted=True) == 1.0
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def test_all_regions_priced():
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assert set(DEFAULT_PRICING) == {"US", "EU", "AU", "APAC"}
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