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* chore: Update dependencies by adding ai-tokenizer and removing tiktoken - Added ai-tokenizer version 1.0.6 to package.json and package-lock.json across multiple packages. - Removed tiktoken version 1.0.15 from package.json and package-lock.json in the same locations, streamlining dependency management. * refactor: replace js-tiktoken with ai-tokenizer - Added support for 'claude' encoding in the AgentClient class to improve model compatibility. - Updated Tokenizer class to utilize 'ai-tokenizer' for both 'o200k_base' and 'claude' encodings, replacing the previous 'tiktoken' dependency. - Refactored tests to reflect changes in tokenizer behavior and ensure accurate token counting for both encoding types. - Removed deprecated references to 'tiktoken' and adjusted related tests for improved clarity and functionality. * chore: remove tiktoken mocks from DALLE3 tests - Eliminated mock implementations of 'tiktoken' from DALLE3-related test files to streamline test setup and align with recent dependency updates. - Adjusted related test structures to ensure compatibility with the new tokenizer implementation. * chore: Add distinct encoding support for Anthropic Claude models - Introduced a new method `getEncoding` in the AgentClient class to handle the specific BPE tokenizer for Claude models, ensuring compatibility with the distinct encoding requirements. - Updated documentation to clarify the encoding logic for Claude and other models. * docs: Update return type documentation for getEncoding method in AgentClient - Clarified the return type of the getEncoding method to specify that it can return an EncodingName or undefined, enhancing code readability and type safety. * refactor: Tokenizer class and error handling - Exported the EncodingName type for broader usage. - Renamed encodingMap to encodingData for clarity. - Improved error handling in getTokenCount method to ensure recovery attempts are logged and return 0 on failure. - Updated countTokens function documentation to specify the use of 'o200k_base' encoding. * refactor: Simplify encoding documentation and export type - Updated the getEncoding method documentation to clarify the default behavior for non-Anthropic Claude models. - Exported the EncodingName type separately from the Tokenizer module for improved clarity and usage. * test: Update text processing tests for token limits - Adjusted test cases to handle smaller text sizes, changing scenarios from ~120k tokens to ~20k tokens for both the real tokenizer and countTokens functions. - Updated token limits in tests to reflect new constraints, ensuring tests accurately assess performance and call reduction. - Enhanced console log messages for clarity regarding token counts and reductions in the updated scenarios. * refactor: Update Tokenizer imports and exports - Moved Tokenizer and countTokens exports to the tokenizer module for better organization. - Adjusted imports in memory.ts to reflect the new structure, ensuring consistent usage across the codebase. - Updated memory.test.ts to mock the Tokenizer from the correct module path, enhancing test accuracy. * refactor: Tokenizer initialization and error handling - Introduced an async `initEncoding` method to preload tokenizers, improving performance and accuracy in token counting. - Updated `getTokenCount` to handle uninitialized tokenizers more gracefully, ensuring proper recovery and logging on errors. - Removed deprecated synchronous tokenizer retrieval, streamlining the overall tokenizer management process. * test: Enhance tokenizer tests with initialization and encoding checks - Added `beforeAll` hooks to initialize tokenizers for 'o200k_base' and 'claude' encodings before running tests, ensuring proper setup. - Updated tests to validate the loading of encodings and the correctness of token counts for both 'o200k_base' and 'claude'. - Improved test structure to deduplicate concurrent initialization calls, enhancing performance and reliability.
56 lines
1.7 KiB
TypeScript
56 lines
1.7 KiB
TypeScript
import Tokenizer from './tokenizer';
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jest.mock('@librechat/data-schemas', () => ({
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logger: {
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error: jest.fn(),
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},
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}));
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describe('Tokenizer', () => {
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it('should be a singleton (same instance)', async () => {
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const AnotherTokenizer = await import('./tokenizer');
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expect(Tokenizer).toBe(AnotherTokenizer.default);
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});
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describe('initEncoding', () => {
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it('should load o200k_base encoding', async () => {
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await Tokenizer.initEncoding('o200k_base');
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const count = Tokenizer.getTokenCount('Hello, world!', 'o200k_base');
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expect(count).toBeGreaterThan(0);
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});
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it('should load claude encoding', async () => {
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await Tokenizer.initEncoding('claude');
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const count = Tokenizer.getTokenCount('Hello, world!', 'claude');
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expect(count).toBeGreaterThan(0);
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});
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it('should deduplicate concurrent init calls', async () => {
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const [, , count] = await Promise.all([
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Tokenizer.initEncoding('o200k_base'),
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Tokenizer.initEncoding('o200k_base'),
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Tokenizer.initEncoding('o200k_base').then(() =>
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Tokenizer.getTokenCount('test', 'o200k_base'),
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),
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]);
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expect(count).toBeGreaterThan(0);
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});
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});
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describe('getTokenCount', () => {
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beforeAll(async () => {
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await Tokenizer.initEncoding('o200k_base');
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await Tokenizer.initEncoding('claude');
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});
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it('should return the number of tokens in the given text', () => {
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const count = Tokenizer.getTokenCount('Hello, world!', 'o200k_base');
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expect(count).toBeGreaterThan(0);
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});
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it('should count tokens using claude encoding', () => {
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const count = Tokenizer.getTokenCount('Hello, world!', 'claude');
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expect(count).toBeGreaterThan(0);
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});
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});
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});
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