oh-my-pi/packages/ai/test/models-cost.test.ts

import { describe, expect, it } from "bun:test";
import type { Usage } from "@oh-my-pi/pi-ai/types";
import { calculateCost, getBundledModel } from "@oh-my-pi/pi-catalog/models";

describe("calculateCost", () => {
	it("keeps token-based calculation for GitHub Copilot models", () => {
		const model = {
			...getBundledModel("github-copilot", "gpt-4o"),
			cost: {
				input: 1000,
				output: 2000,
				cacheRead: 500,
				cacheWrite: 800,
			},
		};
		const usage: Usage = {
			input: 1000,
			output: 500,
			cacheRead: 200,
			cacheWrite: 100,
			totalTokens: 1800,
			cost: {
				input: 123,
				output: 456,
				cacheRead: 789,
				cacheWrite: 321,
				total: 1689,
			},
		};

		calculateCost(model, usage);

		expect(usage.cost.input).toBeCloseTo(1, 8);
		expect(usage.cost.output).toBeCloseTo(1, 8);
		expect(usage.cost.cacheRead).toBeCloseTo(0.1, 8);
		expect(usage.cost.cacheWrite).toBeCloseTo(0.08, 8);
		expect(usage.cost.total).toBeCloseTo(2.18, 8);
	});

	it("keeps token-based calculation for non-Copilot providers", () => {
		const model = {
			...getBundledModel("openai", "gpt-4o-mini"),
			cost: {
				input: 1000,
				output: 2000,
				cacheRead: 500,
				cacheWrite: 800,
			},
		};
		const usage: Usage = {
			input: 1000,
			output: 500,
			cacheRead: 200,
			cacheWrite: 100,
			totalTokens: 1800,
			cost: {
				input: 0,
				output: 0,
				cacheRead: 0,
				cacheWrite: 0,
				total: 0,
			},
		};

		calculateCost(model, usage);

		expect(usage.cost.input).toBeCloseTo(1, 8);
		expect(usage.cost.output).toBeCloseTo(1, 8);
		expect(usage.cost.cacheRead).toBeCloseTo(0.1, 8);
		expect(usage.cost.cacheWrite).toBeCloseTo(0.08, 8);
		expect(usage.cost.total).toBeCloseTo(2.18, 8);
	});

	it("prices provider orchestration tokens without changing visible usage buckets", () => {
		const model = {
			...getBundledModel("openai", "gpt-4o-mini"),
			cost: {
				input: 1000,
				output: 2000,
				cacheRead: 500,
				cacheWrite: 800,
			},
		};
		const usage: Usage = {
			input: 100,
			output: 20,
			cacheRead: 50,
			cacheWrite: 10,
			totalTokens: 250,
			orchestration: { input: 25, output: 40, cacheRead: 5 },
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		expect(usage.input).toBe(100);
		expect(usage.output).toBe(20);
		expect(usage.cacheRead).toBe(50);
		expect(usage.cost.input).toBeCloseTo(0.125, 8);
		expect(usage.cost.output).toBeCloseTo(0.12, 8);
		expect(usage.cost.cacheRead).toBeCloseTo(0.0275, 8);
		expect(usage.cost.cacheWrite).toBeCloseTo(0.008, 8);
		expect(usage.cost.total).toBeCloseTo(0.2805, 8);
	});

	it("prices 1h cache writes at the 1h rate via the cttl breakdown (issue #6876)", () => {
		const model = getBundledModel("anthropic", "claude-opus-5");
		const usage: Usage = {
			input: 0,
			output: 0,
			cacheRead: 0,
			cacheWrite: 344139,
			cttl: { ephemeral1h: 344139 },
			totalTokens: 344139,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		// 1h write bills at 2x base input ($5/MTok -> $10/MTok), not the 5m
		// scalar cost.cacheWrite ($6.25/MTok) which would give $2.15086875.
		expect(usage.cost.cacheWrite).toBeCloseTo(3.44139, 8);
		expect(usage.cost.total).toBeCloseTo(3.44139, 8);
	});

	it("prices a mixed 5m/1h cache write per component", () => {
		const model = getBundledModel("anthropic", "claude-opus-5");
		const usage: Usage = {
			input: 0,
			output: 0,
			cacheRead: 0,
			cacheWrite: 300,
			cttl: { ephemeral5m: 100, ephemeral1h: 200 },
			totalTokens: 300,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		// 100 * $6.25/MTok (5m) + 200 * $10/MTok (1h).
		expect(usage.cost.cacheWrite).toBeCloseTo((6.25 * 100 + 10 * 200) / 1e6, 12);
	});

	it("prices cache-write tokens the breakdown does not account for at the flat rate", () => {
		// message_start supplied the 5m/1h split, a later message_delta bumped
		// cache_creation_input_tokens without repeating `cache_creation`. The
		// unattributed remainder must still be billed, never silently free.
		const model = getBundledModel("anthropic", "claude-opus-5");
		const usage: Usage = {
			input: 0,
			output: 0,
			cacheRead: 0,
			cacheWrite: 1000,
			cttl: { ephemeral1h: 400 },
			totalTokens: 1000,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		// 400 * $10/MTok (1h) + 600 unattributed * $6.25/MTok (flat 5m rate).
		expect(usage.cost.cacheWrite).toBeCloseTo((10 * 400 + 6.25 * 600) / 1e6, 12);
	});

	it("keeps the flat 5m rate for cache writes without a cttl breakdown", () => {
		const model = getBundledModel("anthropic", "claude-opus-5");
		const usage: Usage = {
			input: 0,
			output: 0,
			cacheRead: 0,
			cacheWrite: 1000,
			totalTokens: 1000,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		expect(usage.cost.cacheWrite).toBeCloseTo((6.25 * 1000) / 1e6, 12);
	});

	it("prices OpenAI Codex GPT models from the matching OpenAI catalog entry", () => {
		const openAIModel = getBundledModel("openai", "gpt-5.4");
		const codexModel = getBundledModel("openai-codex", "gpt-5.4");
		const usage: Usage = {
			input: 1000,
			output: 500,
			cacheRead: 200,
			cacheWrite: 0,
			totalTokens: 1700,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		expect(codexModel.cost).toEqual(openAIModel.cost);

		calculateCost(codexModel, usage);

		expect(usage.cost.total).toBeCloseTo(0.01005, 8);
	});

	it("keeps Daybreak Blue at short-context rates through 272K prompt tokens", () => {
		const model = getBundledModel("openai", "daybreak-blue-latest");
		const usage: Usage = {
			input: 270_000,
			output: 1_000,
			cacheRead: 1_000,
			cacheWrite: 1_000,
			totalTokens: 273_000,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		expect(usage.cost.input).toBeCloseTo(1.35, 12);
		expect(usage.cost.output).toBeCloseTo(0.03, 12);
		expect(usage.cost.cacheRead).toBeCloseTo(0.0005, 12);
		expect(usage.cost.cacheWrite).toBeCloseTo(0.00625, 12);
	});

	it("prices the full Daybreak Blue request at long-context rates above 272K prompt tokens", () => {
		const model = getBundledModel("openai", "daybreak-blue-latest");
		const usage: Usage = {
			input: 270_001,
			output: 1_000,
			cacheRead: 1_000,
			cacheWrite: 1_000,
			totalTokens: 273_001,
			cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
		};

		calculateCost(model, usage);

		expect(usage.cost.input).toBeCloseTo(2.70001, 12);
		expect(usage.cost.output).toBeCloseTo(0.045, 12);
		expect(usage.cost.cacheRead).toBeCloseTo(0.001, 12);
		expect(usage.cost.cacheWrite).toBeCloseTo(0.0125, 12);
	});
});