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feat: Google Gemini ❇️ (#1355)

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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
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Danny Avila 2023-12-15 02:18:07 -05:00 • committed by GitHub
parent d259431316
commit 561ce8e86a
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17
api/server/services/Config/loadDefaultModels.js
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@ -1,10 +1,10 @@
const { EModelEndpoint, defaultModels } = require('librechat-data-provider');
const { useAzurePlugins } = require('~/server/services/Config/EndpointService').config;
const {
getOpenAIModels,
getChatGPTBrowserModels,
getAnthropicModels,
} = require('~/server/services/ModelService');
const { EModelEndpoint } = require('librechat-data-provider');
const { useAzurePlugins } = require('~/server/services/Config/EndpointService').config;
const fitlerAssistantModels = (str) => {
return /gpt-4|gpt-3\\.5/i.test(str) && !/vision|instruct/i.test(str);
@ -21,18 +21,7 @@ async function loadDefaultModels() {
[EModelEndpoint.openAI]: openAI,
[EModelEndpoint.azureOpenAI]: azureOpenAI,
[EModelEndpoint.assistant]: openAI.filter(fitlerAssistantModels),
[EModelEndpoint.google]: [
'chat-bison',
'chat-bison-32k',
'codechat-bison',
'codechat-bison-32k',
'text-bison',
'text-bison-32k',
'text-unicorn',
'code-gecko',
'code-bison',
'code-bison-32k',
],
[EModelEndpoint.google]: defaultModels[EModelEndpoint.google],
[EModelEndpoint.bingAI]: ['BingAI', 'Sydney'],
[EModelEndpoint.chatGPTBrowser]: chatGPTBrowser,
[EModelEndpoint.gptPlugins]: gptPlugins,