mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-09-22 08:12:00 +02:00
63afb317c6
* 🤖 refactor: streamline model selection logic for title model in GoogleClient
* refactor: add options for empty object schemas in convertJsonSchemaToZod
* refactor: add utility function to check for empty object schemas in convertJsonSchemaToZod
* fix: Google MCP Tool errors, and remove Object Unescaping as Google fixed this
* fix: google safetySettings
* feat: add safety settings exclusion via GOOGLE_EXCLUDE_SAFETY_SETTINGS environment variable
* fix: rename environment variable for console JSON string length
* fix: disable portal for dropdown in ExportModal component
* fix: screenshot functionality to use image placeholder for remote images
* feat: add visionMode property to BaseClient and initialize in GoogleClient to fix resendFiles issue
* fix: enhance formatMessages to include image URLs in message content for Vertex AI
* fix: safety settings for titleChatCompletion
* fix: remove deprecated model assignment in GoogleClient and streamline title model retrieval
* fix: remove unused image preloading logic in ScreenshotContext
* chore: update default google models to latest models shared by vertex ai and gen ai
* refactor: enhance Google error messaging
* fix: update token values and model limits for Gemini models
* ci: fix model matching
* chore: bump version of librechat-data-provider to 0.7.699
485 lines
19 KiB
JavaScript
485 lines
19 KiB
JavaScript
const { EModelEndpoint } = require('librechat-data-provider');
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const { getModelMaxTokens, processModelData, matchModelName, maxTokensMap } = require('./tokens');
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describe('getModelMaxTokens', () => {
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test('should return correct tokens for exact match', () => {
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expect(getModelMaxTokens('gpt-4-32k-0613')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-32k-0613'],
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);
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});
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test('should return correct tokens for partial match', () => {
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expect(getModelMaxTokens('gpt-4-32k-unknown')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-32k'],
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);
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});
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test('should return correct tokens for partial match (OpenRouter)', () => {
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expect(getModelMaxTokens('openai/gpt-4-32k')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-32k'],
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);
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});
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test('should return undefined for no match', () => {
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expect(getModelMaxTokens('unknown-model')).toBeUndefined();
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});
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test('should return correct tokens for another exact match', () => {
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expect(getModelMaxTokens('gpt-3.5-turbo-16k-0613')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-3.5-turbo-16k-0613'],
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);
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});
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test('should return correct tokens for another partial match', () => {
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expect(getModelMaxTokens('gpt-3.5-turbo-unknown')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-3.5-turbo'],
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);
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});
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test('should return undefined for undefined input', () => {
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expect(getModelMaxTokens(undefined)).toBeUndefined();
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});
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test('should return undefined for null input', () => {
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expect(getModelMaxTokens(null)).toBeUndefined();
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});
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test('should return undefined for number input', () => {
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expect(getModelMaxTokens(123)).toBeUndefined();
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});
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// 11/06 Update
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test('should return correct tokens for gpt-3.5-turbo-1106 exact match', () => {
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expect(getModelMaxTokens('gpt-3.5-turbo-1106')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-3.5-turbo-1106'],
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);
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});
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test('should return correct tokens for gpt-4-1106 exact match', () => {
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expect(getModelMaxTokens('gpt-4-1106')).toBe(maxTokensMap[EModelEndpoint.openAI]['gpt-4-1106']);
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});
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test('should return correct tokens for gpt-4-vision exact match', () => {
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expect(getModelMaxTokens('gpt-4-vision')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-vision'],
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);
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});
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test('should return correct tokens for gpt-3.5-turbo-1106 partial match', () => {
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expect(getModelMaxTokens('something-/gpt-3.5-turbo-1106')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-3.5-turbo-1106'],
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);
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expect(getModelMaxTokens('gpt-3.5-turbo-1106/something-/')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-3.5-turbo-1106'],
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);
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});
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test('should return correct tokens for gpt-4-1106 partial match', () => {
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expect(getModelMaxTokens('gpt-4-1106/something')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-1106'],
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);
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expect(getModelMaxTokens('gpt-4-1106-preview')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-1106'],
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);
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expect(getModelMaxTokens('gpt-4-1106-vision-preview')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-1106'],
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);
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});
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// 01/25 Update
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test('should return correct tokens for gpt-4-turbo/0125 matches', () => {
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expect(getModelMaxTokens('gpt-4-turbo')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-turbo'],
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);
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expect(getModelMaxTokens('gpt-4-turbo-preview')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-turbo'],
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);
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expect(getModelMaxTokens('gpt-4-0125')).toBe(maxTokensMap[EModelEndpoint.openAI]['gpt-4-0125']);
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expect(getModelMaxTokens('gpt-4-0125-preview')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-4-0125'],
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);
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expect(getModelMaxTokens('gpt-3.5-turbo-0125')).toBe(
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maxTokensMap[EModelEndpoint.openAI]['gpt-3.5-turbo-0125'],
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);
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});
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test('should return correct tokens for Anthropic models', () => {
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const models = [
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'claude-2.1',
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'claude-2',
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'claude-1.2',
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'claude-1',
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'claude-1-100k',
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'claude-instant-1',
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'claude-instant-1-100k',
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'claude-3-haiku',
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'claude-3-sonnet',
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'claude-3-opus',
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'claude-3-5-sonnet',
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];
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const maxTokens = {
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'claude-': maxTokensMap[EModelEndpoint.anthropic]['claude-'],
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'claude-2.1': maxTokensMap[EModelEndpoint.anthropic]['claude-2.1'],
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'claude-3': maxTokensMap[EModelEndpoint.anthropic]['claude-3-sonnet'],
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};
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models.forEach((model) => {
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let expectedTokens;
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if (model === 'claude-2.1') {
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expectedTokens = maxTokens['claude-2.1'];
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} else if (model.startsWith('claude-3')) {
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expectedTokens = maxTokens['claude-3'];
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} else {
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expectedTokens = maxTokens['claude-'];
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}
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expect(getModelMaxTokens(model, EModelEndpoint.anthropic)).toEqual(expectedTokens);
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});
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});
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// Tests for Google models
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test('should return correct tokens for exact match - Google models', () => {
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expect(getModelMaxTokens('text-bison-32k', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['text-bison-32k'],
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);
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expect(getModelMaxTokens('codechat-bison-32k', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['codechat-bison-32k'],
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);
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});
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test('should return undefined for no match - Google models', () => {
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expect(getModelMaxTokens('unknown-google-model', EModelEndpoint.google)).toBeUndefined();
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});
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test('should return correct tokens for partial match - Google models', () => {
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expect(getModelMaxTokens('gemini-2.0-flash-lite-preview-02-05', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-2.0-flash-lite'],
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);
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expect(getModelMaxTokens('gemini-2.0-flash-001', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-2.0-flash'],
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);
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expect(getModelMaxTokens('gemini-2.0-flash-exp', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-2.0-flash'],
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);
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expect(getModelMaxTokens('gemini-2.0-pro-exp-02-05', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-2.0'],
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);
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expect(getModelMaxTokens('gemini-1.5-flash-8b', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-1.5-flash-8b'],
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);
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expect(getModelMaxTokens('gemini-1.5-flash-thinking', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-1.5-flash'],
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);
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expect(getModelMaxTokens('gemini-1.5-pro-latest', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-1.5'],
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);
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expect(getModelMaxTokens('gemini-1.5-pro-preview-0409', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-1.5'],
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);
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expect(getModelMaxTokens('gemini-pro-vision', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini-pro-vision'],
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);
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expect(getModelMaxTokens('gemini-1.0', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini'],
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);
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expect(getModelMaxTokens('gemini-pro', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['gemini'],
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);
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expect(getModelMaxTokens('code-', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['code-'],
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);
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expect(getModelMaxTokens('chat-', EModelEndpoint.google)).toBe(
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maxTokensMap[EModelEndpoint.google]['chat-'],
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);
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});
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test('should return correct tokens for partial match - Cohere models', () => {
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expect(getModelMaxTokens('command', EModelEndpoint.custom)).toBe(
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maxTokensMap[EModelEndpoint.custom]['command'],
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);
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expect(getModelMaxTokens('command-r-plus', EModelEndpoint.custom)).toBe(
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maxTokensMap[EModelEndpoint.custom]['command-r-plus'],
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);
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});
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test('should return correct tokens when using a custom endpointTokenConfig', () => {
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const customTokenConfig = {
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'custom-model': 12345,
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};
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expect(getModelMaxTokens('custom-model', EModelEndpoint.openAI, customTokenConfig)).toBe(12345);
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});
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test('should prioritize endpointTokenConfig over the default configuration', () => {
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const customTokenConfig = {
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'gpt-4-32k': 9999,
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};
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expect(getModelMaxTokens('gpt-4-32k', EModelEndpoint.openAI, customTokenConfig)).toBe(9999);
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});
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test('should return undefined if the model is not found in custom endpointTokenConfig', () => {
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const customTokenConfig = {
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'custom-model': 12345,
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};
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expect(
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getModelMaxTokens('nonexistent-model', EModelEndpoint.openAI, customTokenConfig),
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).toBeUndefined();
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});
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test('should return correct tokens for exact match in azureOpenAI models', () => {
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expect(getModelMaxTokens('gpt-4-turbo', EModelEndpoint.azureOpenAI)).toBe(
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maxTokensMap[EModelEndpoint.azureOpenAI]['gpt-4-turbo'],
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);
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});
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test('should return undefined for no match in azureOpenAI models', () => {
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expect(
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getModelMaxTokens('nonexistent-azure-model', EModelEndpoint.azureOpenAI),
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).toBeUndefined();
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});
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test('should return undefined for undefined, null, or number model argument with azureOpenAI endpoint', () => {
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expect(getModelMaxTokens(undefined, EModelEndpoint.azureOpenAI)).toBeUndefined();
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expect(getModelMaxTokens(null, EModelEndpoint.azureOpenAI)).toBeUndefined();
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expect(getModelMaxTokens(1234, EModelEndpoint.azureOpenAI)).toBeUndefined();
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});
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test('should respect custom endpointTokenConfig over azureOpenAI defaults', () => {
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const customTokenConfig = {
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'custom-azure-model': 4096,
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};
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expect(
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getModelMaxTokens('custom-azure-model', EModelEndpoint.azureOpenAI, customTokenConfig),
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).toBe(4096);
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});
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test('should return correct tokens for partial match with custom endpointTokenConfig in azureOpenAI', () => {
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const customTokenConfig = {
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'azure-custom-': 1024,
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};
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expect(
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getModelMaxTokens('azure-custom-gpt-3', EModelEndpoint.azureOpenAI, customTokenConfig),
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).toBe(1024);
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});
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test('should return undefined for a model when using an unsupported endpoint', () => {
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expect(getModelMaxTokens('azure-gpt-3', 'unsupportedEndpoint')).toBeUndefined();
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});
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test('should return correct max context tokens for o1-series models', () => {
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// Standard o1 variations
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const o1Tokens = maxTokensMap[EModelEndpoint.openAI]['o1'];
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expect(getModelMaxTokens('o1')).toBe(o1Tokens);
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expect(getModelMaxTokens('o1-latest')).toBe(o1Tokens);
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expect(getModelMaxTokens('o1-2024-12-17')).toBe(o1Tokens);
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expect(getModelMaxTokens('o1-something-else')).toBe(o1Tokens);
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expect(getModelMaxTokens('openai/o1-something-else')).toBe(o1Tokens);
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// Mini variations
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const o1MiniTokens = maxTokensMap[EModelEndpoint.openAI]['o1-mini'];
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expect(getModelMaxTokens('o1-mini')).toBe(o1MiniTokens);
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expect(getModelMaxTokens('o1-mini-latest')).toBe(o1MiniTokens);
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expect(getModelMaxTokens('o1-mini-2024-09-12')).toBe(o1MiniTokens);
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expect(getModelMaxTokens('o1-mini-something')).toBe(o1MiniTokens);
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expect(getModelMaxTokens('openai/o1-mini-something')).toBe(o1MiniTokens);
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// Preview variations
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const o1PreviewTokens = maxTokensMap[EModelEndpoint.openAI]['o1-preview'];
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expect(getModelMaxTokens('o1-preview')).toBe(o1PreviewTokens);
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expect(getModelMaxTokens('o1-preview-latest')).toBe(o1PreviewTokens);
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expect(getModelMaxTokens('o1-preview-2024-09-12')).toBe(o1PreviewTokens);
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expect(getModelMaxTokens('o1-preview-something')).toBe(o1PreviewTokens);
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expect(getModelMaxTokens('openai/o1-preview-something')).toBe(o1PreviewTokens);
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});
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});
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describe('matchModelName', () => {
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it('should return the exact model name if it exists in maxTokensMap', () => {
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expect(matchModelName('gpt-4-32k-0613')).toBe('gpt-4-32k-0613');
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});
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it('should return the closest matching key for partial matches', () => {
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expect(matchModelName('gpt-4-32k-unknown')).toBe('gpt-4-32k');
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});
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it('should return the input model name if no match is found', () => {
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expect(matchModelName('unknown-model')).toBe('unknown-model');
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});
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it('should return undefined for non-string inputs', () => {
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expect(matchModelName(undefined)).toBeUndefined();
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expect(matchModelName(null)).toBeUndefined();
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expect(matchModelName(123)).toBeUndefined();
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expect(matchModelName({})).toBeUndefined();
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});
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// 11/06 Update
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it('should return the exact model name for gpt-3.5-turbo-1106 if it exists in maxTokensMap', () => {
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expect(matchModelName('gpt-3.5-turbo-1106')).toBe('gpt-3.5-turbo-1106');
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});
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it('should return the exact model name for gpt-4-1106 if it exists in maxTokensMap', () => {
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expect(matchModelName('gpt-4-1106')).toBe('gpt-4-1106');
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});
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it('should return the closest matching key for gpt-3.5-turbo-1106 partial matches', () => {
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expect(matchModelName('gpt-3.5-turbo-1106/something')).toBe('gpt-3.5-turbo-1106');
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expect(matchModelName('something/gpt-3.5-turbo-1106')).toBe('gpt-3.5-turbo-1106');
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});
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it('should return the closest matching key for gpt-4-1106 partial matches', () => {
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expect(matchModelName('something/gpt-4-1106')).toBe('gpt-4-1106');
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expect(matchModelName('gpt-4-1106-preview')).toBe('gpt-4-1106');
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expect(matchModelName('gpt-4-1106-vision-preview')).toBe('gpt-4-1106');
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});
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// 01/25 Update
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it('should return the closest matching key for gpt-4-turbo/0125 matches', () => {
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expect(matchModelName('openai/gpt-4-0125')).toBe('gpt-4-0125');
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expect(matchModelName('gpt-4-turbo-preview')).toBe('gpt-4-turbo');
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expect(matchModelName('gpt-4-turbo-vision-preview')).toBe('gpt-4-turbo');
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expect(matchModelName('gpt-4-0125')).toBe('gpt-4-0125');
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expect(matchModelName('gpt-4-0125-preview')).toBe('gpt-4-0125');
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expect(matchModelName('gpt-4-0125-vision-preview')).toBe('gpt-4-0125');
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});
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// Tests for Google models
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it('should return the exact model name if it exists in maxTokensMap - Google models', () => {
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expect(matchModelName('text-bison-32k', EModelEndpoint.google)).toBe('text-bison-32k');
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expect(matchModelName('codechat-bison-32k', EModelEndpoint.google)).toBe('codechat-bison-32k');
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});
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it('should return the input model name if no match is found - Google models', () => {
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expect(matchModelName('unknown-google-model', EModelEndpoint.google)).toBe(
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'unknown-google-model',
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);
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});
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it('should return the closest matching key for partial matches - Google models', () => {
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expect(matchModelName('code-', EModelEndpoint.google)).toBe('code-');
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expect(matchModelName('chat-', EModelEndpoint.google)).toBe('chat-');
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});
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});
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describe('Meta Models Tests', () => {
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describe('getModelMaxTokens', () => {
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test('should return correct tokens for LLaMa 2 models', () => {
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expect(getModelMaxTokens('llama2')).toBe(4000);
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expect(getModelMaxTokens('llama2.70b')).toBe(4000);
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expect(getModelMaxTokens('llama2-13b')).toBe(4000);
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expect(getModelMaxTokens('llama2-70b')).toBe(4000);
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});
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test('should return correct tokens for LLaMa 3 models', () => {
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expect(getModelMaxTokens('llama3')).toBe(8000);
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expect(getModelMaxTokens('llama3.8b')).toBe(8000);
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expect(getModelMaxTokens('llama3.70b')).toBe(8000);
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expect(getModelMaxTokens('llama3-8b')).toBe(8000);
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expect(getModelMaxTokens('llama3-70b')).toBe(8000);
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});
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test('should return correct tokens for LLaMa 3.1 models', () => {
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expect(getModelMaxTokens('llama3.1:8b')).toBe(127500);
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expect(getModelMaxTokens('llama3.1:70b')).toBe(127500);
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expect(getModelMaxTokens('llama3.1:405b')).toBe(127500);
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expect(getModelMaxTokens('llama3-1-8b')).toBe(127500);
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expect(getModelMaxTokens('llama3-1-70b')).toBe(127500);
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expect(getModelMaxTokens('llama3-1-405b')).toBe(127500);
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});
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test('should handle partial matches for Meta models', () => {
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// Test with full model names
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expect(getModelMaxTokens('meta/llama3.1:405b')).toBe(127500);
|
|
expect(getModelMaxTokens('meta/llama3.1:70b')).toBe(127500);
|
|
expect(getModelMaxTokens('meta/llama3.1:8b')).toBe(127500);
|
|
expect(getModelMaxTokens('meta/llama3-1-8b')).toBe(127500);
|
|
|
|
// Test base versions
|
|
expect(getModelMaxTokens('meta/llama3.1')).toBe(127500);
|
|
expect(getModelMaxTokens('meta/llama3-1')).toBe(127500);
|
|
expect(getModelMaxTokens('meta/llama3')).toBe(8000);
|
|
expect(getModelMaxTokens('meta/llama2')).toBe(4000);
|
|
});
|
|
|
|
test('should match Deepseek model variations', () => {
|
|
expect(getModelMaxTokens('deepseek-chat')).toBe(
|
|
maxTokensMap[EModelEndpoint.openAI]['deepseek'],
|
|
);
|
|
expect(getModelMaxTokens('deepseek-coder')).toBe(
|
|
maxTokensMap[EModelEndpoint.openAI]['deepseek'],
|
|
);
|
|
expect(getModelMaxTokens('deepseek-reasoner')).toBe(
|
|
maxTokensMap[EModelEndpoint.openAI]['deepseek-reasoner'],
|
|
);
|
|
});
|
|
});
|
|
|
|
describe('matchModelName', () => {
|
|
test('should match exact LLaMa model names', () => {
|
|
expect(matchModelName('llama2')).toBe('llama2');
|
|
expect(matchModelName('llama3')).toBe('llama3');
|
|
expect(matchModelName('llama3.1:8b')).toBe('llama3.1:8b');
|
|
});
|
|
|
|
test('should match LLaMa model variations', () => {
|
|
// Test full model names
|
|
expect(matchModelName('meta/llama3.1:405b')).toBe('llama3.1:405b');
|
|
expect(matchModelName('meta/llama3.1:70b')).toBe('llama3.1:70b');
|
|
expect(matchModelName('meta/llama3.1:8b')).toBe('llama3.1:8b');
|
|
expect(matchModelName('meta/llama3-1-8b')).toBe('llama3-1-8b');
|
|
|
|
// Test base versions
|
|
expect(matchModelName('meta/llama3.1')).toBe('llama3.1');
|
|
expect(matchModelName('meta/llama3-1')).toBe('llama3-1');
|
|
});
|
|
|
|
test('should handle custom endpoint for Meta models', () => {
|
|
expect(matchModelName('llama2', EModelEndpoint.bedrock)).toBe('llama2');
|
|
expect(matchModelName('llama3', EModelEndpoint.bedrock)).toBe('llama3');
|
|
expect(matchModelName('llama3.1:8b', EModelEndpoint.bedrock)).toBe('llama3.1:8b');
|
|
});
|
|
|
|
test('should match Deepseek model variations', () => {
|
|
expect(matchModelName('deepseek-chat')).toBe('deepseek');
|
|
expect(matchModelName('deepseek-coder')).toBe('deepseek');
|
|
});
|
|
});
|
|
|
|
describe('processModelData with Meta models', () => {
|
|
test('should process Meta model data correctly', () => {
|
|
const input = {
|
|
data: [
|
|
{
|
|
id: 'llama2',
|
|
pricing: {
|
|
prompt: '0.00001',
|
|
completion: '0.00003',
|
|
},
|
|
context_length: 4000,
|
|
},
|
|
{
|
|
id: 'llama3',
|
|
pricing: {
|
|
prompt: '0.00002',
|
|
completion: '0.00004',
|
|
},
|
|
context_length: 8000,
|
|
},
|
|
],
|
|
};
|
|
|
|
const result = processModelData(input);
|
|
expect(result.llama2).toEqual({
|
|
prompt: 10,
|
|
completion: 30,
|
|
context: 4000,
|
|
});
|
|
expect(result.llama3).toEqual({
|
|
prompt: 20,
|
|
completion: 40,
|
|
context: 8000,
|
|
});
|
|
});
|
|
});
|
|
});
|