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* refactor: add gemini-pro to google Models list; use defaultModels for central model listing * refactor(SetKeyDialog): create useMultipleKeys hook to use for Azure, export `isJson` from utils, use EModelEndpoint * refactor(useUserKey): change variable names to make keyName setting more clear * refactor(FileUpload): allow passing container className string * feat(GoogleClient): Gemini support * refactor(GoogleClient): alternate stream speed for Gemini models * feat(Gemini): styling/settings configuration for Gemini * refactor(GoogleClient): substract max response tokens from max context tokens if context is above 32k (I/O max is combined between the two) * refactor(tokens): correct google max token counts and subtract max response tokens when input/output count are combined towards max context count * feat(google/initializeClient): handle both local and user_provided credentials and write tests * fix(GoogleClient): catch if credentials are undefined, handle if serviceKey is string or object correctly, handle no examples passed, throw error if not a Generative Language model and no service account JSON key is provided, throw error if it is a Generative m odel, but not google API key was provided * refactor(loadAsyncEndpoints/google): activate Google endpoint if either the service key JSON file is provided in /api/data, or a GOOGLE_KEY is defined. * docs: updated Google configuration * fix(ci): Mock import of Service Account Key JSON file (auth.json) * Update apis_and_tokens.md * feat: increase max output tokens slider for gemini pro * refactor(GoogleSettings): handle max and default maxOutputTokens on model change * chore: add sensitive redact regex * docs: add warning about data privacy * Update apis_and_tokens.md
157 lines
4.2 KiB
JavaScript
157 lines
4.2 KiB
JavaScript
const { EModelEndpoint } = require('librechat-data-provider');
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const models = [
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'text-davinci-003',
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'text-davinci-002',
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'text-davinci-001',
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'text-curie-001',
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'text-babbage-001',
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'text-ada-001',
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'davinci',
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'curie',
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'babbage',
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'ada',
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'code-davinci-002',
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'code-davinci-001',
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'code-cushman-002',
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'code-cushman-001',
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'davinci-codex',
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'cushman-codex',
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'text-davinci-edit-001',
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'code-davinci-edit-001',
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'text-embedding-ada-002',
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'text-similarity-davinci-001',
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'text-similarity-curie-001',
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'text-similarity-babbage-001',
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'text-similarity-ada-001',
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'text-search-davinci-doc-001',
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'text-search-curie-doc-001',
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'text-search-babbage-doc-001',
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'text-search-ada-doc-001',
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'code-search-babbage-code-001',
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'code-search-ada-code-001',
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'gpt2',
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'gpt-4',
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'gpt-4-0314',
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'gpt-4-32k',
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'gpt-4-32k-0314',
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'gpt-3.5-turbo',
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'gpt-3.5-turbo-0301',
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];
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// Order is important here: by model series and context size (gpt-4 then gpt-3, ascending)
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const maxTokensMap = {
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[EModelEndpoint.openAI]: {
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'gpt-4': 8191,
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'gpt-4-0613': 8191,
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'gpt-4-32k': 32767,
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'gpt-4-32k-0314': 32767,
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'gpt-4-32k-0613': 32767,
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'gpt-3.5-turbo': 4095,
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'gpt-3.5-turbo-0613': 4095,
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'gpt-3.5-turbo-0301': 4095,
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'gpt-3.5-turbo-16k': 15999,
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'gpt-3.5-turbo-16k-0613': 15999,
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'gpt-3.5-turbo-1106': 16380, // -5 from max
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'gpt-4-1106': 127995, // -5 from max
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},
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[EModelEndpoint.google]: {
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/* Max I/O is combined so we subtract the amount from max response tokens for actual total */
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gemini: 32750, // -10 from max
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'text-bison-32k': 32758, // -10 from max
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'chat-bison-32k': 32758, // -10 from max
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'code-bison-32k': 32758, // -10 from max
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'codechat-bison-32k': 32758,
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/* Codey, -5 from max: 6144 */
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'code-': 6139,
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'codechat-': 6139,
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/* PaLM2, -5 from max: 8192 */
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'text-': 8187,
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'chat-': 8187,
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},
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[EModelEndpoint.anthropic]: {
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'claude-2.1': 200000,
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'claude-': 100000,
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},
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};
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/**
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* Retrieves the maximum tokens for a given model name. If the exact model name isn't found,
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* it searches for partial matches within the model name, checking keys in reverse order.
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*
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* @param {string} modelName - The name of the model to look up.
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* @param {string} endpoint - The endpoint (default is 'openAI').
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* @returns {number|undefined} The maximum tokens for the given model or undefined if no match is found.
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*
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* @example
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* getModelMaxTokens('gpt-4-32k-0613'); // Returns 32767
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* getModelMaxTokens('gpt-4-32k-unknown'); // Returns 32767
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* getModelMaxTokens('unknown-model'); // Returns undefined
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*/
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function getModelMaxTokens(modelName, endpoint = EModelEndpoint.openAI) {
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if (typeof modelName !== 'string') {
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return undefined;
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}
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const tokensMap = maxTokensMap[endpoint];
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if (!tokensMap) {
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return undefined;
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}
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if (tokensMap[modelName]) {
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return tokensMap[modelName];
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}
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const keys = Object.keys(tokensMap);
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for (let i = keys.length - 1; i >= 0; i--) {
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if (modelName.includes(keys[i])) {
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return tokensMap[keys[i]];
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}
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}
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return undefined;
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}
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/**
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* Retrieves the model name key for a given model name input. If the exact model name isn't found,
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* it searches for partial matches within the model name, checking keys in reverse order.
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*
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* @param {string} modelName - The name of the model to look up.
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* @param {string} endpoint - The endpoint (default is 'openAI').
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* @returns {string|undefined} The model name key for the given model; returns input if no match is found and is string.
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*
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* @example
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* matchModelName('gpt-4-32k-0613'); // Returns 'gpt-4-32k-0613'
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* matchModelName('gpt-4-32k-unknown'); // Returns 'gpt-4-32k'
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* matchModelName('unknown-model'); // Returns undefined
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*/
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function matchModelName(modelName, endpoint = EModelEndpoint.openAI) {
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if (typeof modelName !== 'string') {
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return undefined;
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}
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const tokensMap = maxTokensMap[endpoint];
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if (!tokensMap) {
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return modelName;
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}
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if (tokensMap[modelName]) {
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return modelName;
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}
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const keys = Object.keys(tokensMap);
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for (let i = keys.length - 1; i >= 0; i--) {
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if (modelName.includes(keys[i])) {
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return keys[i];
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}
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}
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return modelName;
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}
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module.exports = {
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tiktokenModels: new Set(models),
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maxTokensMap,
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getModelMaxTokens,
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matchModelName,
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};
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