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* updated gpt5-pro it is here and on openrouter https://platform.openai.com/docs/models/gpt-5-pro * feat: Add gpt-5-pro pricing - Implemented handling for the new gpt-5-pro model in the getValueKey function. - Updated tests to ensure correct behavior for gpt-5-pro across various scenarios. - Adjusted token limits and multipliers for gpt-5-pro in the tokens utility files. - Enhanced model matching functionality to include gpt-5-pro variations. * refactor: optimize model pricing and validation logic - Added new model pricing entries for llama2, llama3, and qwen variants in tx.js. - Updated tokenValues to include additional models and their pricing structures. - Implemented validation tests in tx.spec.js to ensure all models resolve correctly to pricing. - Refactored getValueKey function to improve model matching and resolution efficiency. - Removed outdated model entries from tokens.ts to streamline pricing management. * fix: add missing pricing * chore: update model pricing for qwen and gemma variants * chore: update model pricing and add validation for context windows - Removed outdated model entries from tx.js and updated tokenValues with new models. - Added a test in tx.spec.js to ensure all models with pricing have corresponding context windows defined in tokens.ts. - Introduced 'command-text' model pricing in tokens.ts to maintain consistency across model definitions. * chore: update model names and pricing for AI21 and Amazon models - Refactored model names in tx.js for AI21 and Amazon models to remove versioning and improve consistency. - Updated pricing values in tokens.ts to reflect the new model names. - Added comprehensive tests in tx.spec.js to validate pricing for both short and full model names across AI21 and Amazon models. * feat: add pricing and validation for Claude Haiku 4.5 model * chore: increase default max context tokens to 18000 for agents * feat: add Qwen3 model pricing and validation tests * chore: reorganize and update Qwen model pricing in tx.js and tokens.ts --------- Co-authored-by: khfung <68192841+khfung@users.noreply.github.com>
1587 lines
64 KiB
JavaScript
1587 lines
64 KiB
JavaScript
const { maxTokensMap } = require('@librechat/api');
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const { EModelEndpoint } = require('librechat-data-provider');
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const {
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defaultRate,
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tokenValues,
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getValueKey,
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getMultiplier,
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cacheTokenValues,
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getCacheMultiplier,
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} = require('./tx');
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describe('getValueKey', () => {
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it('should return "16k" for model name containing "gpt-3.5-turbo-16k"', () => {
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expect(getValueKey('gpt-3.5-turbo-16k-some-other-info')).toBe('16k');
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});
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it('should return "4k" for model name containing "gpt-3.5"', () => {
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expect(getValueKey('gpt-3.5-some-other-info')).toBe('4k');
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});
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it('should return "32k" for model name containing "gpt-4-32k"', () => {
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expect(getValueKey('gpt-4-32k-some-other-info')).toBe('32k');
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});
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it('should return "8k" for model name containing "gpt-4"', () => {
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expect(getValueKey('gpt-4-some-other-info')).toBe('8k');
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});
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it('should return "gpt-5" for model name containing "gpt-5"', () => {
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expect(getValueKey('gpt-5-some-other-info')).toBe('gpt-5');
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expect(getValueKey('gpt-5-2025-01-30')).toBe('gpt-5');
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expect(getValueKey('gpt-5-2025-01-30-0130')).toBe('gpt-5');
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expect(getValueKey('openai/gpt-5')).toBe('gpt-5');
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expect(getValueKey('openai/gpt-5-2025-01-30')).toBe('gpt-5');
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expect(getValueKey('gpt-5-turbo')).toBe('gpt-5');
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expect(getValueKey('gpt-5-0130')).toBe('gpt-5');
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});
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it('should return "gpt-3.5-turbo-1106" for model name containing "gpt-3.5-turbo-1106"', () => {
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expect(getValueKey('gpt-3.5-turbo-1106-some-other-info')).toBe('gpt-3.5-turbo-1106');
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expect(getValueKey('openai/gpt-3.5-turbo-1106')).toBe('gpt-3.5-turbo-1106');
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expect(getValueKey('gpt-3.5-turbo-1106/openai')).toBe('gpt-3.5-turbo-1106');
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});
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it('should return "gpt-4-1106" for model name containing "gpt-4-1106"', () => {
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expect(getValueKey('gpt-4-1106-some-other-info')).toBe('gpt-4-1106');
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expect(getValueKey('gpt-4-1106-vision-preview')).toBe('gpt-4-1106');
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expect(getValueKey('gpt-4-1106-preview')).toBe('gpt-4-1106');
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expect(getValueKey('openai/gpt-4-1106')).toBe('gpt-4-1106');
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expect(getValueKey('gpt-4-1106/openai/')).toBe('gpt-4-1106');
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});
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it('should return "gpt-4-1106" for model type of "gpt-4-1106"', () => {
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expect(getValueKey('gpt-4-vision-preview')).toBe('gpt-4-1106');
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expect(getValueKey('openai/gpt-4-1106')).toBe('gpt-4-1106');
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expect(getValueKey('gpt-4-turbo')).toBe('gpt-4-1106');
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expect(getValueKey('gpt-4-0125')).toBe('gpt-4-1106');
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});
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it('should return "gpt-4.5" for model type of "gpt-4.5"', () => {
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expect(getValueKey('gpt-4.5-preview')).toBe('gpt-4.5');
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expect(getValueKey('gpt-4.5-2024-08-06')).toBe('gpt-4.5');
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expect(getValueKey('gpt-4.5-2024-08-06-0718')).toBe('gpt-4.5');
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expect(getValueKey('openai/gpt-4.5')).toBe('gpt-4.5');
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expect(getValueKey('openai/gpt-4.5-2024-08-06')).toBe('gpt-4.5');
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expect(getValueKey('gpt-4.5-turbo')).toBe('gpt-4.5');
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expect(getValueKey('gpt-4.5-0125')).toBe('gpt-4.5');
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});
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it('should return "gpt-4.1" for model type of "gpt-4.1"', () => {
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expect(getValueKey('gpt-4.1-preview')).toBe('gpt-4.1');
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expect(getValueKey('gpt-4.1-2024-08-06')).toBe('gpt-4.1');
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expect(getValueKey('gpt-4.1-2024-08-06-0718')).toBe('gpt-4.1');
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expect(getValueKey('openai/gpt-4.1')).toBe('gpt-4.1');
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expect(getValueKey('openai/gpt-4.1-2024-08-06')).toBe('gpt-4.1');
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expect(getValueKey('gpt-4.1-turbo')).toBe('gpt-4.1');
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expect(getValueKey('gpt-4.1-0125')).toBe('gpt-4.1');
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});
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it('should return "gpt-4.1-mini" for model type of "gpt-4.1-mini"', () => {
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expect(getValueKey('gpt-4.1-mini-preview')).toBe('gpt-4.1-mini');
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expect(getValueKey('gpt-4.1-mini-2024-08-06')).toBe('gpt-4.1-mini');
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expect(getValueKey('openai/gpt-4.1-mini')).toBe('gpt-4.1-mini');
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expect(getValueKey('gpt-4.1-mini-0125')).toBe('gpt-4.1-mini');
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});
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it('should return "gpt-4.1-nano" for model type of "gpt-4.1-nano"', () => {
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expect(getValueKey('gpt-4.1-nano-preview')).toBe('gpt-4.1-nano');
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expect(getValueKey('gpt-4.1-nano-2024-08-06')).toBe('gpt-4.1-nano');
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expect(getValueKey('openai/gpt-4.1-nano')).toBe('gpt-4.1-nano');
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expect(getValueKey('gpt-4.1-nano-0125')).toBe('gpt-4.1-nano');
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});
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it('should return "gpt-5" for model type of "gpt-5"', () => {
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expect(getValueKey('gpt-5-2025-01-30')).toBe('gpt-5');
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expect(getValueKey('gpt-5-2025-01-30-0130')).toBe('gpt-5');
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expect(getValueKey('openai/gpt-5')).toBe('gpt-5');
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expect(getValueKey('openai/gpt-5-2025-01-30')).toBe('gpt-5');
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expect(getValueKey('gpt-5-turbo')).toBe('gpt-5');
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expect(getValueKey('gpt-5-0130')).toBe('gpt-5');
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});
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it('should return "gpt-5-mini" for model type of "gpt-5-mini"', () => {
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expect(getValueKey('gpt-5-mini-2025-01-30')).toBe('gpt-5-mini');
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expect(getValueKey('openai/gpt-5-mini')).toBe('gpt-5-mini');
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expect(getValueKey('gpt-5-mini-0130')).toBe('gpt-5-mini');
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expect(getValueKey('gpt-5-mini-2025-01-30-0130')).toBe('gpt-5-mini');
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});
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it('should return "gpt-5-nano" for model type of "gpt-5-nano"', () => {
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expect(getValueKey('gpt-5-nano-2025-01-30')).toBe('gpt-5-nano');
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expect(getValueKey('openai/gpt-5-nano')).toBe('gpt-5-nano');
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expect(getValueKey('gpt-5-nano-0130')).toBe('gpt-5-nano');
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expect(getValueKey('gpt-5-nano-2025-01-30-0130')).toBe('gpt-5-nano');
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});
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it('should return "gpt-5-pro" for model type of "gpt-5-pro"', () => {
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expect(getValueKey('gpt-5-pro-2025-01-30')).toBe('gpt-5-pro');
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expect(getValueKey('openai/gpt-5-pro')).toBe('gpt-5-pro');
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expect(getValueKey('gpt-5-pro-0130')).toBe('gpt-5-pro');
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expect(getValueKey('gpt-5-pro-2025-01-30-0130')).toBe('gpt-5-pro');
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expect(getValueKey('gpt-5-pro-preview')).toBe('gpt-5-pro');
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});
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it('should return "gpt-4o" for model type of "gpt-4o"', () => {
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expect(getValueKey('gpt-4o-2024-08-06')).toBe('gpt-4o');
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expect(getValueKey('gpt-4o-2024-08-06-0718')).toBe('gpt-4o');
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expect(getValueKey('openai/gpt-4o')).toBe('gpt-4o');
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expect(getValueKey('openai/gpt-4o-2024-08-06')).toBe('gpt-4o');
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expect(getValueKey('gpt-4o-turbo')).toBe('gpt-4o');
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expect(getValueKey('gpt-4o-0125')).toBe('gpt-4o');
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});
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it('should return "gpt-4o-mini" for model type of "gpt-4o-mini"', () => {
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expect(getValueKey('gpt-4o-mini-2024-07-18')).toBe('gpt-4o-mini');
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expect(getValueKey('openai/gpt-4o-mini')).toBe('gpt-4o-mini');
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expect(getValueKey('gpt-4o-mini-0718')).toBe('gpt-4o-mini');
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expect(getValueKey('gpt-4o-2024-08-06-0718')).not.toBe('gpt-4o-mini');
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});
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it('should return "gpt-4o-2024-05-13" for model type of "gpt-4o-2024-05-13"', () => {
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expect(getValueKey('gpt-4o-2024-05-13')).toBe('gpt-4o-2024-05-13');
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expect(getValueKey('openai/gpt-4o-2024-05-13')).toBe('gpt-4o-2024-05-13');
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expect(getValueKey('gpt-4o-2024-05-13-0718')).toBe('gpt-4o-2024-05-13');
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expect(getValueKey('gpt-4o-2024-05-13-0718')).not.toBe('gpt-4o');
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});
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it('should return "gpt-4o" for model type of "chatgpt-4o"', () => {
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expect(getValueKey('chatgpt-4o-latest')).toBe('gpt-4o');
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expect(getValueKey('openai/chatgpt-4o-latest')).toBe('gpt-4o');
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expect(getValueKey('chatgpt-4o-latest-0916')).toBe('gpt-4o');
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expect(getValueKey('chatgpt-4o-latest-0718')).toBe('gpt-4o');
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});
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it('should return "claude-3-7-sonnet" for model type of "claude-3-7-sonnet-"', () => {
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expect(getValueKey('claude-3-7-sonnet-20240620')).toBe('claude-3-7-sonnet');
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expect(getValueKey('anthropic/claude-3-7-sonnet')).toBe('claude-3-7-sonnet');
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expect(getValueKey('claude-3-7-sonnet-turbo')).toBe('claude-3-7-sonnet');
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expect(getValueKey('claude-3-7-sonnet-0125')).toBe('claude-3-7-sonnet');
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});
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it('should return "claude-3.7-sonnet" for model type of "claude-3.7-sonnet-"', () => {
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expect(getValueKey('claude-3.7-sonnet-20240620')).toBe('claude-3.7-sonnet');
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expect(getValueKey('anthropic/claude-3.7-sonnet')).toBe('claude-3.7-sonnet');
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expect(getValueKey('claude-3.7-sonnet-turbo')).toBe('claude-3.7-sonnet');
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expect(getValueKey('claude-3.7-sonnet-0125')).toBe('claude-3.7-sonnet');
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});
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it('should return "claude-3-5-sonnet" for model type of "claude-3-5-sonnet-"', () => {
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expect(getValueKey('claude-3-5-sonnet-20240620')).toBe('claude-3-5-sonnet');
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expect(getValueKey('anthropic/claude-3-5-sonnet')).toBe('claude-3-5-sonnet');
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expect(getValueKey('claude-3-5-sonnet-turbo')).toBe('claude-3-5-sonnet');
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expect(getValueKey('claude-3-5-sonnet-0125')).toBe('claude-3-5-sonnet');
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});
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it('should return "claude-3.5-sonnet" for model type of "claude-3.5-sonnet-"', () => {
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expect(getValueKey('claude-3.5-sonnet-20240620')).toBe('claude-3.5-sonnet');
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expect(getValueKey('anthropic/claude-3.5-sonnet')).toBe('claude-3.5-sonnet');
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expect(getValueKey('claude-3.5-sonnet-turbo')).toBe('claude-3.5-sonnet');
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expect(getValueKey('claude-3.5-sonnet-0125')).toBe('claude-3.5-sonnet');
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});
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it('should return "claude-3-5-haiku" for model type of "claude-3-5-haiku-"', () => {
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expect(getValueKey('claude-3-5-haiku-20240620')).toBe('claude-3-5-haiku');
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expect(getValueKey('anthropic/claude-3-5-haiku')).toBe('claude-3-5-haiku');
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expect(getValueKey('claude-3-5-haiku-turbo')).toBe('claude-3-5-haiku');
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expect(getValueKey('claude-3-5-haiku-0125')).toBe('claude-3-5-haiku');
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});
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it('should return "claude-3.5-haiku" for model type of "claude-3.5-haiku-"', () => {
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expect(getValueKey('claude-3.5-haiku-20240620')).toBe('claude-3.5-haiku');
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expect(getValueKey('anthropic/claude-3.5-haiku')).toBe('claude-3.5-haiku');
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expect(getValueKey('claude-3.5-haiku-turbo')).toBe('claude-3.5-haiku');
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expect(getValueKey('claude-3.5-haiku-0125')).toBe('claude-3.5-haiku');
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});
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it('should return expected value keys for "gpt-oss" models', () => {
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expect(getValueKey('openai/gpt-oss-120b')).toBe('gpt-oss-120b');
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expect(getValueKey('openai/gpt-oss:120b')).toBe('gpt-oss:120b');
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expect(getValueKey('openai/gpt-oss-570b')).toBe('gpt-oss');
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expect(getValueKey('gpt-oss-570b')).toBe('gpt-oss');
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expect(getValueKey('groq/gpt-oss-1080b')).toBe('gpt-oss');
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expect(getValueKey('gpt-oss-20b')).toBe('gpt-oss-20b');
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expect(getValueKey('oai/gpt-oss:20b')).toBe('gpt-oss:20b');
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});
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});
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describe('getMultiplier', () => {
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it('should return the correct multiplier for a given valueKey and tokenType', () => {
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expect(getMultiplier({ valueKey: '8k', tokenType: 'prompt' })).toBe(tokenValues['8k'].prompt);
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expect(getMultiplier({ valueKey: '8k', tokenType: 'completion' })).toBe(
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tokenValues['8k'].completion,
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);
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});
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it('should return correct multipliers for o4-mini and o3', () => {
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['o4-mini', 'o3'].forEach((model) => {
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const prompt = getMultiplier({ model, tokenType: 'prompt' });
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const completion = getMultiplier({ model, tokenType: 'completion' });
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expect(prompt).toBe(tokenValues[model].prompt);
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expect(completion).toBe(tokenValues[model].completion);
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});
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});
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it('should return defaultRate if tokenType is provided but not found in tokenValues', () => {
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expect(getMultiplier({ valueKey: '8k', tokenType: 'unknownType' })).toBe(defaultRate);
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});
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it('should derive the valueKey from the model if not provided', () => {
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expect(getMultiplier({ tokenType: 'prompt', model: 'gpt-4-some-other-info' })).toBe(
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tokenValues['8k'].prompt,
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);
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});
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it('should return 1 if only model or tokenType is missing', () => {
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expect(getMultiplier({ tokenType: 'prompt' })).toBe(1);
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expect(getMultiplier({ model: 'gpt-4-some-other-info' })).toBe(1);
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});
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it('should return the correct multiplier for gpt-3.5-turbo-1106', () => {
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expect(getMultiplier({ valueKey: 'gpt-3.5-turbo-1106', tokenType: 'prompt' })).toBe(
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tokenValues['gpt-3.5-turbo-1106'].prompt,
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);
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expect(getMultiplier({ valueKey: 'gpt-3.5-turbo-1106', tokenType: 'completion' })).toBe(
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tokenValues['gpt-3.5-turbo-1106'].completion,
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);
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});
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it('should return the correct multiplier for gpt-4-1106', () => {
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expect(getMultiplier({ valueKey: 'gpt-4-1106', tokenType: 'prompt' })).toBe(
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tokenValues['gpt-4-1106'].prompt,
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|
);
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expect(getMultiplier({ valueKey: 'gpt-4-1106', tokenType: 'completion' })).toBe(
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|
tokenValues['gpt-4-1106'].completion,
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|
);
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|
});
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|
|
|
it('should return the correct multiplier for gpt-5', () => {
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|
const valueKey = getValueKey('gpt-5-2025-01-30');
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expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-5'].prompt);
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|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5'].completion,
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|
);
|
|
expect(getMultiplier({ model: 'gpt-5-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-5'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-5', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-5-mini', () => {
|
|
const valueKey = getValueKey('gpt-5-mini-2025-01-30');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-5-mini'].prompt);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5-mini'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'gpt-5-mini-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-5-mini'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-5-mini', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5-mini'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-5-nano', () => {
|
|
const valueKey = getValueKey('gpt-5-nano-2025-01-30');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-5-nano'].prompt);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5-nano'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'gpt-5-nano-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-5-nano'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-5-nano', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5-nano'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-5-pro', () => {
|
|
const valueKey = getValueKey('gpt-5-pro-2025-01-30');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-5-pro'].prompt);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5-pro'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'gpt-5-pro-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-5-pro'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-5-pro', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-5-pro'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-4o', () => {
|
|
const valueKey = getValueKey('gpt-4o-2024-08-06');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-4o'].prompt);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4o'].completion,
|
|
);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).not.toBe(
|
|
tokenValues['gpt-4-1106'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-4.1', () => {
|
|
const valueKey = getValueKey('gpt-4.1-2024-08-06');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-4.1'].prompt);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4.1'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'gpt-4.1-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-4.1'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-4.1', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4.1'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-4.1-mini', () => {
|
|
const valueKey = getValueKey('gpt-4.1-mini-2024-08-06');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-4.1-mini'].prompt,
|
|
);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4.1-mini'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'gpt-4.1-mini-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-4.1-mini'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-4.1-mini', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4.1-mini'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-4.1-nano', () => {
|
|
const valueKey = getValueKey('gpt-4.1-nano-2024-08-06');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-4.1-nano'].prompt,
|
|
);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4.1-nano'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'gpt-4.1-nano-preview', tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-4.1-nano'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'openai/gpt-4.1-nano', tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4.1-nano'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for gpt-4o-mini', () => {
|
|
const valueKey = getValueKey('gpt-4o-mini-2024-07-18');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(
|
|
tokenValues['gpt-4o-mini'].prompt,
|
|
);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4o-mini'].completion,
|
|
);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).not.toBe(
|
|
tokenValues['gpt-4-1106'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return the correct multiplier for chatgpt-4o-latest', () => {
|
|
const valueKey = getValueKey('chatgpt-4o-latest');
|
|
expect(getMultiplier({ valueKey, tokenType: 'prompt' })).toBe(tokenValues['gpt-4o'].prompt);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).toBe(
|
|
tokenValues['gpt-4o'].completion,
|
|
);
|
|
expect(getMultiplier({ valueKey, tokenType: 'completion' })).not.toBe(
|
|
tokenValues['gpt-4o-mini'].completion,
|
|
);
|
|
});
|
|
|
|
it('should derive the valueKey from the model if not provided for new models', () => {
|
|
expect(
|
|
getMultiplier({ tokenType: 'prompt', model: 'gpt-3.5-turbo-1106-some-other-info' }),
|
|
).toBe(tokenValues['gpt-3.5-turbo-1106'].prompt);
|
|
expect(getMultiplier({ tokenType: 'completion', model: 'gpt-4-1106-vision-preview' })).toBe(
|
|
tokenValues['gpt-4-1106'].completion,
|
|
);
|
|
expect(getMultiplier({ tokenType: 'completion', model: 'gpt-4-0125-preview' })).toBe(
|
|
tokenValues['gpt-4-1106'].completion,
|
|
);
|
|
expect(getMultiplier({ tokenType: 'completion', model: 'gpt-4-turbo-vision-preview' })).toBe(
|
|
tokenValues['gpt-4-1106'].completion,
|
|
);
|
|
expect(getMultiplier({ tokenType: 'completion', model: 'gpt-3.5-turbo-0125' })).toBe(
|
|
tokenValues['gpt-3.5-turbo-0125'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return defaultRate if derived valueKey does not match any known patterns', () => {
|
|
expect(getMultiplier({ tokenType: 'prompt', model: 'gpt-10-some-other-info' })).toBe(
|
|
defaultRate,
|
|
);
|
|
});
|
|
|
|
it('should return correct multipliers for GPT-OSS models', () => {
|
|
const models = ['gpt-oss-20b', 'gpt-oss-120b'];
|
|
models.forEach((key) => {
|
|
const expectedPrompt = tokenValues[key].prompt;
|
|
const expectedCompletion = tokenValues[key].completion;
|
|
expect(getMultiplier({ valueKey: key, tokenType: 'prompt' })).toBe(expectedPrompt);
|
|
expect(getMultiplier({ valueKey: key, tokenType: 'completion' })).toBe(expectedCompletion);
|
|
expect(getMultiplier({ model: key, tokenType: 'prompt' })).toBe(expectedPrompt);
|
|
expect(getMultiplier({ model: key, tokenType: 'completion' })).toBe(expectedCompletion);
|
|
});
|
|
});
|
|
|
|
it('should return correct multipliers for GLM models', () => {
|
|
const models = ['glm-4.6', 'glm-4.5v', 'glm-4.5-air', 'glm-4.5', 'glm-4-32b', 'glm-4', 'glm4'];
|
|
models.forEach((key) => {
|
|
const expectedPrompt = tokenValues[key].prompt;
|
|
const expectedCompletion = tokenValues[key].completion;
|
|
expect(getMultiplier({ valueKey: key, tokenType: 'prompt' })).toBe(expectedPrompt);
|
|
expect(getMultiplier({ valueKey: key, tokenType: 'completion' })).toBe(expectedCompletion);
|
|
expect(getMultiplier({ model: key, tokenType: 'prompt' })).toBe(expectedPrompt);
|
|
expect(getMultiplier({ model: key, tokenType: 'completion' })).toBe(expectedCompletion);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('AWS Bedrock Model Tests', () => {
|
|
const awsModels = [
|
|
'anthropic.claude-3-5-haiku-20241022-v1:0',
|
|
'anthropic.claude-3-haiku-20240307-v1:0',
|
|
'anthropic.claude-3-sonnet-20240229-v1:0',
|
|
'anthropic.claude-3-opus-20240229-v1:0',
|
|
'anthropic.claude-3-5-sonnet-20240620-v1:0',
|
|
'anthropic.claude-v2:1',
|
|
'anthropic.claude-instant-v1',
|
|
'meta.llama2-13b-chat-v1',
|
|
'meta.llama2-70b-chat-v1',
|
|
'meta.llama3-8b-instruct-v1:0',
|
|
'meta.llama3-70b-instruct-v1:0',
|
|
'meta.llama3-1-8b-instruct-v1:0',
|
|
'meta.llama3-1-70b-instruct-v1:0',
|
|
'meta.llama3-1-405b-instruct-v1:0',
|
|
'mistral.mistral-7b-instruct-v0:2',
|
|
'mistral.mistral-small-2402-v1:0',
|
|
'mistral.mixtral-8x7b-instruct-v0:1',
|
|
'mistral.mistral-large-2402-v1:0',
|
|
'mistral.mistral-large-2407-v1:0',
|
|
'cohere.command-text-v14',
|
|
'cohere.command-light-text-v14',
|
|
'cohere.command-r-v1:0',
|
|
'cohere.command-r-plus-v1:0',
|
|
'ai21.j2-mid-v1',
|
|
'ai21.j2-ultra-v1',
|
|
'amazon.titan-text-lite-v1',
|
|
'amazon.titan-text-express-v1',
|
|
'amazon.nova-micro-v1:0',
|
|
'amazon.nova-lite-v1:0',
|
|
'amazon.nova-pro-v1:0',
|
|
];
|
|
|
|
it('should return the correct prompt multipliers for all models', () => {
|
|
const results = awsModels.map((model) => {
|
|
const valueKey = getValueKey(model, EModelEndpoint.bedrock);
|
|
const multiplier = getMultiplier({ valueKey, tokenType: 'prompt' });
|
|
return tokenValues[valueKey].prompt && multiplier === tokenValues[valueKey].prompt;
|
|
});
|
|
expect(results.every(Boolean)).toBe(true);
|
|
});
|
|
|
|
it('should return the correct completion multipliers for all models', () => {
|
|
const results = awsModels.map((model) => {
|
|
const valueKey = getValueKey(model, EModelEndpoint.bedrock);
|
|
const multiplier = getMultiplier({ valueKey, tokenType: 'completion' });
|
|
return tokenValues[valueKey].completion && multiplier === tokenValues[valueKey].completion;
|
|
});
|
|
expect(results.every(Boolean)).toBe(true);
|
|
});
|
|
});
|
|
|
|
describe('Amazon Model Tests', () => {
|
|
describe('Amazon Nova Models', () => {
|
|
it('should return correct pricing for nova-premier', () => {
|
|
expect(getMultiplier({ model: 'nova-premier', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-premier'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'nova-premier', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-premier'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-premier-v1:0', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-premier'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-premier-v1:0', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-premier'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for nova-pro', () => {
|
|
expect(getMultiplier({ model: 'nova-pro', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-pro'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'nova-pro', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-pro'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-pro-v1:0', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-pro'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-pro-v1:0', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-pro'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for nova-lite', () => {
|
|
expect(getMultiplier({ model: 'nova-lite', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-lite'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'nova-lite', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-lite'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-lite-v1:0', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-lite'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-lite-v1:0', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-lite'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for nova-micro', () => {
|
|
expect(getMultiplier({ model: 'nova-micro', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-micro'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'nova-micro', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-micro'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-micro-v1:0', tokenType: 'prompt' })).toBe(
|
|
tokenValues['nova-micro'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.nova-micro-v1:0', tokenType: 'completion' })).toBe(
|
|
tokenValues['nova-micro'].completion,
|
|
);
|
|
});
|
|
|
|
it('should match both short and full model names to the same pricing', () => {
|
|
const models = ['nova-micro', 'nova-lite', 'nova-pro', 'nova-premier'];
|
|
const fullModels = [
|
|
'amazon.nova-micro-v1:0',
|
|
'amazon.nova-lite-v1:0',
|
|
'amazon.nova-pro-v1:0',
|
|
'amazon.nova-premier-v1:0',
|
|
];
|
|
|
|
models.forEach((shortModel, i) => {
|
|
const fullModel = fullModels[i];
|
|
const shortPrompt = getMultiplier({ model: shortModel, tokenType: 'prompt' });
|
|
const fullPrompt = getMultiplier({ model: fullModel, tokenType: 'prompt' });
|
|
const shortCompletion = getMultiplier({ model: shortModel, tokenType: 'completion' });
|
|
const fullCompletion = getMultiplier({ model: fullModel, tokenType: 'completion' });
|
|
|
|
expect(shortPrompt).toBe(fullPrompt);
|
|
expect(shortCompletion).toBe(fullCompletion);
|
|
expect(shortPrompt).toBe(tokenValues[shortModel].prompt);
|
|
expect(shortCompletion).toBe(tokenValues[shortModel].completion);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('Amazon Titan Models', () => {
|
|
it('should return correct pricing for titan-text-premier', () => {
|
|
expect(getMultiplier({ model: 'titan-text-premier', tokenType: 'prompt' })).toBe(
|
|
tokenValues['titan-text-premier'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'titan-text-premier', tokenType: 'completion' })).toBe(
|
|
tokenValues['titan-text-premier'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.titan-text-premier-v1:0', tokenType: 'prompt' })).toBe(
|
|
tokenValues['titan-text-premier'].prompt,
|
|
);
|
|
expect(
|
|
getMultiplier({ model: 'amazon.titan-text-premier-v1:0', tokenType: 'completion' }),
|
|
).toBe(tokenValues['titan-text-premier'].completion);
|
|
});
|
|
|
|
it('should return correct pricing for titan-text-express', () => {
|
|
expect(getMultiplier({ model: 'titan-text-express', tokenType: 'prompt' })).toBe(
|
|
tokenValues['titan-text-express'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'titan-text-express', tokenType: 'completion' })).toBe(
|
|
tokenValues['titan-text-express'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.titan-text-express-v1', tokenType: 'prompt' })).toBe(
|
|
tokenValues['titan-text-express'].prompt,
|
|
);
|
|
expect(
|
|
getMultiplier({ model: 'amazon.titan-text-express-v1', tokenType: 'completion' }),
|
|
).toBe(tokenValues['titan-text-express'].completion);
|
|
});
|
|
|
|
it('should return correct pricing for titan-text-lite', () => {
|
|
expect(getMultiplier({ model: 'titan-text-lite', tokenType: 'prompt' })).toBe(
|
|
tokenValues['titan-text-lite'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'titan-text-lite', tokenType: 'completion' })).toBe(
|
|
tokenValues['titan-text-lite'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.titan-text-lite-v1', tokenType: 'prompt' })).toBe(
|
|
tokenValues['titan-text-lite'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'amazon.titan-text-lite-v1', tokenType: 'completion' })).toBe(
|
|
tokenValues['titan-text-lite'].completion,
|
|
);
|
|
});
|
|
|
|
it('should match both short and full model names to the same pricing', () => {
|
|
const models = ['titan-text-lite', 'titan-text-express', 'titan-text-premier'];
|
|
const fullModels = [
|
|
'amazon.titan-text-lite-v1',
|
|
'amazon.titan-text-express-v1',
|
|
'amazon.titan-text-premier-v1:0',
|
|
];
|
|
|
|
models.forEach((shortModel, i) => {
|
|
const fullModel = fullModels[i];
|
|
const shortPrompt = getMultiplier({ model: shortModel, tokenType: 'prompt' });
|
|
const fullPrompt = getMultiplier({ model: fullModel, tokenType: 'prompt' });
|
|
const shortCompletion = getMultiplier({ model: shortModel, tokenType: 'completion' });
|
|
const fullCompletion = getMultiplier({ model: fullModel, tokenType: 'completion' });
|
|
|
|
expect(shortPrompt).toBe(fullPrompt);
|
|
expect(shortCompletion).toBe(fullCompletion);
|
|
expect(shortPrompt).toBe(tokenValues[shortModel].prompt);
|
|
expect(shortCompletion).toBe(tokenValues[shortModel].completion);
|
|
});
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('AI21 Model Tests', () => {
|
|
describe('AI21 J2 Models', () => {
|
|
it('should return correct pricing for j2-mid', () => {
|
|
expect(getMultiplier({ model: 'j2-mid', tokenType: 'prompt' })).toBe(
|
|
tokenValues['j2-mid'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'j2-mid', tokenType: 'completion' })).toBe(
|
|
tokenValues['j2-mid'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'ai21.j2-mid-v1', tokenType: 'prompt' })).toBe(
|
|
tokenValues['j2-mid'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'ai21.j2-mid-v1', tokenType: 'completion' })).toBe(
|
|
tokenValues['j2-mid'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for j2-ultra', () => {
|
|
expect(getMultiplier({ model: 'j2-ultra', tokenType: 'prompt' })).toBe(
|
|
tokenValues['j2-ultra'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'j2-ultra', tokenType: 'completion' })).toBe(
|
|
tokenValues['j2-ultra'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'ai21.j2-ultra-v1', tokenType: 'prompt' })).toBe(
|
|
tokenValues['j2-ultra'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'ai21.j2-ultra-v1', tokenType: 'completion' })).toBe(
|
|
tokenValues['j2-ultra'].completion,
|
|
);
|
|
});
|
|
|
|
it('should match both short and full model names to the same pricing', () => {
|
|
const models = ['j2-mid', 'j2-ultra'];
|
|
const fullModels = ['ai21.j2-mid-v1', 'ai21.j2-ultra-v1'];
|
|
|
|
models.forEach((shortModel, i) => {
|
|
const fullModel = fullModels[i];
|
|
const shortPrompt = getMultiplier({ model: shortModel, tokenType: 'prompt' });
|
|
const fullPrompt = getMultiplier({ model: fullModel, tokenType: 'prompt' });
|
|
const shortCompletion = getMultiplier({ model: shortModel, tokenType: 'completion' });
|
|
const fullCompletion = getMultiplier({ model: fullModel, tokenType: 'completion' });
|
|
|
|
expect(shortPrompt).toBe(fullPrompt);
|
|
expect(shortCompletion).toBe(fullCompletion);
|
|
expect(shortPrompt).toBe(tokenValues[shortModel].prompt);
|
|
expect(shortCompletion).toBe(tokenValues[shortModel].completion);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('AI21 Jamba Models', () => {
|
|
it('should return correct pricing for jamba-instruct', () => {
|
|
expect(getMultiplier({ model: 'jamba-instruct', tokenType: 'prompt' })).toBe(
|
|
tokenValues['jamba-instruct'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'jamba-instruct', tokenType: 'completion' })).toBe(
|
|
tokenValues['jamba-instruct'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'ai21.jamba-instruct-v1:0', tokenType: 'prompt' })).toBe(
|
|
tokenValues['jamba-instruct'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'ai21.jamba-instruct-v1:0', tokenType: 'completion' })).toBe(
|
|
tokenValues['jamba-instruct'].completion,
|
|
);
|
|
});
|
|
|
|
it('should match both short and full model names to the same pricing', () => {
|
|
const shortPrompt = getMultiplier({ model: 'jamba-instruct', tokenType: 'prompt' });
|
|
const fullPrompt = getMultiplier({
|
|
model: 'ai21.jamba-instruct-v1:0',
|
|
tokenType: 'prompt',
|
|
});
|
|
const shortCompletion = getMultiplier({ model: 'jamba-instruct', tokenType: 'completion' });
|
|
const fullCompletion = getMultiplier({
|
|
model: 'ai21.jamba-instruct-v1:0',
|
|
tokenType: 'completion',
|
|
});
|
|
|
|
expect(shortPrompt).toBe(fullPrompt);
|
|
expect(shortCompletion).toBe(fullCompletion);
|
|
expect(shortPrompt).toBe(tokenValues['jamba-instruct'].prompt);
|
|
expect(shortCompletion).toBe(tokenValues['jamba-instruct'].completion);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('Deepseek Model Tests', () => {
|
|
const deepseekModels = ['deepseek-chat', 'deepseek-coder', 'deepseek-reasoner', 'deepseek.r1'];
|
|
|
|
it('should return the correct prompt multipliers for all models', () => {
|
|
const results = deepseekModels.map((model) => {
|
|
const valueKey = getValueKey(model);
|
|
const multiplier = getMultiplier({ valueKey, tokenType: 'prompt' });
|
|
return tokenValues[valueKey].prompt && multiplier === tokenValues[valueKey].prompt;
|
|
});
|
|
expect(results.every(Boolean)).toBe(true);
|
|
});
|
|
|
|
it('should return the correct completion multipliers for all models', () => {
|
|
const results = deepseekModels.map((model) => {
|
|
const valueKey = getValueKey(model);
|
|
const multiplier = getMultiplier({ valueKey, tokenType: 'completion' });
|
|
return tokenValues[valueKey].completion && multiplier === tokenValues[valueKey].completion;
|
|
});
|
|
expect(results.every(Boolean)).toBe(true);
|
|
});
|
|
|
|
it('should return the correct prompt multipliers for reasoning model', () => {
|
|
const model = 'deepseek-reasoner';
|
|
const valueKey = getValueKey(model);
|
|
expect(valueKey).toBe(model);
|
|
const multiplier = getMultiplier({ valueKey, tokenType: 'prompt' });
|
|
const result = tokenValues[valueKey].prompt && multiplier === tokenValues[valueKey].prompt;
|
|
expect(result).toBe(true);
|
|
});
|
|
});
|
|
|
|
describe('Qwen3 Model Tests', () => {
|
|
describe('Qwen3 Base Models', () => {
|
|
it('should return correct pricing for qwen3 base pattern', () => {
|
|
expect(getMultiplier({ model: 'qwen3', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-4b (falls back to qwen3)', () => {
|
|
expect(getMultiplier({ model: 'qwen3-4b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-4b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-8b', () => {
|
|
expect(getMultiplier({ model: 'qwen3-8b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-8b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-8b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-8b'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-14b', () => {
|
|
expect(getMultiplier({ model: 'qwen3-14b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-14b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-14b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-14b'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-235b-a22b', () => {
|
|
expect(getMultiplier({ model: 'qwen3-235b-a22b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-235b-a22b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-235b-a22b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-235b-a22b'].completion,
|
|
);
|
|
});
|
|
|
|
it('should handle model name variations with provider prefixes', () => {
|
|
const models = [
|
|
{ input: 'qwen3', expected: 'qwen3' },
|
|
{ input: 'qwen3-4b', expected: 'qwen3' },
|
|
{ input: 'qwen3-8b', expected: 'qwen3-8b' },
|
|
{ input: 'qwen3-32b', expected: 'qwen3-32b' },
|
|
];
|
|
models.forEach(({ input, expected }) => {
|
|
const withPrefix = `alibaba/${input}`;
|
|
expect(getMultiplier({ model: withPrefix, tokenType: 'prompt' })).toBe(
|
|
tokenValues[expected].prompt,
|
|
);
|
|
expect(getMultiplier({ model: withPrefix, tokenType: 'completion' })).toBe(
|
|
tokenValues[expected].completion,
|
|
);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('Qwen3 VL (Vision-Language) Models', () => {
|
|
it('should return correct pricing for qwen3-vl-8b-thinking', () => {
|
|
expect(getMultiplier({ model: 'qwen3-vl-8b-thinking', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-vl-8b-thinking'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-vl-8b-thinking', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-vl-8b-thinking'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-vl-8b-instruct', () => {
|
|
expect(getMultiplier({ model: 'qwen3-vl-8b-instruct', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-vl-8b-instruct'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-vl-8b-instruct', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-vl-8b-instruct'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-vl-30b-a3b', () => {
|
|
expect(getMultiplier({ model: 'qwen3-vl-30b-a3b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-vl-30b-a3b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-vl-30b-a3b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-vl-30b-a3b'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-vl-235b-a22b', () => {
|
|
expect(getMultiplier({ model: 'qwen3-vl-235b-a22b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-vl-235b-a22b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-vl-235b-a22b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-vl-235b-a22b'].completion,
|
|
);
|
|
});
|
|
});
|
|
|
|
describe('Qwen3 Specialized Models', () => {
|
|
it('should return correct pricing for qwen3-max', () => {
|
|
expect(getMultiplier({ model: 'qwen3-max', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-max'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-max', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-max'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-coder', () => {
|
|
expect(getMultiplier({ model: 'qwen3-coder', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-coder'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-coder', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-coder'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-coder-plus', () => {
|
|
expect(getMultiplier({ model: 'qwen3-coder-plus', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-coder-plus'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-coder-plus', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-coder-plus'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-coder-flash', () => {
|
|
expect(getMultiplier({ model: 'qwen3-coder-flash', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-coder-flash'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-coder-flash', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-coder-flash'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct pricing for qwen3-next-80b-a3b', () => {
|
|
expect(getMultiplier({ model: 'qwen3-next-80b-a3b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['qwen3-next-80b-a3b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'qwen3-next-80b-a3b', tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3-next-80b-a3b'].completion,
|
|
);
|
|
});
|
|
});
|
|
|
|
describe('Qwen3 Model Variations', () => {
|
|
it('should handle all qwen3 models with provider prefixes', () => {
|
|
const models = ['qwen3', 'qwen3-8b', 'qwen3-max', 'qwen3-coder', 'qwen3-vl-8b-instruct'];
|
|
const prefixes = ['alibaba', 'qwen', 'openrouter'];
|
|
|
|
models.forEach((model) => {
|
|
prefixes.forEach((prefix) => {
|
|
const fullModel = `${prefix}/${model}`;
|
|
expect(getMultiplier({ model: fullModel, tokenType: 'prompt' })).toBe(
|
|
tokenValues[model].prompt,
|
|
);
|
|
expect(getMultiplier({ model: fullModel, tokenType: 'completion' })).toBe(
|
|
tokenValues[model].completion,
|
|
);
|
|
});
|
|
});
|
|
});
|
|
|
|
it('should handle qwen3-4b falling back to qwen3 base pattern', () => {
|
|
const testCases = ['qwen3-4b', 'alibaba/qwen3-4b', 'qwen/qwen3-4b-preview'];
|
|
testCases.forEach((model) => {
|
|
expect(getMultiplier({ model, tokenType: 'prompt' })).toBe(tokenValues['qwen3'].prompt);
|
|
expect(getMultiplier({ model, tokenType: 'completion' })).toBe(
|
|
tokenValues['qwen3'].completion,
|
|
);
|
|
});
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('getCacheMultiplier', () => {
|
|
it('should return the correct cache multiplier for a given valueKey and cacheType', () => {
|
|
expect(getCacheMultiplier({ valueKey: 'claude-3-5-sonnet', cacheType: 'write' })).toBe(
|
|
cacheTokenValues['claude-3-5-sonnet'].write,
|
|
);
|
|
expect(getCacheMultiplier({ valueKey: 'claude-3-5-sonnet', cacheType: 'read' })).toBe(
|
|
cacheTokenValues['claude-3-5-sonnet'].read,
|
|
);
|
|
expect(getCacheMultiplier({ valueKey: 'claude-3-5-haiku', cacheType: 'write' })).toBe(
|
|
cacheTokenValues['claude-3-5-haiku'].write,
|
|
);
|
|
expect(getCacheMultiplier({ valueKey: 'claude-3-5-haiku', cacheType: 'read' })).toBe(
|
|
cacheTokenValues['claude-3-5-haiku'].read,
|
|
);
|
|
expect(getCacheMultiplier({ valueKey: 'claude-3-haiku', cacheType: 'write' })).toBe(
|
|
cacheTokenValues['claude-3-haiku'].write,
|
|
);
|
|
expect(getCacheMultiplier({ valueKey: 'claude-3-haiku', cacheType: 'read' })).toBe(
|
|
cacheTokenValues['claude-3-haiku'].read,
|
|
);
|
|
});
|
|
|
|
it('should return null if cacheType is provided but not found in cacheTokenValues', () => {
|
|
expect(
|
|
getCacheMultiplier({ valueKey: 'claude-3-5-sonnet', cacheType: 'unknownType' }),
|
|
).toBeNull();
|
|
});
|
|
|
|
it('should derive the valueKey from the model if not provided', () => {
|
|
expect(getCacheMultiplier({ cacheType: 'write', model: 'claude-3-5-sonnet-20240620' })).toBe(
|
|
cacheTokenValues['claude-3-5-sonnet'].write,
|
|
);
|
|
expect(getCacheMultiplier({ cacheType: 'read', model: 'claude-3-haiku-20240307' })).toBe(
|
|
cacheTokenValues['claude-3-haiku'].read,
|
|
);
|
|
});
|
|
|
|
it('should return null if only model or cacheType is missing', () => {
|
|
expect(getCacheMultiplier({ cacheType: 'write' })).toBeNull();
|
|
expect(getCacheMultiplier({ model: 'claude-3-5-sonnet' })).toBeNull();
|
|
});
|
|
|
|
it('should return null if derived valueKey does not match any known patterns', () => {
|
|
expect(getCacheMultiplier({ cacheType: 'write', model: 'gpt-4-some-other-info' })).toBeNull();
|
|
});
|
|
|
|
it('should handle endpointTokenConfig if provided', () => {
|
|
const endpointTokenConfig = {
|
|
'custom-model': {
|
|
write: 5,
|
|
read: 1,
|
|
},
|
|
};
|
|
expect(
|
|
getCacheMultiplier({ model: 'custom-model', cacheType: 'write', endpointTokenConfig }),
|
|
).toBe(endpointTokenConfig['custom-model'].write);
|
|
expect(
|
|
getCacheMultiplier({ model: 'custom-model', cacheType: 'read', endpointTokenConfig }),
|
|
).toBe(endpointTokenConfig['custom-model'].read);
|
|
});
|
|
|
|
it('should return null if model is not found in endpointTokenConfig', () => {
|
|
const endpointTokenConfig = {
|
|
'custom-model': {
|
|
write: 5,
|
|
read: 1,
|
|
},
|
|
};
|
|
expect(
|
|
getCacheMultiplier({ model: 'unknown-model', cacheType: 'write', endpointTokenConfig }),
|
|
).toBeNull();
|
|
});
|
|
|
|
it('should handle models with "bedrock/" prefix', () => {
|
|
expect(
|
|
getCacheMultiplier({
|
|
model: 'bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0',
|
|
cacheType: 'write',
|
|
}),
|
|
).toBe(cacheTokenValues['claude-3-5-sonnet'].write);
|
|
expect(
|
|
getCacheMultiplier({
|
|
model: 'bedrock/anthropic.claude-3-haiku-20240307-v1:0',
|
|
cacheType: 'read',
|
|
}),
|
|
).toBe(cacheTokenValues['claude-3-haiku'].read);
|
|
});
|
|
});
|
|
|
|
describe('Google Model Tests', () => {
|
|
const googleModels = [
|
|
'gemini-2.5-pro',
|
|
'gemini-2.5-flash',
|
|
'gemini-2.5-flash-lite',
|
|
'gemini-2.5-pro-preview-05-06',
|
|
'gemini-2.5-flash-preview-04-17',
|
|
'gemini-2.5-exp',
|
|
'gemini-2.0-flash-lite-preview-02-05',
|
|
'gemini-2.0-flash-001',
|
|
'gemini-2.0-flash-exp',
|
|
'gemini-2.0-pro-exp-02-05',
|
|
'gemini-1.5-flash-8b',
|
|
'gemini-1.5-flash-thinking',
|
|
'gemini-1.5-pro-latest',
|
|
'gemini-1.5-pro-preview-0409',
|
|
'gemini-pro-vision',
|
|
'gemini-1.0',
|
|
'gemini-pro',
|
|
];
|
|
|
|
it('should return the correct prompt and completion rates for all models', () => {
|
|
const results = googleModels.map((model) => {
|
|
const valueKey = getValueKey(model, EModelEndpoint.google);
|
|
const promptRate = getMultiplier({
|
|
model,
|
|
tokenType: 'prompt',
|
|
endpoint: EModelEndpoint.google,
|
|
});
|
|
const completionRate = getMultiplier({
|
|
model,
|
|
tokenType: 'completion',
|
|
endpoint: EModelEndpoint.google,
|
|
});
|
|
return { model, valueKey, promptRate, completionRate };
|
|
});
|
|
|
|
results.forEach(({ valueKey, promptRate, completionRate }) => {
|
|
expect(promptRate).toBe(tokenValues[valueKey].prompt);
|
|
expect(completionRate).toBe(tokenValues[valueKey].completion);
|
|
});
|
|
});
|
|
|
|
it('should map to the correct model keys', () => {
|
|
const expected = {
|
|
'gemini-2.5-pro': 'gemini-2.5-pro',
|
|
'gemini-2.5-flash': 'gemini-2.5-flash',
|
|
'gemini-2.5-flash-lite': 'gemini-2.5-flash-lite',
|
|
'gemini-2.5-pro-preview-05-06': 'gemini-2.5-pro',
|
|
'gemini-2.5-flash-preview-04-17': 'gemini-2.5-flash',
|
|
'gemini-2.5-exp': 'gemini-2.5',
|
|
'gemini-2.0-flash-lite-preview-02-05': 'gemini-2.0-flash-lite',
|
|
'gemini-2.0-flash-001': 'gemini-2.0-flash',
|
|
'gemini-2.0-flash-exp': 'gemini-2.0-flash',
|
|
'gemini-2.0-pro-exp-02-05': 'gemini-2.0',
|
|
'gemini-1.5-flash-8b': 'gemini-1.5-flash-8b',
|
|
'gemini-1.5-flash-thinking': 'gemini-1.5-flash',
|
|
'gemini-1.5-pro-latest': 'gemini-1.5',
|
|
'gemini-1.5-pro-preview-0409': 'gemini-1.5',
|
|
'gemini-pro-vision': 'gemini-pro-vision',
|
|
'gemini-1.0': 'gemini',
|
|
'gemini-pro': 'gemini',
|
|
};
|
|
|
|
Object.entries(expected).forEach(([model, expectedKey]) => {
|
|
const valueKey = getValueKey(model, EModelEndpoint.google);
|
|
expect(valueKey).toBe(expectedKey);
|
|
});
|
|
});
|
|
|
|
it('should handle model names with different formats', () => {
|
|
const testCases = [
|
|
{ input: 'google/gemini-pro', expected: 'gemini' },
|
|
{ input: 'gemini-pro/google', expected: 'gemini' },
|
|
{ input: 'google/gemini-2.0-flash-lite', expected: 'gemini-2.0-flash-lite' },
|
|
];
|
|
|
|
testCases.forEach(({ input, expected }) => {
|
|
const valueKey = getValueKey(input, EModelEndpoint.google);
|
|
expect(valueKey).toBe(expected);
|
|
expect(
|
|
getMultiplier({ model: input, tokenType: 'prompt', endpoint: EModelEndpoint.google }),
|
|
).toBe(tokenValues[expected].prompt);
|
|
expect(
|
|
getMultiplier({ model: input, tokenType: 'completion', endpoint: EModelEndpoint.google }),
|
|
).toBe(tokenValues[expected].completion);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('Grok Model Tests - Pricing', () => {
|
|
describe('getMultiplier', () => {
|
|
test('should return correct prompt and completion rates for Grok vision models', () => {
|
|
const models = ['grok-2-vision-1212', 'grok-2-vision', 'grok-2-vision-latest'];
|
|
models.forEach((model) => {
|
|
expect(getMultiplier({ model, tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-2-vision'].prompt,
|
|
);
|
|
expect(getMultiplier({ model, tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-2-vision'].completion,
|
|
);
|
|
});
|
|
});
|
|
|
|
test('should return correct prompt and completion rates for Grok text models', () => {
|
|
const models = ['grok-2-1212', 'grok-2', 'grok-2-latest'];
|
|
models.forEach((model) => {
|
|
expect(getMultiplier({ model, tokenType: 'prompt' })).toBe(tokenValues['grok-2'].prompt);
|
|
expect(getMultiplier({ model, tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-2'].completion,
|
|
);
|
|
});
|
|
});
|
|
|
|
test('should return correct prompt and completion rates for Grok beta models', () => {
|
|
expect(getMultiplier({ model: 'grok-vision-beta', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-vision-beta'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-vision-beta', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-vision-beta'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-beta', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-beta'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-beta', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-beta'].completion,
|
|
);
|
|
});
|
|
|
|
test('should return correct prompt and completion rates for Grok 3 models', () => {
|
|
expect(getMultiplier({ model: 'grok-3', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3-fast', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3-fast'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3-fast', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3-fast'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3-mini', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3-mini'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3-mini', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3-mini'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3-mini-fast', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3-mini-fast'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-3-mini-fast', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3-mini-fast'].completion,
|
|
);
|
|
});
|
|
|
|
test('should return correct prompt and completion rates for Grok 4 model', () => {
|
|
expect(getMultiplier({ model: 'grok-4-0709', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-4'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'grok-4-0709', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-4'].completion,
|
|
);
|
|
});
|
|
|
|
test('should return correct prompt and completion rates for Grok 3 models with prefixes', () => {
|
|
expect(getMultiplier({ model: 'xai/grok-3', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3-fast', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3-fast'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3-fast', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3-fast'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3-mini', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3-mini'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3-mini', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3-mini'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3-mini-fast', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-3-mini-fast'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-3-mini-fast', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-3-mini-fast'].completion,
|
|
);
|
|
});
|
|
|
|
test('should return correct prompt and completion rates for Grok 4 model with prefixes', () => {
|
|
expect(getMultiplier({ model: 'xai/grok-4-0709', tokenType: 'prompt' })).toBe(
|
|
tokenValues['grok-4'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'xai/grok-4-0709', tokenType: 'completion' })).toBe(
|
|
tokenValues['grok-4'].completion,
|
|
);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('GLM Model Tests', () => {
|
|
it('should return expected value keys for GLM models', () => {
|
|
expect(getValueKey('glm-4.6')).toBe('glm-4.6');
|
|
expect(getValueKey('glm-4.5')).toBe('glm-4.5');
|
|
expect(getValueKey('glm-4.5v')).toBe('glm-4.5v');
|
|
expect(getValueKey('glm-4.5-air')).toBe('glm-4.5-air');
|
|
expect(getValueKey('glm-4-32b')).toBe('glm-4-32b');
|
|
expect(getValueKey('glm-4')).toBe('glm-4');
|
|
expect(getValueKey('glm4')).toBe('glm4');
|
|
});
|
|
|
|
it('should match GLM model variations with provider prefixes', () => {
|
|
expect(getValueKey('z-ai/glm-4.6')).toBe('glm-4.6');
|
|
expect(getValueKey('z-ai/glm-4.5')).toBe('glm-4.5');
|
|
expect(getValueKey('z-ai/glm-4.5-air')).toBe('glm-4.5-air');
|
|
expect(getValueKey('z-ai/glm-4.5v')).toBe('glm-4.5v');
|
|
expect(getValueKey('z-ai/glm-4-32b')).toBe('glm-4-32b');
|
|
|
|
expect(getValueKey('zai/glm-4.6')).toBe('glm-4.6');
|
|
expect(getValueKey('zai/glm-4.5')).toBe('glm-4.5');
|
|
expect(getValueKey('zai/glm-4.5-air')).toBe('glm-4.5-air');
|
|
expect(getValueKey('zai/glm-4.5v')).toBe('glm-4.5v');
|
|
|
|
expect(getValueKey('zai-org/GLM-4.6')).toBe('glm-4.6');
|
|
expect(getValueKey('zai-org/GLM-4.5')).toBe('glm-4.5');
|
|
expect(getValueKey('zai-org/GLM-4.5-Air')).toBe('glm-4.5-air');
|
|
expect(getValueKey('zai-org/GLM-4.5V')).toBe('glm-4.5v');
|
|
expect(getValueKey('zai-org/GLM-4-32B-0414')).toBe('glm-4-32b');
|
|
});
|
|
|
|
it('should match GLM model variations with suffixes', () => {
|
|
expect(getValueKey('glm-4.6-fp8')).toBe('glm-4.6');
|
|
expect(getValueKey('zai-org/GLM-4.6-FP8')).toBe('glm-4.6');
|
|
expect(getValueKey('zai-org/GLM-4.5-Air-FP8')).toBe('glm-4.5-air');
|
|
});
|
|
|
|
it('should prioritize more specific GLM model patterns', () => {
|
|
expect(getValueKey('glm-4.5-air-something')).toBe('glm-4.5-air');
|
|
expect(getValueKey('glm-4.5-something')).toBe('glm-4.5');
|
|
expect(getValueKey('glm-4.5v-something')).toBe('glm-4.5v');
|
|
});
|
|
|
|
it('should return correct multipliers for all GLM models', () => {
|
|
expect(getMultiplier({ model: 'glm-4.6', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4.6'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'glm-4.6', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4.6'].completion,
|
|
);
|
|
|
|
expect(getMultiplier({ model: 'glm-4.5v', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4.5v'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'glm-4.5v', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4.5v'].completion,
|
|
);
|
|
|
|
expect(getMultiplier({ model: 'glm-4.5-air', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4.5-air'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'glm-4.5-air', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4.5-air'].completion,
|
|
);
|
|
|
|
expect(getMultiplier({ model: 'glm-4.5', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4.5'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'glm-4.5', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4.5'].completion,
|
|
);
|
|
|
|
expect(getMultiplier({ model: 'glm-4-32b', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4-32b'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'glm-4-32b', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4-32b'].completion,
|
|
);
|
|
|
|
expect(getMultiplier({ model: 'glm-4', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'glm-4', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4'].completion,
|
|
);
|
|
|
|
expect(getMultiplier({ model: 'glm4', tokenType: 'prompt' })).toBe(tokenValues['glm4'].prompt);
|
|
expect(getMultiplier({ model: 'glm4', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm4'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct multipliers for GLM models with provider prefixes', () => {
|
|
expect(getMultiplier({ model: 'z-ai/glm-4.6', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4.6'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'zai/glm-4.5-air', tokenType: 'completion' })).toBe(
|
|
tokenValues['glm-4.5-air'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'zai-org/GLM-4.5V', tokenType: 'prompt' })).toBe(
|
|
tokenValues['glm-4.5v'].prompt,
|
|
);
|
|
});
|
|
});
|
|
|
|
describe('Claude Model Tests', () => {
|
|
it('should return correct prompt and completion rates for Claude 4 models', () => {
|
|
expect(getMultiplier({ model: 'claude-sonnet-4', tokenType: 'prompt' })).toBe(
|
|
tokenValues['claude-sonnet-4'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'claude-sonnet-4', tokenType: 'completion' })).toBe(
|
|
tokenValues['claude-sonnet-4'].completion,
|
|
);
|
|
expect(getMultiplier({ model: 'claude-opus-4', tokenType: 'prompt' })).toBe(
|
|
tokenValues['claude-opus-4'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'claude-opus-4', tokenType: 'completion' })).toBe(
|
|
tokenValues['claude-opus-4'].completion,
|
|
);
|
|
});
|
|
|
|
it('should return correct prompt and completion rates for Claude Haiku 4.5', () => {
|
|
expect(getMultiplier({ model: 'claude-haiku-4-5', tokenType: 'prompt' })).toBe(
|
|
tokenValues['claude-haiku-4-5'].prompt,
|
|
);
|
|
expect(getMultiplier({ model: 'claude-haiku-4-5', tokenType: 'completion' })).toBe(
|
|
tokenValues['claude-haiku-4-5'].completion,
|
|
);
|
|
});
|
|
|
|
it('should handle Claude Haiku 4.5 model name variations', () => {
|
|
const modelVariations = [
|
|
'claude-haiku-4-5',
|
|
'claude-haiku-4-5-20250420',
|
|
'claude-haiku-4-5-latest',
|
|
'anthropic/claude-haiku-4-5',
|
|
'claude-haiku-4-5/anthropic',
|
|
'claude-haiku-4-5-preview',
|
|
];
|
|
|
|
modelVariations.forEach((model) => {
|
|
const valueKey = getValueKey(model);
|
|
expect(valueKey).toBe('claude-haiku-4-5');
|
|
expect(getMultiplier({ model, tokenType: 'prompt' })).toBe(
|
|
tokenValues['claude-haiku-4-5'].prompt,
|
|
);
|
|
expect(getMultiplier({ model, tokenType: 'completion' })).toBe(
|
|
tokenValues['claude-haiku-4-5'].completion,
|
|
);
|
|
});
|
|
});
|
|
|
|
it('should handle Claude 4 model name variations with different prefixes and suffixes', () => {
|
|
const modelVariations = [
|
|
'claude-sonnet-4',
|
|
'claude-sonnet-4-20240229',
|
|
'claude-sonnet-4-latest',
|
|
'anthropic/claude-sonnet-4',
|
|
'claude-sonnet-4/anthropic',
|
|
'claude-sonnet-4-preview',
|
|
'claude-sonnet-4-20240229-preview',
|
|
'claude-opus-4',
|
|
'claude-opus-4-20240229',
|
|
'claude-opus-4-latest',
|
|
'anthropic/claude-opus-4',
|
|
'claude-opus-4/anthropic',
|
|
'claude-opus-4-preview',
|
|
'claude-opus-4-20240229-preview',
|
|
];
|
|
|
|
modelVariations.forEach((model) => {
|
|
const valueKey = getValueKey(model);
|
|
const isSonnet = model.includes('sonnet');
|
|
const expectedKey = isSonnet ? 'claude-sonnet-4' : 'claude-opus-4';
|
|
|
|
expect(valueKey).toBe(expectedKey);
|
|
expect(getMultiplier({ model, tokenType: 'prompt' })).toBe(tokenValues[expectedKey].prompt);
|
|
expect(getMultiplier({ model, tokenType: 'completion' })).toBe(
|
|
tokenValues[expectedKey].completion,
|
|
);
|
|
});
|
|
});
|
|
|
|
it('should return correct cache rates for Claude 4 models', () => {
|
|
expect(getCacheMultiplier({ model: 'claude-sonnet-4', cacheType: 'write' })).toBe(
|
|
cacheTokenValues['claude-sonnet-4'].write,
|
|
);
|
|
expect(getCacheMultiplier({ model: 'claude-sonnet-4', cacheType: 'read' })).toBe(
|
|
cacheTokenValues['claude-sonnet-4'].read,
|
|
);
|
|
expect(getCacheMultiplier({ model: 'claude-opus-4', cacheType: 'write' })).toBe(
|
|
cacheTokenValues['claude-opus-4'].write,
|
|
);
|
|
expect(getCacheMultiplier({ model: 'claude-opus-4', cacheType: 'read' })).toBe(
|
|
cacheTokenValues['claude-opus-4'].read,
|
|
);
|
|
});
|
|
|
|
it('should handle Claude 4 model cache rates with different prefixes and suffixes', () => {
|
|
const modelVariations = [
|
|
'claude-sonnet-4',
|
|
'claude-sonnet-4-20240229',
|
|
'claude-sonnet-4-latest',
|
|
'anthropic/claude-sonnet-4',
|
|
'claude-sonnet-4/anthropic',
|
|
'claude-sonnet-4-preview',
|
|
'claude-sonnet-4-20240229-preview',
|
|
'claude-opus-4',
|
|
'claude-opus-4-20240229',
|
|
'claude-opus-4-latest',
|
|
'anthropic/claude-opus-4',
|
|
'claude-opus-4/anthropic',
|
|
'claude-opus-4-preview',
|
|
'claude-opus-4-20240229-preview',
|
|
];
|
|
|
|
modelVariations.forEach((model) => {
|
|
const isSonnet = model.includes('sonnet');
|
|
const expectedKey = isSonnet ? 'claude-sonnet-4' : 'claude-opus-4';
|
|
|
|
expect(getCacheMultiplier({ model, cacheType: 'write' })).toBe(
|
|
cacheTokenValues[expectedKey].write,
|
|
);
|
|
expect(getCacheMultiplier({ model, cacheType: 'read' })).toBe(
|
|
cacheTokenValues[expectedKey].read,
|
|
);
|
|
});
|
|
});
|
|
});
|
|
|
|
describe('tokens.ts and tx.js sync validation', () => {
|
|
it('should resolve all models in maxTokensMap to pricing via getValueKey', () => {
|
|
const tokensKeys = Object.keys(maxTokensMap[EModelEndpoint.openAI]);
|
|
const txKeys = Object.keys(tokenValues);
|
|
|
|
const unresolved = [];
|
|
|
|
tokensKeys.forEach((key) => {
|
|
// Skip legacy token size mappings (e.g., '4k', '8k', '16k', '32k')
|
|
if (/^\d+k$/.test(key)) return;
|
|
|
|
// Skip generic pattern keys (end with '-' or ':')
|
|
if (key.endsWith('-') || key.endsWith(':')) return;
|
|
|
|
// Try to resolve via getValueKey
|
|
const resolvedKey = getValueKey(key);
|
|
|
|
// If it resolves and the resolved key has pricing, success
|
|
if (resolvedKey && txKeys.includes(resolvedKey)) return;
|
|
|
|
// If it resolves to a legacy key (4k, 8k, etc), also OK
|
|
if (resolvedKey && /^\d+k$/.test(resolvedKey)) return;
|
|
|
|
// If we get here, this model can't get pricing - flag it
|
|
unresolved.push({
|
|
key,
|
|
resolvedKey: resolvedKey || 'undefined',
|
|
context: maxTokensMap[EModelEndpoint.openAI][key],
|
|
});
|
|
});
|
|
|
|
if (unresolved.length > 0) {
|
|
console.log('\nModels that cannot resolve to pricing via getValueKey:');
|
|
unresolved.forEach(({ key, resolvedKey, context }) => {
|
|
console.log(` - '${key}' → '${resolvedKey}' (context: ${context})`);
|
|
});
|
|
}
|
|
|
|
expect(unresolved).toEqual([]);
|
|
});
|
|
|
|
it('should not have redundant dated variants with same pricing and context as base model', () => {
|
|
const txKeys = Object.keys(tokenValues);
|
|
const redundant = [];
|
|
|
|
txKeys.forEach((key) => {
|
|
// Check if this is a dated variant (ends with -YYYY-MM-DD)
|
|
if (key.match(/.*-\d{4}-\d{2}-\d{2}$/)) {
|
|
const baseKey = key.replace(/-\d{4}-\d{2}-\d{2}$/, '');
|
|
|
|
if (txKeys.includes(baseKey)) {
|
|
const variantPricing = tokenValues[key];
|
|
const basePricing = tokenValues[baseKey];
|
|
const variantContext = maxTokensMap[EModelEndpoint.openAI][key];
|
|
const baseContext = maxTokensMap[EModelEndpoint.openAI][baseKey];
|
|
|
|
const samePricing =
|
|
variantPricing.prompt === basePricing.prompt &&
|
|
variantPricing.completion === basePricing.completion;
|
|
const sameContext = variantContext === baseContext;
|
|
|
|
if (samePricing && sameContext) {
|
|
redundant.push({
|
|
key,
|
|
baseKey,
|
|
pricing: `${variantPricing.prompt}/${variantPricing.completion}`,
|
|
context: variantContext,
|
|
});
|
|
}
|
|
}
|
|
}
|
|
});
|
|
|
|
if (redundant.length > 0) {
|
|
console.log('\nRedundant dated variants found (same pricing and context as base):');
|
|
redundant.forEach(({ key, baseKey, pricing, context }) => {
|
|
console.log(` - '${key}' → '${baseKey}' (pricing: ${pricing}, context: ${context})`);
|
|
console.log(` Can be removed - pattern matching will handle it`);
|
|
});
|
|
}
|
|
|
|
expect(redundant).toEqual([]);
|
|
});
|
|
|
|
it('should have context windows in tokens.ts for all models with pricing in tx.js (openAI catch-all)', () => {
|
|
const txKeys = Object.keys(tokenValues);
|
|
const missingContext = [];
|
|
|
|
txKeys.forEach((key) => {
|
|
// Skip legacy token size mappings (4k, 8k, 16k, 32k)
|
|
if (/^\d+k$/.test(key)) return;
|
|
|
|
// Check if this model has a context window defined
|
|
const context = maxTokensMap[EModelEndpoint.openAI][key];
|
|
|
|
if (!context) {
|
|
const pricing = tokenValues[key];
|
|
missingContext.push({
|
|
key,
|
|
pricing: `${pricing.prompt}/${pricing.completion}`,
|
|
});
|
|
}
|
|
});
|
|
|
|
if (missingContext.length > 0) {
|
|
console.log('\nModels with pricing but missing context in tokens.ts:');
|
|
missingContext.forEach(({ key, pricing }) => {
|
|
console.log(` - '${key}' (pricing: ${pricing})`);
|
|
console.log(` Add to tokens.ts openAIModels/bedrockModels/etc.`);
|
|
});
|
|
}
|
|
|
|
expect(missingContext).toEqual([]);
|
|
});
|
|
});
|