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https://github.com/danny-avila/LibreChat.git
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* feat: update PaLM icons * feat: add additional google models * POC: formatting inputs for Vertex AI streaming * refactor: move endpoints services outside of /routes dir to /services/Endpoints * refactor: shorten schemas import * refactor: rename PALM to GOOGLE * feat: make Google editable endpoint * feat: reusable Ask and Edit controllers based off Anthropic * chore: organize imports/logic * fix(parseConvo): include examples in googleSchema * fix: google only allows odd number of messages to be sent * fix: pass proxy to AnthropicClient * refactor: change `google` altName to `Google` * refactor: update getModelMaxTokens and related functions to handle maxTokensMap with nested endpoint model key/values * refactor: google Icon and response sender changes (Codey and Google logo instead of PaLM in all cases) * feat: google support for maxTokensMap * feat: google updated endpoints with Ask/Edit controllers, buildOptions, and initializeClient * feat(GoogleClient): now builds prompt for text models and supports real streaming from Vertex AI through langchain * chore(GoogleClient): remove comments, left before for reference in git history * docs: update google instructions (WIP) * docs(apis_and_tokens.md): add images to google instructions * docs: remove typo apis_and_tokens.md * Update apis_and_tokens.md * feat(Google): use default settings map, fully support context for both text and chat models, fully support examples for chat models * chore: update more PaLM references to Google * chore: move playwright out of workflows to avoid failing tests
182 lines
6.8 KiB
JavaScript
182 lines
6.8 KiB
JavaScript
const { EModelEndpoint } = require('~/server/services/Endpoints');
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const { getModelMaxTokens, 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-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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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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];
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const claudeMaxTokens = maxTokensMap[EModelEndpoint.anthropic]['claude-'];
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const claude21MaxTokens = maxTokensMap[EModelEndpoint.anthropic]['claude-2.1'];
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models.forEach((model) => {
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const expectedTokens = model === 'claude-2.1' ? claude21MaxTokens : claudeMaxTokens;
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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('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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});
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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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// 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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