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🤖 feat: OpenAI Assistants v2 (initial support) (#2781)
* 🤖 Assistants V2 Support: Part 1 - Separated Azure Assistants to its own endpoint - File Search / Vector Store integration is incomplete, but can toggle and use storage from playground - Code Interpreter resource files can be added but not deleted - GPT-4o is supported - Many improvements to the Assistants Endpoint overall data-provider v2 changes copy existing route as v1 chore: rename new endpoint to reduce comparison operations and add new azure filesource api: add azureAssistants part 1 force use of version for assistants/assistantsAzure chore: switch name back to azureAssistants refactor type version: string | number Ensure assistants endpoints have version set fix: isArchived type issue in ConversationListParams refactor: update assistants mutations/queries with endpoint/version definitions, update Assistants Map structure chore: FilePreview component ExtendedFile type assertion feat: isAssistantsEndpoint helper chore: remove unused useGenerations chore(buildTree): type issue chore(Advanced): type issue (unused component, maybe in future) first pass for multi-assistant endpoint rewrite fix(listAssistants): pass params correctly feat: list separate assistants by endpoint fix(useTextarea): access assistantMap correctly fix: assistant endpoint switching, resetting ID fix: broken during rewrite, selecting assistant mention fix: set/invalidate assistants endpoint query data correctly feat: Fix issue with assistant ID not being reset correctly getOpenAIClient helper function feat: add toast for assistant deletion fix: assistants delete right after create issue for azure fix: assistant patching refactor: actions to use getOpenAIClient refactor: consolidate logic into helpers file fix: issue where conversation data was not initially available v1 chat support refactor(spendTokens): only early return if completionTokens isNaN fix(OpenAIClient): ensure spendTokens has all necessary params refactor: route/controller logic fix(assistants/initializeClient): use defaultHeaders field fix: sanitize default operation id chore: bump openai package first pass v2 action service feat: retroactive domain parsing for actions added via v1 feat: delete db records of actions/assistants on openai assistant deletion chore: remove vision tools from v2 assistants feat: v2 upload and delete assistant vision images WIP first pass, thread attachments fix: show assistant vision files (save local/firebase copy) v2 image continue fix: annotations fix: refine annotations show analyze as error if is no longer submitting before progress reaches 1 and show file_search as retrieval tool fix: abort run, undefined endpoint issue refactor: consolidate capabilities logic and anticipate versioning frontend version 2 changes fix: query selection and filter add endpoint to unknown filepath add file ids to resource, deleting in progress enable/disable file search remove version log * 🤖 Assistants V2 Support: Part 2 🎹 fix: Autocompletion Chrome Bug on Action API Key Input chore: remove `useOriginNavigate` chore: set correct OpenAI Storage Source fix: azure file deletions, instantiate clients by source for deletion update code interpret files info feat: deleteResourceFileId chore: increase poll interval as azure easily rate limits fix: openai file deletions, TODO: evaluate rejected deletion settled promises to determine which to delete from db records file source icons update table file filters chore: file search info and versioning fix: retrieval update with necessary tool_resources if specified fix(useMentions): add optional chaining in case listMap value is undefined fix: force assistant avatar roundedness fix: azure assistants, check correct flag chore: bump data-provider * fix: merge conflict * ci: fix backend tests due to new updates * chore: update .env.example * meilisearch improvements * localization updates * chore: update comparisons * feat: add additional metadata: endpoint, author ID * chore: azureAssistants ENDPOINTS exclusion warning
This commit is contained in:
Danny Avila
GitHub
parent
af8bcb08d6
commit
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158 changed files with 4184 additions and 1204 deletions
650
api/server/controllers/assistants/chatV1.js
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650
api/server/controllers/assistants/chatV1.js
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const { v4 } = require('uuid');
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const {
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Constants,
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RunStatus,
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CacheKeys,
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ContentTypes,
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EModelEndpoint,
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ViolationTypes,
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ImageVisionTool,
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checkOpenAIStorage,
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AssistantStreamEvents,
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} = require('librechat-data-provider');
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const {
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initThread,
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recordUsage,
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saveUserMessage,
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checkMessageGaps,
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addThreadMetadata,
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saveAssistantMessage,
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} = require('~/server/services/Threads');
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const { sendResponse, sendMessage, sleep, isEnabled, countTokens } = require('~/server/utils');
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const { runAssistant, createOnTextProgress } = require('~/server/services/AssistantService');
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const { formatMessage, createVisionPrompt } = require('~/app/clients/prompts');
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const { createRun, StreamRunManager } = require('~/server/services/Runs');
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const { addTitle } = require('~/server/services/Endpoints/assistants');
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const { getTransactions } = require('~/models/Transaction');
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const checkBalance = require('~/models/checkBalance');
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const { getConvo } = require('~/models/Conversation');
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const getLogStores = require('~/cache/getLogStores');
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const { getModelMaxTokens } = require('~/utils');
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const { getOpenAIClient } = require('./helpers');
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const { logger } = require('~/config');
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const { handleAbortError } = require('~/server/middleware');
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const ten_minutes = 1000 * 60 * 10;
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/**
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* @route POST /
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* @desc Chat with an assistant
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* @access Public
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* @param {Express.Request} req - The request object, containing the request data.
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* @param {Express.Response} res - The response object, used to send back a response.
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* @returns {void}
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*/
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const chatV1 = async (req, res) => {
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logger.debug('[/assistants/chat/] req.body', req.body);
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const {
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text,
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model,
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endpoint,
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files = [],
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promptPrefix,
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assistant_id,
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instructions,
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thread_id: _thread_id,
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messageId: _messageId,
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conversationId: convoId,
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parentMessageId: _parentId = Constants.NO_PARENT,
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} = req.body;
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/** @type {Partial<TAssistantEndpoint>} */
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const assistantsConfig = req.app.locals?.[endpoint];
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if (assistantsConfig) {
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const { supportedIds, excludedIds } = assistantsConfig;
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const error = { message: 'Assistant not supported' };
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if (supportedIds?.length && !supportedIds.includes(assistant_id)) {
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return await handleAbortError(res, req, error, {
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sender: 'System',
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conversationId: convoId,
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messageId: v4(),
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parentMessageId: _messageId,
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error,
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});
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} else if (excludedIds?.length && excludedIds.includes(assistant_id)) {
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return await handleAbortError(res, req, error, {
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sender: 'System',
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conversationId: convoId,
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messageId: v4(),
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parentMessageId: _messageId,
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});
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}
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}
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/** @type {OpenAIClient} */
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let openai;
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/** @type {string|undefined} - the current thread id */
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let thread_id = _thread_id;
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/** @type {string|undefined} - the current run id */
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let run_id;
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/** @type {string|undefined} - the parent messageId */
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let parentMessageId = _parentId;
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/** @type {TMessage[]} */
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let previousMessages = [];
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/** @type {import('librechat-data-provider').TConversation | null} */
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let conversation = null;
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/** @type {string[]} */
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let file_ids = [];
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/** @type {Set<string>} */
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let attachedFileIds = new Set();
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/** @type {TMessage | null} */
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let requestMessage = null;
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/** @type {undefined | Promise<ChatCompletion>} */
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let visionPromise;
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const userMessageId = v4();
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const responseMessageId = v4();
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/** @type {string} - The conversation UUID - created if undefined */
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const conversationId = convoId ?? v4();
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const cache = getLogStores(CacheKeys.ABORT_KEYS);
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const cacheKey = `${req.user.id}:${conversationId}`;
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/** @type {Run | undefined} - The completed run, undefined if incomplete */
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let completedRun;
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const handleError = async (error) => {
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const defaultErrorMessage =
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'The Assistant run failed to initialize. Try sending a message in a new conversation.';
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const messageData = {
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thread_id,
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assistant_id,
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conversationId,
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parentMessageId,
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sender: 'System',
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user: req.user.id,
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shouldSaveMessage: false,
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messageId: responseMessageId,
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endpoint,
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};
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if (error.message === 'Run cancelled') {
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return res.end();
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} else if (error.message === 'Request closed' && completedRun) {
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return;
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} else if (error.message === 'Request closed') {
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logger.debug('[/assistants/chat/] Request aborted on close');
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} else if (/Files.*are invalid/.test(error.message)) {
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const errorMessage = `Files are invalid, or may not have uploaded yet.${
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endpoint === EModelEndpoint.azureAssistants
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? ' If using Azure OpenAI, files are only available in the region of the assistant\'s model at the time of upload.'
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: ''
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}`;
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return sendResponse(res, messageData, errorMessage);
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} else if (error?.message?.includes('string too long')) {
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return sendResponse(
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res,
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messageData,
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'Message too long. The Assistants API has a limit of 32,768 characters per message. Please shorten it and try again.',
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);
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} else if (error?.message?.includes(ViolationTypes.TOKEN_BALANCE)) {
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return sendResponse(res, messageData, error.message);
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} else {
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logger.error('[/assistants/chat/]', error);
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}
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if (!openai || !thread_id || !run_id) {
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return sendResponse(res, messageData, defaultErrorMessage);
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}
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await sleep(2000);
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try {
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const status = await cache.get(cacheKey);
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if (status === 'cancelled') {
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logger.debug('[/assistants/chat/] Run already cancelled');
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return res.end();
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}
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await cache.delete(cacheKey);
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const cancelledRun = await openai.beta.threads.runs.cancel(thread_id, run_id);
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logger.debug('[/assistants/chat/] Cancelled run:', cancelledRun);
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} catch (error) {
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logger.error('[/assistants/chat/] Error cancelling run', error);
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}
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await sleep(2000);
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let run;
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try {
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run = await openai.beta.threads.runs.retrieve(thread_id, run_id);
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await recordUsage({
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...run.usage,
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model: run.model,
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user: req.user.id,
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conversationId,
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});
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} catch (error) {
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logger.error('[/assistants/chat/] Error fetching or processing run', error);
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}
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let finalEvent;
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try {
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const runMessages = await checkMessageGaps({
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openai,
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run_id,
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endpoint,
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thread_id,
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conversationId,
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latestMessageId: responseMessageId,
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});
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const errorContentPart = {
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text: {
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value:
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error?.message ?? 'There was an error processing your request. Please try again later.',
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},
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type: ContentTypes.ERROR,
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};
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if (!Array.isArray(runMessages[runMessages.length - 1]?.content)) {
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runMessages[runMessages.length - 1].content = [errorContentPart];
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} else {
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const contentParts = runMessages[runMessages.length - 1].content;
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for (let i = 0; i < contentParts.length; i++) {
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const currentPart = contentParts[i];
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/** @type {CodeToolCall | RetrievalToolCall | FunctionToolCall | undefined} */
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const toolCall = currentPart?.[ContentTypes.TOOL_CALL];
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if (
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toolCall &&
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toolCall?.function &&
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!(toolCall?.function?.output || toolCall?.function?.output?.length)
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) {
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contentParts[i] = {
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...currentPart,
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[ContentTypes.TOOL_CALL]: {
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...toolCall,
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function: {
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...toolCall.function,
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output: 'error processing tool',
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},
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},
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};
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}
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}
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runMessages[runMessages.length - 1].content.push(errorContentPart);
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}
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finalEvent = {
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final: true,
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conversation: await getConvo(req.user.id, conversationId),
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runMessages,
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};
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} catch (error) {
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logger.error('[/assistants/chat/] Error finalizing error process', error);
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return sendResponse(res, messageData, 'The Assistant run failed');
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}
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return sendResponse(res, finalEvent);
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};
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try {
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res.on('close', async () => {
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if (!completedRun) {
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await handleError(new Error('Request closed'));
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}
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});
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if (convoId && !_thread_id) {
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completedRun = true;
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throw new Error('Missing thread_id for existing conversation');
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}
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if (!assistant_id) {
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completedRun = true;
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throw new Error('Missing assistant_id');
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}
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const checkBalanceBeforeRun = async () => {
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if (!isEnabled(process.env.CHECK_BALANCE)) {
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return;
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}
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const transactions =
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(await getTransactions({
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user: req.user.id,
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context: 'message',
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conversationId,
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})) ?? [];
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const totalPreviousTokens = Math.abs(
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transactions.reduce((acc, curr) => acc + curr.rawAmount, 0),
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);
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// TODO: make promptBuffer a config option; buffer for titles, needs buffer for system instructions
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const promptBuffer = parentMessageId === Constants.NO_PARENT && !_thread_id ? 200 : 0;
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// 5 is added for labels
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let promptTokens = (await countTokens(text + (promptPrefix ?? ''))) + 5;
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promptTokens += totalPreviousTokens + promptBuffer;
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// Count tokens up to the current context window
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promptTokens = Math.min(promptTokens, getModelMaxTokens(model));
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await checkBalance({
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req,
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res,
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txData: {
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model,
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user: req.user.id,
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tokenType: 'prompt',
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amount: promptTokens,
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},
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});
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};
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const { openai: _openai, client } = await getOpenAIClient({
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req,
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res,
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endpointOption: req.body.endpointOption,
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initAppClient: true,
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});
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openai = _openai;
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if (previousMessages.length) {
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parentMessageId = previousMessages[previousMessages.length - 1].messageId;
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}
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let userMessage = {
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role: 'user',
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content: text,
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metadata: {
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messageId: userMessageId,
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},
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};
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/** @type {CreateRunBody | undefined} */
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const body = {
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assistant_id,
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model,
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};
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if (promptPrefix) {
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body.additional_instructions = promptPrefix;
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}
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if (instructions) {
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body.instructions = instructions;
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}
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const getRequestFileIds = async () => {
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let thread_file_ids = [];
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if (convoId) {
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const convo = await getConvo(req.user.id, convoId);
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if (convo && convo.file_ids) {
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thread_file_ids = convo.file_ids;
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}
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}
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file_ids = files.map(({ file_id }) => file_id);
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if (file_ids.length || thread_file_ids.length) {
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userMessage.file_ids = file_ids;
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attachedFileIds = new Set([...file_ids, ...thread_file_ids]);
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}
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};
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const addVisionPrompt = async () => {
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if (!req.body.endpointOption.attachments) {
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return;
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}
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/** @type {MongoFile[]} */
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const attachments = await req.body.endpointOption.attachments;
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if (attachments && attachments.every((attachment) => checkOpenAIStorage(attachment.source))) {
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return;
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}
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const assistant = await openai.beta.assistants.retrieve(assistant_id);
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const visionToolIndex = assistant.tools.findIndex(
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(tool) => tool?.function && tool?.function?.name === ImageVisionTool.function.name,
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);
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if (visionToolIndex === -1) {
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return;
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}
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let visionMessage = {
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role: 'user',
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content: '',
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};
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const files = await client.addImageURLs(visionMessage, attachments);
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if (!visionMessage.image_urls?.length) {
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return;
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}
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const imageCount = visionMessage.image_urls.length;
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const plural = imageCount > 1;
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visionMessage.content = createVisionPrompt(plural);
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visionMessage = formatMessage({ message: visionMessage, endpoint: EModelEndpoint.openAI });
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visionPromise = openai.chat.completions.create({
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model: 'gpt-4-vision-preview',
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messages: [visionMessage],
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max_tokens: 4000,
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});
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const pluralized = plural ? 's' : '';
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body.additional_instructions = `${
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body.additional_instructions ? `${body.additional_instructions}\n` : ''
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}The user has uploaded ${imageCount} image${pluralized}.
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Use the \`${ImageVisionTool.function.name}\` tool to retrieve ${
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plural ? '' : 'a '
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}detailed text description${pluralized} for ${plural ? 'each' : 'the'} image${pluralized}.`;
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return files;
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};
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const initializeThread = async () => {
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/** @type {[ undefined | MongoFile[]]}*/
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const [processedFiles] = await Promise.all([addVisionPrompt(), getRequestFileIds()]);
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// TODO: may allow multiple messages to be created beforehand in a future update
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const initThreadBody = {
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messages: [userMessage],
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metadata: {
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user: req.user.id,
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conversationId,
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},
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};
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if (processedFiles) {
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for (const file of processedFiles) {
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if (!checkOpenAIStorage(file.source)) {
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attachedFileIds.delete(file.file_id);
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const index = file_ids.indexOf(file.file_id);
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if (index > -1) {
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file_ids.splice(index, 1);
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}
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}
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}
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userMessage.file_ids = file_ids;
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}
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const result = await initThread({ openai, body: initThreadBody, thread_id });
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thread_id = result.thread_id;
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|
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createOnTextProgress({
|
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openai,
|
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conversationId,
|
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userMessageId,
|
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messageId: responseMessageId,
|
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thread_id,
|
||||
});
|
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|
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requestMessage = {
|
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user: req.user.id,
|
||||
text,
|
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messageId: userMessageId,
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parentMessageId,
|
||||
// TODO: make sure client sends correct format for `files`, use zod
|
||||
files,
|
||||
file_ids,
|
||||
conversationId,
|
||||
isCreatedByUser: true,
|
||||
assistant_id,
|
||||
thread_id,
|
||||
model: assistant_id,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
previousMessages.push(requestMessage);
|
||||
|
||||
/* asynchronous */
|
||||
saveUserMessage({ ...requestMessage, model });
|
||||
|
||||
conversation = {
|
||||
conversationId,
|
||||
endpoint,
|
||||
promptPrefix: promptPrefix,
|
||||
instructions: instructions,
|
||||
assistant_id,
|
||||
// model,
|
||||
};
|
||||
|
||||
if (file_ids.length) {
|
||||
conversation.file_ids = file_ids;
|
||||
}
|
||||
};
|
||||
|
||||
const promises = [initializeThread(), checkBalanceBeforeRun()];
|
||||
await Promise.all(promises);
|
||||
|
||||
const sendInitialResponse = () => {
|
||||
sendMessage(res, {
|
||||
sync: true,
|
||||
conversationId,
|
||||
// messages: previousMessages,
|
||||
requestMessage,
|
||||
responseMessage: {
|
||||
user: req.user.id,
|
||||
messageId: openai.responseMessage.messageId,
|
||||
parentMessageId: userMessageId,
|
||||
conversationId,
|
||||
assistant_id,
|
||||
thread_id,
|
||||
model: assistant_id,
|
||||
},
|
||||
});
|
||||
};
|
||||
|
||||
/** @type {RunResponse | typeof StreamRunManager | undefined} */
|
||||
let response;
|
||||
|
||||
const processRun = async (retry = false) => {
|
||||
if (endpoint === EModelEndpoint.azureAssistants) {
|
||||
body.model = openai._options.model;
|
||||
openai.attachedFileIds = attachedFileIds;
|
||||
openai.visionPromise = visionPromise;
|
||||
if (retry) {
|
||||
response = await runAssistant({
|
||||
openai,
|
||||
thread_id,
|
||||
run_id,
|
||||
in_progress: openai.in_progress,
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
/* NOTE:
|
||||
* By default, a Run will use the model and tools configuration specified in Assistant object,
|
||||
* but you can override most of these when creating the Run for added flexibility:
|
||||
*/
|
||||
const run = await createRun({
|
||||
openai,
|
||||
thread_id,
|
||||
body,
|
||||
});
|
||||
|
||||
run_id = run.id;
|
||||
await cache.set(cacheKey, `${thread_id}:${run_id}`, ten_minutes);
|
||||
sendInitialResponse();
|
||||
|
||||
// todo: retry logic
|
||||
response = await runAssistant({ openai, thread_id, run_id });
|
||||
return;
|
||||
}
|
||||
|
||||
/** @type {{[AssistantStreamEvents.ThreadRunCreated]: (event: ThreadRunCreated) => Promise<void>}} */
|
||||
const handlers = {
|
||||
[AssistantStreamEvents.ThreadRunCreated]: async (event) => {
|
||||
await cache.set(cacheKey, `${thread_id}:${event.data.id}`, ten_minutes);
|
||||
run_id = event.data.id;
|
||||
sendInitialResponse();
|
||||
},
|
||||
};
|
||||
|
||||
const streamRunManager = new StreamRunManager({
|
||||
req,
|
||||
res,
|
||||
openai,
|
||||
handlers,
|
||||
thread_id,
|
||||
visionPromise,
|
||||
attachedFileIds,
|
||||
responseMessage: openai.responseMessage,
|
||||
// streamOptions: {
|
||||
|
||||
// },
|
||||
});
|
||||
|
||||
await streamRunManager.runAssistant({
|
||||
thread_id,
|
||||
body,
|
||||
});
|
||||
|
||||
response = streamRunManager;
|
||||
};
|
||||
|
||||
await processRun();
|
||||
logger.debug('[/assistants/chat/] response', {
|
||||
run: response.run,
|
||||
steps: response.steps,
|
||||
});
|
||||
|
||||
if (response.run.status === RunStatus.CANCELLED) {
|
||||
logger.debug('[/assistants/chat/] Run cancelled, handled by `abortRun`');
|
||||
return res.end();
|
||||
}
|
||||
|
||||
if (response.run.status === RunStatus.IN_PROGRESS) {
|
||||
processRun(true);
|
||||
}
|
||||
|
||||
completedRun = response.run;
|
||||
|
||||
/** @type {ResponseMessage} */
|
||||
const responseMessage = {
|
||||
...(response.responseMessage ?? response.finalMessage),
|
||||
parentMessageId: userMessageId,
|
||||
conversationId,
|
||||
user: req.user.id,
|
||||
assistant_id,
|
||||
thread_id,
|
||||
model: assistant_id,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
sendMessage(res, {
|
||||
final: true,
|
||||
conversation,
|
||||
requestMessage: {
|
||||
parentMessageId,
|
||||
thread_id,
|
||||
},
|
||||
});
|
||||
res.end();
|
||||
|
||||
await saveAssistantMessage({ ...responseMessage, model });
|
||||
|
||||
if (parentMessageId === Constants.NO_PARENT && !_thread_id) {
|
||||
addTitle(req, {
|
||||
text,
|
||||
responseText: response.text,
|
||||
conversationId,
|
||||
client,
|
||||
});
|
||||
}
|
||||
|
||||
await addThreadMetadata({
|
||||
openai,
|
||||
thread_id,
|
||||
messageId: responseMessage.messageId,
|
||||
messages: response.messages,
|
||||
});
|
||||
|
||||
if (!response.run.usage) {
|
||||
await sleep(3000);
|
||||
completedRun = await openai.beta.threads.runs.retrieve(thread_id, response.run.id);
|
||||
if (completedRun.usage) {
|
||||
await recordUsage({
|
||||
...completedRun.usage,
|
||||
user: req.user.id,
|
||||
model: completedRun.model ?? model,
|
||||
conversationId,
|
||||
});
|
||||
}
|
||||
} else {
|
||||
await recordUsage({
|
||||
...response.run.usage,
|
||||
user: req.user.id,
|
||||
model: response.run.model ?? model,
|
||||
conversationId,
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
await handleError(error);
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = chatV1;
|
||||
618
api/server/controllers/assistants/chatV2.js
Normal file
618
api/server/controllers/assistants/chatV2.js
Normal file
|
|
@ -0,0 +1,618 @@
|
|||
const { v4 } = require('uuid');
|
||||
const {
|
||||
Constants,
|
||||
RunStatus,
|
||||
CacheKeys,
|
||||
ContentTypes,
|
||||
ToolCallTypes,
|
||||
EModelEndpoint,
|
||||
ViolationTypes,
|
||||
retrievalMimeTypes,
|
||||
AssistantStreamEvents,
|
||||
} = require('librechat-data-provider');
|
||||
const {
|
||||
initThread,
|
||||
recordUsage,
|
||||
saveUserMessage,
|
||||
checkMessageGaps,
|
||||
addThreadMetadata,
|
||||
saveAssistantMessage,
|
||||
} = require('~/server/services/Threads');
|
||||
const { sendResponse, sendMessage, sleep, isEnabled, countTokens } = require('~/server/utils');
|
||||
const { runAssistant, createOnTextProgress } = require('~/server/services/AssistantService');
|
||||
const { createRun, StreamRunManager } = require('~/server/services/Runs');
|
||||
const { addTitle } = require('~/server/services/Endpoints/assistants');
|
||||
const { getTransactions } = require('~/models/Transaction');
|
||||
const checkBalance = require('~/models/checkBalance');
|
||||
const { getConvo } = require('~/models/Conversation');
|
||||
const getLogStores = require('~/cache/getLogStores');
|
||||
const { getModelMaxTokens } = require('~/utils');
|
||||
const { getOpenAIClient } = require('./helpers');
|
||||
const { logger } = require('~/config');
|
||||
|
||||
const { handleAbortError } = require('~/server/middleware');
|
||||
|
||||
const ten_minutes = 1000 * 60 * 10;
|
||||
|
||||
/**
|
||||
* @route POST /
|
||||
* @desc Chat with an assistant
|
||||
* @access Public
|
||||
* @param {Express.Request} req - The request object, containing the request data.
|
||||
* @param {Express.Response} res - The response object, used to send back a response.
|
||||
* @returns {void}
|
||||
*/
|
||||
const chatV2 = async (req, res) => {
|
||||
logger.debug('[/assistants/chat/] req.body', req.body);
|
||||
|
||||
/** @type {{ files: MongoFile[]}} */
|
||||
const {
|
||||
text,
|
||||
model,
|
||||
endpoint,
|
||||
files = [],
|
||||
promptPrefix,
|
||||
assistant_id,
|
||||
instructions,
|
||||
thread_id: _thread_id,
|
||||
messageId: _messageId,
|
||||
conversationId: convoId,
|
||||
parentMessageId: _parentId = Constants.NO_PARENT,
|
||||
} = req.body;
|
||||
|
||||
/** @type {Partial<TAssistantEndpoint>} */
|
||||
const assistantsConfig = req.app.locals?.[endpoint];
|
||||
|
||||
if (assistantsConfig) {
|
||||
const { supportedIds, excludedIds } = assistantsConfig;
|
||||
const error = { message: 'Assistant not supported' };
|
||||
if (supportedIds?.length && !supportedIds.includes(assistant_id)) {
|
||||
return await handleAbortError(res, req, error, {
|
||||
sender: 'System',
|
||||
conversationId: convoId,
|
||||
messageId: v4(),
|
||||
parentMessageId: _messageId,
|
||||
error,
|
||||
});
|
||||
} else if (excludedIds?.length && excludedIds.includes(assistant_id)) {
|
||||
return await handleAbortError(res, req, error, {
|
||||
sender: 'System',
|
||||
conversationId: convoId,
|
||||
messageId: v4(),
|
||||
parentMessageId: _messageId,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
/** @type {OpenAIClient} */
|
||||
let openai;
|
||||
/** @type {string|undefined} - the current thread id */
|
||||
let thread_id = _thread_id;
|
||||
/** @type {string|undefined} - the current run id */
|
||||
let run_id;
|
||||
/** @type {string|undefined} - the parent messageId */
|
||||
let parentMessageId = _parentId;
|
||||
/** @type {TMessage[]} */
|
||||
let previousMessages = [];
|
||||
/** @type {import('librechat-data-provider').TConversation | null} */
|
||||
let conversation = null;
|
||||
/** @type {string[]} */
|
||||
let file_ids = [];
|
||||
/** @type {Set<string>} */
|
||||
let attachedFileIds = new Set();
|
||||
/** @type {TMessage | null} */
|
||||
let requestMessage = null;
|
||||
|
||||
const userMessageId = v4();
|
||||
const responseMessageId = v4();
|
||||
|
||||
/** @type {string} - The conversation UUID - created if undefined */
|
||||
const conversationId = convoId ?? v4();
|
||||
|
||||
const cache = getLogStores(CacheKeys.ABORT_KEYS);
|
||||
const cacheKey = `${req.user.id}:${conversationId}`;
|
||||
|
||||
/** @type {Run | undefined} - The completed run, undefined if incomplete */
|
||||
let completedRun;
|
||||
|
||||
const handleError = async (error) => {
|
||||
const defaultErrorMessage =
|
||||
'The Assistant run failed to initialize. Try sending a message in a new conversation.';
|
||||
const messageData = {
|
||||
thread_id,
|
||||
assistant_id,
|
||||
conversationId,
|
||||
parentMessageId,
|
||||
sender: 'System',
|
||||
user: req.user.id,
|
||||
shouldSaveMessage: false,
|
||||
messageId: responseMessageId,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
if (error.message === 'Run cancelled') {
|
||||
return res.end();
|
||||
} else if (error.message === 'Request closed' && completedRun) {
|
||||
return;
|
||||
} else if (error.message === 'Request closed') {
|
||||
logger.debug('[/assistants/chat/] Request aborted on close');
|
||||
} else if (/Files.*are invalid/.test(error.message)) {
|
||||
const errorMessage = `Files are invalid, or may not have uploaded yet.${
|
||||
endpoint === EModelEndpoint.azureAssistants
|
||||
? ' If using Azure OpenAI, files are only available in the region of the assistant\'s model at the time of upload.'
|
||||
: ''
|
||||
}`;
|
||||
return sendResponse(res, messageData, errorMessage);
|
||||
} else if (error?.message?.includes('string too long')) {
|
||||
return sendResponse(
|
||||
res,
|
||||
messageData,
|
||||
'Message too long. The Assistants API has a limit of 32,768 characters per message. Please shorten it and try again.',
|
||||
);
|
||||
} else if (error?.message?.includes(ViolationTypes.TOKEN_BALANCE)) {
|
||||
return sendResponse(res, messageData, error.message);
|
||||
} else {
|
||||
logger.error('[/assistants/chat/]', error);
|
||||
}
|
||||
|
||||
if (!openai || !thread_id || !run_id) {
|
||||
return sendResponse(res, messageData, defaultErrorMessage);
|
||||
}
|
||||
|
||||
await sleep(2000);
|
||||
|
||||
try {
|
||||
const status = await cache.get(cacheKey);
|
||||
if (status === 'cancelled') {
|
||||
logger.debug('[/assistants/chat/] Run already cancelled');
|
||||
return res.end();
|
||||
}
|
||||
await cache.delete(cacheKey);
|
||||
const cancelledRun = await openai.beta.threads.runs.cancel(thread_id, run_id);
|
||||
logger.debug('[/assistants/chat/] Cancelled run:', cancelledRun);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/chat/] Error cancelling run', error);
|
||||
}
|
||||
|
||||
await sleep(2000);
|
||||
|
||||
let run;
|
||||
try {
|
||||
run = await openai.beta.threads.runs.retrieve(thread_id, run_id);
|
||||
await recordUsage({
|
||||
...run.usage,
|
||||
model: run.model,
|
||||
user: req.user.id,
|
||||
conversationId,
|
||||
});
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/chat/] Error fetching or processing run', error);
|
||||
}
|
||||
|
||||
let finalEvent;
|
||||
try {
|
||||
const runMessages = await checkMessageGaps({
|
||||
openai,
|
||||
run_id,
|
||||
endpoint,
|
||||
thread_id,
|
||||
conversationId,
|
||||
latestMessageId: responseMessageId,
|
||||
});
|
||||
|
||||
const errorContentPart = {
|
||||
text: {
|
||||
value:
|
||||
error?.message ?? 'There was an error processing your request. Please try again later.',
|
||||
},
|
||||
type: ContentTypes.ERROR,
|
||||
};
|
||||
|
||||
if (!Array.isArray(runMessages[runMessages.length - 1]?.content)) {
|
||||
runMessages[runMessages.length - 1].content = [errorContentPart];
|
||||
} else {
|
||||
const contentParts = runMessages[runMessages.length - 1].content;
|
||||
for (let i = 0; i < contentParts.length; i++) {
|
||||
const currentPart = contentParts[i];
|
||||
/** @type {CodeToolCall | RetrievalToolCall | FunctionToolCall | undefined} */
|
||||
const toolCall = currentPart?.[ContentTypes.TOOL_CALL];
|
||||
if (
|
||||
toolCall &&
|
||||
toolCall?.function &&
|
||||
!(toolCall?.function?.output || toolCall?.function?.output?.length)
|
||||
) {
|
||||
contentParts[i] = {
|
||||
...currentPart,
|
||||
[ContentTypes.TOOL_CALL]: {
|
||||
...toolCall,
|
||||
function: {
|
||||
...toolCall.function,
|
||||
output: 'error processing tool',
|
||||
},
|
||||
},
|
||||
};
|
||||
}
|
||||
}
|
||||
runMessages[runMessages.length - 1].content.push(errorContentPart);
|
||||
}
|
||||
|
||||
finalEvent = {
|
||||
final: true,
|
||||
conversation: await getConvo(req.user.id, conversationId),
|
||||
runMessages,
|
||||
};
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/chat/] Error finalizing error process', error);
|
||||
return sendResponse(res, messageData, 'The Assistant run failed');
|
||||
}
|
||||
|
||||
return sendResponse(res, finalEvent);
|
||||
};
|
||||
|
||||
try {
|
||||
res.on('close', async () => {
|
||||
if (!completedRun) {
|
||||
await handleError(new Error('Request closed'));
|
||||
}
|
||||
});
|
||||
|
||||
if (convoId && !_thread_id) {
|
||||
completedRun = true;
|
||||
throw new Error('Missing thread_id for existing conversation');
|
||||
}
|
||||
|
||||
if (!assistant_id) {
|
||||
completedRun = true;
|
||||
throw new Error('Missing assistant_id');
|
||||
}
|
||||
|
||||
const checkBalanceBeforeRun = async () => {
|
||||
if (!isEnabled(process.env.CHECK_BALANCE)) {
|
||||
return;
|
||||
}
|
||||
const transactions =
|
||||
(await getTransactions({
|
||||
user: req.user.id,
|
||||
context: 'message',
|
||||
conversationId,
|
||||
})) ?? [];
|
||||
|
||||
const totalPreviousTokens = Math.abs(
|
||||
transactions.reduce((acc, curr) => acc + curr.rawAmount, 0),
|
||||
);
|
||||
|
||||
// TODO: make promptBuffer a config option; buffer for titles, needs buffer for system instructions
|
||||
const promptBuffer = parentMessageId === Constants.NO_PARENT && !_thread_id ? 200 : 0;
|
||||
// 5 is added for labels
|
||||
let promptTokens = (await countTokens(text + (promptPrefix ?? ''))) + 5;
|
||||
promptTokens += totalPreviousTokens + promptBuffer;
|
||||
// Count tokens up to the current context window
|
||||
promptTokens = Math.min(promptTokens, getModelMaxTokens(model));
|
||||
|
||||
await checkBalance({
|
||||
req,
|
||||
res,
|
||||
txData: {
|
||||
model,
|
||||
user: req.user.id,
|
||||
tokenType: 'prompt',
|
||||
amount: promptTokens,
|
||||
},
|
||||
});
|
||||
};
|
||||
|
||||
const { openai: _openai, client } = await getOpenAIClient({
|
||||
req,
|
||||
res,
|
||||
endpointOption: req.body.endpointOption,
|
||||
initAppClient: true,
|
||||
});
|
||||
|
||||
openai = _openai;
|
||||
|
||||
if (previousMessages.length) {
|
||||
parentMessageId = previousMessages[previousMessages.length - 1].messageId;
|
||||
}
|
||||
|
||||
let userMessage = {
|
||||
role: 'user',
|
||||
content: [
|
||||
{
|
||||
type: ContentTypes.TEXT,
|
||||
text,
|
||||
},
|
||||
],
|
||||
metadata: {
|
||||
messageId: userMessageId,
|
||||
},
|
||||
};
|
||||
|
||||
/** @type {CreateRunBody | undefined} */
|
||||
const body = {
|
||||
assistant_id,
|
||||
model,
|
||||
};
|
||||
|
||||
if (promptPrefix) {
|
||||
body.additional_instructions = promptPrefix;
|
||||
}
|
||||
|
||||
if (instructions) {
|
||||
body.instructions = instructions;
|
||||
}
|
||||
|
||||
const getRequestFileIds = async () => {
|
||||
let thread_file_ids = [];
|
||||
if (convoId) {
|
||||
const convo = await getConvo(req.user.id, convoId);
|
||||
if (convo && convo.file_ids) {
|
||||
thread_file_ids = convo.file_ids;
|
||||
}
|
||||
}
|
||||
|
||||
if (files.length || thread_file_ids.length) {
|
||||
attachedFileIds = new Set([...file_ids, ...thread_file_ids]);
|
||||
|
||||
let attachmentIndex = 0;
|
||||
for (const file of files) {
|
||||
file_ids.push(file.file_id);
|
||||
if (file.type.startsWith('image')) {
|
||||
userMessage.content.push({
|
||||
type: ContentTypes.IMAGE_FILE,
|
||||
[ContentTypes.IMAGE_FILE]: { file_id: file.file_id },
|
||||
});
|
||||
}
|
||||
|
||||
if (!userMessage.attachments) {
|
||||
userMessage.attachments = [];
|
||||
}
|
||||
|
||||
userMessage.attachments.push({
|
||||
file_id: file.file_id,
|
||||
tools: [{ type: ToolCallTypes.CODE_INTERPRETER }],
|
||||
});
|
||||
|
||||
if (file.type.startsWith('image')) {
|
||||
continue;
|
||||
}
|
||||
|
||||
const mimeType = file.type;
|
||||
const isSupportedByRetrieval = retrievalMimeTypes.some((regex) => regex.test(mimeType));
|
||||
if (isSupportedByRetrieval) {
|
||||
userMessage.attachments[attachmentIndex].tools.push({
|
||||
type: ToolCallTypes.FILE_SEARCH,
|
||||
});
|
||||
}
|
||||
|
||||
attachmentIndex++;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const initializeThread = async () => {
|
||||
await getRequestFileIds();
|
||||
|
||||
// TODO: may allow multiple messages to be created beforehand in a future update
|
||||
const initThreadBody = {
|
||||
messages: [userMessage],
|
||||
metadata: {
|
||||
user: req.user.id,
|
||||
conversationId,
|
||||
},
|
||||
};
|
||||
|
||||
const result = await initThread({ openai, body: initThreadBody, thread_id });
|
||||
thread_id = result.thread_id;
|
||||
|
||||
createOnTextProgress({
|
||||
openai,
|
||||
conversationId,
|
||||
userMessageId,
|
||||
messageId: responseMessageId,
|
||||
thread_id,
|
||||
});
|
||||
|
||||
requestMessage = {
|
||||
user: req.user.id,
|
||||
text,
|
||||
messageId: userMessageId,
|
||||
parentMessageId,
|
||||
// TODO: make sure client sends correct format for `files`, use zod
|
||||
files,
|
||||
file_ids,
|
||||
conversationId,
|
||||
isCreatedByUser: true,
|
||||
assistant_id,
|
||||
thread_id,
|
||||
model: assistant_id,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
previousMessages.push(requestMessage);
|
||||
|
||||
/* asynchronous */
|
||||
saveUserMessage({ ...requestMessage, model });
|
||||
|
||||
conversation = {
|
||||
conversationId,
|
||||
endpoint,
|
||||
promptPrefix: promptPrefix,
|
||||
instructions: instructions,
|
||||
assistant_id,
|
||||
// model,
|
||||
};
|
||||
|
||||
if (file_ids.length) {
|
||||
conversation.file_ids = file_ids;
|
||||
}
|
||||
};
|
||||
|
||||
const promises = [initializeThread(), checkBalanceBeforeRun()];
|
||||
await Promise.all(promises);
|
||||
|
||||
const sendInitialResponse = () => {
|
||||
sendMessage(res, {
|
||||
sync: true,
|
||||
conversationId,
|
||||
// messages: previousMessages,
|
||||
requestMessage,
|
||||
responseMessage: {
|
||||
user: req.user.id,
|
||||
messageId: openai.responseMessage.messageId,
|
||||
parentMessageId: userMessageId,
|
||||
conversationId,
|
||||
assistant_id,
|
||||
thread_id,
|
||||
model: assistant_id,
|
||||
},
|
||||
});
|
||||
};
|
||||
|
||||
/** @type {RunResponse | typeof StreamRunManager | undefined} */
|
||||
let response;
|
||||
|
||||
const processRun = async (retry = false) => {
|
||||
if (endpoint === EModelEndpoint.azureAssistants) {
|
||||
body.model = openai._options.model;
|
||||
openai.attachedFileIds = attachedFileIds;
|
||||
if (retry) {
|
||||
response = await runAssistant({
|
||||
openai,
|
||||
thread_id,
|
||||
run_id,
|
||||
in_progress: openai.in_progress,
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
/* NOTE:
|
||||
* By default, a Run will use the model and tools configuration specified in Assistant object,
|
||||
* but you can override most of these when creating the Run for added flexibility:
|
||||
*/
|
||||
const run = await createRun({
|
||||
openai,
|
||||
thread_id,
|
||||
body,
|
||||
});
|
||||
|
||||
run_id = run.id;
|
||||
await cache.set(cacheKey, `${thread_id}:${run_id}`, ten_minutes);
|
||||
sendInitialResponse();
|
||||
|
||||
// todo: retry logic
|
||||
response = await runAssistant({ openai, thread_id, run_id });
|
||||
return;
|
||||
}
|
||||
|
||||
/** @type {{[AssistantStreamEvents.ThreadRunCreated]: (event: ThreadRunCreated) => Promise<void>}} */
|
||||
const handlers = {
|
||||
[AssistantStreamEvents.ThreadRunCreated]: async (event) => {
|
||||
await cache.set(cacheKey, `${thread_id}:${event.data.id}`, ten_minutes);
|
||||
run_id = event.data.id;
|
||||
sendInitialResponse();
|
||||
},
|
||||
};
|
||||
|
||||
const streamRunManager = new StreamRunManager({
|
||||
req,
|
||||
res,
|
||||
openai,
|
||||
handlers,
|
||||
thread_id,
|
||||
attachedFileIds,
|
||||
responseMessage: openai.responseMessage,
|
||||
// streamOptions: {
|
||||
|
||||
// },
|
||||
});
|
||||
|
||||
await streamRunManager.runAssistant({
|
||||
thread_id,
|
||||
body,
|
||||
});
|
||||
|
||||
response = streamRunManager;
|
||||
};
|
||||
|
||||
await processRun();
|
||||
logger.debug('[/assistants/chat/] response', {
|
||||
run: response.run,
|
||||
steps: response.steps,
|
||||
});
|
||||
|
||||
if (response.run.status === RunStatus.CANCELLED) {
|
||||
logger.debug('[/assistants/chat/] Run cancelled, handled by `abortRun`');
|
||||
return res.end();
|
||||
}
|
||||
|
||||
if (response.run.status === RunStatus.IN_PROGRESS) {
|
||||
processRun(true);
|
||||
}
|
||||
|
||||
completedRun = response.run;
|
||||
|
||||
/** @type {ResponseMessage} */
|
||||
const responseMessage = {
|
||||
...(response.responseMessage ?? response.finalMessage),
|
||||
parentMessageId: userMessageId,
|
||||
conversationId,
|
||||
user: req.user.id,
|
||||
assistant_id,
|
||||
thread_id,
|
||||
model: assistant_id,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
sendMessage(res, {
|
||||
final: true,
|
||||
conversation,
|
||||
requestMessage: {
|
||||
parentMessageId,
|
||||
thread_id,
|
||||
},
|
||||
});
|
||||
res.end();
|
||||
|
||||
await saveAssistantMessage({ ...responseMessage, model });
|
||||
|
||||
if (parentMessageId === Constants.NO_PARENT && !_thread_id) {
|
||||
addTitle(req, {
|
||||
text,
|
||||
responseText: response.text,
|
||||
conversationId,
|
||||
client,
|
||||
});
|
||||
}
|
||||
|
||||
await addThreadMetadata({
|
||||
openai,
|
||||
thread_id,
|
||||
messageId: responseMessage.messageId,
|
||||
messages: response.messages,
|
||||
});
|
||||
|
||||
if (!response.run.usage) {
|
||||
await sleep(3000);
|
||||
completedRun = await openai.beta.threads.runs.retrieve(thread_id, response.run.id);
|
||||
if (completedRun.usage) {
|
||||
await recordUsage({
|
||||
...completedRun.usage,
|
||||
user: req.user.id,
|
||||
model: completedRun.model ?? model,
|
||||
conversationId,
|
||||
});
|
||||
}
|
||||
} else {
|
||||
await recordUsage({
|
||||
...response.run.usage,
|
||||
user: req.user.id,
|
||||
model: response.run.model ?? model,
|
||||
conversationId,
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
await handleError(error);
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = chatV2;
|
||||
158
api/server/controllers/assistants/helpers.js
Normal file
158
api/server/controllers/assistants/helpers.js
Normal file
|
|
@ -0,0 +1,158 @@
|
|||
const { EModelEndpoint, CacheKeys, defaultAssistantsVersion } = require('librechat-data-provider');
|
||||
const {
|
||||
initializeClient: initAzureClient,
|
||||
} = require('~/server/services/Endpoints/azureAssistants');
|
||||
const { initializeClient } = require('~/server/services/Endpoints/assistants');
|
||||
const { getLogStores } = require('~/cache');
|
||||
|
||||
/**
|
||||
* @param {Express.Request} req
|
||||
* @param {string} [endpoint]
|
||||
* @returns {Promise<string>}
|
||||
*/
|
||||
const getCurrentVersion = async (req, endpoint) => {
|
||||
const index = req.baseUrl.lastIndexOf('/v');
|
||||
let version = index !== -1 ? req.baseUrl.substring(index + 1, index + 3) : null;
|
||||
if (!version && req.body.version) {
|
||||
version = `v${req.body.version}`;
|
||||
}
|
||||
if (!version && endpoint) {
|
||||
const cache = getLogStores(CacheKeys.CONFIG_STORE);
|
||||
const cachedEndpointsConfig = await cache.get(CacheKeys.ENDPOINT_CONFIG);
|
||||
version = `v${
|
||||
cachedEndpointsConfig?.[endpoint]?.version ?? defaultAssistantsVersion[endpoint]
|
||||
}`;
|
||||
}
|
||||
if (!version?.startsWith('v') && version.length !== 2) {
|
||||
throw new Error(`[${req.baseUrl}] Invalid version: ${version}`);
|
||||
}
|
||||
return version;
|
||||
};
|
||||
|
||||
/**
|
||||
* Asynchronously lists assistants based on provided query parameters.
|
||||
*
|
||||
* Initializes the client with the current request and response objects and lists assistants
|
||||
* according to the query parameters. This function abstracts the logic for non-Azure paths.
|
||||
*
|
||||
* @async
|
||||
* @param {object} params - The parameters object.
|
||||
* @param {object} params.req - The request object, used for initializing the client.
|
||||
* @param {object} params.res - The response object, used for initializing the client.
|
||||
* @param {string} params.version - The API version to use.
|
||||
* @param {object} params.query - The query parameters to list assistants (e.g., limit, order).
|
||||
* @returns {Promise<object>} A promise that resolves to the response from the `openai.beta.assistants.list` method call.
|
||||
*/
|
||||
const listAssistants = async ({ req, res, version, query }) => {
|
||||
const { openai } = await getOpenAIClient({ req, res, version });
|
||||
return openai.beta.assistants.list(query);
|
||||
};
|
||||
|
||||
/**
|
||||
* Asynchronously lists assistants for Azure configured groups.
|
||||
*
|
||||
* Iterates through Azure configured assistant groups, initializes the client with the current request and response objects,
|
||||
* lists assistants based on the provided query parameters, and merges their data alongside the model information into a single array.
|
||||
*
|
||||
* @async
|
||||
* @param {object} params - The parameters object.
|
||||
* @param {object} params.req - The request object, used for initializing the client and manipulating the request body.
|
||||
* @param {object} params.res - The response object, used for initializing the client.
|
||||
* @param {string} params.version - The API version to use.
|
||||
* @param {TAzureConfig} params.azureConfig - The Azure configuration object containing assistantGroups and groupMap.
|
||||
* @param {object} params.query - The query parameters to list assistants (e.g., limit, order).
|
||||
* @returns {Promise<AssistantListResponse>} A promise that resolves to an array of assistant data merged with their respective model information.
|
||||
*/
|
||||
const listAssistantsForAzure = async ({ req, res, version, azureConfig = {}, query }) => {
|
||||
/** @type {Array<[string, TAzureModelConfig]>} */
|
||||
const groupModelTuples = [];
|
||||
const promises = [];
|
||||
/** @type {Array<TAzureGroup>} */
|
||||
const groups = [];
|
||||
|
||||
const { groupMap, assistantGroups } = azureConfig;
|
||||
|
||||
for (const groupName of assistantGroups) {
|
||||
const group = groupMap[groupName];
|
||||
groups.push(group);
|
||||
|
||||
const currentModelTuples = Object.entries(group?.models);
|
||||
groupModelTuples.push(currentModelTuples);
|
||||
|
||||
/* The specified model is only necessary to
|
||||
fetch assistants for the shared instance */
|
||||
req.body.model = currentModelTuples[0][0];
|
||||
promises.push(listAssistants({ req, res, version, query }));
|
||||
}
|
||||
|
||||
const resolvedQueries = await Promise.all(promises);
|
||||
const data = resolvedQueries.flatMap((res, i) =>
|
||||
res.data.map((assistant) => {
|
||||
const deploymentName = assistant.model;
|
||||
const currentGroup = groups[i];
|
||||
const currentModelTuples = groupModelTuples[i];
|
||||
const firstModel = currentModelTuples[0][0];
|
||||
|
||||
if (currentGroup.deploymentName === deploymentName) {
|
||||
return { ...assistant, model: firstModel };
|
||||
}
|
||||
|
||||
for (const [model, modelConfig] of currentModelTuples) {
|
||||
if (modelConfig.deploymentName === deploymentName) {
|
||||
return { ...assistant, model };
|
||||
}
|
||||
}
|
||||
|
||||
return { ...assistant, model: firstModel };
|
||||
}),
|
||||
);
|
||||
|
||||
return {
|
||||
first_id: data[0]?.id,
|
||||
last_id: data[data.length - 1]?.id,
|
||||
object: 'list',
|
||||
has_more: false,
|
||||
data,
|
||||
};
|
||||
};
|
||||
|
||||
async function getOpenAIClient({ req, res, endpointOption, initAppClient, overrideEndpoint }) {
|
||||
let endpoint = overrideEndpoint ?? req.body.endpoint ?? req.query.endpoint;
|
||||
const version = await getCurrentVersion(req, endpoint);
|
||||
if (!endpoint) {
|
||||
throw new Error(`[${req.baseUrl}] Endpoint is required`);
|
||||
}
|
||||
|
||||
let result;
|
||||
if (endpoint === EModelEndpoint.assistants) {
|
||||
result = await initializeClient({ req, res, version, endpointOption, initAppClient });
|
||||
} else if (endpoint === EModelEndpoint.azureAssistants) {
|
||||
result = await initAzureClient({ req, res, version, endpointOption, initAppClient });
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
const fetchAssistants = async (req, res) => {
|
||||
const { limit = 100, order = 'desc', after, before, endpoint } = req.query;
|
||||
const version = await getCurrentVersion(req, endpoint);
|
||||
const query = { limit, order, after, before };
|
||||
|
||||
/** @type {AssistantListResponse} */
|
||||
let body;
|
||||
|
||||
if (endpoint === EModelEndpoint.assistants) {
|
||||
({ body } = await listAssistants({ req, res, version, query }));
|
||||
} else if (endpoint === EModelEndpoint.azureAssistants) {
|
||||
const azureConfig = req.app.locals[EModelEndpoint.azureOpenAI];
|
||||
body = await listAssistantsForAzure({ req, res, version, azureConfig, query });
|
||||
}
|
||||
|
||||
return body;
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
getOpenAIClient,
|
||||
fetchAssistants,
|
||||
getCurrentVersion,
|
||||
};
|
||||
262
api/server/controllers/assistants/v1.js
Normal file
262
api/server/controllers/assistants/v1.js
Normal file
|
|
@ -0,0 +1,262 @@
|
|||
const { FileContext } = require('librechat-data-provider');
|
||||
const { getStrategyFunctions } = require('~/server/services/Files/strategies');
|
||||
const { deleteAssistantActions } = require('~/server/services/ActionService');
|
||||
const { uploadImageBuffer } = require('~/server/services/Files/process');
|
||||
const { updateAssistant, getAssistants } = require('~/models/Assistant');
|
||||
const { getOpenAIClient, fetchAssistants } = require('./helpers');
|
||||
const { deleteFileByFilter } = require('~/models/File');
|
||||
const { logger } = require('~/config');
|
||||
|
||||
/**
|
||||
* Create an assistant.
|
||||
* @route POST /assistants
|
||||
* @param {AssistantCreateParams} req.body - The assistant creation parameters.
|
||||
* @returns {Assistant} 201 - success response - application/json
|
||||
*/
|
||||
const createAssistant = async (req, res) => {
|
||||
try {
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
|
||||
const { tools = [], endpoint, ...assistantData } = req.body;
|
||||
assistantData.tools = tools
|
||||
.map((tool) => {
|
||||
if (typeof tool !== 'string') {
|
||||
return tool;
|
||||
}
|
||||
|
||||
return req.app.locals.availableTools[tool];
|
||||
})
|
||||
.filter((tool) => tool);
|
||||
|
||||
let azureModelIdentifier = null;
|
||||
if (openai.locals?.azureOptions) {
|
||||
azureModelIdentifier = assistantData.model;
|
||||
assistantData.model = openai.locals.azureOptions.azureOpenAIApiDeploymentName;
|
||||
}
|
||||
|
||||
assistantData.metadata = {
|
||||
author: req.user.id,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
const assistant = await openai.beta.assistants.create(assistantData);
|
||||
if (azureModelIdentifier) {
|
||||
assistant.model = azureModelIdentifier;
|
||||
}
|
||||
logger.debug('/assistants/', assistant);
|
||||
res.status(201).json(assistant);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants] Error creating assistant', error);
|
||||
res.status(500).json({ error: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Retrieves an assistant.
|
||||
* @route GET /assistants/:id
|
||||
* @param {string} req.params.id - Assistant identifier.
|
||||
* @returns {Assistant} 200 - success response - application/json
|
||||
*/
|
||||
const retrieveAssistant = async (req, res) => {
|
||||
try {
|
||||
/* NOTE: not actually being used right now */
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
|
||||
const assistant_id = req.params.id;
|
||||
const assistant = await openai.beta.assistants.retrieve(assistant_id);
|
||||
res.json(assistant);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/:id] Error retrieving assistant', error);
|
||||
res.status(500).json({ error: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Modifies an assistant.
|
||||
* @route PATCH /assistants/:id
|
||||
* @param {object} req - Express Request
|
||||
* @param {object} req.params - Request params
|
||||
* @param {string} req.params.id - Assistant identifier.
|
||||
* @param {AssistantUpdateParams} req.body - The assistant update parameters.
|
||||
* @returns {Assistant} 200 - success response - application/json
|
||||
*/
|
||||
const patchAssistant = async (req, res) => {
|
||||
try {
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
|
||||
const assistant_id = req.params.id;
|
||||
const { endpoint: _e, ...updateData } = req.body;
|
||||
updateData.tools = (updateData.tools ?? [])
|
||||
.map((tool) => {
|
||||
if (typeof tool !== 'string') {
|
||||
return tool;
|
||||
}
|
||||
|
||||
return req.app.locals.availableTools[tool];
|
||||
})
|
||||
.filter((tool) => tool);
|
||||
|
||||
if (openai.locals?.azureOptions && updateData.model) {
|
||||
updateData.model = openai.locals.azureOptions.azureOpenAIApiDeploymentName;
|
||||
}
|
||||
|
||||
const updatedAssistant = await openai.beta.assistants.update(assistant_id, updateData);
|
||||
res.json(updatedAssistant);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/:id] Error updating assistant', error);
|
||||
res.status(500).json({ error: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Deletes an assistant.
|
||||
* @route DELETE /assistants/:id
|
||||
* @param {object} req - Express Request
|
||||
* @param {object} req.params - Request params
|
||||
* @param {string} req.params.id - Assistant identifier.
|
||||
* @returns {Assistant} 200 - success response - application/json
|
||||
*/
|
||||
const deleteAssistant = async (req, res) => {
|
||||
try {
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
|
||||
const assistant_id = req.params.id;
|
||||
const deletionStatus = await openai.beta.assistants.del(assistant_id);
|
||||
if (deletionStatus?.deleted) {
|
||||
await deleteAssistantActions({ req, assistant_id });
|
||||
}
|
||||
res.json(deletionStatus);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/:id] Error deleting assistant', error);
|
||||
res.status(500).json({ error: 'Error deleting assistant' });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Returns a list of assistants.
|
||||
* @route GET /assistants
|
||||
* @param {object} req - Express Request
|
||||
* @param {AssistantListParams} req.query - The assistant list parameters for pagination and sorting.
|
||||
* @returns {AssistantListResponse} 200 - success response - application/json
|
||||
*/
|
||||
const listAssistants = async (req, res) => {
|
||||
try {
|
||||
const body = await fetchAssistants(req, res);
|
||||
|
||||
if (req.app.locals?.[req.query.endpoint]) {
|
||||
/** @type {Partial<TAssistantEndpoint>} */
|
||||
const assistantsConfig = req.app.locals[req.query.endpoint];
|
||||
const { supportedIds, excludedIds } = assistantsConfig;
|
||||
if (supportedIds?.length) {
|
||||
body.data = body.data.filter((assistant) => supportedIds.includes(assistant.id));
|
||||
} else if (excludedIds?.length) {
|
||||
body.data = body.data.filter((assistant) => !excludedIds.includes(assistant.id));
|
||||
}
|
||||
}
|
||||
|
||||
res.json(body);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants] Error listing assistants', error);
|
||||
res.status(500).json({ message: 'Error listing assistants' });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Returns a list of the user's assistant documents (metadata saved to database).
|
||||
* @route GET /assistants/documents
|
||||
* @returns {AssistantDocument[]} 200 - success response - application/json
|
||||
*/
|
||||
const getAssistantDocuments = async (req, res) => {
|
||||
try {
|
||||
res.json(await getAssistants({ user: req.user.id }));
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/documents] Error listing assistant documents', error);
|
||||
res.status(500).json({ error: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Uploads and updates an avatar for a specific assistant.
|
||||
* @route POST /avatar/:assistant_id
|
||||
* @param {object} req - Express Request
|
||||
* @param {object} req.params - Request params
|
||||
* @param {string} req.params.assistant_id - The ID of the assistant.
|
||||
* @param {Express.Multer.File} req.file - The avatar image file.
|
||||
* @param {object} req.body - Request body
|
||||
* @param {string} [req.body.metadata] - Optional metadata for the assistant's avatar.
|
||||
* @returns {Object} 200 - success response - application/json
|
||||
*/
|
||||
const uploadAssistantAvatar = async (req, res) => {
|
||||
try {
|
||||
const { assistant_id } = req.params;
|
||||
if (!assistant_id) {
|
||||
return res.status(400).json({ message: 'Assistant ID is required' });
|
||||
}
|
||||
|
||||
let { metadata: _metadata = '{}' } = req.body;
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
|
||||
const image = await uploadImageBuffer({
|
||||
req,
|
||||
context: FileContext.avatar,
|
||||
metadata: {
|
||||
buffer: req.file.buffer,
|
||||
},
|
||||
});
|
||||
|
||||
try {
|
||||
_metadata = JSON.parse(_metadata);
|
||||
} catch (error) {
|
||||
logger.error('[/avatar/:assistant_id] Error parsing metadata', error);
|
||||
_metadata = {};
|
||||
}
|
||||
|
||||
if (_metadata.avatar && _metadata.avatar_source) {
|
||||
const { deleteFile } = getStrategyFunctions(_metadata.avatar_source);
|
||||
try {
|
||||
await deleteFile(req, { filepath: _metadata.avatar });
|
||||
await deleteFileByFilter({ filepath: _metadata.avatar });
|
||||
} catch (error) {
|
||||
logger.error('[/avatar/:assistant_id] Error deleting old avatar', error);
|
||||
}
|
||||
}
|
||||
|
||||
const metadata = {
|
||||
..._metadata,
|
||||
avatar: image.filepath,
|
||||
avatar_source: req.app.locals.fileStrategy,
|
||||
};
|
||||
|
||||
const promises = [];
|
||||
promises.push(
|
||||
updateAssistant(
|
||||
{ assistant_id },
|
||||
{
|
||||
avatar: {
|
||||
filepath: image.filepath,
|
||||
source: req.app.locals.fileStrategy,
|
||||
},
|
||||
user: req.user.id,
|
||||
},
|
||||
),
|
||||
);
|
||||
promises.push(openai.beta.assistants.update(assistant_id, { metadata }));
|
||||
|
||||
const resolved = await Promise.all(promises);
|
||||
res.status(201).json(resolved[1]);
|
||||
} catch (error) {
|
||||
const message = 'An error occurred while updating the Assistant Avatar';
|
||||
logger.error(message, error);
|
||||
res.status(500).json({ message });
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
createAssistant,
|
||||
retrieveAssistant,
|
||||
patchAssistant,
|
||||
deleteAssistant,
|
||||
listAssistants,
|
||||
getAssistantDocuments,
|
||||
uploadAssistantAvatar,
|
||||
};
|
||||
208
api/server/controllers/assistants/v2.js
Normal file
208
api/server/controllers/assistants/v2.js
Normal file
|
|
@ -0,0 +1,208 @@
|
|||
const { ToolCallTypes } = require('librechat-data-provider');
|
||||
const { validateAndUpdateTool } = require('~/server/services/ActionService');
|
||||
const { getOpenAIClient } = require('./helpers');
|
||||
const { logger } = require('~/config');
|
||||
|
||||
/**
|
||||
* Create an assistant.
|
||||
* @route POST /assistants
|
||||
* @param {AssistantCreateParams} req.body - The assistant creation parameters.
|
||||
* @returns {Assistant} 201 - success response - application/json
|
||||
*/
|
||||
const createAssistant = async (req, res) => {
|
||||
try {
|
||||
/** @type {{ openai: OpenAIClient }} */
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
|
||||
const { tools = [], endpoint, ...assistantData } = req.body;
|
||||
assistantData.tools = tools
|
||||
.map((tool) => {
|
||||
if (typeof tool !== 'string') {
|
||||
return tool;
|
||||
}
|
||||
|
||||
return req.app.locals.availableTools[tool];
|
||||
})
|
||||
.filter((tool) => tool);
|
||||
|
||||
let azureModelIdentifier = null;
|
||||
if (openai.locals?.azureOptions) {
|
||||
azureModelIdentifier = assistantData.model;
|
||||
assistantData.model = openai.locals.azureOptions.azureOpenAIApiDeploymentName;
|
||||
}
|
||||
|
||||
assistantData.metadata = {
|
||||
author: req.user.id,
|
||||
endpoint,
|
||||
};
|
||||
|
||||
const assistant = await openai.beta.assistants.create(assistantData);
|
||||
if (azureModelIdentifier) {
|
||||
assistant.model = azureModelIdentifier;
|
||||
}
|
||||
logger.debug('/assistants/', assistant);
|
||||
res.status(201).json(assistant);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants] Error creating assistant', error);
|
||||
res.status(500).json({ error: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Modifies an assistant.
|
||||
* @param {object} params
|
||||
* @param {Express.Request} params.req
|
||||
* @param {OpenAIClient} params.openai
|
||||
* @param {string} params.assistant_id
|
||||
* @param {AssistantUpdateParams} params.updateData
|
||||
* @returns {Promise<Assistant>} The updated assistant.
|
||||
*/
|
||||
const updateAssistant = async ({ req, openai, assistant_id, updateData }) => {
|
||||
const tools = [];
|
||||
|
||||
let hasFileSearch = false;
|
||||
for (const tool of updateData.tools ?? []) {
|
||||
let actualTool = typeof tool === 'string' ? req.app.locals.availableTools[tool] : tool;
|
||||
|
||||
if (!actualTool) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (actualTool.type === ToolCallTypes.FILE_SEARCH) {
|
||||
hasFileSearch = true;
|
||||
}
|
||||
|
||||
if (!actualTool.function) {
|
||||
tools.push(actualTool);
|
||||
continue;
|
||||
}
|
||||
|
||||
const updatedTool = await validateAndUpdateTool({ req, tool: actualTool, assistant_id });
|
||||
if (updatedTool) {
|
||||
tools.push(updatedTool);
|
||||
}
|
||||
}
|
||||
|
||||
if (hasFileSearch && !updateData.tool_resources) {
|
||||
const assistant = await openai.beta.assistants.retrieve(assistant_id);
|
||||
updateData.tool_resources = assistant.tool_resources ?? null;
|
||||
}
|
||||
|
||||
if (hasFileSearch && !updateData.tool_resources?.file_search) {
|
||||
updateData.tool_resources = {
|
||||
...(updateData.tool_resources ?? {}),
|
||||
file_search: {
|
||||
vector_store_ids: [],
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
updateData.tools = tools;
|
||||
|
||||
if (openai.locals?.azureOptions && updateData.model) {
|
||||
updateData.model = openai.locals.azureOptions.azureOpenAIApiDeploymentName;
|
||||
}
|
||||
|
||||
return await openai.beta.assistants.update(assistant_id, updateData);
|
||||
};
|
||||
|
||||
/**
|
||||
* Modifies an assistant with the resource file id.
|
||||
* @param {object} params
|
||||
* @param {Express.Request} params.req
|
||||
* @param {OpenAIClient} params.openai
|
||||
* @param {string} params.assistant_id
|
||||
* @param {string} params.tool_resource
|
||||
* @param {string} params.file_id
|
||||
* @param {AssistantUpdateParams} params.updateData
|
||||
* @returns {Promise<Assistant>} The updated assistant.
|
||||
*/
|
||||
const addResourceFileId = async ({ req, openai, assistant_id, tool_resource, file_id }) => {
|
||||
const assistant = await openai.beta.assistants.retrieve(assistant_id);
|
||||
const { tool_resources = {} } = assistant;
|
||||
if (tool_resources[tool_resource]) {
|
||||
tool_resources[tool_resource].file_ids.push(file_id);
|
||||
} else {
|
||||
tool_resources[tool_resource] = { file_ids: [file_id] };
|
||||
}
|
||||
|
||||
delete assistant.id;
|
||||
return await updateAssistant({
|
||||
req,
|
||||
openai,
|
||||
assistant_id,
|
||||
updateData: { tools: assistant.tools, tool_resources },
|
||||
});
|
||||
};
|
||||
|
||||
/**
|
||||
* Deletes a file ID from an assistant's resource.
|
||||
* @param {object} params
|
||||
* @param {Express.Request} params.req
|
||||
* @param {OpenAIClient} params.openai
|
||||
* @param {string} params.assistant_id
|
||||
* @param {string} [params.tool_resource]
|
||||
* @param {string} params.file_id
|
||||
* @param {AssistantUpdateParams} params.updateData
|
||||
* @returns {Promise<Assistant>} The updated assistant.
|
||||
*/
|
||||
const deleteResourceFileId = async ({ req, openai, assistant_id, tool_resource, file_id }) => {
|
||||
const assistant = await openai.beta.assistants.retrieve(assistant_id);
|
||||
const { tool_resources = {} } = assistant;
|
||||
|
||||
if (tool_resource && tool_resources[tool_resource]) {
|
||||
const resource = tool_resources[tool_resource];
|
||||
const index = resource.file_ids.indexOf(file_id);
|
||||
if (index !== -1) {
|
||||
resource.file_ids.splice(index, 1);
|
||||
}
|
||||
} else {
|
||||
for (const resourceKey in tool_resources) {
|
||||
const resource = tool_resources[resourceKey];
|
||||
const index = resource.file_ids.indexOf(file_id);
|
||||
if (index !== -1) {
|
||||
resource.file_ids.splice(index, 1);
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
delete assistant.id;
|
||||
return await updateAssistant({
|
||||
req,
|
||||
openai,
|
||||
assistant_id,
|
||||
updateData: { tools: assistant.tools, tool_resources },
|
||||
});
|
||||
};
|
||||
|
||||
/**
|
||||
* Modifies an assistant.
|
||||
* @route PATCH /assistants/:id
|
||||
* @param {object} req - Express Request
|
||||
* @param {object} req.params - Request params
|
||||
* @param {string} req.params.id - Assistant identifier.
|
||||
* @param {AssistantUpdateParams} req.body - The assistant update parameters.
|
||||
* @returns {Assistant} 200 - success response - application/json
|
||||
*/
|
||||
const patchAssistant = async (req, res) => {
|
||||
try {
|
||||
const { openai } = await getOpenAIClient({ req, res });
|
||||
const assistant_id = req.params.id;
|
||||
const { endpoint: _e, ...updateData } = req.body;
|
||||
updateData.tools = updateData.tools ?? [];
|
||||
const updatedAssistant = await updateAssistant({ req, openai, assistant_id, updateData });
|
||||
res.json(updatedAssistant);
|
||||
} catch (error) {
|
||||
logger.error('[/assistants/:id] Error updating assistant', error);
|
||||
res.status(500).json({ error: error.message });
|
||||
}
|
||||
};
|
||||
|
||||
module.exports = {
|
||||
patchAssistant,
|
||||
createAssistant,
|
||||
updateAssistant,
|
||||
addResourceFileId,
|
||||
deleteResourceFileId,
|
||||
};
|
||||
Loading…
Add table
Add a link
Reference in a new issue