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https://github.com/danny-avila/LibreChat.git
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561ce8e86a
* 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
32 lines
1.2 KiB
JavaScript
32 lines
1.2 KiB
JavaScript
const { EModelEndpoint, defaultModels } = require('librechat-data-provider');
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const { useAzurePlugins } = require('~/server/services/Config/EndpointService').config;
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const {
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getOpenAIModels,
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getChatGPTBrowserModels,
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getAnthropicModels,
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} = require('~/server/services/ModelService');
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const fitlerAssistantModels = (str) => {
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return /gpt-4|gpt-3\\.5/i.test(str) && !/vision|instruct/i.test(str);
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};
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async function loadDefaultModels() {
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const openAI = await getOpenAIModels();
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const anthropic = getAnthropicModels();
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const chatGPTBrowser = getChatGPTBrowserModels();
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const azureOpenAI = await getOpenAIModels({ azure: true });
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const gptPlugins = await getOpenAIModels({ azure: useAzurePlugins, plugins: true });
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return {
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[EModelEndpoint.openAI]: openAI,
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[EModelEndpoint.azureOpenAI]: azureOpenAI,
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[EModelEndpoint.assistant]: openAI.filter(fitlerAssistantModels),
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[EModelEndpoint.google]: defaultModels[EModelEndpoint.google],
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[EModelEndpoint.bingAI]: ['BingAI', 'Sydney'],
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[EModelEndpoint.chatGPTBrowser]: chatGPTBrowser,
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[EModelEndpoint.gptPlugins]: gptPlugins,
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[EModelEndpoint.anthropic]: anthropic,
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};
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}
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module.exports = loadDefaultModels;
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